Yang Li

With the public's enhanced awareness of eco-safety, environmentally benign measures based on microorganisms and microbial aggregates have become more accepted as methods of removing pollutants from aquatic systems. In this review, the application of microorganisms and microbial aggregates for removing pollutants from aqueous solutions is introduced and described based on mechanisms such as assimilation, adsorption, and biodegradation. The advantages of and future studies regarding the use of microorganisms and microbial aggregates to remove pollutants are discussed. Due to the limitation of a single microorganism species in adapting to heterogeneous conditions, this review demonstrates that the application of microbial aggregates consisting of multiple photoautotrophic and heterotrophic microorganisms, is a promising method of removing multiple pollutants from complex wastewaters and warrants further research.

Transformer models have advanced the state of the art in many Natural Language Processing (NLP) tasks.In this paper, we present a new Transformer architecture, Extended Transformer Construction (ETC), that addresses two key challenges of standard Transformer architectures, namely scaling input length and encoding structured inputs.To scale attention to longer inputs, we introduce a novel global-local attention mechanism between global tokens and regular input tokens.We also show that combining global-local attention with relative position encodings and a Contrastive Predictive Coding (CPC) pretraining objective allows ETC to encode structured inputs.We achieve state-of-the-art results on four natural language datasets requiring long and/or structured inputs.

With the development of virtual reality (VR) and human-computer interaction technology, how to use natural and efficient interaction methods in the virtual environment has become a hot topic of research. Gesture is one of the most important communication methods of human beings, which can effectively express users’ demands. In the past few decades, gesture-based interaction has made significant progress. This article focuses on the gesture interaction technology and discusses the definition and classification of gestures, input devices for gesture interaction, and gesture interaction recognition technology. The application of gesture interaction technology in virtual reality is studied, the existing problems in the current gesture interaction are summarized, and the future development is prospected.

AgCl/ZnO/g-C3N4, a visible light activated ternary composite catalyst, was prepared by combining calcination, hydrothermal reaction and in-situ deposition processes to treat/photocatalyse tetracycline hydrochloride (TC-HCl) from pharmaceutical wastewater under visible light. The morphological, structural, electrical, and optical features of the novel photocatalyst were characterized using scanning electron microscopy (SEM), UV-visible light absorption spectrum (UV-Vis DRS), X-ray diffractometer (XRD), Fourier transform infrared spectroscopy (FT-IR), X-ray photoelectron spectroscopy (XPS), and transient photocurrent techniques. All analyses confirmed that the formation of heterojunctions between AgCl/ZnO and g-C3N4 significantly increase electron-hole transfer and separation compared to pure ZnO and g-C3N4. Thus, AgCl/ZnO/g-C3N4 could exhibit superior photocatalytic activity during TC-HCl assays (over 90% removal) under visible light irradiation. The composite could maintain its photocatalytic stability even after four consecutive reaction cycles. Hydrogen peroxide (H2O2) and superoxide radical (·O2) contributed more than holes (h+) and hydroxyl radicals (·OH) to the degradation process as showed by trapping experiments. Liquid chromatograph-mass spectrometer (LC-MS) was used for the representation of the TC-HCl potential degradation pathway. The applicability and the treatment potential of AgCl/ZnO/g-C3N4 against actual pharmaceutical wastewater showed that the composite can achieve removal efficiencies of 81.7%, 71.4% and 69.0% for TC-HCl, chemical oxygen demand (COD) and total organic carbon (TOC) respectively. AgCl/ZnO/g-C3N4 can be a prospective key photocatalyst in the field of degradation of persistent, hardly-degradable pollutants, from industrial wastewater and not only.

The aim of this study was to develop a promising and competitive bioadsorbent with the abundant of source, low price and environmentally friendly characters to remove cationic dye from wastewater. The swede rape straw (Brassica napus L.) modified by tartaric acid (SRSTA) was prepared, characterized and used to remove methylene blue (MB) from aqueous solution at varied operational conditions (including MB initial concentrations, adsorbent dose, etc.). Results demonstrated that the equilibrium data was well fitted by Langmuir isotherm model. The maximum MB adsorption capacity of SRSTA was 246.4 mg g(-1), which was comparable to the results of some previous studied activated carbons. The higher dye adsorption capacity could be attributed to the presence of more functional groups such as carboxyl group on the surface of SRSTA. The adsorption mechanism was also discussed. The results indicate that SRSTA is a promising and valuable absorbent to remove methylene blue from wastewater.

Mg–Fe layered double hydroxide (MgFe-LDH) particles were incorporated into wheat-straw biochar by liquid-phase deposition. The obtained biochar/MgFe-LDH composite was used to remove nitrate from aqueous solutions. X-ray diffraction patterns demonstrated that LDH particles were successfully deposited onto the carbon surface within the biochar matrix. Adsorption kinetic and isotherm studies and the effects of co-existing anions and adsorbents dosages were investigated using laboratory batch sorption experiments. The biochar/MgFe-LDH composite showed a strong sorption ability to nitrate in aqueous solutions with the Langmuir maximum adsorption capacity of 24.8 mg/g. A high selectivity for nitrate of the biochar/MgFe-LDH composite was also observed irrespective of the co-existence of sulfate and phosphate. The biochar/MgFe-LDH composite can thus be potentially used as an alternative adsorbent for the treatment of nitrate-contaminated waters as well as a soil amendment for the reduction of soil nitrate leaching.

The aim of this project was to establish an economical and environmentally benign biotechnology for removing methylene blue (MB) from wastewater. The adsorption process of MB onto abandoned sesame hull (Sesamum indicum L.) (SH) was investigated in a batch system. The results showed that a wide range of pH (3.54–10.50) was favorable for the adsorption of MB onto SH. The Langmuir model displayed the best fit for the isothermal data. The exothermic adsorption process fits a pseudo-second-order kinetic model. The maximum monolayer adsorption capacity (359.88 mg g−1) was higher than most previously investigated low-cost bioadsorbents (e.g., peanut hull, wheat straw, etc.). This study indicated that sesame hull is a promising, unconventional, affordable and environmentally friendly bio-measure that is easily deployed for removing high levels of MB from wastewater.

The knowledge regarding the effects of metal or metal oxide nanoparticles on soil microbial metabolic activity and key ecological functions is limited, relative to the information about their species diversity. For this reason, the responses of soil microbial metabolic activity to silver (AgNPs) and iron oxide (FeONPs) nanoparticles, along concentration gradients of each, were evaluated by microcalorimetry and soil nitrification potential. The changes in abundances of bacteria, eukaryotes and ammonia-oxidizing bacteria were measured by real time quantitative PCR. It was found that AgNP (at 0.1, 1 and 10 mg kg−1 soil) amendments decreased soil microbial metabolic activity, nitrification potential and the abundances of bacteria and ammonia-oxidizing bacteria; on the contrary, FeONPs had the positive effects on soil microbial metabolic activity (at 1 and 10 mg kg−1 soil) and soil nitrification potential (at 0.1 and 1 mg kg−1 soil). Specific microbial metabolic activity and specific nitrification potential further revealed that metal or metal oxide nanoparticles could change the C and N cycles of the agricultural soil through influencing soil microbial metabolism. These findings could deepen the understanding of the influence of NPs on soil microorganisms and their driven soil ecology process.

Swede rape straw (Brassica napus L.) was modified by oxalic acid under mild conditions producing an efficient dye adsorbent (SRSOA). This low-cost and environmental friendly bioadsorbent was characterized by various techniques and then applied to purify dye-contaminated aqueous solutions. Equilibrium study showed that the Langmuir model demonstrated the best fit to the equilibrium data and the methylene blue (MB) adsorption capacity calculated by this model was 432 mg g−1. The adsorption process and mechanism is also discussed. To properly deal with the dye-loaded bioadsorbents, the disposal methodology is discussed and a biochar based on depleted bioadsorbents was for the first time produced and examined. This method both solved the disposal problem of contaminant-loaded bioadsorbents and produced an useful adsorbent thereafter. The study indicates that SRSOA is a promising substitute for ACs in purifying dye-contaminated wastewater and that producing biochars from contaminant-loaded bioadsorbents maybe a feasible disposal method.

This study prepared a carboxylic functionalized bioadsorbent that met the "4-E" criteria: Efficient, Economical, Environmentally friendly, and Easily-produced. Sesame straw (Sesamum indicum L.) was functionalized through treatment with citric acid (SSCA) and tartaric acid (SSTA). The products were examined for adsorption capacity and mechanisms. Langmuir model gave the best fit for the isotherm data, and the maximum monolayer adsorption capacity of SSCA was 650mgg-1 for methylene blue (MB). The excellent dye adsorption capacity of SSCA can be attributed to the introduction of ester groups during citric-acid modification and the tube-like structures (i.e., sesame straw cell wall remnants). At last, the cost of carboxylic acid functionalized bioadsorbents was evaluated, which showed that SSCA would be the most cost-effective bioadsorbent. Additionally, this study presents a thermo-decomposition methodology for contaminant-loaded bioadsorbent. Results showed that SSCA is probably one of the few bioadsorbents that can be produced and applied in industrial scale.

In this study, nano-cerium oxide functionalized maize straw biochar (Ce-MSB) was prepared and utilized to remove P from agricultural wastewater. Response Surface Model was applied to optimize the operating conditions. Moreover, Ce-MSB was applied to actual rice paddy column for the first time. Response Surface Model (RSM) showed higher materials ratio had positive effect on PO43- adsorption capacity, while higher pyrolysis temperature had negative effect. The maximum adsorption capacity of Ce-MSB for PO43- was 78 mg g-1, implying that Ce-MSB was an effective functionalized adsorbent for P removal. Paddy soil column experiment showed that application of Ce-MSB decreased total phosphorus concentration of surface water by 27.33% and increased total phosphors (TP) content of top soil by 7.22%. Further, Ce-MSB tends to increase rice plant height and leaf area. Therefore, Ce-MSB can be used as a promising functionalized biochar to reduce the risk of phosphorus loss from paddy field surface running water.

Polyphenols are readily affected by environmental factors, such as heat and light, which cause them to degrade; however, the functional properties of polyphenols can be protected by complexing them with proteins. In this study, we investigate the effects of acid and alkali treatments on the functional properties of soybean protein isolate (SPI) and interactions between the treated protein and (−)-epigallocatechin-3-gallate (EGCG). The results show that alkali treatment (pH 12–7) affects the structure and functional performance of the protein more significantly than acid treatment (pH 2–7) because the protein structure unfolds, resulting in improved solubility, surface hydrophobicity, and emulsification. In addition, because alkali treatment can change the structure of a protein more than acid treatment, its structure loosens. The interactions between alkali-treated proteins and EGCG were also found to be stronger than those of acid-treated proteins and the control protein, and EGCG binds to a protein through van der Waals forces and hydrophobic interactions; these interactions protect EGCG from degradation, ensuring that its antioxidant properties are maintained and its bioavailability rate is improved.

Hydrothermal carbonization represents a promising technique for transforming microalgae into the hydrochar with abundant phytoavailable nutrients. However, the effects of microalgae-derived hydrochars on the gaseous nitrogen (N) loss from agricultural field are still unclear. Chlorella vulgaris powder (CVP) and two Chlorella vulgaris-derived hydrochars that employ water (CVHW) or citrate acid solution (CVHCA) as the reaction medium were applied to a soil column system grown with rice. The temporal variations of nitrous oxide (N2O) emissions and ammonia (NH3) volatilization were monitored during the whole rice-growing season. Results showed that CVHW and CVHCA addition significantly increased the grain yield (by 13.5–26.8% and 10.5–23.4%) compared with control and CVP group, while concomitantly increasing the ammonia volatilization (by 53.8% and 72.9%) as well as N2O emissions (by 2.17- and 2.82-fold) from paddy soil compared to control. The microbial functional genes (AOA, AOB, nirk, nirS, nosZ) in soil indicated that CVHW and CVHCA treatment stimulated the nitrification and denitrification, and inhibited the N2O oxidation in soil. Notably, CVHW was recommended in the view of improving yield and controlling NH3 volatilization because no significant difference of the yield-scale NH3 volatilization was detected between control and CVHW treatment. This study for the first time uncovered that Chlorella vulgaris-derived hydrochars have positive effects on rice N utilization and growth but negative effects on the atmospheric environment.

Wood vinegar (WV) was applied alone or combined with biochar (BC) to observe their efficiency on suppressing the ammonia (NH3) volatilization from rice paddy soil. Five treatments, i.e., control (240 kg N ha-1 applied in urea), WV-5 and WV-10 (240 kg N ha-1 plus 5 and 10 t WV ha-1, respectively), and their counterparts WV-5-BC and WV-10-BC (WV-5 and WV-10 plus 7 t BC ha-1), were evaluated by a soil columns experiment. The N fertilizer was split applied as basal and two supplementary fertilizations (named BF, SF1 and SF2, respectively). The results showed that WV-5 treatment increased rice grain yield up to 11.2% compared to the control. Compared with the control, four WV-amended treatments, exhibited lower pH values of the floodwater (7.94-8.18 vs 8.47 and 7.85-7.91 vs 7.98) and the topsoil (6.52-6.76 vs 6.82 and 6.82-6.92 vs 6.99) during the BF and SF1 periods. Both WV-5 and WV-10 increased the NH4+-N contents of topsoil by 10.9-17.8% and 16.1-36.2% after BF and SF1, respectively, than control treatment. Additionally, the floodwater of the WV-amended treatments had higher NH4+-N concentration than control during the first three days after N fertilization, which can be attributed to the stimulating effect of WV on soil urease enzyme activity. WV did not effectively reduce NH3 volatilization as hypothesized. Interestingly, four WV-amended had relatively reduced the yield-scale NH3 volatilization by 13.6% than the control. It is suggested that WV needs to be applied with BC at a moderate rate to achieve optimum rice yield and mitigate NH3 volatilization.

Hydrothermal carbonization (HTC) is a promising technique for treating sewage sludge. In this study, three sewage sludge-derived hydrochars produced with water (SSHW), 1 wt% magnesium citrate (SSHM) solution, and 1 wt% magnesium citrate mixed with 1 wt% sulfuric acid (SSHMS) solution were applied to columns of packed paddy soil. We evaluated the effects of these differently modified sewage sludge-hydrochars on ammonia volatilization, soil nitrogen (N) retention and rice growth. Results showed that compared to the control, SSHMS reduced the cumulative ammonia volatilization determined after three split application of N-fertilizer. SSHM and SSHMS both reduced the yield-scale ammonia volatilization by 20.3% and 41.2% respectively. Moreover, the addition of three sewage sludge-derived hydrochars increased soil ammonium-N retention after the first supplementary fertilization; however, after the second supplementary fertilization, only SSHMS addition significantly increased soil ammonium-N retention. Of the three hydrochars tested, SSHMS has the strongest effects on soil ammonium-N retention and inhibition of ammonium-N loss in floodwater. This was attributed to increased ammonium sorption driven by SSHMS's lower surface pH and porous diameter, larger adsorption porous volume and higher abundance of carboxyl functional groups. Additionally, the increased soil N retention increased grain N content and yield. Our results provide a novel method to valorize sewage sludge into a valuable fertilizer that if applied to paddy soil it can inhibit ammonia volatilization, N loss in floodwater, and promote N use efficiency by rice, with positive implications for sustainable rice production.

In our review of the research on PGS (park green space) spatial equity, little consideration has been given to the impacts of small spatial scales and measurement accuracy on spatial equity assessments. Based on the web map API open data platform (including location and navigation data, etc.), this study established a fine-scaled evaluation framework of spatial equity from the aspects of sensitivity to measurement and the urban micro-perspective. The framework was integrated within the KD2SFCA (kernel density two-step floating catchment area) method, which planners use to accurately locate areas of under or over supply of urban public facilities. Taking Zhengzhou as a case study, we identified 2494 residential areas and 106 PGSs to describe the spatial equity of residents accessing different PGS levels by four travel modes. The results showed that there were significant differences in spatial equity between different PGS levels. Of the three PGS levels, the overall spatial equity for district PGS was the highest, community PGS was second, and municipal PGS was the lowest. We also found that different travel modes had important impacts on PGS spatial equity. One interesting phenomenon was that when residents chose to walk to a higher level PGS, the percentages of the population with “no supply” increased; when residents chose bicycle and private car modes to reach higher level PGS, the percentages of the population with “weak supply” and “over supply” increased. In addition, it is worth noting that community PGS was originally established to meet the needs of residents for short-distance entertainment. However, we found that almost all residents in the study area were in the extreme states of “no supply” or “over supply” when they reached community PGS by walking. These results provide a scientific basis for more reasonable and equitable allocation of urban PGS and the optimization of transportation facilities. This work can also provide a more fine-scaled research perspective and improve the scientific evaluation system for studying urban infrastructure spatial equity.

Microbially-aged hydrochar were prepared to investigate how aging affected their ability to remove Cd2+ from aqueous solutions. Based on aging time in an anaerobic fermenter, four samples were produced: HC, M20-HC, M40-HC, and M60-HC. Results indicated increases in specific surface area, pH, and negative charge on hydrochar surface with aging process. Also, there were a decrease in O/C and an increase in surface functional groups, such as -COOH. The adsorption experiments confirmed the positive correlation between aging time and adsorption performance. The 60-day-aged M60-HC treatment displayed the maximum adsorption capacity, which was 3.8 times higher than that of HC. The Langmuir and pseudo-second-order kinetic equations fitted well with isothermal and kinetic data, respectively. Thermodynamic study indicated that Cd2+ adsorption is dominated by chemisorption. This study showed that microbial aging process is an effective and promising measure to improve hydrochar adsorption capacity for Cd2+.

Due to the finite stocks of phosphate rock and low phosphorus (P) use efficiency (PUE) of traditional mineral P fertilizers, more sustainable alternatives are desirable. One possibility is to culture microalgae in wastewater to recover the P and then convert the microalgae biomass into slow-release fertilizers through hydrothermal carbonization (HTC). Therefore, this study aimed to recycle P from wastewater to agricultural field using microalgae and HTC technology. Chlorella vulgaris (CV) and Microcystis sp. (MS) were cultured in poultry farm wastewater with an initial concentration of 41.3 mg P kg−1. MS removed 88.4% P from the wastewater, which was superior to CV. CV- and MS-derived hydrochars were produced at 200 or 260 °C, in solutions using deionized water or 1 wt% citric acid. The MS-derived hydrochar using 1 wt% citric acid solution at 260 °C (MSHCA260) recovered the highest amount of P (91.5%) after HTC. The charring promoted the transformation of soluble and exchangeable P into moderately available P (Fe/Al-bound P), and using citric acid solution as feedwater increased the P recovery rate and formation of Fe/Al-bound P. With the abundant moderately available P pool, hydrochar amendment released P more slowly and enhanced the soil P availability more persistently than chemical fertilizer did, which helped to improve PUE. In a wheat-cultivation pot experiment, MSHCA260 treatment improved wheat PUE by 34.4% and yield by 21.6% more than chemical fertilizer did. These results provide a novel sustainable strategy for recycling P from wastewater to crop-soil systems, substituting the mineral P fertilizer, and improving plant PUE.

In this study, La(OH)3 nanoparticles were immobilized on C3N4 to effectively restrict their aggregation and subsequently enhance the La utilization efficiency to promote phosphate adsorption. The prepared La(OH)3-C3N4 nanocomposite was characterized by SEM, XRD, FTIR, XPS, BET and Zeta potential analysis. Batch and continuously-fed (fixed-bed column) experiments to assess the adsorption performance of La(OH)3-C3N4 showed that the composite exhibits superior utilization efficiency, resulting to relatively quick adsorption with a short equilibrium time of 30 min. The theoretical maximum P adsorption capacity reached the 148.35 mg·g-1, efficiency that remained unaffected by the anions and HA present. The adsorption mechanism showed stability in a wide pH range (4.0-11.0) and is considered effective even after extensive use (five-cycles). The dynamics of the adsorption capacity and the half-penetration time values were estimated by 'Thomas' and 'Yoon-Nelson' models showed that are better represented from the experimental values obtained from the fixed-bed column trial. The adsorption mechanisms were attributed to surface precipitation, electrostatic attraction, and inner-sphere complexation via ligand exchange. Furthermore, La(OH)3-C3N4 demonstrated high efficiency in scavenging phosphate from both diluted and concentrated wastewater (natural pond and swine wastewater respectively). The above confirm that La(OH)3-C3N4 is a promising composite material for phosphate management in aqueous environments.

Good practices in controlling ammonia produced from the predominant agricultural contributor, crop farming, are the most direct yet effective approaches for mitigating ammonia emissions and further relieving air pollution. Of all the practices that have been investigated in recent decades, fertilizer amendment technologies are garnering increased attention as the low nitrogen use efficiency in most applied quick-acting fertilizers is the main cause of high ammonia emissions. This paper systematically reviews the fertilizer amendment technologies and associated mechanisms that have been developed for ammonia control, especially the technology development of inorganic additives-based complex fertilizers, coating-based enhanced efficiency fertilizers, organic waste-based resource fertilizers and microbial agent and algae-based biofertilizers, and their corresponding mechanisms in farmland properties shifting towards inhibiting ammonia volatilization and enhancing nitrogen use efficiency. The systematic analysis of the literature shows that both enhanced efficiency fertilizers technique and biofertilizers technique present outstanding ammonia inhibition performance with an average mitigation efficiency of 54% and 50.1%, respectively, which is mainly attributed to the slowing down in release and hydrolysis of nitrogen fertilizer, the enhancement in the adsorption and retention of NH4+/NH3 in soil, and the promotion in the microbial consumption of NH4+ in soil. Furthermore, a combined physical and chemical means, namely membrane/film-based mulching technology, for ammonia volatilization inhibition is also evaluated, which is capable of increasing the resistance of ammonia volatilization. Finally, the review addresses the challenges of mitigating agricultural ammonia emissions with the aim of providing an outlook for future research.

Conversational agents show the promise to allow users to interact with mobile devices using language. However, to perform diverse UI tasks with natural language, developers typically need to create separate datasets and models for each specific task, which is expensive and effort-consuming. Recently, pre-trained large language models (LLMs) have been shown capable of generalizing to various downstream tasks when prompted with a handful of examples from the target task. This paper investigates the feasibility of enabling versatile conversational interactions with mobile UIs using a single LLM. We designed prompting techniques to adapt an LLM to mobile UIs. We experimented with four important modeling tasks that address various scenarios in conversational interaction. Our method achieved competitive performance on these challenging tasks without requiring dedicated datasets and training, offering a lightweight and generalizable approach to enable language-based mobile interaction.

Due to their resistance to degradation, wide distribution, easy diffusion and potential uptake by organisms, microplastics (MPs) pollution has become a major environmental concern. In this study, PEG-modified Fe3O4 magnetic nanoparticles demonstrated superior adsorption efficiency against polyethylene (PE) microspheres compared to other adsorbents (bare Fe3O4, PEI/Fe3O4 and CA/Fe3O4). The maximum adsorption capacity of PE was found to be 2203 mg/g by adsorption isotherm analysis. PEG/Fe3O4 maintained a high adsorption capacity even at low temperature (5°C, 2163 mg/g), while neutral pH was favorable for MP adsorption. The presence of anions (Cl−, SO42−, HCO3−, NO3−) and of humic acids inhibited the adsorption of MPs. It is proposed that the adsorption process was mainly driven by intermolecular hydrogen bonding. Overall, the study demonstrated that PEG/Fe3O4 can potentially be used as an efficient control against MPs, thus improving the quality of the aquatic environment and of our water resources.

In the era of big data, knowledge engineering faces fundamental challenges induced by fragmented knowledge from heterogeneous, autonomous sources with complex and evolving relationships. The knowledge representation, acquisition, and inference techniques developed in the 1970s and 1980s, driven by research and development of expert systems, must be updated to cope with both fragmented knowledge from multiple sources in the big data revolution and in-depth knowledge from domain experts. This article presents BigKE, a knowledge engineering framework that handles fragmented knowledge modeling and online learning from multiple information sources, nonlinear fusion on fragmented knowledge, and automated demand-driven knowledge navigation.

We present Weave, a framework for developers to create cross-device wearable interaction by scripting. Weave provides a set of high-level APIs, based on JavaScript, for developers to easily distribute UI output and combine sensing events and user input across mobile and wearable devices. Weave allows developers to focus on their target interaction behaviors and manipulate devices regarding their capabilities and affordances, rather than low-level specifications. Weave also contributes an integrated authoring environment for developers to program and test cross-device behaviors, and when ready, deploy these behaviors to its runtime environment on users' ad-hoc network of devices. An evaluation of Weave with 12 participants on a range of tasks revealed that Weave significantly reduced the effort of developers for creating and iterating on cross-device interaction.

Hydrochar is produced under hydrothermal carbonization, which can be considered as a cleaner process for black carbon production. Hydrochar shows good prospects in agro-environmental applications, but it is recommended to be ameliorated before application to improve its surface characteristics and reduce potential side-effects. This study, for the first time, proposed ameliorating poplar sawdust hydrochar via a microbial-aging process and applying it to rice paddy soil. In a soil-column experiment, sawdust hydrochar (SHC), microbial-aged SHC (M-SHC), and water-washed SHC (W-SHC) were added at different rates to examine their effects on rice growth and nitrogen usage efficiency (NUE). Additionally, the effects of hydrochar application on rice grain free amino acids (FAAs) were investigated. The study revealed that M-SHC had a positive effect on rice growth and increased the grain yield by 17.13%–22.99% compared with control. The NUE was also improved by M-SHC treatment. The positive effect of M-SHC on rice yield might be attributed to the reduced toxic biochar-derived dissolved organic matters, increased specific surface area, elevated hydrochar pH, and more nutrients released due to the microbial-aging process. Moreover, under M-SHC treatment, all 17 FAAs of grain were significantly higher than the control, by 46.26%. Both microbial-aging and water-washing amelioration of hydrochar had a positive effect on rice yield and FAAs, with the former exhibiting better prospects for application. This study will provide a new direction for cleaner recycling and utilization of biowaste.

Co-contaminated soils by organic pollutants (OPs), antibiotics and antibiotic resistance genes (ARGs) have been becoming an emerging problem. However, it is unclear if an interaction exists between mixed pollutants and ARG abundance. Therefore, the potential relationship between OP contents and ARG and class 1 integron-integrase gene (intI1) abundance was investigated from seven dairy farms in Nanjing, Eastern China. Phenanthrene, pentachlorophenol, sulfadiazine, roxithromycin, associated ARG genes, and intI1 had the highest detection frequencies. Correlation analysis suggested a stronger positive relationship between the ARG abundance and the bioaccessible OP content than the total OP content. Additionally, the significant correlation between the bioaccessible mixed pollutant contents and ARG/intI1 abundance suggested a direct/indirect impact of the bioaccessible mixed pollutants on soil ARG dissemination. This study provided a preliminary understanding of the interaction between mixed pollutants and ARGs in co-contaminated soils.

Hydrothermal carbonization (HTC) thermally converts wet biomasses to carbon materials, dramatically reducing energy use for drying and improving solid product yield compared to pyrolysis process. However, researches regarding agricultural usage of hydrochar (HC) are limited. In the present study, the influence of HC amendment on CH4 and N2O emissions, as well as global warming potential (GWP) and greenhouse gas intensity (GHGI) were investigated. Additionally, pyrochar (PC) treatments as well as two char-free control treatments with (CKU) or without (CK) N fertilizer were also included for comparison. Chars were produced from wheat straw (WC) and saw dust (SC) and applied at different rates (0.5% and 3%, w/w). Both hydrochar and pyrochar decreased paddy CH4 emissions when amended at a lower rate (0.5%) compared to CKU treatment, which was more obvious for pyrochar when applied at the rate of 3%. Contrarily, 3%-HC significantly stimulated CH4 emissions, which were around 5 and 3 times higher than that of CKU for WC and SC, respectively. Furthermore, hydrochar showed the potential to decrease paddy N2O emissions (6.06–32.32%) at both application rates. However, N2O emissions with PC treatments varied depending on application rate (20.20–75.76%). GWP and GHGI values of 0.5%-HC and PC treatments were similar, 6.67–25.00% and 3.85–25.00% lower than those of CKU treatment, respectively. However, 3%-HC amendments led to significantly increased GWP and GHGI. This study suggested that application rate of hydrochar used in rice fields should be taken into serious consideration to fulfill its potential in GHGs mitigation and minimize environmental side effects.

Clay-hydrochar composites (CHCs) are of great significance in ammonium (NH4+) adsorption and have the potential to be applied to paddy fields to prevent ammonia (NH3) volatilization. In this study, three CHCs were produced by infusing different clays to poplar-sawdust-derived hydrochar, including a bentonite hydrochar composite (BTHC), montmorillonite hydrochar composite (MTHC), and kaolinite hydrochar composite (KTHC). These three CHCs were applied to a paddy soil column system growing rice. The temporal variations in NH3 volatilization and NH4+ loss in floodwater were monitored after three fertilization dates. The results showed that among the three CHCs, only the BTHC significantly reduced cumulative NH3 volatilization (by 41.8%), compared to that of the unamended control (without addition of hydrochar or clay-hydrochar-composite). In the unamended control, NH3 volatilization loss accounted for 31.4% of the applied N fertilizer; with the BTHC amendment, NH3 volatilization loss accounted for 17.4% of the applied N fertilizer. The reduced N loss via the BTHC amendment resulted in an increased N supply and further improved the N use efficiency and yield by 37.36% and 18.8% compared to that of the control, respectively. The inhibited NH3 volatilization was mainly attributed to the increased soil NH4+ retention as a result of BTHC's larger pore volume and specific surface area. In addition, the BTHC treatment significantly reduced the abundance of archaeal amoA genes (AOA), which possibly inhibited nitrification and increased soil NH4+ retention. This study, for the first time, screened BTHC as an excellent material for mitigating NH3 volatilization from paddy fields. The reduced NH3 volatilization loss might contribute to increased soil N retention and plant N use efficiency.

Tofu is a traditional product made mainly from soybeans, which has become globally popular because of its inclusion in vegetarian, vegan, and hypocaloric diets. However, with both commercial production of tofu and scientific research, it remains a challenge to produce tofu with high quality, high nutrition, and excellent flavor. This is because tofu production involves multiple complicated steps, such as soybean selection, utilization of appropriate coagulants, and tofu packaging. To make high-quality tofu product, it is important to systematically understand critical factors that influence tofu quality. This article reviews the current research status of tofu production. The diversity of soybean seeds (the raw material), protein composition, structural properties, and nutritional values are reviewed. Then, selection of tofu coagulants is reviewed to provide insights on its role in tofu quality, where the focus is on the usage of mix coagulants and recent developments with new coagulants. Moreover, a comprehensive summary is provided on recent development in making high-fiber tofu using Okara (the major by-product during tofu production), which has a number of potential applications in the food industry. To help encourage automatic, environmental friendly, and high-efficient tofu production, new developments and applications in production technology, such as ultrasound and high-pressure process, are reviewed. Tofu packaging, including packaging materials and techniques, is evaluated as it has been found to have a positive impact on extending the shelf life and improving the quality of tofu products. Finally, the future research directions and potential areas for new developments are discussed.

Hydrothermal carbonization (HTC) of food waste is a promising technology to dispose these widely generated and notorious wastes. Food waste hydrochar (FWHTC) was produced during this process. However, production and application of FWHTC remained at embryo stage. Herein, this study for the first time produced leftover steamed bread hydrochar (LSHTC) and pitaya peel hydrochar (PPHTC), and then applied them to adsorptive remove rare earth ions (REI) from wastewater. FWHTCs were systematically characterized by SEM, FTIR, XPS, BET, elemental analysis and TG-DSC. Isotherm study showed that Langmuir model fitted the data well at lower initial REI concentrations while Freundlich model fitted better at higher concentrations. The maximum adsorption capacity of LSHTC for La3+ reached 108 mg g−1. Continuous adsorption experiment in adsorption column was also conducted and key operation parameters were predicted by Yoon-Nelson model. The adsorption mechanisms were dominated by physisorption (electrostatic attraction) at the very starting stage, followed by chemisorption (ion exchange and/or surface complexation) playing a key role. At last, a sustainable “Reduce-Reuse-Recycle” pattern of food waste disposal methodology was proposed.

Attribute value extraction refers to the task of identifying values of an attribute of interest from product information. It is an important research topic which has been widely studied in e-Commerce and relation learning. There are two main limitations in existing attribute value extraction methods: scalability and generalizability. Most existing methods treat each attribute independently and build separate models for each of them, which are not suitable for large scale attribute systems in real-world applications. Moreover, very limited research has focused on generalizing extraction to new attributes.

Hydrochar (HC) serves as a promising adsorbent to remove the cadmium from aqueous solution due to porous structure. The chemical aging method is an efficient and easy-operated approach to improve the adsorption capacity of HC. In this study, four chemical aging hydrochars (CAHCs) were obtained by using nitric acid (HNO3) with mass fractions of 5% (N5-HC), 10% (N10-HC), and 15% (N15-HC) to age the pristine HC (N0-HC) and remove the Cd2+ from the aqueous solution. The results displayed that the N15-HC adsorption capacity was 19.99 mg g−1 (initial Cd2+ concentration was 50 mg L−1), which increased by 7.4 folds compared to N0-HC. After chemical aging, the specific surface area and oxygen-containing functional groups of CAHCs were increased, which contributed to combination with Cd2+ by physical adsorption and surface complexation. Moreover, ion exchange also occurred during the adsorption process of Cd2+. These findings have important implications for wastewater treatment to transform the forestry waste into a valuable adsorbent for Cd2+ removal from water.

Attribute value extraction refers to the task of identifying values of an attribute of interest from product information. Product attribute values are essential in many e-commerce scenarios, such as customer service robots, product ranking, retrieval and recommendations. While in the real world, the attribute values of a product are usually incomplete and vary over time, which greatly hinders the practical applications. In this paper, we introduce MAVE, a new dataset to better facilitate research on product attribute value extraction. MAVE is composed of a curated set of 2.2 million products from Amazon pages, with 3 million attribute-value annotations across 1257 unique categories. MAVE has four main and unique advantages: First, MAVE is the largest product attribute value extraction dataset by the number of attribute-value examples. Second, MAVE includes multi-source representations from the product, which captures the full product information with high attribute coverage. Third, MAVE represents a more diverse set of attributes and values relative to what previous datasets cover. Lastly, MAVE provides a very challenging zero-shot test set, as we empirically illustrate in the experiments. We further propose a novel approach that effectively extracts the attribute value from the multi-source product information. We conduct extensive experiments with several baselines and show that MAVE is an effective dataset for attribute value extraction task. It is also a very challenging task on zero-shot attribute extraction. Data is available at \urlhttps://github.com/google-research-datasets/MAVE .

Abstract The development of biochar-based granule-like adsorbents suitable for scaled-up application has been attracting increasing attention in the field of water treatment. Herein, a new formable porous granulated biochar loaded with La-Fe(hydr)oxides/montmorillonite (LaFe/MB) was fabricated via a granulation and pyrolysis process for enhanced phosphorus (P) removal from wastewater. Montmorillonite acted as a binder that increased the size of the granulated biochar, while the use of Fe promoted the surface charge and facilitated the dispersion of La, which was responsible for selective phosphate removal. LaFe/MB exhibited rapid phosphate adsorption kinetics and a high maximum adsorption capacity (Langmuir model, 52.12 mg P g −1 ), which were better than those of many existing granulated materials. The desorption and recyclability experiments showed that LaFe/MB could be regenerated, and maintained 76.7% of its initial phosphate adsorption capacity after four adsorption cycles. The high hydraulic endurance strength retention rate of the developed material (91.6%) suggested high practical applicability in actual wastewater. Electrostatic attraction, surface precipitation, and inner-sphere complexation via ligand exchange were found to be involved in selective P removal over a wide pH range of 3–9. The thermodynamic parameters were determined, which revealed the feasibility and spontaneity of adsorption. Based on approximate site energy distribution analyses, high distribution frequency contributed to efficient P removal. The research results provide a new insight that LaFe/MB shows great application prospects for advanced phosphate removal from wastewater. Graphical Abstract

Photocatalytic removal of ammonium-nitrogen ( NH4+ -N) from water using solar energy is an approach of high interest and applicability due to the convenience in application. ZnO has a great potential in photocatalytic decomposition of NH4+ -N and conversion of this nutrient to under visible light irradiations. However the applicability of pristine ZnO though is limited due to its reduced capacity to utilize light from natural light. Herein, we report a two-step ZnO-modified strategy (Cu-doped ZnO nanoparticles, immobilized on reduced graphene oxide (rGO) sheets) for the promotion of photocatalytic degradation of NH4+ -N under visible light. UV-Vis spectra showed that the Cu/ZnO/rGO can be highly efficient in the utilization of photons from the visible region. Hence, Cu/ZnO/rGO managed to demonstrate adequate photocatalytic activity and effective NH4+ -N removal from water under visible light compared to single ZnO. Specifically, up to 83.1% of NH4+ -N (initial concentration 50 mg·L-1, catalyst dosage 2 g·L-1, pH 10) was removed within 2 h retention time under Xe lamp irradiation. From the catalysis, the major by-product was N2. The high ammonia degradation efficiency from the ZnO/Cu/rGO is attributed to the improvement of the reactive oxygen species (ROSs) production efficiency and the further activation of the interfacial catalytic sites. This study also demonstrated that such nanocomposite is a recyclable agent. Its NH4+ -N removal capacity remained effective even after five batch cycles. In addition, Cu/ZnO/rGO was applied to treat real domestic wastewater, and it was found that chemical oxygen demand (COD), total nitrogen (TN) and total phosphorus (TP) removal efficiencies can reach 84.3, 80.7, and 90.3%, respectively. Thus, Cu/ZnO/rGO in the presence of solar light can be a promising photocatalyst in the field of wastewater treatment.

Nutrient emissions from paddy fields are one of the main sources of agricultural non-point source (NPS) pollution. Based on the “4R” (Reduce-Retain-Reuse-Restore) strategical system of agricultural NPS pollution control, ecological ditches are effective control measures under the “Retain” system. In this study, the nutrient removal efficiency and stoichiometric variations in three different ecological ditch systems were studied in order to better understand the long-term performance of ecological ditches, and to determine which type of ecological ditch system (Eh, concrete ecological ditch with holes on the wall; Ec, concrete ecological ditch; and Es, soil ecological ditch) is optimal for the removal of agricultural NPS pollutants. The results indicated that the converted ecological ditch (Eh type) significantly reduced nutrient levels in two-year rice season runoff compared to a traditional concrete ditch. The average removal efficiencies of total organic carbon (TOC), total nitrogen (TN) and total phosphorus (TP) in the converted ecological ditch were 20.8 %, 37.0 %, and 44.4 %, respectively. All ecological ditch types had considerable capacity to remove nutrients in simulated rice season runoff. There were no significant differences in the efficiency of nutrient removal between Eh (TOC 24.1 %, TN 42.8 %, and TP 52.6 %) and Es (TOC 20.3 %, TN 35.7 %, and TP 47.9 %). However, the results indicated that Eh systems could provide a relatively stable environment for plants with increased capacity to maintain biological homeostasis. Of the three ditch types, Ec (TOC 12.9 %, TN 23.3 %, and TP 32.6 %) had a relatively low removal efficiency. Redundancy analysis (RDA) indicated that leaf P content, sediment C:N ratio and root N content were more closely related to water variables, and nutrient stoichiometric characteristics of water, plants, and sediment systems were significantly related to the nutrient removal capacity of ecological ditches (99.5 % of the total variation). It is anticipated that this study will promote further development of the “4R” strategical system, and encourage additional improvements to ecological ditches so they can become more effective in reducing agricultural NPS pollution in the field.

Surface runoff is the main cause of farmland nitrogen (N) losses in plain areas, which adversely affect water quality.The impact of fertilization on N runoff loss often varies.A meta-analysis was performed using 245 observations from 31 studies in China, to estimate the response of N loss in both paddy and upland fields subjected to different fertilization strategies, and investigate the link between N runoffs, soil properties, as well as precipitation in planting season.The results showed that compared to the control (without fertilization), N losses subjected to fertilization increased from 3.31 kg/ha to 10.03 kg/ha and from 3.00 kg/ha to 11.24 kg/ha in paddy and upland fields respectively.Importantly, paddy N loss was significantly correlated with fertilizer type and N application rate (predictors); in upland fields N application rate and seasonal precipitation were the main driving factors.For the N application rate, N loss increased with increase in rates for both paddies and upland fields.Moreover, the N loss from upland fields increased with the precipitation during planting season.Between the three fertilizers used in paddies, the increase in loss of CRF (controlled release fertilizer) or OF (organic fertilizer) was lower than that of CF (inorganic chemical fertilizer) with the lowest value in CRF.Subset analysis showed that the effect of CRF and OF in paddies was not affected by the predictors, revealing the steadily controlling property of CRF and OF in paddies.Also, all the predictors had an insignificant impact to N loss risk in paddies during the high application rate.Overall, the results confirm the importance of N dosage in N runoff loss from farmland.Fertilizer type is a key consideration for N loss control in paddies, while the seasonal precipitation should not be ignored in upland fields.

In this study, La(OH) 3 /g-C 3 N 4 photocatalyst was designed for degradation of tetracycline hydrochloride (TCH) under visible light.

To understand the impacts of wood vinegar (WV), a by-product of biochar production, on N2O and CH4 emissions and their total global warming potential (GWPt) from N-fertilized rice paddy soil, a soil column experiment was conducted using three treatments: 240 kg urea-N ha−1 accompanied with 0, 5, and 10 t WV ha−1, respectively. Results showed that N2O and CH4 emission flux patterns were dominated by water regime of rice growth cycle, which was independent with WV application. The total N2O, CH4 emission loads and GWPt over rice season of three N received treatments were 6.41–8.85 kg ha−1, 127.7–405.0 kg ha−1, and 5.24–12.03 t CO2-e ha−1, respectively. Rice seasonal N2O and CH4 emissions were synchronously mitigated by 22.4% and 36.4%, respectively, when WV was applied at 5 t ha−1. Consequently, 5 t ha−1 WV treatment reduced 31.5% of GWPt compared with the urea treatment. In addition, 10 t ha−1 WV treatment exerted a more positive effect on suppressing N2O with 27.6% reduction. However, it increased GWPt by 57.2% because its CH4 emission load was increased by 101.8%. In conclusion, WV amendment applied at an appropriate rate (5 t ha−1) or combination with other CH4 control technologies were suggested to reduce both N2O and CH4 emissions and thereby the GWPt in N-fertilized rice paddy soil.

Both biochar (BC) and wood vinegar (WV) influence the nitrous oxide (N2O) and methane (CH4) emissions from agricultural systems. However, the impacts of BC and WV co-application on rice production, N2O and CH4 emissions are not well documented. We here conducted a two-year soil columns experiment with four treatments: WV (5 t WV ha−1), BC (7.5 t BC ha−1), WV + BC (5 t WV ha−1 +7.5 t BC ha−1) and a control (no treatment). The results showed that BC and WV + BC produced higher rice grain yield than the control by 14.1–15.9% in 2016 and by 4.1–5.2% in 2017, respectively. While WV increased rice grain yield by 11.2% in 2016, it had no significant influence on yield in 2017. Both WV and BC significantly mitigated N2O emissions by 22.4–41.8% in 2016 and 22.4–36.9% in 2017, respectively. Interestingly, WV + BC treatment showed the highest N2O mitigation efficiency, with a 52.9–62.8% mitigations in 2016 and 2017. Furthermore, the co-application of WV and BC significantly mitigated CH4 emissions by 42.6% in 2016 and 35.3% in 2017, respectively, while applying WV or BC alone had no annually-consistent mitigation effect on CH4 emissions. Overall, GWPt of rice growth cycle was most significantly suppressed by WV + BC with a 48.7–56.1% reduction, followed by WV and BC with 20.4–28.0% and 19.7–35.7% reductions, respectively. Consequently, the WV + BC treatment had the highest GHGI mitigation effect, averaging with 56.7% over two consecutive rice growth cycles. In conclusion, co-application of WV and BC is recommended for rice cultivation, which can both improve rice yield and minimize GHG emissions.

With the favorable microporous structure and excellent adsorption capacity, clay-hydrochar composites (CHCs) serve as promising materials to mitigate greenhouse gas emissions (GHG) from the paddy fields. Three clays were co-pyrolyzed with hydrochar derived from poplar sawdust to obtain CHCs, which were applied to the paddy fields to investigate the effects on methane (CH4) and nitrous oxide (N2O) emissions. Three CHCs were labeled as bentonite-hydrochar composite (BTHC), montmorillonite-hydrochar composite (MTHC), and kaolinite-hydrochar composite (KTHC), respectively. The effects of these three CHCs on GHG emissions were determined by monitoring the dynamic CH4 and N2O emissions in the paddy soil column ecosystem during the rice-growing season. The results showed that compared with the control group, three CHCs significantly mitigated CH4 and N2O emissions by 21.4%–47.5% and 5.2%–36.8%, respectively. Furthermore, the fluorescent components result displayed CHCs increased humic-like content by 29.62%–59.72%. A structural equation model was used to assess the hypothesis mitigation mechanism, which exemplified that GHG emissions negatively correlated with pmoA and nosZ genes, possibly resulting in the CH4 and N2O mitigation. Among the three CHCs, the KTHC amendment mitigated the CH4 and N2O emissions by 47.5% and 36.8%, respectively, which was superior to BTHC and MTHC. Hence, it was recommended for application to the field. Overall, this study demonstrates the mitigating effects of CHCs on GHG emissions for the first time, and the reduced CH4 and N2O emissions could contribute to increased soil C and N retention for better agricultural nutrients management.

Soils are exposed to various types of chemical contaminants due to anthropogenic activities; however, research on persistent organic pollutants and the existence of antibiotic resistance genes (ARGs) is limited. To our knowledge, the present work for the first time focused on the bioremediation of soil co-contaminated with pyrene and tetracycline/sulfonamide-resistance genes. After 90 days of incubation, the pyrene concentration and the abundance of the four ARGs (tetW, tetM, sulI, and sulII) significantly decreased in different treatment conditions (p<0.05). The greatest pyrene removal (47.8%) and greatest decrease in ARG abundance (from 10(-7) to 10(-8) ARG copies per 16S rRNA copy) were observed in microcosms with a combination of bacterial and sophorolipid treatment. Throughout the incubation, pyrene bioaccessibility constantly declined in the microcosm inoculated with bacteria. However, an increased pyrene bioaccessibility and ARG abundance at day 40 were observed in soil treated with sophorolipid alone. Tenax extraction methods and linear correlation analysis indicated a strong positive relationship between the rapidly desorbing fraction (Fr) of pyrene and ARG abundance. Therefore, we conclude that bioaccessible pyrene rather than total pyrene plays a major role in the maintenance and fluctuation of ARG abundance in the soil.

Split fertilization strategy is popularly adopted in rice to synchronize soil nitrogen (N) supply and crop N demand. Attention has been paid more on mid-season topdressing N, but limited on basal N. A clearer understanding of the basal N fate under split fertilization is crucial for determining rational basal N split ratio to improve the yield and reduce the loss to environment. A two-year field experiment with two N rates of 150 and 300 kg N ha−1, two split ratios of basal N, 40% and 25%, and two rice varieties, Wuyunjing 23 (japonica) and Y-liangyou 2 (super hybrid indica), was conducted. Labelled 15N urea was supplied in micro-plots as basal fertilizer to determine the plant uptake, translocation, soil residual, and loss of basal N fertilizer. The results showed that basal N absorbed by rice was only 1.6%–11.5% before tillering fertilization (8–10 d after transplanting), 6.5%–21.4% from tillering fertilization to panicle fertilization, and little (0.1%–4.4%) after panicle fertilization. The recovery efficiency of basal N for the entire rice growth stage was low and ranged from 18.7% to 24.8%, not significantly affected by cultivars or N treatments. Soil residual basal N accounted for 10.3%–36.4% and decreased with increasing total N rate and basal N ratio, regardless of variety and year. 43.8%–70.4% of basal N was lost into the environment based on the N balance. Basal N loss was significantly linearly positive related with the basal N rate and obviously enhanced by the increasing basal N ratio for both varieties in both 2012 and 2013. The N use efficiency and yield was significantly improved when decreasing the basal N ratio from 40% to 25%. The results indicated that the basal N ratio should be reduced, especially with limited N inputs, to improve the yield and reduce the N loss to the environment.

Straw incorporation and domestic sewage irrigation have been recommended as an environmentally friendly agricultural practice and are widely used not only in China but also in other countries. The individual effects on yield and environmental impacts have been studied extensively, but the comprehensive effect when straw returning and domestic sewage irrigation are combined together has seldom been reported. This study was conducted to examine the effects of straw returning and domestic sewage irrigation on rice yields, greenhouse gas emissions (GHGs) and ammonia (NH3) volatilization from paddy fields from 2015 to 2016. The results showed that the rice yield was not affected by the irrigation water sources and straw returning under the same total N input, which was similar in both years. Due to the rich N in the domestic sewage, domestic sewage irrigation could reduce approximately 45.2% of chemical nitrogen fertilizer input without yield loss. Compared to straw removal treatments, straw returning significantly increased the CH4 emissions by approximately 7–9-fold under domestic sewage irrigation and 13–14-fold under tap water irrigation. Straw returning also increased the N2O emissions under the two irrigation water types. In addition, the seasonal NH3 volatilization loss was significantly increased by 88.8% and 61.2% under straw returning compared to straw removal in 2015 and 2016, respectively. However, domestic sewage irrigation could decrease CH4 emissions by 24.5–26.6%, N2O emissions by 37.0–39.0% and seasonal NH3 volatilization loss by 27.2–28.3% under straw returning compared to tap water irrigation treatments. Global warming potentials (GWP) and greenhouse gas intensities (GHGI) were significantly increased with straw returning compared with those of straw removal, while they were decreased by domestic sewage irrigation under straw returning compared to tap water irrigation. Significant interactions between straw returning and domestic sewage irrigation on NH3 volatilization loss, CH4 and N2O emissions were observed. The results indicate that domestic sewage irrigation combined with straw returning could be an environmentally friendly and resource-saving agricultural management measure for paddy fields with which to reduce the chemical N input, GHG emissions, and NH3 volatilization loss while maintaining high rice productivity.

Staphylococcus aureus (S. aureus) is one of the most common pathogens causing both human and animal infections. Transmission of S. aureus to humans via contaminated food continues to be a health public concern. In the present study, 104 strains including eight MRSA strains were identified from 507 chicken samples (20.5%) in three cities of China. These strains harbored the highest resistance against penicillin (91.4%), followed by tetracycline (64.4%), erythromycin (53.5%), and kanamycin (32.7%). We used spa typing to classify these isolates into 28 types belonging to two lineages including the predominant type t112 (n = 26) and four newly identified spa types. Among the 104 strains, six carried the CRISPR-Cas system, a prokaryotic immune system which protects against foreign genetic elements. Interestingly, rpoB gene sequencing demonstrated that these six initially designated ST2250 strains were in fact S. argenteus, a novel Staphylococcus species genetically closely related to S. aureus. Three Staphylococcus CRIPSR types containing ten spacers identified in these strains have been reported in CRISPR-positive S. aureus. Additionally, 80% of the spacers showed homology to S. aureus phages demonstrating that these conserved spacers were closely related to the phages in the environment of S. argenteus. We speculated that the identical CRISPR types and spacers in both S. argenteus and S. aureus have resulted via exchange of mobile elements between these two species. Emergence of food-borne ST2250 S. argenteus is a potential threat to human public health.

Inhibiting reductive transformation of arsenic (As) in flooded paddy soils is fundamentally important for mitigating As transfer into the food chain. In this study, oxygen-nanobubble-loaded-zeolites (ZON) and -vermiculites (VON) were tested as a novel approach for supplying oxygen to paddy soils to inhibit As influx into rice. The dynamic physio- and bio-chemical variations in the rhizosphere and bulk soil were profiled in a rhizobox experiment. Upon adding ZON and VON, the redox potential and dissolved oxygen consistently increased throughout the cultivation period. The improved redox environment inhibited As(III) release into porewater and increased As(V) adsorbed on crystalline Fe (hydr)oxides, following the reduction of arsC and arrA gene abundances and enhancement of the aioA gene. Moreover, adding ZON and VON promoted root iron plaque formation, which increased As retention on iron plaque. Both ZON and VON treatments mitigated As translocation from soil to rice, meanwhile increasing root and shoot biomass. ZON was superior to VON in repressing As transfer and promoting rice growth due to its higher oxygen loading capacity. This study provides a novel and environment-friendly material to both mitigate the As translocation from paddy soil to rice and improve rice growth.

Abstract Belowground fertilization is a prevalent strategy for considerable grain yield and N utilization. However, the optimal fertilization depth remains uncertain in paddies, especially for slow/controlled release fertilizers. This study aimed to clarify the effect of deep “controlled‐release blended fertilizer” (CRBF) fertilization on rice ( Oryza sativa L.) yield and N utilization. Two N‐fertilizer types were selected (a) urea and (b) CRBF, both combined at three fertilization depths (a) 0 cm, (b) 5 cm, and (c) 10 cm. The results showed that the grain yield was significantly affected by fertilizer type and fertilization depth. The yield achieved from CRBF was 7.8% higher than that from the urea application. Deep fertilization could also increase the rice yield with the optimum achieved from the 5‐cm depth fertilization (yield increased by 15.1% compared to that from the manual surface fertilization). Overall, the 5‐cm depth CRBF fertilization achieved the highest yield among all treatments with 12.21 and 11.84 t ha –1 for 2018 and 2019, respectively. The larger sink was the main reason for this performance. Additionally, the higher photosynthetic efficient population after earing was another principal driver to the higher yield from CRBF. Due to the higher N uptake, CRBF application increased both N partial factor productivity (PFP) and recovery efficiency (RE) ( P &lt; .05); fertilization depth also had a striking effect on PFP and RE ( P &lt; .05 or .01). The 5‐cm depth fertilization of CRBF achieved the highest N utilization for both years. The results suggest that 5‐cm depth fertilization combined with controlled‐release fertilizer is a suitable strategy for higher rice yield and N utilization.

Hydrochars-based dissolved organic matters (DOM) are easily available to organisms and thus have important influence on the biota once applying hydrochars as environment amendment. Thus, positive modifications on molecular composition of DOM is indispensable before hydrochars application. In this study, the impacts of microbial-aging by anaerobic fermentation on DOM of agro-waste-hydrochars was systematically assessed. Results revealed that microbial-aging caused lower DOM release but higher DOM molecular diversity. Moreover, microbial-aging resulted in the production of more biodegradable compounds, including lipids and proteins, and reduced the aromaticity of DOM. The highly oxygenated molecules (O/C > 0.6) were shifted into lower-order ones in the hydrochars-based DOM, suggesting the transformation of hydrophilic compounds into hydrophobic ones. Additionally, microbial-aging promoted the degradation of phenols by 99.0–98.9%, phenolic acids 37.8–73.5%, and polycyclic aromatic hydrocarbons by 83.4–90.4% in hydrochar-based DOM. Overall, this study demonstrates that microbial-aging changes the molecular characteristics of hydrochars-based DOM in a positive manner.

Biogas slurry (BS) and bio-waste hydrothermal carbonization aqueous phase (HP) are nutrient-rich wastewater. To prevent environment contamination, transforming BS and HP into synthetic fertilizers in the agricultural field can potentially realize resource utilization. We hypothesized that acidic HP could neutralize alkaline BS, adjusting floodwater pH from 6.88 to 8.00 and mitigating ammonia (NH3) volatilization from the paddy soil. In this soil column study, the mixture of BS and HP was applied to paddy soil to substitute 50%, 75%, and 100% to urea. With a low (L) or high (H) ratio of HP, treatments were labeled as BCL50, BCL75, BCL100, BCH50, BCH75, and BCH100. Results showed that microbial byproduct- and fulvic acid-like substance were the main components in BS and HP using 3D-EEM analysis, respectively. Co-application of BS and HP mitigated the NH3 volatilization by 4.2%–65.5% compared with CKU. BCL100 and BCH100 treatments significantly (P < 0.05) mitigated NH3 volatilization by 65.5% and 56.8%, which also significantly (P < 0.05) mitigated the yield-scale NH3 volatilization by 49.6% and 42.3%, compared with CKU. The low NH4+-N concentration and pH value in floodwater were the main reason explained the NH3 mitigation. Therefore, this study demonstrated that BS and HP co-application can substitute the urea as a valuable N fertilizer in a rational rate and meanwhile mitigate the NH3 volatilization. This study will provide new ideas for the utilization of BS and HP resources in the context of ammonia mitigation.

To improve the efficiency of wastewater treatment and characterize the microorganism communities, microorganisms were cultured and concentrated in hybrid bioreactors at a low temperature (∼4 °C, low-temperature hybrid bioreactor, LTHB) and room temperature (∼25 °C, room-temperature hybrid bioreactor, RTHB). The performance of the LTHB and RTHB in terms of COD removal efficiency, dehydrogenase activity and functional diversity of microbial communities were evaluated. The results show COD removal efficiency increased gradually over time from 39.76% to 66.27% for LTHB and fluctuated between 81.85% and 94.78% for RTHB. The dehydrogenase activity and microbial activity in LTHB was higher than those in RTHB, implying that microorganisms cultured at low temperature had higher activities and adaptabilities than those cultured at room temperature. This study suggests that hybrid bioreactors can treat wastewater at both low and room temperatures and provides valuable insight into the adaptation processes of the microorganisms during temperature changes.

Predicting human performance in interaction tasks allows designers or developers to understand the expected performance of a target interface without actually testing it with real users. In this work, we present a deep neural net to model and predict human performance in performing a sequence of UI tasks. In particular, we focus on a dominant class of tasks, i.e., target selection from a vertical list or menu. We experimented with our deep neural net using a public dataset collected from a desktop laboratory environment and a dataset collected from hundreds of touchscreen smartphone users via crowdsourcing. Our model significantly outperformed previous methods on these datasets. Importantly, our method, as a deep model, can easily incorporate additional UI attributes such as visual appearance and content semantics without changing model architectures. By understanding about how a deep learning model learns from human behaviors, our approach can be seen as a vehicle to discover new patterns about human behaviors to advance analytical modeling.

Abstract To elucidate the mechanism of adaptation of leguminous plants to iron (Fe)‐deficient environment, comprehensive analyses of soybean ( Glycine max ) plants (sampled at anthesis) were conducted under Fe‐sufficient control and Fe‐deficient treatment using metabolomic and physiological approach. Our results show that soybeans grown under Fe‐deficient conditions showed lower nitrogen (N) fixation efficiency; however, ureides increased in different tissues, indicating potential N‐feedback inhibition. N assimilation was inhibited as observed in the repressed amino acids biosynthesis and reduced proteins in roots and nodules. In Fe‐deficient leaves, many amino acids increased, accompanied by the reduction of malate, fumarate, succinate, and α‐ketoglutarate, which implies the N reprogramming was stimulated by the anaplerotic pathway. Accordingly, many organic acids increased in roots and nodules; however, enzymes involved in the related metabolic pathway (e.g., Krebs cycle) showed opposite activity between roots and nodules, indicative of different mechanisms. Sugars increased or maintained at constant level in different tissues under Fe deficiency, which probably relates to oxidative stress, cell wall damage, and feedback regulation. Increased ascorbate, nicotinate, raffinose, galactinol, and proline in different tissues possibly helped resist the oxidative stress induced by Fe deficiency. Overall, Fe deficiency induced the coordinated metabolic reprogramming in different tissues of symbiotic soybean plants.

Periphyton plays a significant role in heavy metal transfer in wetlands, but its contribution to cadmium (Cd) bioavailability in paddy fields remains largely unexplored. The main aim of this study was to investigate the effect of periphyton on Cd behavior in paddy fields. Periphyton significantly decreased Cd concentrations in paddy waters. Non-invasive micro-test technology analyses indicated that periphyton can absorb Cd from water with a maximum Cd2+ influx rate of 394 pmol cm-2 s-1 and periphyton intrusion significantly increased soil Cd concentrations. However, soil Cd bioavailability declined significantly due to soil pH increase and soil redox potential (Eh) decrease induced by periphyton. With periphyton, more Cd was adsorbed and immobilized on organic matter, carbonates, and iron and manganese oxides in soil. Consequently, Cd content in rice decreased significantly. These findings give insights into Cd biogeochemistry in paddy fields with periphyton, and may provide a novel strategy for reducing Cd accumulation in rice.

Reusing domestic sewage for crop irrigation is a promising practice, particularly in developing countries, since it is a substitute for chemical fertilizer and reduces water contamination. More attention was paid to the effect of sewage irrigation on crop yield and soil nutrients, but little attention was paid to greenhouse gas (GHG) emission from straw-returning paddy fields. In this study, a soil column monitoring experiment was conducted to assess the effects of untreated domestic sewage (dominated with ammonia) and treated domestic sewage (dominated with nitrate) irrigation on methane (CH4), nitrous oxide (N2O) emission, and related soil microorganisms in straw-returning paddy fields. Results showed that straw-returning dramatically promoted CH4 emission but had little effect on N2O emission. Both untreated and treated domestic sewage irrigation decreased CH4 emission of straw-returning paddy whether nitrogen fertilizer applied or not. The mitigating effect of treated sewage irrigation on CH4 emission was greater than untreated sewage irrigation. CH4 emission had a significant correlation with the abundance of soil methanogens and methanogens/methanotrophs. N2O emission increased with untreated or treated domestic sewage irrigation, although the total N input, including the N carried by sewage water, was the same for all treatments. No significant correlation between N2O and denitrification functional genes was found in this study. Treated domestic sewage irrigation reduced the global warming potential (GWP) by 66.7%, but untreated domestic sewage had no evident influence on the GWP. Results indicated that treated domestic sewage irrigation could significantly inhibit CH4 emission and the GWP by decreasing the ratio of methanogens to methanotrophs, and is promising in mitigating GWP from straw-returned paddy fields.

Code review is one of the best practices as a powerful safeguard for software quality. In practice, senior or highly skilled reviewers inspect source code and provide constructive comments, consider- ing what authors may ignore, for example, some special cases. The collaborative validation between contributors results in code being highly qualified and less chance of bugs. However, since personal knowledge is limited and varies, the efficiency and effectiveness of code review practice are worthy of further improvement. In fact, it still takes a colossal and time-consuming effort to deliver useful review comments. This paper explores a synergy of multiple practical review comments to enhance code review and proposes AUGER (AUtomatically GEnerating Review comments): a review comments generator with pre-training models. We first collect empirical review data from 11 notable Java projects and construct a dataset of 10,882 code changes. By leveraging Text-to-Text Transfer Transformer (T5) models, the framework synthesizes valuable knowledge in the training stage and effectively outperforms baselines by 37.38% in ROUGE-L. 29% of our automatic review comments are considered useful according to prior studies. The inference generates just in 20 seconds and is also open to training further. Moreover, the performance also gets improved when thoroughly analyzed in case study.

Phosphorus (P) is a key limiting nutrient for crops. Oscillation of redox conditions usually induces formation of Fe-enriched cutans in the plow layer of paddy soils. This study investigated P biogeochemistry in the cutans, which were collected from high-yield paddy soils in Taihu Lake region, China. Mössbauer spectroscopy showed that the content of Fe3+ was eight times higher than Fe2+ in the cutans. Based on the evidences from XRD and wet chemical analysis, the enriched Fe in the cutans mostly existed as amorphous oxides, which owned high surface areas for P sorption. In addition, the cutans were composed of spherical particles with diameters of 20–130 μm under microscopy. Moreover , the particles showed evident "trench" structures on their top surface under SEM imaging. These features caused the cutans to retain three times higher P than that in the matrix soils. Furthermore, the cutans demonstrated both high microbial richness and community diversity, in contrast to the matrix soils. In particular, the abundance of phosphate-solubilizing fungi (with relatively highly competitive saprophytic ability) was also significantly promoted. Therefore, the cutans could be considered as hotspots of P accumulation in paddy soils. The subsequent enhancement of the available P would promote rice production.

Drainage ditches are used for surface water management as well as for the interception of pollutants from farmlands. In this study, ditches with floating ryegrass mat (FRM), Vallisneria natans (VN) and the combination of the two (FRMVN) (including an unamended control ditch) were trialed to evaluate the N interception rates of simulated, low-concentrated run offs at low temperature. The nitrogen removal efficiency of FRMs under low and high-water level (25 cm and 50 cm, respectively) was also investigated during a warmer period. The results showed that the NH4+ removal efficiency was fairly stable for the ditches with FRMs and the interception rates were 30.5% ∼ 46.0% for the low and high influent N concentration (5 mg L−1 and 15 mg L−1) respectively. These NH4+ interception rates were higher than those from the control, especially in the phases of high influent N. The NO3− and TN removal efficiency was kept low for all treatments especially during the cold period likely due to lack of readily available carbon source. Water level had no significant influence to the FRM-based TN, NH4+, and NO3− removal - interception rates though were higher compared to those from the Control ditches during the low N period. In terms of nitrogen budget, the N reduction from FRMs treatments was 8.4% ∼ 16.9% higher than those of the controls due to plant uptake, adsorption, and other pathways. Further improvement in denitrification can be achieved by supplementing cellulosic carbon.

Four types of vascular plant communities were established on a wasteland of the copper mined tailings located in Tongling, East China. Biotic crusts, as an earlier stage of primary succession or a ground-layer within plant communities, became widely distributed on the surface of the tailings wasteland. The major aim of this study is to investigate the relationship between biotic crusts and the chemical properties of the upper tailings. According to the difference in vascular plant communities, authors divided the tailings wasteland into six types of areas, i.e., Hippochaete ramosissimum + Zoysia sinica community area (Type 1), Imperata cylindrica community area (Type 2), Z. sinica community area (Type 3), Cynodon dactylon community area (Type 4), biotic crust area (no vascular plants, Type 5), and bare tailings area (Type 6). Each of Types 1–4 was again divided into subtype with biotic crusts and subtype without biotic crusts. Eighty samples of the upper tailings (area: 20 cm × 20 cm, depth: 0–3 cm) were collected. Then, pH, electrical conductivity, organic matter, total nitrogen, available phosphorus, available potassium, and water content were determined. Results showed that the bare tailings were very deficient in nutrients. Plant communities growing on the tailings wasteland, especially plant communities with biotic crusts, could significantly improve the water content and chemical properties of the upper tailings. Organic matter, total nitrogen, extractable potassium, water-soluble potassium, electrical conductivity, and water content in the upper tailings with biotic crusts (Subtypes 1.1, 2.1, 3.1 and 4.1) were 1.9–3.6, 3.3–10.7, 2.0–4.4, 2.4–5.9, 2.3–10.9 and 3.7–10.5 times that of the bare tailings, respectively. Compared to the bare tailings, pH values of the upper tailings of Subtypes 1.1, 2.1, 3.1 and 4.1 depressed 0.27–0.74 units. Compared to the four subtypes with biotic crusts, the effect of four subtypes without biotic crusts from the same type of vascular plant communities on the water content and chemical properties of the upper tailings was less. A comparison between Type 5 and Type 6 also indicated that biotic crusts could significantly improve the water content and chemical properties of the upper tailings. The contents of organic matter, total nitrogen, extractable potassium, water-soluble potassium, and water in the upper tailings of the former were 1.5, 2.0, 2.1, 2.4 and 5.0 times that of the later, respectively. Among four types of vascular plant communities, H. ramosissimum + Z. sinica community was the best and the C. dactylon community was the least in improving water content and chemical properties of the upper tailings. This investigation also indicated that the influence of biotic crusts on available phosphorus of the upper tailings was not significant. Increase of water content in the upper tailings caused by biotic crusts played a very important role in improving chemical properties of the upper tailings.

The purpose of this study was to treat complex wastewater consisting of domestic wastewater, tobacco processing and building materials washings. The proposed multi-level bioreactor consists of a biopond–biofilter, anoxic/aerobic (A/O) fluidized beds and a photoautotrophic system. The results show that when the hydraulic load of the bioreactor was 200m3/d, it successfully and simultaneously removed the organic matter and metals. When the bioreactor was in a relatively steady-state condition, the overall average organic matter and metals removal efficiencies are as follows, COD (89%), UV245 nm-matter (91%), Cu (78%), Zn (79%) and Fe (84%). The growth conditions of the native bacterial habitat were improved, which resulted from the increase of the in bacterial diversity under the rejuvenated conditions induced by the bioreactor. The results demonstrate that the multi-level bioreactor, without a sludge treatment system, can remove heterogeneous organic matter and metals from wastewater.

Core Ideas CSRF application (RBB basal , RBB BP , SCU BP ) increased the NUE in both seedling‐transplanted and direct‐seeded fields. Yield increase of resin‐blending controlled‐release fertilizer was better than that of sulfur‐coated fertilizer under the two planting modes. “Base‐panicle” fertilization with RBB and urea was suitable for the seedling‐transplanted mode. A single basal application of RBB was suitable for direct‐seeded mode for achieving the high yield. ABSTRACT To understand the response of rice yield and N utilization to controlled or slow‐release fertilizers (CSRFs) under direct‐seeded or seedling‐transplanted modes of rice production, a field experiment with rice variety Wuyunjing 23 was performed in 2013 and 2014. Five treatments, including two CSRFs: sulfur‐coated urea (SCU) and resin‐blending controlled‐release fertilizer (RBB), two fertilization modes: single basal application and a split “base‐panicle” (BP) application, and conventional split fertilization (CONV) as a control, were conducted. The results showed that there was no improvement of yield for SCU application compared with CONV in the seedling‐transplanted and direct‐seeded modes in both years. The yield increasing effect of RBB was better than that of SCU under the two planting modes. The interaction effect between the planting mode and fertilizer treatment on the yield was significant. The yield of RBB BP treatment was the highest in seedling‐transplanted fields, reaching 12.04 t ha −1 in 2013 and 13.44 t ha −1 in 2014. By contrast, the yield of RBB basal treatment was the highest in direct‐seeded rice, although the difference among the treatments was not significant. The CSRF application (RBB basal , RBB BP , SCU BP ) increased the NUE in both the seedling‐transplanted and direct‐seeded fields. Except for the NUE of RBB basal , which was the highest for direct‐seeded rice in 2013, the RBB BP treatment showed the highest NUE in seedling‐transplanted and direct‐seeded rice in both years. The results indicated that RBB increased the yield and NUE in both seedling‐transplanted and direct‐seeded modes, and the combined panicle urea and RBB was better in seedling‐transplanted fields, while a single basal application with RBB was better in direct‐seeded rice.

In the past year, the global epidemic situation is still not optimistic, showing a trend of continuous expansion. With the research and application of vaccines, there is an urgent need to develop some optimal vaccination strategies. How to make a reasonable vaccination strategy to determine the priority of vaccination under the limited vaccine resources to control the epidemic and reduce human casualties? We build a dynamic model with vaccination which is extended the classical SEIR model. By fitting the epidemic data of three countries-China, Brazil, Indonesia, we have evaluated age-specific vaccination strategy for the number of infections and deaths. Furthermore, we have evaluated the impact of age-specific vaccination strategies on the number of the basic reproduction number. At last, we also have evaluated the different age structure of the vaccination priority. It shows that giving priority to vaccination of young people can control the number of infections, while giving priority to vaccination of the elderly can greatly reduce the number of deaths in most cases. Furthermore, we have found that young people should be mainly vaccinated to reduce the number of infections. When the emphasis is on reducing the number of deaths, it is important to focus vaccination on the elderly. Simulations suggest that appropriate age-specific vaccination strategies can effectively control the epidemic, both in terms of the number of infections and deaths.

The application of waste biomass-derived hydrochar to soil may cause extremely intensive nitrous oxide (N2O) fluxes that can challenge our current mechanistic understanding of the global nitrogen cycle in the biosphere. In this study, two waste biomasses were used to prepare cyanobacterial biomas-derived hydrochar (CHC) and wheat straw-derived hydrochar (SHC) for short-term incubation experiments to identify their effects and mechanisms of waste biomass-derived hydrochar on soil N2O efflux, with time-series samples collected for N2O efflux and soil analysis. The results showed that CHC and SHC caused short-term bursts of N2O effluxes without nitrogen inputs. Moreover, the enrichment of exogenous organics and nutrients at the hydrochar-soil interface was identified as the key factor for enhancing N2O fluxes, which stimulated microbial nitrification (i.e., increased gene copy number of ammonia oxidizing bacteria) and denitrification (i.e., increased gene copy number of nitrate and N2O reducing bacteria) processes. The concentrations of Fe (II) and hydroxyl radicals (HO•) were 6.49 and 5.63 times higher, respectively, in the hydrochar layer of CHC than SHC amendment. Furthermore, structural equation models demonstrated that HO•, as well as soil microbiomes, played an important role in driving N2O fluxes. Together, our findings provide a deeper insight into the assessment and prognosis of the short-term environmental risk arising from agricultural waste management in integrated agriculture. Further studies under practical field application conditions are warranted to verify the findings.

Rainfed agriculture is important to meet the increasing demands of food production . However, there is a lack of knowledges for the rainfed wheat systems in abundant rainfall areas, where the erratic rainfall may constrain the wheat yield and increases N losses from wheat fields with excessive fertilizer inputs. In the present study, a 6 consecutive years field experiments were conducted to investigate the wheat yield and N losses responses to different N fertilizer rates in the Taihu Lake region. Despite the fluctuations in the wheat yield, a 10–30% reduction of the district average N input sustained the current-level of wheat yield for the 6 consecutive years. The N rate of 168 kg ha −1 might be the threshold N application rate, because if it was exceeded, it was no longer the predominant factor determining the wheat yield, but significantly increased the N losses fluxes. The seasonal total N losses fluxes were 69.2 kg N ha −1 , which accounted for 28.8% of district averaged N input. Runoff was the predominant pathway of N loss from the wheat field, followed by ammonia volatilization and leaching. Nitrate was the predominant form in the runoff and leakage water. Seasonal cumulative nitrate losses via runoff and ammonia volatilization averaged 25.2 and 20.1 kg ha −1 per wheat season, respectively, corresponding to 10.5% and 8.38% of the regional N application rates. However, the seasonal nitrate loss via leakage was the lowest, less than 8.98 kg ha −1 . Reducing the fertilizer N rates significantly decreased the N losses via runoff and ammonia volatilization, but not by leaching. Our findings indicated that reducing N fertilizer was impressive for the sustainable development of agriculture in Eastern China and 168 kg N ha −1 was recommended for the rainfed wheat. • Reducing N inputs (168–216 kg ha −1 ) sustained current-level of wheat yields for 6 years in rice-wheat rotation. • N loss (kg ha −1 ) was affected by, in order, N runoff (30.7) > ammonia volatilization (20.1) > nitrate leaching (11.0). • Precipitations, solar radiations and sunshine durations were the critical factors determining wheat yields.

Method names are crucial to program comprehension and maintenance. Recently, many approaches have been proposed to automatically recommend method names and detect inconsistent names. Despite promising, their results are still suboptimal considering the three following drawbacks: 1) These models are mostly trained from scratch, learning two different objectives simultaneously. The misalignment between two objectives will negatively affect training efficiency and model performance. 2) The enclosing class context is not fully exploited, making it difficult to learn the abstract functionality of the method. 3) Current method name consistency checking methods follow a generate-then-compare process, which restricts the accuracy as they highly rely on the quality of generated names and face difficulty measuring the semantic consistency.In this paper, we propose an approach named AUMENA to AUtomate MEthod NAming tasks with context-aware prompt-tuning. Unlike existing deep learning based approaches, our model first learns the contextualized representation(i.e., class attributes) of programming language and natural language through the pre-training model, then fully exploits the capacity and knowledge of large language model with prompt-tuning to precisely detect inconsistent method names and recommend more accurate names. To better identify semantically consistent names, we model the method name consistency checking task as a two-class classification problem, avoiding the limitation of previous generate-then-compare consistency checking approaches. Experiment results reflect that AUMENA scores 68.6%, 72.0%, 73.6%, 84.7% on four datasets of method name recommendation, surpassing the state-of-the-art baseline by 8.5%, 18.4%, 11.0%, 12.0%, respectively. And our approach scores 80.8% accuracy on method name consistency checking, reaching an 5.5% outperformance. All data and trained models are publicly available.

With the increasing security issues in the blockchain, smart contract vulnerability detection has gradually become the focus of research. Recently, many approaches have been proposed to detect smart contract vulnerabilities. Despite promising results, these approaches still have three drawbacks: 1) Symbolic execution and static analysis methods are constrained by predefined rules, which limits their adaptability to different vulnerabilities. 2) Most smart contract code contains abundant irrelevant information which is useless for vulnerability detection. 3) Pre-trained models fail to bridge the gap between pre-training and detecting smart contract vulnerabilities.To solve these problems, we propose an approach named PSCVFinder for detecting reentrancy vulnerability and times-tamp dependency vulnerability, which are two severe vulnerabilities in smart contract. To better detect these vulnerabilities, we propose CSCV which is a smart contract slicing method to reduce the irrelevant code. Unlike existing approaches, our model first learns the representation of programming language through the pre-training model, then fully exploits the capacity of large language model with prompt-tuning to precisely detect smart contract vulnerability. We conduct experiments on real-world dataset and the results reflect that PSCVFinder scores 93.83% and 93.49% on two kinds of vulnerabilities in F1-score, surpassing the state-of-the-art baseline by 1.14% and 4.02%, respectively.

The automation of code review activities, a long-standing pursuit in software engineering, has been primarily addressed by numerous domain-specific pre-trained models. Despite their success, these models frequently demand extensive resources for pre-training from scratch. In contrast, Large Language Models (LLMs) provide an intriguing alternative, given their remarkable capabilities when supplemented with domain-specific knowledge. However, their potential for automating code review tasks remains largely unexplored.In response to this research gap, we present LLaMA-Reviewer, an innovative framework that leverages the capabilities of LLaMA, a popular LLM, in the realm of code review. Mindful of resource constraints, this framework employs parameter-efficient fine-tuning (PEFT) methods, delivering high performance while using less than 1% of trainable parameters.An extensive evaluation of LLaMA-Reviewer is conducted on two diverse, publicly available datasets. Notably, even with the smallest LLaMA base model consisting of 6.7B parameters and a limited number of tuning epochs, LLaMA-Reviewer equals the performance of existing code-review-focused models.The ablation experiments provide insights into the influence of various fine-tuning process components, including input representation, instruction tuning, and different PEFT methods. To foster continuous progress in this field, the code and all PEFT-weight plugins have been made open-source.

Text-to-image generation is conducted through Generative Adversarial Networks (GANs) or transformer models. However, the current challenge lies in accurately generating images based on textual descriptions, especially in scenarios where the content and theme of the target image are ambiguous. In this paper, we propose a method that utilizes artificial intelligence models for thematic creativity, followed by a classification modeling of the actual painting process. The method involves converting all visual elements into quantifiable data structures before creating images. We evaluate the effectiveness of this approach in terms of semantic accuracy, image reproducibility, and computational efficiency, in comparison with existing image generation algorithms.

(1) Background: Excessive nitrogen (N) fertilizer application in tea plantations leads to challenges such as soil acidification and nitrogen loss, impending the sustainable development of the plantation system. Yet, there is a lack of research on blended fertilization strategies, and limited data regarding N loss when substituting with organic fertilizer. (2) Methods: A year-long field monitoring experiment was conducted to evaluate the effects of substituting compound fertilizer with organic fertilizer, specifically with respect to runoff N loss and uptake of chemical fertilizer N by tea trees. (3) Results: The annual runoff N loss ranged from 0.16 to 0.57 kg·hm−2 and accounted for a mere 0.22–0.48% of N from fertilizer applications. Substitution with organic fertilizer reduced runoff N loss by 21–53% and improved the tea tree utilization efficiency of chemical fertilizer N from 16% to 27%. A 50% organic fertilizer substitution (based on the amount of N) promoted a net soil N mineralization rate, creating an ammonium-rich environment favored by tea trees. (4) Conclusions: The positive effects of partially substituting N fertilizer with organic fertilizer in tea plantation systems on both N utilization efficiency and N loss were confirmed. If conditions permit, the study team would aim to expand the temporal scope of the study, and to investigate the impact of organic fertilizer substitution on N loss under various precipitation intensities.

This study aimed to research the effects of enzyme and ultrasound combined modification on the structure and gel properties of soy protein isolate (SPI). Different modified protein samples were obtained by hydrolyzing soy isolate with alkaline protease and pepsin at 0%, 0.1%, 0.5%, and 1.0% of hydrolysis by ultrasound treatment (400 W, 20 min). The results showed that the SPI particle size, which modified by combined enzyme and ultrasound treatment (co-modified), was significantly lower (P < 0.05) and the particle size was more evenly distributed compared with those of the single modified samples. The best improvement in solubility and turbidity was observed for the co-modified SPI. The Fourier transform–infrared spectroscopy showed the most significant changes in the secondary structure content of the co-modified SPI. The protein structure was unfolded, and the contents of free sulfhydryl and H0 were improved. Additionally, the co-modified SPI gel had a uniform and compact gel network and higher water-holding capacity (WHC) and gel strength. After frozen storage, the combined enzyme and ultrasound treatment showed better frozen storage stability than single treatment: the WHC of the gel decreased slightly, the gel strength increased slowly, and the gel network was less damaged. In conclusion, combined enzyme and ultrasound treatment could be effective in improving the SPI structure and gel properties.

Macros are building block tasks of our everyday smartphone activity (e.g., "login", or "booking a flight"). Effectively extracting macros is important for understanding mobile interaction and enabling task automation. These macros are however difficult to extract at scale as they can be comprised of multiple steps yet hidden within programmatic components of mobile apps. In this paper, we introduce a novel approach based on Large Language Models (LLMs) to automatically extract semantically meaningful macros from both random and user-curated mobile interaction traces. The macros produced by our approach are automatically tagged with natural language descriptions and are fully executable. We conduct multiple studies to validate the quality of extracted macros, including user evaluation, comparative analysis against human-curated tasks, and automatic execution of these macros. These experiments and analyses demonstrate the effectiveness of our approach and the usefulness of extracted macros in various downstream applications.

Spatial and time-dependent data is of interest in many applications. This task is difficult due to its complex spatial dependency, long-range temporal dependency, data non-stationarity, and data heterogeneity. To address these challenges, we propose Forecaster, a graph Transformer architecture. Specifically, we start by learning the structure of the graph that parsimoniously represents the spatial dependency between the data at different locations. Based on the topology of the graph, we sparsify the Transformer to account for the strength of spatial dependency, long-range temporal dependency, data non-stationarity, and data heterogeneity. We evaluate Forecaster in the problem of forecasting taxi ride-hailing demand and show that our proposed architecture significantly outperforms the state-of-the-art baselines.

The benefits of biochar as a soil amendment have been investigated extensively, but few studies have considered the effects of different application modes on nitrogen (N) dynamics. In the present study, a pot experiment was conducted to evaluate the effects of two different biochar application modes [plough layer mixing (PLM) and surface soil mixing (SSM)] on the N dynamics in a paddy system. It was found that biochar application significantly reduced the total N (TN), NH4+-N, and NO3--N contents of the paddy surface water after fertilization, and that the SSM mode of application was more effective in doing this, particularly for NH4+-N, reducing TN by 11-76%, NH4+-N by 31-77%, and NO3--N by 31-60% compared with the control at 7 days after fertilizer dressing. By contrast, the effect of biochar application on soil N varied with biochar application mode, N form, and rice growth period. In general, there was no significant effect of biochar type on soil N content, with both types of biochar resulting in a higher TN content of the soil after the tiller stage compared with the control. In addition, the SSM mode of application led to a higher TN content but lower NH4+-N content of the soil than the PLM mode, while the two application modes had varying effects on the NO3--N content depending on the growing period of the rice. The rice grain yield increased by 25-36% with the SSM application mode and 11-14% with the PLM mode. These findings indicate that the SSM mode of biochar application in paddy soils is a more promising strategy for both reducing the risk of N loss and improving rice yield than PLM mode.

Transformer models have advanced the state of the art in many Natural Language Processing (NLP) tasks. In this paper, we present a new Transformer architecture, Extended Transformer Construction (ETC), that addresses two key challenges of standard Transformer architectures, namely scaling input length and encoding structured inputs. To scale attention to longer inputs, we introduce a novel global-local attention mechanism between global tokens and regular input tokens. We also show that combining global-local attention with relative position encodings and a Contrastive Predictive Coding (CPC) pre-training objective allows ETC to encode structured inputs. We achieve state-of-the-art results on four natural language datasets requiring long and/or structured inputs.

Greenhouse cultivation consumes large volumes of freshwater, and excessive irrigation induces environmental problems, such as nutrient leaching and secondary salinization. Pyrochar (biochar from high-temperature pyrolysis) is an effective soil amendment, and researches have shown that pyrochar application could maintain soil nutrient and enhance carbon sequestration. In addition to pyrochar from pyrolysis, hydrochar from hydrothermic carbonization is considered as a new type of biochar and has the advantages of low energy consumption and a high productive rate. However, the effect of these two biochars on water evaporation in clayey soils under a greenhouse system has seldom been studied. The relationship between water evaporation and biochar properties is still unknown. Thus, in the present study, water evaporation under pyrochar and hydrochar application were recorded. Results showed that both pyrochar and hydrochar application could inhibit water evaporation in clayey soil under greenhouse cultivation. Pyrochar showed a better inhibition effect compared with hydrochar. Correlation analysis indicated that the water evaporation rate was significantly positively correlated with bulk density of biochar (p &lt; 0.05). Overall, application of pyrochar or hydrochar could both reduce soil bulk density and inhibit soil evaporation, and be available for greenhouse cultivation. However, the inhibition effect depends on the properties of the biochar.

Attentional mechanisms are order-invariant. Positional encoding is a crucial component to allow attention-based deep model architectures such as Transformer to address sequences or images where the position of information matters. In this paper, we propose a novel positional encoding method based on learnable Fourier features. Instead of hard-coding each position as a token or a vector, we represent each position, which can be multi-dimensional, as a trainable encoding based on learnable Fourier feature mapping, modulated with a multi-layer perceptron. The representation is particularly advantageous for a spatial multi-dimensional position, e.g., pixel positions on an image, where $L_2$ distances or more complex positional relationships need to be captured. Our experiments based on several public benchmark tasks show that our learnable Fourier feature representation for multi-dimensional positional encoding outperforms existing methods by both improving the accuracy and allowing faster convergence.

Abstract The first total synthesis of the decapeptide antibiotics loloatins A–D ( 1 – 4 ), originally isolated from the marine bacterial isolate MK‐PNG‐276A, possibly in the genus Bacillus , was accomplished by solid‐phase peptide synthesis (SPPS), followed by ‘head‐to‐tail’ cyclization of the activated linear precursors, without protection of nucleophilic side‐chain functions, on a safety‐catch resin. The synthetic peptides were equally active as the natural products isolated from the bacterial source and found to possess similar bacterial selectivity as other members in the family of amphipathic antimicrobial cyclic decapeptides.

To address the increasing functionality (or information) overload of smartphones, prior research has explored a variety of methods to extend the input vocabulary of mobile devices. In particular, body tapping has been previously proposed as a technique that allows the user to quickly access a target functionality by simply tapping at a specific location of the body with a smartphone. Though compelling, prior work often fell short in enabling users' unconstrained tapping locations or behaviors. To address this problem, we developed a novel recognition method that combines both offline-before the system sees any user-defined gestures and online learning to reliably recognize arbitrary, user-defined body tapping gestures, only using a smartphone's built-in sensors. Our experiment indicates that our method significantly outperforms baseline approaches in several usage conditions. In particular, provided only with a single sample per location, our accuracy is 30.8% over an SVM baseline and 24.8% over a template matching method. Based on these findings, we discuss how our approach can be generalized to other user-defined gesture problems.

Reuse of treated wastewater effluent for crop irrigation can be a promising strategy to substitute/reduce chemical fertilizers and mitigate contamination of water environment. The effect of the effluent irrigation strategies on crop yield and nitrogen (N) loss to the environment have not been yet well explored. In the present study, a soil column monitoring experiment was conducted for over two years (2016–2017) to assess the effect of domestic sewage tail water (DSTW) irrigation on rice growth and N-loss. DSTW irrigation was established substituting N fertilizer at percentages of 15 %, 30 % and 45 % (namely N3S1, N2S2 and N1S3) with a total nitrogen (TN) input of 210 kg·hm−2; controls with conventional fertilizer (N210) and no fertilizer (N0) but tap water irrigation were also set up. A field plot experiment was also conducted using the same treatments in 2017. The results of the soil column experiment showed that the grain yield from treatments with different proportions of DSTW and N fertilizer were no lower than those subjected to conventional fertilizer in both years. The NH3 volatilization from the treatments using reclaimed DSTW accounted for 20.9 %–34.4 % TN in 2016, but this fell to 6.9 %–16.1 % in 2017. Compared with N210, the DSTW irrigation treatment (N1S3) significantly reduced NH3 emissions by 32.8 %–61.3 % over the two years (p < 0.05). The field plot experiment also indicated that DSTW reclamation could not significantly affect the rice growth and yield, and treatments with a higher proportion of N substituting by DSTW tended to have lower NH3 volatilization. With respect to the rice yield and N-loss, the recommended ratio of N fertilizer substitution is 30 %–45 %; however, long-term trials would be required to further evaluate of any adverse environmental impacts.

施肥是农业生态系统中的重要一环, 因土壤生物特性如土壤酶活力、微生物量、呼吸以及生物多样性等对外来扰动的灵敏性优于理化特性而在近几年受到了广泛关注。长期配施有机肥能显著调节土壤营养环境，提高微生物碳氮含量, 降低代谢呼吸商值并提高多种土壤酶的活力和土壤生物多样性, 为作物稳产高产创造良好的土壤生态环境, 而化肥施用的效果恰相反。土壤生物特性的变动关系到土壤质量、农业生产的产量以及生态系统的稳定, 本文综述了近几年国内外关于施用有机肥对土壤生物性质影响的研究结果。

The Chinese black truffle Tuber indicum (Ascomycota, Pezizales) is an ectomycorrhizal fungus forming hypogeous edible ascocarps. As a famous wild edible mushroom in the world, this species also attracted an increasing interest in their chemical composition and pharmacological activity. In this study, the total phenolic content, total flavonoid content and antioxidant activities of Tuber indicum collected from July to November at different maturity stages in China were analyzed. Our results showed that T. indicum collected in July (immature stage) possessed the highest amount of flavonoids (3.89 mg/g dw) and the highest ABTS.+ scavenging activity (EC50 =3.73 mg/ml). In addition, those samples collected in August (moderate mature stage) contained the highest phenolics content (4.78 mg/g dw), the highest DPPH⋅ radical scavenging activity (EC50 =3.73 mg/ml) and ferric reducing activity power (243.63 μmol FeSO4 /g). The study reveals T. indicum in the early maturity stage yield significantly higher content of phenolics and flavonoids and possessed stronger antioxidant activity than those collected in other months. This study provided important data for understanding the relationship between maturity stages and truffle formation and evaluating the quality of Chinese black truffle at different maturity.

A semantic image database system (OISDBS) has been designed for structural management of image data. A semantic image data model has been presented to describe the inner structure and contexts of images. A diagrammatic query language with a QBE (Query-by-example) flavor is proposed together with a discussion of its foundation on object rewriting. This data model describes the structure and contents of images by incorporating type constructors, functions on types, and inheritance. It supports composite modeling for entities which consist of pictorial data as well as alphanumeric attributes. The interactive query language allows users to do direct manipulation on the pictorial database because such diagrammatic query formulations represent the users' view of the database schema. Various aspects of OISDBS such as the schema design, storage management, and mapping from semantic schema to relational schema, are also discussed.

The rate of nitrous oxide emission from a laboratory sequence batch reactor (SBR) wastewater treatment system using synthetic wastewater was measured under controlled conditions. The SBR was operated in the mode of 4 h for aeration, 3.5 h for stirring without aeration, 0.5 h for settling and drainage, and 4 h of idle. The sludge was acclimated by running the system to achieve a stable running state as indicated by rhythmic changes of total N, dissolved oxygen, chemical oxygen demand, NO−2, NO−3 NH+4, pH, and N2O. Under the present experimental conditions measured nitrous oxide emitted from the off-gas in the aerobic and anaerobic phases, respectively, accounted for 8.6%–16.1% and 0–0.05% of N removed, indicating that the aerobic phase was the main source of N2O emission from the system. N2O dissolved in discharged water was considerable in term of concentration. Thus, measures to be developed for the purpose of reducing N2O emission from the system should be effective in the aeration phase.

The objective of the present research was to study the potential of Vis-NIR (visible-near-infrared) high spectra for nondestructive determination of nitrate content in spinach leaves. Five different nitrogen treatments were carried out to achieve a wide range of nitrate content in spinach leaves. The leaf reflectance was measured between 350 to 2,500 nm with a 1 nm step with a leaf clip by ASD Fieldspec FR spectroradiometer, and the nitrate content was measured by spectrophotometric method (National Standard Method of P. R. China). Statistical models were developed using partial least squares (PLS) and principal component regression (PCR) analysis technique, different mathematical treatments for spectra processing such as smoothing, first and second derivative analysis, baseline correction, multiplicative scatter correction (MSC), and standard normal variate correction (SNV), and different wavelength ranges were compared to determine the best model. The dataset was separated into two parts: one used for calibration (n=43), and the other used for test (n=15). First, the model was calibrated and cross-validated with the calibration dataset, then the model was validated with the test dataset to test its prediction ability. The results showed that smoothing, first derivative and second derivative analysis can improve the prediction obviously, while other spectra pre-processing technique e. g. baseline correction, MSC and SNV technique can improve the prediction little. PCR analysis could get better modeling results than PLS analysis. The best model was obtained with the spectra first processed by smoothing then by first derivative change in the full range (350-2,500 nm). Test of the best PLS model and PCR model with an independent dataset exhibited a good agreement between the predicted and observed values, with the correlation coefficient of 0.94 for PLS model and 0.95 for PCR model, and the prediction RMSE was 128.2 mg x kg(-1) for PLS model and 120.8 mg x kg(-1) for PCR model, respectively. These results indicate that visible-NIR spectra technique is a feasible, nondestructive way to predict the nitrate content in spinach leaves.

Leaching is a major path for chemical nitrogen fertilizer loss from in vegetable soil, which would destroy soil pH buffering capacity soil and result in acidification. It has been a common phenomenon in Tai Lake Region, China. However, few study focused on the change soil pH buffering capacity, especially the effect of soil amendment on pH buffering capacity. In this study, a pot experiment was conducted to research the effects of biochar addition to a vegetable soil on nitrogen leaching and pH buffering capacity with pakchoi (B.chinensis L.) growth as the experimental crop. The results showed that biochar could significantly increase the pakchoi nitrogen utilization efficiency, decrease 48%-65% nitrogen loss from leaching under the urea continuous applied condition. Biochar also could effectively maintain the content of soil organic matter and base cations. Therefore, it rose up soil pH buffering capacity by 9.4%-36.8% and significantly slowed down acidification rate. It was suggested that 1%-2% addition ratio was recommended from this study when used as similar soil condition.

A floating ryegrass mat was constructed for low-pollution wastewater treatment during a low-temperature season. Plastic tanks were used as containers, and filled with low-pollution wastewater with low or high nitrogen concentrations, and with and without the floating ryegrass mat, creating four treatments in total (Group Low, Control Low, Group High and Control High). The experiment was conducted for 61 days. The results showed that the removal rates of TN, NH4+, and NO3− were considerably higher in Group Low and Group High than in the controls. The removal rates of TN were 86.8–88.8% in Group Low and 95.0–96.1% in Group High, while the removal rates of NH4+ were 91.1–92.5% in Group Low and 97.9–99.1% in Group High. Meanwhile, the COD values were in the range of 5.5–20.9 mg/L in Group Low and 7.0–26.7 mg/L in Group High, which were relatively higher compared to the controls. The higher COD/N ratios in Group Low and Group High might enhance nitrogen removal. Overall, the ratio of plant assimilation to TN input was estimated to be 33.0% and 47.6% in Group Low and Group High, respectively. The ryegrass mat displayed advantages such as easy transport and high seedling survival rate. The constructed floating ryegrass mat effectively reduced nitrogen concentration. Therefore, this technique can be an alternative approach for low-pollution wastewater treatment.

Pre-trained language models have been widely recognized and applied. While common pre-training language representation models(PLMs) usually focus on grasping the co-occurrence of words or sentences in simple tasks, more and more researchers realize that external information, i.e., knowledge graph (KG) and clear structured semantics, can be vital in natural language understanding tasks. Therefore, using external information to enhance PLMs (such as BERT) has gradually become a popular direction. However, the existing improvement methods often only use a certain type of external information, and it is difficult to solve the problems of common PLMs that lack common sense and semantic incompleteness in one fell swoop. Suppose the model wants to integrate multiple external information. In that case, it not only requires the model to deal with the noise problem that external information may bring but also requires the model to ensure that different information can work together effectively. In this paper, we propose Sem-K-BERT, which integrates the information of KG and semantic role labeling(SRL) before and after the BERT encoding layer, and introduces a context-aware knowledge screening mechanism based on semantic correlation calculation and a text-semantic alignment mechanism to effectively integrate the two external information and reduce the impact of noise. Experiments and analysis on 8 different Chinese natural language processing tasks show that Sem-K-BERT has better performance than BERT and the BERT model that only incorporates KG. This indicates that the simultaneous use of knowledge graph and SRL information offers a promising solution to improve the performance of PLMs.

Natural language descriptions of user interface (UI) elements such as alternative text are crucial for accessibility and language-based interaction in general. Yet, these descriptions are constantly missing in mobile UIs. We propose widget captioning, a novel task for automatically generating language descriptions for UI elements from multimodal input including both the image and the structural representations of user interfaces. We collected a large-scale dataset for widget captioning with crowdsourcing. Our dataset contains 162,859 language phrases created by human workers for annotating 61,285 UI elements across 21,750 unique UI screens. We thoroughly analyze the dataset, and train and evaluate a set of deep model configurations to investigate how each feature modality as well as the choice of learning strategies impact the quality of predicted captions. The task formulation and the dataset as well as our benchmark models contribute a solid basis for this novel multimodal captioning task that connects language and user interfaces.

A pot experiment was conducted to study the effect of straw returning and domestic sewage irrigation on the dynamics of NH4+-N concentration and pH in the flood water, and ammonia volatilization of paddy fields. The results showed that the NH4+-N concentration in flood water was significantly increased by wheat straw returning while significantly decreased by domestic sewage irrigation. The cumulative ammonia volatilization in the whole rice season under tap water irrigation and straw removal treatment was 58.29 kg·hm-2, accounting for 24.29% of the total N applied. The N loss ratio of ammonia volatilization was significantly increased to 45.66% by wheat straw returning, while significantly decreased to 17.26% under straw removal and 32.72% under straw returning by domestic sewage irrigation. Significant positive interaction was observed between straw incorporation and domestic sewage irrigation on ammonia volatilization loss. The average N loss from ammonia volatilization during the tillering stage was the highest among the three fertilization stages, accounting for 7.38%-24.44% of the total N applied. In addition, ammonia volatilization fluxes showed a significant positive correlation with the flood water NH4+-N concentration, irrespective of the irrigation water, but had no significant correlation with pH. These results indicated that straw returning increased ammonia volatilization losses, whereas domestic sewage irrigation could effectively reduce ammonia volatilization losses and simultaneously replace 44.41% of chemical nitrogen fertilizer by the N contained in the domestic sewage. The combination of domestic sewage irrigation and straw returning would be an ecological and environmental-friendly measure for rice nitrogen management in Taihu Lake region.

Modelling prosody variation is critical for synthesizing natural and expressive speech in endto-end text-to-speech (TTS) systems.In this paper, a cross-utterance conditional VAE (CUC-VAE) is proposed to estimate a posterior probability distribution of the latent prosody features for each phoneme by conditioning on acoustic features, speaker information, and text features obtained from both past and future sentences.At inference time, instead of the standard Gaussian distribution used by VAE, CUC-VAE allows sampling from an utterance-specific prior distribution conditioned on cross-utterance information, which allows the prosody features generated by the TTS system to be related to the context and is more similar to how humans naturally produce prosody.The performance of CUC-VAE is evaluated via a qualitative listening test for naturalness, intelligibility and quantitative measurements, including word error rates and the standard deviation of prosody attributes.Experimental results on LJ-Speech and LibriTTS data show that the proposed CUC-VAE TTS system improves naturalness and prosody diversity with clear margins.

Recovering nitrogen (N) from agricultural wastewater for reuse in planting fields is a more sustainable and economical strategy to limit N pollution than using conventional treatments. Hereby, regular biochar produced by wheat straw pyrolysis and Mg-modified biochar were used as the N carriers to assess inorganic-N adsorption from simulated agricultural wastewater and the potential for reuse of the carried N in a planting system. The results showed that biochar materials have different affinities towards inorganic-N types. The amount of biochar carried-N increased with the increase in inorganic-N concentration and reached 4.44 mg/g as the maximum. The biochar carried ~4 mg/g of inorganic N substituting nearly 40% of N fertilizer following a 1% w/w addition rate for vegetable planting. After a trial season, 34.7–42.7% of the carried N from biochar was assimilated by the plant, 45.9–53.7% was retained by the soil, and only about 10% was lost. In comparison to the condition with all N inputs from chemical fertilizer, the addition of part of N by the N–biochar matrix significantly reduced the N loss by improving the plant N uptake or increasing the N content in the soil. This study demonstrates that biochar materials could be used as N carriers to recover N from wastewater for reuse in soil, carrier stability, and bioavailability preservation.

Antibiotics and antibiotic resistance genes (ARGs) are emerging environmental contaminants. TiO2 photocatalytic degradation has been proved an important removal technique, but its photocatalytic ability needs be improved. In our work, natural N-doped carbon quantum dots (N-SCQDs) were extracted from hydrothermal carbonization waste liquid of straw and were attached onto TiO2 nanospheres for remediating antibiotics [sulfadiazine (SA)] and ARGs (sul1, sul2, and intl1). The maximum SA reduction rates were close to 100%, and the ARG reduction rates were 52.91-83.52%/lg10 (sul1), 32.10-68.23%/lg10 (sul2), and 46.29-76.55%/lg10 (inlt1). The temperature of the straw derivatives would influence their photoelectric properties. N-SCQDs@TiO2 expands the application range of a novel potential high-efficiency degradation catalyst and offers a new way of hydrothermal carbonization waste liquid of agricultural waste.