Jiahao Liu

Abstract The Metaverse has been the centre of attraction for educationists for quite some time. This field got renewed interest with the announcement of social media giant Facebook as it rebranding and positioning it as Meta. While several studies conducted literature reviews to summarize the findings related to the Metaverse in general, no study to the best of our knowledge focused on systematically summarizing the finding related to the Metaverse in education. To cover this gap, this study conducts a systematic literature review of the Metaverse in education. It then applies both content and bibliometric analysis to reveal the research trends, focus, and limitations of this research topic. The obtained findings reveal the research gap in lifelogging applications in educational Metaverse. The findings also show that the design of Metaverse in education has evolved over generations, where generation Z is more targeted with artificial intelligence technologies compared to generation X or Y. In terms of learning scenarios, there have been very few studies focusing on mobile learning, hybrid learning, and micro learning. Additionally, no study focused on using the Metaverse in education for students with disabilities. The findings of this study provide a roadmap of future research directions to be taken into consideration and investigated to enhance the adoption of the Metaverse in education worldwide, as well as to enhance the learning and teaching experiences in the Metaverse.

Abstract Soaring cases of coronavirus disease (COVID-19) are pummeling the global health system. Overwhelmed health facilities have endeavored to mitigate the pandemic, but mortality of COVID-19 continues to increase. Here, we present a mortality risk prediction model for COVID-19 (MRPMC) that uses patients’ clinical data on admission to stratify patients by mortality risk, which enables prediction of physiological deterioration and death up to 20 days in advance. This ensemble model is built using four machine learning methods including Logistic Regression, Support Vector Machine, Gradient Boosted Decision Tree, and Neural Network. We validate MRPMC in an internal validation cohort and two external validation cohorts, where it achieves an AUC of 0.9621 (95% CI: 0.9464–0.9778), 0.9760 (0.9613–0.9906), and 0.9246 (0.8763–0.9729), respectively. This model enables expeditious and accurate mortality risk stratification of patients with COVID-19, and potentially facilitates more responsive health systems that are conducive to high risk COVID-19 patients.

In a water electrolysis system, the cathode and anode produce H2 and O2 with HER and OER, respectively. The energy conversion efficiency of the electrolysis systems is about 56–73% in practical application, and the low energy conversion efficiency greatly limits the large-scale application. Hence, the electrocatalytic water splitting has attracted much attention. Recently, a variety of heterogeneous catalysts have emerged, showing high catalytic water splitting performance. Among them, the heterojunction catalysts occupied a very important position in emerging catalysts. In the heterojunction catalysts, electrons can be rearranged on heterostructures interfaces to modify the properties of active sites, and synergy of different active sites is used to promote the reaction kinetics. The heterojunction catalysts often show a better activity of electrolysis water than single-component catalysts. Herein, we mainly summarize the design strategies and synthesis methods of various heterojunction catalysts and the related applications of these heterojunction catalysts in HER and OER, and further discusses the catalytical mechanisms in HER and OER processes respectively. Through the summary of present progress in electrocatalytic water splitting, this review provides a reasonable prospect on heterojunction catalysts in electrocatalytic water splitting.

Materials featured with self-supported three-dimensional network, hierarchical pores and rich electrochemical active sites are considered as promising electrodes for pseudocapacitors. Herein, a novel strategy for the growth of nickel-cobalt bisulfide (NiCoS) nanosheets arrays on carbon cloth (CC) as supercapacitor electrodes is reported, involving deposition of two-dimensional metal-organic framework (MOF) precursors on the CC skeletons, conversion of MOF into nickel-cobalt layered double-hydroxide by ion exchange process and formation of NiCoS by a sulfidation treatment. The NiCoS nanosheets with rough surface and porous structures are uniformly anchored on the CC skeletons. The unique architecture endows the composite (NiCoS/CC) with abundant accessible active sites. Besides, robust electrical/mechanical joint between the nanosheets and the substrates is attained, leading to the improved electrochemical performance. Moreover, an asymmetric supercapacitor device is constructed by using NiCoS/CC and activated carbon as a positive electrode and a negative electrode, respectively. The optimized device exhibits a high specific capacitance, large energy density and long cycle life. The NiCoS/CC electrode with intriguing electrochemical properties and mechanical flexibility holds great prospect for next-generation wearable devices.

In this study, magnetic [email protected] nanoparticles were firstly developed and then elevated to the upper layer of polyether sulfone (PES) membrane by an external magnetic field during the wet phase inversion process. Flux of the prepared [email protected] membrane was 2.5 times of that of the control PES membrane. Moreover, [email protected] membranes showed a significant promotion of antifouling ability, evidenced by the flux recovery rates (FRR) of 64.6% and 99.8% for bovine serum albumin (BSA) and humic acid (HA) solutions, respectively. The antifouling performance of the [email protected] membrane was comparable or better than those in the literature studies. Meanwhile, the optimal [email protected] membrane possessed an efficient decoloration ability for Congo red (CR) solution and colored emulsion. To analyze the anti-fouling mechanism, the interaction energies between the membrane surface and pollutants (BSA and HA) were computed via the extended Derjaguin-Landau-Verwey-Overbeek (XDLVO) theory. The results showed that the total attraction energy between [email protected] membrane and pollutant interface was smaller than that between the control PES membrane and pollutant interface. This study provided a new incentive to development of high-efficient Mxene-based membranes.

We propose an objective Mn-based competitive capacity evolution protocol and a recusing strategy for dead Mn-based Zn-ion batteries. The findings would provide new insights to understand the electrochemical behaviors more comprehensively.

The first example of room temperature non-noble metal homogeneous system catalyzed selective N-alkylation of anilines with alcohols by a bis-NHC manganese complex is presented. This system was applied to a large range of alcohols and anilines, including biologically relevant motifs and challenging methanol. Experimental and computational studies suggest an outer-sphere mechanism for this NHC-Mn system.

Metal-organic frameworks (MOFs) have been considered as promising nanofillers to fabricate mixed matrix membranes for water treatment. However, manipulating distribution of MOFs nanoparticles in the membrane matrix remains a great challenge. In this study, UiO-66 was firstly coated by magnetic Ni via an in-situ reduction reaction, and then incorporated into polyethersulfone (PES) membrane matrix to prepare PES-Ni@UiO-66 membrane. The magnetic Ni allowed to manipulate the distribution of magnetic Ni@UiO-66 in the phase-inversion process by an external magnetic field. The hydrophilic Ni@UiO-66 can be pulled onto membrane surface by the magnetic force, endowing the prepared membrane with rather higher hydrophilicity. The prepared membrane exhibited superior water permeability with a pure water flux of 611.5 ± 19.8 L·m-2·h-1 and improved antifouling performance. Moreover, benifiting from photocatalytic activity of the exposed Ni@UiO-66 on membrane surface, the obtained PES-Ni@UiO-66 membrane demonstrated excellent photocatalytic self-cleaning ability with a flux recovery rate (FRR) higher than 95% under UV irradiation. Analyzing by extended Derjaguin-Landau-Verwey-Overbeek (XDLVO) theory indicated that the improved antifouling performance could be attributed to less attractive or even repulsive interaction between the prepared membrane and pollutants. This work provided valuable guidance for structural regulation and development of high-performance MOFs-based membranes for water treatment.

While membrane technology emerges as one of the promising candidates for printing and dyeing wastewater treatment, it still suffers problems of "trade-off" effect and membrane fouling. It is therefore highly desired to fabricate high-performance membranes. This study reported a new functional polyvinylidene fluoride (PVDF)-Ni-Co membrane fabricated via an in-situ reduction method. The PVDF-Ni-Co membrane displayed conductive property, magnetic property and special in-situ micro-aeration function under assistance of electric field. Benefiting from in-situ micro-aeration function, the membrane showed excellent decoloration efficiency to Rhodamine B (RB), Congo red (CR) and methylene blue (MB) solutions. Particularly, the PVDF-Ni-Co membrane possessed 98.33% rejection to CR solution with flux up to 69.30 L m−2 h−1·bar−1, which is far better than the data reported in the literature. Moreover, in-situ micro-aeration was confirmed to be critical to enhance membrane antifouling performance. Cycling filtration results revealed that flux recovery rate (FRR) of PVDF-Ni-Co membrane reached to 90% and 94% for sodium alginate (SA) and bovine serum albumin (BSA) solutions, respectively. Thermodynamic calculation suggested that attractive energy of interaction between PVDF-Ni-Co membrane and foulants was largely reduced so that the foulants could hardly adhere onto membrane surface. This study simultaneously provided interesting findings regarding functional PVDF-Ni-Co membrane as well as its fabrication strategy, and new membrane fouling mitigation method of in-situ micro-aeration.

Oxygen evolution reaction (OER) is a bottle-neck process in many sustainable energy conversion systems due to its sluggish kinetics. The development of cost-effective yet efficient electrocatalysts towards OER is highly desirable but still a great challenge at current stage. Herein, a new type of hybrid nanostructure, consisting of two-dimensional (2D) Cerium-doped NiFe-layered double hydroxide nanoflakes directly grown on the 2D Ti3C2Tx MXene surface (denoted as NiFeCe-LDH/MXene), is designed using a facile in-situ coprecipitation method. The resultant NiFeCe-LDH/MXene hybrid presents a hierarchical nanoporous structure, high electrical conductivity and strong interfacial junction because of the synergistic effect of Ce doping and MXene coupling. As a result, the hybrid catalyst exhibits an excellent catalytic activity for OER, delivering a low onset overpotential of 197 mV and an overpotential of 260 mV at a current density of 10 mA·cm−2 in the alkaline medium, much lower than its pure LDH counterparts and IrO2 catalyst. Besides, the hybrid catalyst also displays a fast reaction kinetics and a remarkable stable durability. Further theoretic studies using density function theory (DFT) methods reveal that Ce doping could effectively narrow the bandgap of NiFe-LDH and reduce the overpotential in OER process. This work may shed light on the exploration of advanced electrocatalysts for renewable energy conversion and storage systems.

The diffusion-limited aggregation (DLA) of metal ion (Mn+) during the repeated solid-to-liquid (StoL) plating and liquid-to-solid (LtoS) stripping processes intensifies fatal dendrite growth of the metallic anodes. Here, we report a new solid-to-solid (StoS) conversion electrochemistry to inhibit dendrites and improve the utilization ratio of metals. In this StoS strategy, reversible conversion reactions between sparingly soluble carbonates (Zn or Cu) and their corresponding metals have been identified at the electrode/electrolyte interface. Molecular dynamics simulations confirm the superiority of the StoS process with accelerated anion transport, which eliminates the DLA and dendrites in the conventional LtoS/StoL processes. As proof of concept, 2ZnCO3·3Zn(OH)2 exhibits a high zinc utilization of ca. 95.7% in the asymmetry cell and 91.3% in a 2ZnCO3·3Zn(OH)2 || Ni-based full cell with 80% capacity retention over 2000 cycles. Furthermore, the designed 1-Ah pouch cell device can operate stably with 500 cycles, delivering a satisfactory total energy density of 135 Wh kg-1.

Abstract Background Salinity is a worldwide factor limiting the agricultural production. Cotton is an important cash crop; however, its yield and product quality are negatively affected by soil salinity. Use of nanomaterials such as cerium oxide nanoparticles (nanoceria) to improve plant tolerance to stress conditions, e.g. salinity, is an emerged approach in agricultural production. Nevertheless, to date, our knowledge about the role of nanoceria in cotton salt response and the behind mechanisms is still rare. Results We found that PNC (poly acrylic acid coated nanoceria) helped to improve cotton tolerance to salinity, showing better phenotypic performance, higher chlorophyll content (up to 68% increase) and biomass (up to 38% increase), and better photosynthetic performance such as carbon assimilation rate (up to 144% increase) in PNC treated cotton plants than the NNP (non-nanoparticle control) group. Under salinity stress, in consistent to the results of the enhanced activities of antioxidant enzymes, PNC treated cotton plants showed significant lower MDA (malondialdehyde, up to 44% decrease) content and reactive oxygen species (ROS) level such as hydrogen peroxide (H 2 O 2 , up to 79% decrease) than the NNP control group, both in the first and second true leaves. Further experiments showed that under salinity stress, PNC treated cotton plants had significant higher cytosolic K + (up to 84% increase) and lower cytosolic Na + (up to 77% decrease) fluorescent intensity in both the first and second true leaves than the NNP control group. This is further confirmed by the leaf ion content analysis, showed that PNC treated cotton plants maintained significant higher leaf K + (up to 84% increase) and lower leaf Na + content (up to 63% decrease), and thus the higher K + /Na + ratio than the NNP control plants under salinity stress. Whereas no significant increase of mesophyll cell vacuolar Na + intensity was observed in PNC treated plants than the NNP control under salinity stress, suggesting that the enhanced leaf K + retention and leaf Na + exclusion, but not leaf vacuolar Na + sequestration are the main mechanisms behind PNC improved cotton salt tolerance. qPCR results showed that under salinity stress, the modulation of HKT1 but not SOS1 refers more to the PNC improved cotton leaf Na + exclusion than the NNP control. Conclusions PNC enhanced leaf K + retention and Na + exclusion, but not vacuolar Na + sequestration to enable better maintained cytosolic K + /Na + homeostasis and thus to improve cotton salt tolerance. Our results add more knowledge for better understanding the complexity of plant-nanoceria interaction in terms of nano-enabled plant stress tolerance. Graphic abstract

As a consequence of rapid industrialization throughout the world, various environmental pollutants have begun to accumulate in water, air, and soil. This endangers the ecological environment of the earth, and environmental remediation has become an immediate priority. Among various environmental remediation techniques, piezocatalytic techniques, which uniquely take advantage of the piezoelectric effect, have attracted much attention. Piezoelectric effects allow pollutant degradation directly, while also enhancing photocatalysis by reducing the recombination of photogenerated carriers. In this Review, we provide a comprehensive summary of recent developments in piezocatalytic techniques for environmental remediation. The origin of the piezoelectric effect as well as classification of piezoelectric materials and their application in environmental remediation are systematically summarized. We also analyze the potential underlying mechanisms. Finally, urgent problems and the future development of piezocatalytic techniques are discussed.

For several decades, the promise of implementing of lithium (Li) metal anodes for Li batteries has been a ‘‘holy grail’’ for researchers. Herein, we have proposed a facile design of a MOF-derived Co3O4 nanoparticles modified nickel foam, i.e., Co3O4-NF, as a 3D host to achieve a uniform infusion of the molten Li. The molten Li was uniformly absorbed on the Co3O4-NF host only in 10 s due to its high Li lithiophilicity. The obtained Li-Co3O4-NF composite electrode shows high cycling stability in symmetric cells with low voltage hysteresis even at a high current density of 5 mA/cm2. The full cells of Li-Co3O4-NF/LiFePO4 can cycle for more than 500 cycles at 2C without obvious capacity decay. SEM after cycling and in situ optical microscope results suggest that the unique 3D host structure of the Li-Co3O4-NF anode plays key roles on suppressing the dendrite growth and decreasing the local current inhomogeneity. We believe this work might provide a new strategy for fabricating dendrite-free Li metal anodes and facilitate practical applications in Li batteries.

Abstract Minimum quantity lubrication (MQL) is a relatively efficient and clean alternative to flooding workpiece machining. Electrostatic atomization has the merits of small droplet diameter, high uniformity of droplet size, and strong coating, hence its superiority to pneumatic atomization. However, as the current research hotspot, the influence of jet parameters and electrical parameters on the average diameter of droplets is not clear. First, by observing the shape of the liquid film at the nozzle outlet, the influence law of air pressure and voltage on liquid film thickness ( h ) and transverse and longitudinal fluctuations are determined. Then, the mathematical model of charged droplet volume average diameter (VAD) is constructed based on three dimensions of the liquid film, namely its thickness, transverse wavelength ( λ h ), and longitudinal wavelength ( λ z ). The model results under different working conditions are obtained by numerical simulation. Comparisons of the model results with the experimental VAD of the droplet confirm the error of the mathematical model to be less than 10%. The droplet diameter distribution span value Rosin-Rammler distribution span (R.S) and percentage concentrations of PM10 (particle size of less than 10 µm)/PM2.5 (particle size of less than 2.5 µm) under different working conditions are further analyzed. The results show that electrostatic atomization not only reduces the diameter distribution span of atomized droplets but also significantly inhibits the formation of PM10 and PM2.5 fine-suspension droplets. When the air pressure is 0.3 MPa, and the voltage is 40 kV, the percentage concentrations of PM10 and PM2.5 can be reduced by 80.72% and 92.05%, respectively, compared with that under the pure pneumatic atomization condition at 0.3 MPa.

BackgroundUltrasound is a critical non-invasive test for preoperative diagnosis of ovarian cancer. Deep learning is making advances in image-recognition tasks; therefore, we aimed to develop a deep convolutional neural network (DCNN) model that automates evaluation of ultrasound images and to facilitate a more accurate diagnosis of ovarian cancer than existing methods.MethodsIn this retrospective, multicentre, diagnostic study, we collected pelvic ultrasound images from ten hospitals across China between September 2003, and May 2019. We included consecutive adult patients (aged ≥18 years) with adnexal lesions in ultrasonography and healthy controls and excluded duplicated cases and patients without adnexa or pathological diagnosis. For DCNN model development, patients were assigned to the training dataset (34 488 images of 3755 patients with ovarian cancer, 541 442 images of 101 777 controls). For model validation, patients were assigned to the internal validation dataset (3031 images of 266 patients with ovarian cancer, 5385 images of 602 with benign adnexal lesions), external validation datasets 1 (486 images of 67 with ovarian cancer, 933 images of 268 with benign adnexal lesions), and 2 (1253 images of 166 with ovarian cancer, 5257 images of 723 benign adnexal lesions). Using these datasets, we assessed the diagnostic value of DCNN, compared DCNN with 35 radiologists, and explored whether DCNN could augment the diagnostic accuracy of six radiologists. Pathological diagnosis was the reference standard.FindingsFor DCNN to detect ovarian cancer, AUC was 0·911 (95% CI 0·886–0·936) in the internal dataset, 0·870 (95% CI 0·822–0·918) in external validation dataset 1, and 0·831 (95% CI 0·793–0·869) in external validation dataset 2. The DCNN model was more accurate than radiologists at detecting ovarian cancer in the internal dataset (88·8% vs 85·7%) and external validation dataset 1 (86·9% vs 81·1%). Accuracy and sensitivity of diagnosis increased more after DCNN-assisted diagnosis than assessment by radiologists alone (87·6% [85·0–90·2] vs 78·3% [72·1–84·5], p<0·0001; 82·7% [78·5–86·9] vs 70·4% [59·1–81·7], p<0·0001). The average accuracy of DCNN-assisted evaluations for six radiologists reached 0·876 and were significantly augmented when they were DCNN-assisted (p<0·05).InterpretationThe performance of DCNN-enabled ultrasound exceeded the average diagnostic level of radiologists matched the level of expert ultrasound image readers, and augmented radiologists’ accuracy. However, these observations warrant further investigations in prospective studies or randomised clinical trials.FundingNational Key Basic Research Program of China, National Sci-Tech Support Projects, and National Natural Science Foundation of China.

Photocatalytic reduction of carbon dioxide (CO2) into high-value chemicals is a very effective way to solve the greenhouse effect, improve the utilization ratio of resources, and cope with the energy crisis. However, the low catalytic activity and poor product selectivity of the catalyst have been largely restricting its large-scale application. Herein, we successfully synthesized an ultra-thin two-dimensional trimetallic metal–organic framework (NiZrCu-BDC) nanosheet as a photocatalyst for CO2 reduction, and the average thickness of NiZrCu-BDC is about 4 nm. The NiZrCu-BDC nanosheet has the ability to reduce CO2 to methanol (41.05 μmol h–1 g–1) and ethanol (36.62 μmol h–1 g–1), and the turnover frequency of NiZrCu-BDC is 34 times more than that of NiZr-BDC. Zr and Cu doping enables enrichment of Ni surface charges to promote CO2 chemisorption, and the ultra-thin structure can shorten the electron transport path. Meanwhile, the electron density of Ni catalytical sites in NiZrCu-BDC is enhanced by doping Cu and Zr to facilitate COOH* and CHO formation, which are deemed as key species for CO2 reduction reactions to liquid products. This work provides further insights into the photocatalytic reduction of CO2 based on the multi-metal–organic framework.

The accurate knowledge of the physics-based state of charge (SOC) and anode potential for lithium-ion batteries (LIBs) plays an essential role in the driving range prediction and charge strategy optimization of electric vehicles (EVs). However, the SOC estimation based on empirical equivalent circuit models and the lack of anode potential information makes it challenging in developing advanced battery management systems for EVs. For this reason, this paper proposes a low-complexity SOC and anode potential prediction method for LIBs using a simplified electrochemical model (SEM)-based observer under variable load condition. First, based on the Padé approximation and volume average method, a reduced-order SEM is proposed and verified. Then, a low-complexity proportional-integral-differential observer framework incorporating the SEM is developed to obtain the physics-based SOC and anode potential. Finally, the effectiveness of the proposed method under variable load conditions is assessed by combining data collected by experiment and COMOSL simulation. The results show that the maximum absolute errors of SOC estimation are basically maintained within 2% under HPPC test profiles and the root mean squared errors of anode potential can be kept at 4.31 mV under US06 test profiles, which achieves a good balance between accuracy and computation cost and provides a strong support on substantially ensuring safe operation of EVs.

As the world steps into the era of Internet of Things (IoT), numerous miniaturized electronic devices requiring autonomous micropower sources will be connected to the internet. All-solid-state thin-film lithium/lithium-ion microbatteries (TFBs) combining solid-state battery architecture and thin-film manufacturing are regarded as ideal on-chip power sources for IoT-enabled microelectronic devices. However, unlike commercialized lithium-ion batteries, TFBs are still in the immature state, and new advances in materials, manufacturing, and structure are required to improve their performance. In this review, the current status and existing challenges of TFBs for practical application in internet-connected devices for the IoT are discussed. Recent progress in thin-film deposition, electrode and electrolyte materials, interface modification, and 3D architecture design is comprehensively summarized and discussed, with emphasis on state-of-the-art strategies to improve the areal capacity and cycling stability of TFBs. Moreover, to be suitable power sources for IoT devices, the design of next-generation TFBs should consider multiple functionalities, including wide working temperature range, good flexibility, high transparency, and integration with energy-harvesting systems. Perspectives on designing practically accessible TFBs are provided, which may guide the future development of reliable power sources for IoT devices.

As a common filler in polymer electrolytes, Metal-organic frameworks (MOFs) has been studied extensively in recent years. In this study, we propose a novel solid composite electrolytes (SCEs) based on PEO/LiTFSI/a-MIL-100 (Fe)/PVDF by using a straightforward solution-casting method. Unactivated and activated MIL-100 (Fe) (a-MIL-100 (Fe)) as the fillers were compared, and the interactions of functional groups of unactivated MIL-100 (Fe) and a-MIL-100 (Fe) with anions of electrolyte salts through Lewis acid-base interaction are studied with density functional theory (DFT) calculations. The influences of different a-MIL-100 (Fe) contents on electrochemical performances were also examined. The Li/SCEs/LiFePO4 cell displayed high average discharge capacities of 161.8 mAh g−1, 166.8 mAh g−1, 158.9 mAh g−1, 146.2 mAh g−1 and 92.6 mAh g−1 at the rate of 0.1, 0.2, 0.5, 1 and 2 C at 60 ℃, respectively, without liquid electrolytes. This work might provide new insight into the role of activated MOFs fillers in polymer electrolytes.

Accurate insight into the heat generation rate (HGR) of lithium-ion batteries (LIBs) is one of key issues for battery management systems to formulate thermal safety warning strategies in advance. For this reason, this paper proposes a novel physics-informed neural network (PINN) approach for HGR estimation of LIBs under various driving conditions. Specifically, a single particle model with thermodynamics (SPMT) is first constructed for extracting the critical physical knowledge related with battery HGR. Subsequently, the surface concentrations of positive and negative electrodes in battery SPMT model are integrated into the bidirectional long short-term memory (BiLSTM) networks as physical information. And combined with other feature variables, a novel PINN approach to achieve HGR estimation of LIBs with higher accuracy is constituted. Additionally, some critical hyperparameters of BiLSTM used in PINN approach are determined through Bayesian optimization algorithm (BOA) and the results of BOA-based BiLSTM are compared with other traditional BiLSTM/LSTM networks. Eventually, combined with the HGR data generated from the validated virtual battery, it is proved that the proposed approach can well predict the battery HGR under the dynamic stress test (DST) and worldwide light vehicles test procedure (WLTP), the mean absolute error under DST is 0.542 kW/m3, and the root mean square error under WLTP is 1.428 kW/m3 at 25 °C. Lastly, the investigation results of this paper also show a new perspective in the application of the PINN approach in battery HGR estimation.

Although lithium-ion batteries (LIBs) have received more attentions as the increasing number of new energy vehicles, in-depth exploration for the heat generation characteristics of LIBs during operation remains challenging. This paper establishes an electrochemical-thermal model (ETM) to evaluate the heat generation characteristics of cylindrical LIBs considering the discharge rates and the ratio of negative to positive electrode capacity (N/P ratio). To ensure a wider range of research on thermal characteristics of LIBs, the proposed ETM is validated based on the experimental data under the ambient temperature of 25 °C and 35 °C. Subsequently, the distribution profiles of heat generation characteristics of LIBs under different conditions are numerically investigated. More innovatively, the effects of different discharge rates and N/P ratios on battery heat generation are comprehensively analyzed. The results show that the heat generation in the negative electrode occupies a major part and the influences of reversible term on the total heat generation of LIB cell cannot be ignored, especially at low discharge rates. Additionally, it is found that the proper selection of N/P ratio can improve the total heat generation of LIBs, which is helpful for optimizing performance in the early stages of battery design and thermal management.

Comprehensive Summary This work systematically reviews recent progresses in the applications of MOF‐derived materials modified 3D porous conductive framework as hosts for uniform lithium deposition in LMBs. A series of commonly used lithiophilic materials and several kinds of representative MOF‐derivation‐modified 3D hosts as lithium metal anode (LMA) are presented. Finally, the challenges and future development of employing MOF‐derived materials to modify the 3D porous conductive framework for LMA are included.

Metal-organic frameworks (MOFs) are becoming more and more popular as the fillers in polymer electrolytes in recent years. In this study, a series of MOFs (NH2-MIL-101(Fe), MIL-101(Fe), activated NH2-MIL-101(Fe) and activated MIL-101(Fe)) were synthesized and added to PEO-based solid composite electrolytes (SCEs). Furthermore, the role of the —NH2 groups and open metal sites (OMSs) were both examined. Different ratios of MOFs vs polymers were also studied by the electrochemical characterizations. At last, we successfully designed a novel solid composite electrolyte containing activated NH2-MIL-101(Fe), PEO, LiTFSI and PVDF for the high-performance all-solid-state lithium-metal batteries. This work might provide new insight to understand the interactions between polymers and functional groups or OMSs of MOFs better.

During feeding process in intensive chicken farms, the prolonged exposure of chickens to elevated level of ammonia leads to substantial economic losses within poultry farming industry. Luteolin (Lut), known as its anti-inflammatory and antioxidant properties, possesses the ability to eliminate free radicals and enhance the activities of antioxidant enzymes, thus rendering it highly esteemed in production. The objective of this study was to examine the effects of Lut on antioxidant and anti-inflammatory responses of chicken splenic lymphocytes exposed to ammonia. In order to achieve this, we have replicated a protective model involving Lut against ammonia exposure in chicken splenic lymphocytes. The findings of the study indicated that Lut mitigated the elevation of lactate dehydrogenase (LDH), malondialdehyde (MDA), and reactive oxygen species (ROS) induced by ammonia poisoning. Additionally, Lut demonstrated an increase in the expression of antioxidant enzymes, namely superoxide dismutase (SOD) and glutathione peroxidase (GSH-Px). Furthermore, Lut exhibited a protective effect on cell morphology and ultrastructure following exposure to ammonia. Moreover, Lut exhibited a reduction in the expression of heat shock proteins (HSPs) and inflammatory cytokines, which were found to be highly expressed in splenic lymphocytes after ammonia exposure. Additionally, Lut demonstrated the ability to inhibit the overexpression of pyroptosis-related genes and proteins (NLRP3 and Caspase-1) in splenic lymphocytes following ammonia exposure. Lut exerted an antioxidant effect on lymphocytes, counteracting elevated levels of oxidative stress following exposure to ammonia. Additionally, Lut had the potential to modulate the expression of HSPs, suppressed the inflammatory response subsequent to ammonia exposure, and influenced the expression of NLRP3 and Caspase-1, thereby mitigating pyroptosis induced by ammonia exposure. The exploration of this subject matter can elucidate the protective properties of Lut against NH4Cl-induced damage in chicken splenic lymphocytes, while also offer insights and experimental groundwork for the utilization of natural therapeutics in animal husbandry to prevent and treat ammonia-related conditions.

The cardiotoxic effects of doxorubicin, a potent chemotherapeutic agent, have been linked to DNA damage, oxidative mitochondrial damage, and nuclear translocation of p53, but the exact molecular mechanisms causing p53 transactivation and doxorubicin-induced cardiomyopathy are not clear. The present study was carried out to determine whether extracellular signal-regulated kinases (ERKs), which are known to be activated by DNA damaging agents, are responsible for doxorubicin-induced p53 activation and oxidative mitochondrial damage in H9c2 cells. Cell death was measured by terminal deoxynucleotidyl transferase dUTP-mediated nick-end labeling, annexin V-fluorescein isothiocyanate, activation of caspase-9 and -3, and cleavage of poly(ADP-ribose) polymerase (PARP). We found that doxorubicin produced cell death in H9c2 cells in a time-dependent manner, beginning at 6 h, and these changes are associated decreased expression of Bcl-2, increases in Bax and p53 upregulated modulator of apoptosis-alpha expression, and collapse of mitochondria membrane potential. The changes in cell death and Bcl-2 family proteins, however, were preceded by earlier activation and nuclear translocation of ERKs, followed by increased phosphorylation at Ser15 and nuclear translocation of the phosphorylated p53. The functional importance of ERK1/2 and p53 in doxorubicin-induced toxicity was further demonstrated by the specific ERK inhibitor U-0126 and p53 inhibitor pifithrin (PFT)-alpha, which abrogated the changes in Bcl-2 family proteins and cell death produced by doxorubicin. U-0126 blocked the phosphorylation and nuclear translocation of both ERK1/2 and p53, whereas PFT-alpha blocked only the changes in p53. Doxorubicin and ERK inhibitors produced similar changes in ERK1/2-p53, PARP, and caspase-3 in neonatal rat cultured cardiomyocytes. Thus we conclude that ERK1/2 are functionally linked to p53 and that the ERK1/2-p53 cascade is the upstream signaling pathway responsible for doxorubicin-induced cardiac cell apoptosis. ERKs and p53 may be considered as novel therapeutic targets for the treatment of doxorubicin-induced cardiotoxicity.

About 250 thermokarst lakes, with an average size of 5580 m2 and a total size of 139 × 104 m2, are spread between the Kunlun Mountain pass and the Fenghuo Mountain pass along the Qinghai–Tibet railway, where ice-rich and warm permafrost exists. Approximately 56% of the lakes are elliptical and 23% are elongated. The water depth varies between 0.4 and 3 m. Most of the lakes in the Chumarhe High Plain and other mountain regions are shallower than the thickness of winter ice (60 to 80 cm), and are frozen to the bottom during the cold seasons. However, in the Hoh Xil Hill region and Beiluhe basin, the water depth is greater than the thickness of winter ice and the relatively warm lake bottoms can cause considerable disturbance to the surrounding continuous permafrost. The lakes in the Chumarhe High Plain are saltwater or brine lakes; and in other regions, the lakes contain freshwater or brackish water. Ages of formation, enlargement rates, water and lake-bottom temperatures, the configuration of permafrost, and active-layer thickness were measured at a typical thermokarst lake in the Beiluhe basin between 2007 and 2009. The lake formed about 890 years ago and is 150 m long, 100 m wide, with a water depth of 2.5 m now. The size of the lake is growing at a rate of about 1 m/a at some shores. The lakeshores are underlain by permafrost, which terminates almost vertically at their edge. The mean annual temperature measured at lake bottom in the centre was 5.45 °C, while the temperature of permafrost at 15 m depth in the lakeshore varied from − 0.84 °C near the edge of the lake to − 1.26 °C at 80 m from the edge. The corresponding active layer depths varied from 2.45 to 1.80 m. The configuration of the talik indicates that no permafrost is found beneath the centre of the lake.

The fire behavior of lithium-ion battery is affected by the environment conditions. In this paper, an experimental study is performed to assess the fire hazards of lithium-ion batteries at different atmospheric pressures by means of the in-situ calorimeters built in a sea-level city Hefei (100.8 kPa, 24 m) and a high altitude city Lhasa (64.3 kPa, 3650 m), respectively. The fire hazards of lithium-ion batteries were characterized by measuring the ignition time, mass loss, heat release rate (HRR), and total heat release (THR). From the results, the ignition time of single battery decreases with the ascending of the state of charge (SOC), whiles the mass loss, and ejection energy increase with that at two pressures. The increment of altitude causes the battery to ignite faster, while the mass loss, heat release rate and total heat release both for single battery and bundle batteries decrease at low pressure. The total heat release in the bundle increases with the battery numbers in a power function. The coefficient of the proportionality is pressure dependent.

Traffic flow prediction has received extensive attention recently, since it is a key step to prevent and mitigate traffic congestion in urban areas. However, most previous studies on traffic flow prediction fail to capture fine-grained traffic information (like link-level traffic) and ignore the impacts from other factors, such as route structure and weather conditions. In this paper, we propose a deep and embedding learning approach (DELA) that can help to explicitly learn from fine-grained traffic information, route structure, and weather conditions. In particular, our DELA consists of an embedding component, a convolutional neural network (CNN) component and a long short-term memory (LSTM) component. The embedding component can capture the categorical feature information and identify correlated features. Meanwhile, the CNN component can learn the 2-D traffic flow data while the LSTM component has the benefits of maintaining a long-term memory of historical data. The integration of the three models together can improve the prediction accuracy of traffic flow. We conduct extensive experiments on realistic traffic flow dataset to evaluate the performance of our DELA and make comparison with other existing models. The experimental results show that the proposed DELA outperforms the existing methods in terms of prediction accuracy.

A lithium-ion battery (LIB) may experience overcharge or over-discharge when it is used in a battery pack because of capacity variation of different batteries in the pack and the difficulty of maintaining identical state of charge (SOC) of every single battery. A series of experiments were established to investigate the thermal and fire characteristics of a commercial LIB under overcharge/over-discharge failure conditions. According to the results, it is clear that the batteries experienced a clear temperature rise in the overcharge/over-discharge process. The temperature rise worsened and required less time when the battery was overcharged/over-discharged to failure with the increasing charge/discharge rate. Besides, the closer the position to the opening of the battery, the higher the surface temperature. It was demonstrated that LIBs can fail when overcharged/over-discharged to a critical degree regardless of the charge/discharge rate. Under different rates, the final capacities were around a critical value. Finally, there existed an explosion phenomenon in the external heating test of battery failure after overcharge, whereas the fire behaviors of the over-discharged battery were much more moderate.

Understanding the fire hazard of lithium-ion battery (LIB) is important for the safety issues during their manufacture, storage, transportation, and usage. In this work, experiments are conducted to analyze the mechanisms of thermal and fire propagation of multiple LIBs in the package. According to the results, it is found that the thermal and fire propagation of multiple LIBs can be triggered easily, and will accelerate continuously. In the later stage of the fire, more and more batteries can be ignited simultaneously. The maximum of 5.6 batteries in Test A ignite at the same time, and in Test B, there can be 32 batteries burning together to reach the largest mass loss rate (MLR). The package with more batteries has higher average MLR and fire propagation has a great effect on the combustion efficiency of LIB. The heat flux and impact pressure results also indicate the simultaneous combustion and ejection of multiple batteries. This work can provide more useful data for fire protection in large-scale battery storage systems.

The thermal failure propagation is one of the most severe challenges for battery pack and it usually aggravates the thermal hazards, further resulting in serious accidents. A series of thermal failure researches were conducted to explore the effects of state of charge (SOC), the number of heaters, failure location and pack size on the thermal failure propagation of battery pack. According to the results, it is found that there exists an obvious domino effect in the thermal failure propagation of battery pack. Typically, the thermal failure of battery pack can be divided into several phases. The higher SOC worsens the propagation of battery pack. Besides, the thermal failure appears earlier for the pack with larger number of heaters. If the battery close to the center of pack takes thermal failure, the failure propagation will be aggravated. Moreover, it is exhibited that the thermal failure propagation will be delayed longer when failure propagates to the outermost layer of batteries with the increase of pack size.

The unusual nonbifunctional outer-sphere strategy was successfully utilized in developing an easily accessible N-heterocyclic carbene manganese (NHC-Mn) system for highly active α-alkylation of ketones with alcohols. This system was efficient for a wide range of ketones and alcohols under mild reaction conditions, and also for the green synthesis of quinoline derivatives. The direct outer-sphere mechanism and the high activity of the present system demonstrate the potential of nonbifunctional outer-sphere strategy in catalyst design for acceptorless dehydrogenative transformations.

The environmental pressure effect on thermal runaway and fire behaviors in the 18650 lithium-ion battery (LIB) with various cathodes and states of charge (SOC) are experimentally investigated in this work. The fire hazards were characterized by the combustion process, total mass loss (TML) and total heat release (THR). The TML and THR increase with the ascending of the SOC at two pressures. The amount of materials ejected by both LiFePO4 and LiCoO2 batteries during the combustion is slightly affected by the environmental pressure. Meanwhile, the environmental pressure has a significant influence on the combustion heat that the THR value at high pressure is relatively bigger than that at low pressure. The unit growth rate in combustion heat between the two pressures also increases with the SOC.

Ultrahigh Zn ion storage is achieved by tuning the valence state and constructing a three-dimensional structure on V₆O₁₃ multi-valent oxide cathodes.

Modern development of flexible electronics has made use of bioelectronic materials as artificial tissue in vivo. As hydrogels are more similar to nerve tissue, functional hydrogels have become a promising candidate for bioelectronics. Meanwhile, interfacing functional hydrogels and living tissues is at the forefront of bioelectronics. The peripheral nerve injury often leads to paralysis, chronic pain, neurologic disorders, and even disability, because it has affected the bioelectrical signal transmission between the brain and the rest of body. Here, a kind of light-stimuli-responsive and stretchable conducting polymer hydrogel (CPH) is developed to explore artificial nerve. The conductivity of CPH can be enhanced when illuminated by near-infrared light, which can promote the conduction of the bioelectrical signal. When CPH is mechanically elongated, it still has high durability of conductivity and, thus, can accommodate unexpected strain of nerve tissues in motion. Thereby, CPH can better serve as an implant of the serious peripheral nerve injury in vivo, especially in the case that the length of the missing nerve exceeds 10 mm.

Ferroelectric polymers are of interest as most promising electroactive materials. Flexible transducers from ferroelectric polymer thin film with underneath semiconducting polymer active layer for high sensitive and versatile detection of physiological signals are described. When attached directly on the wrist, the flexible transducers can distinguish the transient pulse waves non‐invasively and in situ, due to their fast response (milliseconds) and high sensitivity (down to several Pascal) to instantaneous change of blood pressure. High‐resolution picture of one pulse wave is available to provide two most common parameters for arterial stiffness diagnosis. The transducers are also suitable for dynamic recognizing physiological signals under both physical exercise and medicine treatment, demonstrating their enormous potential for warning the risk of cardiovascular disease, and evaluating the efficacy of heart medicines. The transducers are easy to carry around with an operating voltage of 1 V and the power consumption less than 1 μW. Thus, they are valuable for applications like electronic skin and mobile health monitoring.

Abstract Biological ion channels and ion pumps with sub‐nanometer sizes modulate ion transport in response to external stimuli. Realizing such functions with sub‐nanometer solid‐state nanopores has been an important topic with wide practical applications. Herein, we demonstrate a biomimetic photoresponsive ion channel and photodriven ion pump using a porphyrin‐based metal–organic framework membrane with pore sizes comparable to hydrated ions. We show that the molecular‐size pores enable precise and robust optoelectronic ion transport modulation in a broad range of concentrations, unparalleled with conventional solid‐state nanopores. Upon decoration with platinum nanoparticles to form a Schottky barrier photodiode, photovoltage across the membrane is generated with “uphill” ion transport from low concentration to high concentration. These results may spark applications in energy conversion, ion sieving, and artificial photosynthesis.

A bifunctional strategy for efficient Ir-catalyzed <italic>N</italic>-alkylation of amines and sulfonamides with alcohols under aqueous and base-free conditions.

The ferocious global assault of COVID-19 continues. Critically ill patients witnessed significantly higher mortality than severe and moderate ones. Herein, we aim to comprehensively delineate clinical features of COVID-19 and explore risk factors of developing critical disease.This is a Mini-national multicenter, retrospective, cohort study involving 2,387 consecutive COVID-19 inpatients that underwent discharge or death between January 27 and March 21, 2020. After quality control, 2,044 COVID-19 inpatients were enrolled. Electronic medical records were collected to identify the risk factors of developing critical COVID-19.The severity of COVID-19 climbed up straightly with age. Critical group was characterized by higher proportion of dyspnea, systemic organ damage, and long-lasting inflammatory storm. All-cause mortality of critical group was 85•45%, by contrast with 0•58% for severe group and 0•18% for moderate group. Logistic regression revealed that sex was an effect modifier for hypertension and coronary heart disease (CHD), where hypertension and CHD were risk factors solely in males. Multivariable regression showed increasing odds of critical illness associated with hypertension, CHD, tumor, and age ≥ 60 years for male, and chronic obstructive pulmonary disease (COPD), chronic kidney disease (CKD), tumor, and age ≥ 60 years for female.We provide comprehensive front-line information about different severity of COVID-19 and insights into different risk factors associated with critical COVID-19 between sexes. These results highlight the significance of dividing risk factors between sexes in clinical and epidemiologic works of COVID-19, and perhaps other coronavirus appearing in future.10.13039/100000001 National Science Foundation of China.

Salinity is an issue impairing crop production across the globe. Under salinity stress, besides the osmotic stress and Na+ toxicity, ROS (reactive oxygen species) overaccumulation is a secondary stress which further impairs plant performance. Chloroplasts, mitochondria, the apoplast, and peroxisomes are the main ROS generation sites in salt-stressed plants. In this review, we summarize ROS generation, enzymatic and non-enzymatic antioxidant systems in salt-stressed plants, and the potential for plant biotechnology to maintain ROS homeostasis. Overall, this review summarizes the current understanding of ROS homeostasis of salt-stressed plants and highlights potential applications of plant nanobiotechnology to enhance plant tolerance to stresses.

This paper investigates a location problem of public charging stations for electric vehicles with the objective of CO2 emissions minimization through massive GPS-enabled trajectory data. The problem considers two distinct features, including CO2 emissions generated in round trips to charging stations and remaining electricity restrictions on charging decisions. A data-driven and particle swarm optimization-based intelligent optimization approach is developed to handle this problem. We then present how to implement this approach by using taxi trip data in Chengdu, China as case data and explore how much data could reflect effectively the travel patterns of an area. The results of case study show that one-week taxi trip data are sufficient to handle the investigated problem. The results also validate the necessity of considering two realistic features, including CO2 emissions in round trips to charging stations and remaining electricity restrictions on charging decisions, in charging station location problems. It can lead to (1) the reduction of daily CO2 emissions captured by about 0.14–0.37 ha of forests in one year, and (2) 0.85%–2.64% more charging demands being satisfied per day.

Solid composite electrolytes (SCEs) are regarded as an effective solution to ensure safety and enhance the energy density of lithium-based batteries. This work reports an ultrathin SCE membrane (∼ 15 μm) based on Li6.4La3Zr1.4Ta0.6O12/PVDF-HFP/LiTFSI/succinonitrile; it not only possesses good ionic conductivity (6.53 × 10–4 S cm–1 with a little amount of liquid electrolyte) at 30 °C and a satisfactory lithium ion transfer number (0.55 without electrolyte), but also exhibits excellent thermal and mechanical properties. A symmetric cell with SCE succinonitrile-10% (SN-10%) can be continuously cycled without short circuit at 0.2 mA cm–2 for about 340 h. Moreover, a high reversible discharge capacity of 150.2 mAh g–1 at 0.5 C was maintained by the cell (LiFePO4/SCE SN-10%/Li) after 269 cycles at room temperature. Notably, a capacity of about 100 mAh g–1 at 5 C was also obtained. This work might guide the improvement of future solid-state lithium/sodium metal batteries and lithium–sulfur batteries, even for wearable flexible batteries.

Autophagy can protect cells and organisms from stressors such as nutrient deprivation, and is involved in many pathological processes including human cancer.Therefore, it is necessary to investigate the role of autophagyrelated genes (ARGs) in cancer.In this study, we investigated the gene expression of 222 ARGs in 1048 Kidney Renal Clear Cell Carcinoma (KIRC) cases, from 5 independent cohorts.The gene expression of ARGs were first evaluated in the The Cancer Genome Atlas (TCGA) by Recevier Operating Characteristic (ROC) analysis to select potential biomarkers with extremely high ability in KIRC detection (AUC≥0.85 and p<0.0001).Then in silico procedure progressively leads to the selection of two genes in a three rounds of validation performed in four human KIRC-patients datasets including two independent Gene Expression Omnibus (GEO) datasets, Oncomine dataset and Human Protein Atlas dataset.Finally, only P4HB (Prolyl 4-hydroxylase, beta polypeptide) gene was experimentally validated by RT-PCR between control kidney cells and cancer cells.Following univariate and multivariate analyses of TCGA-KIRC clinical data showed that P4HB expression is an independent prognostic indicator of unfavorable overall survival (OS) for KIRC patients.Based on these findings, we proposed that P4HB might be one potential novel KIRC diagnostic and prognostic biomarker at both mRNA and protein levels.

Starch is considered as the most promising material of biodegradable polymer films. However, up to date, the preparation of starch film by film blowing technique is still a challenge. Herein, cassava starch, glycerol and nano-silica (nano-SiO2) were used to prepare thermoplastic starch (TPS) films by film blowing technique. The effects of glycerol and nano-SiO2 on the mechanical properties, thermal properties and structure of TPS films were investigated. The results showed that the elongation at break of the TPS film with 40 parts of glycerol per 100 parts of dried starch (40 phs glycerol) was up to 108%. After the addition of 1 part of nano-SiO2 per 100 parts of dried starch (1 phs nano-SiO2), the tensile strength significantly increased by about 95%, while the elongation at break did not decrease. The thermal stability of starch increased with the increase of glycerol and nano-SiO2, while its melting transition temperature did not change significantly. The crystalline structure of starch changed after processing, and the crystallinity of starch decreased with increasing glycerol and nano-SiO2.

Intelligent health monitoring devices automatically detect abnormalities in users' biomedical signals (e.g. arrhythmia from an ECG signal or a seizure from an EEG signal) through signal classification. Compared to conventional machine learning methods, neural-network-based AI classification methods are promising in achieving higher classification accuracy, but with significantly increased computational complexity, posing challenges to real-time performance and low power consumption. AI processors have been designed to accelerate neural networks for general AI applications such as image and voice recognition. They are not suitable for biomedical AI processing, which requires a combination of biomedical and AI processing hardware. In addition, the design redundancy for general AI applications results in large power consumption making it unsuitable for ultra-low-power health monitoring devices. There are also some biomedical AI processors such as ECG/EEG/EMG AI processors. However, they are customized for specific algorithms and tasks, prohibiting algorithm upgrades, limiting their applicability. In addition, prior designs lack adaptive learning to address the patient-to-patient variation issue. In this work, the BioAlP is proposed - a reconfigurable biomedical Al processor with adaptive learning. It has the following key features: 1) A reconfigurable biomedical Al processing architecture with reconfigurable neural network and biomedical processing engines to support versatile biomedical Al processing. 2) An event-driven biomedical Al processing architecture and approximate data compression technique to reduce power consumption. 3) An Al-based adaptive-learning architecture to address patient-to-patient variation. 4) A reconfigurable FIR engine reusing the neural-network engine to reduce the hardware overhead.

Salinity is a big threat to agriculture by limiting crop production. Nanopriming (seed priming with nanomaterials) is an emerged approach to improve plant stress tolerance; however, our knowledge about the underlying mechanisms is limited.Herein, we used cerium oxide nanoparticles (nanoceria) to prime rapeseeds and investigated the possible mechanisms behind nanoceria improved rapeseed salt tolerance. We synthesized and characterized polyacrylic acid coated nanoceria (PNC, 8.5 ± 0.2 nm, -43.3 ± 6.3 mV) and monitored its distribution in different tissues of the seed during the imbibition period (1, 3, 8 h priming). Our results showed that compared with the no nanoparticle control, PNC nanopriming improved germination rate (12%) and biomass (41%) in rapeseeds (Brassica napus) under salt stress (200 mM NaCl). During the priming hours, PNC were located mostly in the seed coat, nevertheless the intensity of PNC in cotyledon and radicle was increased alongside with the increase of priming hours. During the priming hours, the amount of the absorbed water (52%, 14%, 12% increase at 1, 3, 8 h priming, respectively) and the activities of α-amylase were significantly higher (175%, 309%, 295% increase at 1, 3, 8 h priming, respectively) in PNC treatment than the control. PNC primed rapeseeds showed significantly lower content of MDA, H2O2, and •O2- in both shoot and root than the control under salt stress. Also, under salt stress, PNC nanopriming enabled significantly higher K+ retention (29%) and significantly lower Na+ accumulation (18.5%) and Na+/K+ ratio (37%) than the control.Our results suggested that besides the more absorbed water and higher α-amylase activities, PNC nanopriming improves salt tolerance in rapeseeds through alleviating oxidative damage and maintaining Na+/K+ ratio. It adds more knowledge regarding the mechanisms underlying nanopriming improved plant salt tolerance.

In the system reliability evaluation of the process industries, it is sometimes difficult to get precise and sufficient failure data of system components utilized to calculate the failure probability. In this study, a Noisy-OR gate Bayesian network method based on intuitionistic fuzzy theory is proposed in cases of imprecise and insufficient historical data. The main contributes of this method include: a set of triangular intuitionistic fuzzy numbers considering uncertainty and hesitation is defined based on the standards and industry practices, meanwhile, a corresponding probability conversion method is also proposed; an improved similarity aggregation method is employed for less uncertainty accumulation and reducing the deviation caused by individual differences during the aggregation; the uncertain causal relationship among the relevant nodes is determined by applying the Noisy-OR gate in the Bayesian network. Furthermore, a case study of the crude oil tank fire and explosion accident is performed to illustrate the applicability of proposed approach. The comparison between the obtained results and that from pre-existing methods shows that the proposed method can provide a more suitable result in an uncertain environment. The weak links of the crude oil tank system are identified through Bayesian reasoning and sensitivity analysis, which can aid decision-making and improve the security execution of the crude oil tank system.

Silicon oxide is regarded as a promising anode material for lithium-ion batteries owing to high theoretical capacity, abundant reserve, and environmental friendliness. Large volumetric variations during the discharging/charging and intrinsically poor electrical conductivity, however, severely hinder its application. Herein, a core-shell structured composite is constructed by hollow carbon spheres and SiO2 nanosheets decorated with nickel nanoparticles (Ni-SiO2 /C HS). Hollow carbon spheres, as mesoporous cores, not only significantly facilitate the electron transfer but also prominently enhance the mechanical robustness of anode materials, which separately improves the rate performance and the cyclic durability. Besides, ultrathin SiO2 nanosheets, as hierarchical shells, provide abundant electrochemical active surface for capacity increment. Moreover, nickel nanoparticles boost the transport capacity of electrons in SiO2 nanosheets. Such a unique architecture of Ni-SiO2 /C HS guarantees an enhanced discharge capacity (712 mAh g-1 at 0.1 A g-1 ) and prolonged cyclic durability (352 mAh g-1 at 1.0 A g-1 after 500 cycles). The present work offers a possibility for silica-based anode materials in the application of next-generation lithium-ion batteries.

The successful application of oil-immersed transformers inspires the thought about the feasibility of the transformer oil on developing an oil-immersed battery thermal management system. This paper tentatively designs a model-scale transformer oil-immersed battery thermal management system to investigate the feasibility of the cyclic transformer oil fluid on cooling the battery. It is found that at 2C discharge rate, the battery immersed in the stationary transformer oil fluid exhibits a maximum temperature of 37.35 °C and a maximum temperature inhomogeneity of 2.64 °C, much lower than that exposed to the open air. To further improve the heat dissipation performance of the oil-immersed cooling system, different oil volumetric flow rates ranging from 3 to 50 mL/min are tested to examine the cooling effectiveness. As the oil fluid circulates, the maximum battery temperature can maintain below 35 °C. The increasing TO volumetric flow rate can continuously lower the battery temperature, while this effect gradually wanes as the flow rate exceeds 15 mL/min. The theoretical analysis indicates that as the heat transfer mode is dominated by natural convection, the increasing TO flow rate will significantly improve the cooling effectiveness of the system. In other cases, the increasing flow rate improves the cooling performance to a small extent, and concurrently intensifies the consumption of pumping power. The TO fluid with a flow rate of 15 mL/min (Reynolds number = 0.59) is suggested as the optimal choice for the current TO-immersed BTMS. The current oil-immersed battery cooling system validates the concept of direct-contact cooling method through model-scale experiments and theoretical considerations, which provides novel insights into the development of more efficient oil-immersed battery thermal management systems utilizing the dielectric oils.

The development of offshore oil and gas resources is inevitable for a submarine pipe network. Submarine pipeline leakage can easily escalate into a catastrophic event, causing enormous loss of life and property and environmental pollution. Therefore, it is imperative to conduct risk assessments of submarine pipelines. A failure mode and effects analysis (FMEA) is a significant method in risk analysis. However, due to the uncertainty in the risk analysis process, the assessment results may not be sufficiently accurate. In this paper, to evaluate the risk of submarine pipeline with enhanced reliability, an improved FMEA method based on cloud model and extended vlsekriterijumska optimizacija i kompromisno resenje (VIKOR) is proposed. The main contributions of this method are as follows. First, to minimize the associated linguistic uncertainties during the evaluation process, the cloud model theory is used, enabling the fuzziness and randomness to be comprehensively considered. Second, an improved synthetic dynamic weight algorithm, considering the personal status of experts as well as the agreement degree and confidence level of expert comments is proposed to strengthen the knowledge of the experts to minimize incompleteness. Third, an extended two-level risk factor hierarchy of submarine pipeline failure is established to improve the comprehensiveness of risk assessment, meanwhile, an integrated weighting method considering both subjective and objective aspects is utilized to obtain the risk factor weights, which can comprehensively reveal the risk factors’ relative importance. Fourth, the VIKOR method is extended with the cloud model to determine the risk priority of failure modes, which can offer a compromise solution in the context of uncertainty. Furthermore, a case study on a submarine pipeline of the Chengbei oilfield in China is performed to illustrate the applicability of proposed approach. Sensitivity analysis are carried out to observe the robustness of the proposed method. Finally, the comparison between the obtained results and that from pre-existing methods shows that the proposed method is a more accurate and effective method for the risk assessment of a submarine pipeline.

Strawberries are a widely consumed fruit that contains a variety of antioxidant metabolites. However, postharvest strawberries are highly perishable and susceptible to a variety of fungal pathogens. In this study, a chitosan-based coating containing turmeric (TU) and green tea (GT) extracts was developed and evaluated for the preservation of strawberries. Both TU and GT extracts contained high phenolic contents (>5.8 g kg−1 dry weight), but only TU extract showed strong antifungal activity. SEM observations revealed that high concentrations of extract (3–5% v/v) caused the formation of agglomerates within the films, reduced elongation at break and increased tensile strength. The postharvest treatment of strawberries with chitosan coating containing TU extract inhibited the proliferation of Botrytis cinerea during 7 d of storage at 20 °C, whereas the coating containing GT extract extended the antioxidant properties of postharvest strawberries from 4 to 8 d at 20 °C. Sensory analysis indicated that the coatings did not significantly affect flavor and taste. Overall, TU extract was used for the first time for food packaging purposes and proved to be a great complement to the antioxidant properties of GT to extend the shelf-life of postharvest strawberries.

Finely tuned mitogen-activated protein kinase (MAPK) signaling is important for cancer cell survival. Perturbations that push cells out of the MAPK fitness zone result in cell death. Previously, in a screen of the North China Pharmaceutical Group Corporation's pure compound library of microbial origin, we identified elaiophylin as an autophagy inhibitor. Here, we demonstrated a new role for elaiophylin in inducing excessive endoplasmic reticulum (ER) stress, ER-derived cytoplasmic vacuolization, and consequent paraptosis by hyperactivating the MAPK pathway in multiple cancer cells. Genome-wide CRISPR/Cas9 knockout library screening identified SHP2, an upstream intermediary of the MAPK pathway, as a critical target in elaiophylin-induced paraptosis. The cellular thermal shift assay (CETSA) and surface plasmon resonance (SPR) assay further confirmed the direct binding between the SHP2 and elaiophylin. Inhibition of the SHP2/SOS1/MAPK pathway through SHP2 knockdown or pharmacological inhibitors distinctly attenuated elaiophylin-induced paraptosis and autophagy inhibition. Interestingly, elaiophylin markedly increased the already-elevated MAPK levels and preferentially killed drug-resistant cells with enhanced basal MAPK levels. Elaiophylin overcame drug resistance by triggering paraptosis in multiple tumor-bearing mouse models resistant to platinum, taxane, or PARPi, suggesting that elaiophylin might offer a reasonable therapeutic strategy for refractory ovarian cancer.

This paper presents a periodic event-triggered sliding mode control (SMC) scheme based on human-robot cooperation for lower limb exoskeletons. Firstly, a Genetic Algorithm-Back propagation (GA-BP) neural network is proposed to estimate the motion intention of the wearer through electromyography (EMG) signals. Secondly, the periodic event-triggered SMC strategy based on tanh function is designed to ensure the asymptotic convergence of the exoskeleton system and save communication resources, where the detailed expressions of sampling period and control gain are designed. Finally, comparative simulation and experimental analysis is presented to verify the effectiveness of the proposed control method.

ECG classification is a key technology in intelligent electrocardiogram (ECG) monitoring. In the past, traditional machine learning methods such as support vector machine (SVM) and K-nearest neighbor (KNN) have been used for ECG classification, but with limited classification accuracy. Recently, the end-to-end neural network has been used for ECG classification and shows high classification accuracy. However, the end-to-end neural network has large computational complexity including a large number of parameters and operations. Although dedicated hardware such as field-programmable gate array (FPGA) and application-specific integrated circuit (ASIC) can be developed to accelerate the neural network, they result in large power consumption, large design cost, or limited flexibility. In this work, we have proposed an ultra-lightweight end-to-end ECG classification neural network that has extremely low computational complexity (∼8.2k parameters & ∼227k multiplication/addition operations) and can be squeezed into a low-cost microcontroller (MCU) such as MSP432 while achieving 99.1% overall classification accuracy. This outperforms the state-of-the-art ECG classification neural network. Implemented on MSP432, the proposed design consumes only 0.4 mJ and 3.1 mJ per heartbeat classification for normal and abnormal heartbeats respectively for real-time ECG classification.

System auditing provides a low-level view into cyber threats by monitoring system entity interactions. In response to advanced cyber-attacks, one prevalent solution is to apply data provenance analysis on audit records to search for anomalies (anomalous behaviors) or specifications of known attacks. However, existing approaches suffer from several limitations: 1) generating high volumes of false alarms, 2) relying on expert knowledge, or 3) producing coarse-grained detection signals. In this paper, we recognize the structural similarity between threat detection in cybersecurity and recommendation in information retrieval. By mapping security concepts of system entity interactions to recommendation concepts of user-item interactions, we identify cyber threats by predicting the preferences of a system entity on its interactive entities. Furthermore, inspired by the recent advances in modeling high-order connectivity via item side information in the recommendation, we transfer the insight to cyber threat analysis and customize an automated detection system, SHADEWATCHER. It fulfills the potential of high-order information in audit records via graph neural networks to improve detection effectiveness. Besides, we equip SHADEWATCHER with dynamic updates towards better generalization to false alarms. In our evaluation against both real-life and simulated cyber-attack scenarios, SHADEWATCHER shows its advantage in identifying threats with high precision and recall rates. Moreover, SHADEWATCHER is capable of pinpointing threats from nearly a million system entity interactions within seconds.

Biological ion channels regulate the ion flow across cell membrane via opening or closing of the pores in response to various external stimuli. Replicating the function of high ion gating effects with artificial porous materials has been challenging. Herein, we report that the self-assembled two-dimensional metal-organic framework (MOF) membrane can serve as an excellent nanofluidic platform for smart regulation of ion transport. The MOF membrane with good photothermal performance exhibits extremely high ion gating ratio (up to 104 ), which is among the highest values in MOF membrane nanochannels for light-controlled ion gating reported so far. By repeatedly turning on and off the light, the nanofluidic device shows outstanding stability and reversibility that can be applied in the remote light-switching system. This work may spark promising applications of MOF membrane with variety of stimuli responsive properties in ion sieving, biosensing, and energy conversion.

Chemotherapy is an important adjuvant treatment of glioma, while the efficacy is far from satisfactory, due not only to the biological barriers of blood‒brain barrier (BBB) and blood‒tumor barrier (BTB) but also to the intrinsic resistance of glioma cells via multiple survival mechanisms such as up-regulation of P-glycoprotein (P-gp). To address these limitations, we report a bacteria-based drug delivery strategy for BBB/BTB transportation, glioma targeting, and chemo-sensitization. Bacteria selectively colonized into hypoxic tumor region and modulated tumor microenvironment, including macrophages repolarization and neutrophils infiltration. Specifically, tumor migration of neutrophils was employed as hitchhiking delivery of doxorubicin (DOX)-loaded bacterial outer membrane vesicles (OMVs/DOX). By virtue of the surface pathogen-associated molecular patterns derived from native bacteria, OMVs/DOX could be selectively recognized by neutrophils, thus facilitating glioma targeted delivery of drug with significantly enhanced tumor accumulation by 18-fold as compared to the classical passive targeting effect. Moreover, the P-gp expression on tumor cells was silenced by bacteria type III secretion effector to sensitize the efficacy of DOX, resulting in complete tumor eradication with 100% survival of all treated mice. In addition, the colonized bacteria were finally cleared by anti-bacterial activity of DOX to minimize the potential infection risk, and cardiotoxicity of DOX was also avoided, achieving excellent compatibility. This work provides an efficient trans-BBB/BTB drug delivery strategy via cell hitchhiking for enhanced glioma therapy.

Herein, poly(3-alkylthiophene)s (P3ATs) and poly[(3-alkylthio)thiophene]s (P3ATTs) are respectively synthesized using poly(thiophene)s with linear/branched alkyl groups and branched alkylthio moieties with short/long side chain lengths for dispersing single-walled carbon nanotubes (SWCNTs), and the resulting composites are solution-processed for use as p-type thin film thermoelectric devices. With an additional sulfur atom on the side chain, a well-dispersed P3ATTs/SWCNTs nanocomposite is obtained by polymer-wrapping at the SWCNTs surfaces driven by S − π and π − π interactions between the alkylthio side chain substituents and π-conjugated backbones of the P3ATTs and SWCNTs, thereby contributing to greatly improved thermoelectric performance relative to the P3ATs/SWCNTs nanocomposite without the added sulfur. The poly[3-(2-hexyldecylthio)thiophene] (P3HDTT) nanocomposite with the longest alkylthio side chain exhibits the strongest interaction with the SWCNTs, yielding the highest power factor (PF) of 307.7 μW m−1 K−2. The ability of this spray-coated nanocomposite film to generate power is demonstrated with a prototype flexible thermoelectric generator (TEG) that produces 888.1 μW m−2. Thus, the introduction of debundled SWCNTs networks wrapped by P3ATTs with alkylthio side chains suggests a feasible strategy for the design of high-performance thermoelectric materials and opens up new opportunities for capturing waste heat in wearable electronics.

Molybdenum disulfide (MoS2) has attracted great attention in hydrogen peroxide (H2O2) activation as a Fenton-like catalyst and cocatalyst, but the distinct mechanism of generating •OH remains unclear. In this paper, the metallic 1T phase and semiconducting 2H phase of MoS2 nanosheets were prepared and applied in MoS2/H2O2 and MoS2/Fe2+/H2O2 systems with and without light irradiation. Compared with 2H-MoS2, 1T-MoS2 exhibited superior removal rates in degrading organic pollutants in the two systems under light irradiation. However, the phase had little effect on activating H2O2 in the MoS2/H2O2 system under dark conditions. This is because it was difficult for the surface •OHads generated in the MoS2/H2O2 system to diffuse into solution, while the •OHfree radicals were mainly responsible for degrading organic pollutants. When introducing light irradiation, external energy may accelerate the desorption of •OHads into •OHfree. Interestingly, the conversion between Mo4+ and Mo5+ triggered the decomposition of H2O2 in the Fenton-like reaction, while the cycle of Mo4+/Mo6+ promoted the regeneration of Fe3+ when employing 1T-MoS2 as a cocatalyst. Meanwhile, the 1T-MoS2 catalysts exhibited excellent stability and ability to degrade various organics in the two systems. This work offers deeper insight into the MoS2-based Fenton-like and cocatalytic mechanisms.

High-performance nanofiltration membrane is of great importance to alleviate the worldwide freshwater crisis. Recent studies have shown that the performance of nanofiltration membranes can be enhanced by optimizing the properties of the substrates. Substrates with large pores are favorable to mass transfer but difficult to prepare highly selective polyamide layers on them by interfacial polymerization reaction. Here we employed porous two-dimensional (2D) aluminum-metal organic framework (Al-MOF) nanosheets to tune the commercial Nylon microfiltration substrate, and then prepared polyamide nanofiltration membranes by interfacial polymerization. 2D Al-MOF nanosheets were chosen for the tuning material except for their obvious advantages of easy synthesis and structural stability, the most important thing was their high porosity, which provided additional water transport channels. The morphologies as well as the separation properties were analyzed systematically. The best-performing Nylon-2.5 TFC membrane achieved an ultrahigh permeability (42.4 L m−2 h−1 bar−1), 13 times that of a control (PES-0) TFC membrane prepared on commercial PES substrate under the same interfacial polymerization conditions while ensuring the high rejection of Na2SO4 (97.0%). Our work provides insights for optimizing substrate properties to prepare high-performance nanofiltration membranes.

Resveratrol has been garnering considerable attention as a promising chemopreventive and chemotherapeutic drug against metastatic tumors such as triple-negative breast cancer (TNBC). However, the potential in vivo application of resveratrol has been highly limited due to its poor solubility, rapid conjugation, low bioavailability, and bioactivity. In this study, a silica mesoporous nanoparticle (MSN)-based drug delivery system (DDS), named Au-Se@MSN, is developed to deliver the loaded resveratrol, endowing it with properties of targeted delivery, excellent bioavailability, and antioxidation of resveratrol. In Au-Se@MSN(RES), gold nanoparticles functionalized with selenol-modified uPA-specific peptides act as gatekeepers to avoid the interference of glutathione in the bloodstream and realize negligible premature release of resveratrol during delivery. Au-Se@MSN(RES) shows prolonged resveratrol release at the tumor site and endows resveratrol with a remarkable in vitro therapeutic effect. The pharmacological dose of resveratrol treatment on MDA-MB-231 cells was found to result in the generation of a high level of NAD(P)H other than H2O2, indicating reductive stress instead of oxidative stress involved in the resveratrol therapeutic process. In vivo experiments showed that Au-Se@MSN greatly improves the chemotherapeutic effect of resveratrol on mice bearing TNBC tumors, and damage to normal tissues and cells is negligible. Overall, Au-Se@MSN is a potential tool for further studies on the anticancer mechanism and clinical applications of resveratrol.

This review predominantly focuses on the progress of a variety of cobalt-based nitride materials, especially pertaining to their photo(electro)catalytic applications in solar energy conversion.

Photoperiod is one of the most important environmental cues for the organism, and it plays a critical role in regulating organisms' survival, growth, and metabolism. In the present study, the effects of photoperiod (0 L∶24 D, 6 L∶18 D, 12 L∶12 D, 18 L∶6 D, and 24 L∶0 D) on mortality, growth performance, and lipid metabolism of juvenile mud crab (Scylla paramamosain) were studied with an 8-week experiment. The results showed that the highest final weight of crabs was observed in the 18 L∶6 D (0.48 ± 0.08 g), which was significantly higher than 0 L∶24 D (0.22 ± 0.03 g) and 6 L∶18 D (0.28 ± 0.04 g) (P < 0.05). In addition, the specific growth rate (SGR) of crabs reared at 12 L∶12 D (natural photoperiod) (5.83 ± 0.26% day−1) and 18 L∶6 D (6.28 ± 0.27% day−1) were significantly higher than 0 L∶24 D (4.70 ± 0.42% day−1), 6 L∶18 D (5.16 ± 0.22% day−1) and 24 L∶0 D (5.60 ± 0.23% day−1) (P < 0.05). The survival rate of the natural photoperiod group was significantly higher than 18 L∶6 D group (69.23 ± 6.28% vs 35.90 ± 3.63%) (P < 0.05), but no significant difference between 0 L∶24 D (58.97 ± 3.63%), 6 L∶18D (66.67 ± 7.25%) and 24 L∶0 D (58.97 ± 7.25%) groups was observed (P > 0.05). Crabs exposed to 18 L∶6 D photoperiod also had higher melatonin (311.12 ± 79.53 pg mL−1 vs 168.79 ± 31.24 pg mL−1) and cortisol levels (451.37 ± 237.64 ng mL−1 vs 112.91 ± 39.32 ng mL−1) than those reared in constant light (24 L∶0 D) (P < 0.05). In addition, compared with natural photoperiod, crabs reared under constant darkness showed significantly higher TG and TC content (P < 0.05). Moreover, in constant darkness, lipogenesis-related genes such as fatty acid synthase (fas), sterol regulatory element binding protein-1 (srebp-1), and acetyl-CoA carboxylase (acc) of the crab were up-regulated, and lipolysis-related genes as carnitine palmitoyltransferase-1 (cpt-1), Acyl-CoA oxidase-3 (aco-3) were significantly down-regulated (P < 0.05). Besides, fatty acid binding protein (fabp) was also up-regulated in crabs reared under constant darkness. Thus, these results suggest that the crabs in constant darkness did not effectively utilise the lipid as an energy source. Overall, the present research confirmed that light cues are indispensable for the indoor mud crab culture system, and the natural photoperiod was recommended for mud crab during the juvenile grow-out phase in commercial operations.

For a pump as turbine (PAT) unit in storage mode, based on the design requirements for flow rate reduction without loss of efficiency and radial force performances, in this study, an effective parameterization method was used to control the geometric shape of guide vane, efficiency and radial force of the unit are set as optimization goals. It is proposed an optimization strategy that combining Fuzzy Logic (FL) with Genetic Algorithm (GA), and combining numerical simulation with experimental verification. The optimization results showed that the efficiency of each working condition has obviously increased while the radial force has decreased. For the target working condition after flow rate reduction, the efficiency is increased by 2.8 % and the radial force is effectively reduced by 37.3 %. It indicated that the study provided a new and effective optimization strategy for improving matching relationship between the impeller and guide vane of turbine machineries.

Lithium-sulfur (Li-S) batteries have the advantages of high-energy-density, low cost, and environmental friendliness, but the sluggish sulfur redox reactions and the severe shuttle effect of lithium polysulfide (LiPSs) affect their performance. Herein, we developed a highly efficient electrocatalyst (CNT/HEA-NC) consisting of high-entropy alloy (HEA) nanoparticles decorated with nitrogen-doped carbon (NC) and carbon nanotubes (CNTs) conductive networks. In the elaborate nanostructured protocol, the HEA nanoparticles with high catalytic activity accelerate the bidirectional conversion of LiPSs, the NC with strong sulfophilic activity effectively adsorb LiPSs to suppress the shuttle effect, and the CNT conductive network provides a fast electrons/ions transport pathway. Benefiting from the hierarchical confinement, Li-S batteries with CNT/HEA-NC modified separators deliver a discharge specific capacity of 692.0 mA h g−1 after 300 cycles at 1 C with a capacity decay rate of only 0.03% per cycle. Even at a current density of 5 C, the cell exhibits a superior capacity of 521.1 mAh g−1. This work provides a general strategy for integrating multifunctional electrocatalysts for high-performance Li-S batteries.

Accurate prediction of capacity and remaining useful life (RUL) for lithium-ion batteries (LIBs) is crucial for ensuring safe and reliable operation of electric vehicles. However, the battery capacity degradation and external environmental disturbances make it still challenging to achieve this goal. In this article, an accurate capacity and RUL prediction method is proposed by combining improved particle swarm optimization (IPSO) with particle filter (PF) algorithms. First, the parameters of particle swarm optimization (PSO) algorithm are adjusted by adaptive weights to avoid the problem of local optimal solution. Subsequently, the optimal particle searched by IPSO is updated continuously by the PF algorithm to achieve a more accurate posterior estimation. Finally, the proposed IPSO-PF method is verified by two independent and public datasets of NASA and CALCE batteries. The results validate that the proposed method has high precision and generalizability in predicting the capacity and RUL of LIBs even at various charging rates and battery types.

The crystallization kinetics, phase formation and magnetic properties of (FeCoNiMn0.25Al0.25)75Si13B12 high-entropy metallic glass are investigated by thermal analysis, electron microscopic imaging, X-ray and magnetic tests. The results indicate that the alloy combines good glass forming ability and thermal stability. After heat treatment, the alloy precipitates with a feature of three-dimensional growth, while the α-Fe,Co phase first precipitates, and following the lamellar eutectic precipitate as Fe-B and Co2Si. This ultra-fine α-Fe,Co at low temperatures and the solid solution of non-ferromagnetic elements in the α-Fe,Co at high temperatures decrease the saturation magnetization of the alloy. In addition, the change from antiferromagnetic to ferromagnetic of Mn is confirmed through first-principles density functional theory calculations.

For sustained and stable improvement of the diabetic wound microenvironment, a temperature-sensitive composite hydrogel (ZnDBs/HBC) composed of inorganic zinc mineralized diatom biosilica (ZnDBs) and hydroxybutyl chitosan (HBC) was developed. The interfacial anchoring effect between ZnDBs and HBC enhanced the mechanical strength of the hydrogel. The mechanical strength of the composite hydrogel containing 3 wt% ZnDBs was increased by nearly 2.3times. The hydrogel can be used as a carrier for sustained release of Zn2+ for at least 72 h. In diabetic rats models, ZnDBs/HBC composite hydrogel could accelerate the inflammatory process by regulating the expression of pro-inflammatory factor IL-6 and anti-inflammatory factor IL-10, and also promote tissue cell proliferation and collagen deposition, thereby restoring the normal healing process and accelerating wound healing. The wound contraction rate of the composite hydrogel group was more than 2 times that of the control group. Therefore, ZnDBs/HBC composite hydrogel has the potential to be used as a therapeutic dressing for diabetic chronic wounds.

Aqueous sodium-ion batteries are practically promising for large-scale energy storage, however energy density and lifespan are limited by water decomposition. Current methods to boost water stability include, expensive fluorine-containing salts to create a solid electrolyte interface and addition of potentially-flammable co-solvents to the electrolyte to reduce water activity. However, these methods significantly increase costs and safety risks. Shifting electrolytes from near neutrality to alkalinity can suppress hydrogen evolution while also initiating oxygen evolution and cathode dissolution. Here, we present an alkaline-type aqueous sodium-ion batteries with Mn-based Prussian blue analogue cathode that exhibits a lifespan of 13,000 cycles at 10 C and high energy density of 88.9 Wh kg-1 at 0.5 C. This is achieved by building a nickel/carbon layer to induce a H3O+-rich local environment near the cathode surface, thereby suppressing oxygen evolution. Concurrently Ni atoms are in-situ embedded into the cathode to boost the durability of batteries.

In vivo sensing of the dynamics of ions with high selectivity is essential for gaining molecular insights into numerous physiological and pathological processes. In this work, we report an ion-selective micropipette sensor (ISMS) through the integration of functional crown ether-encapsulated metal–organic frameworks (MOFs) synthesized in situ within the micropipette tip. The ISMS features distinctive sodium ion (Na+) conduction and high selectivity toward Na+ sensing. The selectivity is attributed to the synergistic effects of subnanoconfined space and the specific coordination of 18-crown-6 toward potassium ions (K+), which largely increase the steric hindrance and transport resistance for K+ to pass through the ISMS. Furthermore, the ISMS exhibits high stability and sensitivity, facilitating real-time monitoring of Na+ dynamics in the living rat brain during spreading of the depression events process. In light of the diversity of crown ethers and MOFs, we believe this study paves the way for a nanofluidic platform for in vivo sensing and neuromorphic electrochemical sensing.

Background and Purpose— Little is known about the metabolic syndrome (MetS) and the risk of incident stroke. This study is designed to identify particular clusters of MetS components that carry the highest risk of incident stroke. Methods— We analyzed the public use data from the population-based Atherosclerosis Risk in Communities study. At baseline, 14 993 stroke-free middle-aged individuals were followed-up over 9 years for incident stroke. MetS components were defined according to the National Heart, Lung, and Blood Institute/American Heart Association criteria. Incident stroke was identified using a standardized incident events identification and classification protocol. Proportional hazard models were used to assess the RRs and 95% CIs of ischemic stroke associated with MetS and its different clusters. Results— At baseline, the prevalence of MetS was 39%. The mean age was 54, with 26% blacks and 55% females. The hazard ratio of incident ischemic stroke associated with MetS among women (hazard ratio, 2.41; 95% CI, 1.69 to 3.49) and men (hazard ratio, 2.11; 95% CI, 1.56–2.85) was similar. There was a dose–response relationship between the numbers of MetS components and the risk of incidence stroke. Persons with either elevated blood pressure or elevated fasting glucose in the clusters to form a MetS had the highest risk for incident stroke (hazard ratio, 2.74–4.16 comparing to the reference group) than MetS without these 2 components (hazard ratio, ≤2.00 comparing to the reference group). Conclusions— The data support the need to target MetS, especially MetS, with these 2 highest risk components (elevated blood pressure or elevated fasting glucose) in the clusters.

Purpose The purpose of this study is to compare human serum levels of TH1 and TH2 cytokines between 2 stages of primary open-angle glaucoma (POAG) and nonglaucomatous controls. Methods Thirty-two patients with primary POAG and 26 normal control subjects were enrolled into this study. The 32 patients with POAG were divided into 2 subgroups according to their mean defect (MD) with MD better than −12 dB and worse than −12 dB on the visual field. Enzyme-linked immunosorbent assay was used to assay for the levels of TH1 cytokines serum soluble interleukin-2 receptor (sIL-2R), interleukin (IL)-2, IL-12p40, IL-12p70, IL-23, tumor necrosis factor (TNF)-alpha, interferon-gamma, and TH2 cytokines IL-4, IL-6 in the peripheral serum. Results Patients with mild glaucomatous neuropathy exhibited significant elevations in IL-4 (P<0.0001) and IL-6 (P=0.0302) compared with the controls, whereas higher concentrations of IL-4 (P<0.0001) and IL-6 (P=0.0084) were found in patients with severe glaucomatous neuropathy. The level of IL-12p70 was significantly increased in both the MD ≥12 dB (P<0.0001) and MD <12 dB (P<0.0001) groups. A significant decrease in TNF-alpha levels were observed in MD <12 dB group compared with the controls (P=0.0464), and TNF-alpha levels in MD <12 dB group were lower than MD ≥12 dB group (P=0.0328). No significant differences in serum concentrations of IL-2, sIL-2R IL-12p40, IL-23 and interferon-gamma were found between MD <12 dB group, MD ≥12 dB group, and control group. Conclusions Significant alterations of serum TH1 and TH2 cytokines are associated with glaucoma, suggesting the possibility that abnormal immune environments contribute to the glaucomatous neuropathy of POAG.

The retrogression and thermal regime of a thaw slump affecting the stability of a slope along the Qinghai–Tibet Highway in China were studied over the last twenty years. The thaw slump was initiated in 1992 and the retrogression rate at the headwall slowed down somewhat in the recent years following the thermal stabilization of the affected area. According to field observation and monitoring, while the ground temperature was still not stabilized after the occurrence of the thaw slump, the depth of the permafrost table was usually shallower in the recently disturbed area than in the undisturbed area away from the thaw slump. However, due to a positive heat budget in the disturbed area, the ground temperature was increasing and the permafrost table was deepening. Moreover, since the ground temperature is higher close to the headwall than in the undisturbed area, lateral heat flux occurs in the thaw slump area inducing more retrogression at the headwall. However, as soon as the vegetation invaded the bare ground surface of the disturbed area, the ground temperature was decreasing in the disturbed area over the past two years and stabilization of the disturbed area was occurring. Following the stopping of the headwall retrogression and the decrease of the lateral heat flux, the ground temperature near the headwall is also decreasing.

Water-in-salt (WIS) electrolytes are successfully introduced into carbon-based supercapacitors to effectively promote energy density. However, temperature-dependent performance of carbon-based supercapacitors with these electrolytes is rarely discussed, and the key factors, determined electrochemical performance at a wide temperature range, are not revealed completely. Herein, three rose petal-derived porous carbons (RPC) with different pore properties are prepared by a KOH activation strategy. The electrochemical performance of RPC-based supercapacitors with different concentration LiTFSI WIS electrolytes is investigated from −20 to 100 °C. The working voltage of these supercapacitors can reach 2.4 V, and thus the energy density of RPC supercapacitors with 20 m LiTFSI electrolyte can highly attain 44 W h kg−1 at 564 W kg−1 and 60 °C. Even though the power density is 3.5 kW kg−1 at 25 °C, it can be maintained to 12 W h kg−1. More importantly, the electrochemical performance intimately depends on the temperature. Both electrolyte concentration and pore properties of RPC significantly influence the electrochemical performance of these supercapacitors at different temperature. Therefore, to achieve superior performance for carbon-based supercapacitors with the LiTFSI WIS electrolyte at a wide temperature range, the optimization of electrolyte concentration and rational design for pore properties of carbon materials are essential strategies.

The present study seeks to detect oxidative damage and to compare anti-oxidative responses among liver, gills and brain of adult zebrafish that were cooled from 28 °C (control) to 12 °C (treatment) for 0–24 h. The lipid peroxidation of liver, gill and brain tissues significantly increased at 1 h after transfer, but reactive oxygen species in the treatment group increased significantly after 24 h as compared to the control. The fish were found to develop a cascading anti-oxidative mechanism beginning with an increase in Cu/Zn-SOD levels, followed by increased CAT and GPx mRNA expressions in the three tissue types. Both smtB and mt2 mRNAs increased in the hepatic and brain tissues following 1 h of cold stress, but only smtB exhibited a significant increase in the gills at 1 h and 6 h after transfer to 12 °C. Furthermore, cellular apoptosis in the brain was not evident after cold shock, but liver and gills showed cellular apoptosis at 1–3 h, with another peak in the liver at 6 h after cold shock. The results suggest that the cold shock induced oxidative stress, and the enzymatic (SOD, GPx and CAT) and non-enzymatic (mt-2 and smt-B) mRNA expressions all play a role in the resulting anti-oxidation within 1–6 h of cold shock. A functional comparison showed that the brain had the most powerful antioxidant defense system of the three tissue types since it had the highest smtB mRNA expression and a lower level of cell apoptosis than the liver and gills after exposure to cold stress.

Numerous lithium-ion battery (LIB) fires and explosions have raised serious concerns about the safety issued associated with LIBs; some of these incidents were mainly caused by overcharging of LIBs.Therefore, to have a better understanding of the fire hazards caused by LIB overcharging, two widely used commercial LIBs, nickel manganese cobalt oxide (NMC) and lithium iron phosphate (LFP), with different cut-off voltages (4.2 V, 4.5 V, 4.8 V and 5.0 V), were tested in this work.Some parameters including the surface temperature, the flame temperature, voltage, and radiative heat flux were measured and analyzed.The results indicate that the initial discharging voltage increases with the growth of charge cut-off voltage.Moreover, the higher the cut-off voltage, the longer the discharging time to reach 2.5 V.An overcharged LIB will undergo a more violent combustion process and has lower stability than a normal one, and the increasing cut-off voltage aggravates the severity.In addition, it is also revealed that the NMC fails earlier than the LFP under the same condition.The temperatures for safety vent cracking, ignition, and thermal runaway of LIBs exhibit similar values for the same condition, which demonstrates that the LIB will fail at a certain temperature.Finally, the peak heat flux, total radiative heat flux, and total radiative heat will rise with the increase in voltage.

We focus on essay generation, which is a challenging task that generates a paragraph-level text with multiple topics.Progress towards understanding different topics and expressing diversity in this task requires more powerful generators and richer training and evaluation resources. To address this, we develop a multi-topic aware long short-term memory (MTA-LSTM) network.In this model, we maintain a novel multi-topic coverage vector, which learns the weight of each topic and is sequentially updated during the decoding process.Afterwards this vector is fed to an attention model to guide the generator.Moreover, we automatically construct two paragraph-level Chinese essay corpora, 305,000 essay paragraphs and 55,000 question-and-answer pairs.Empirical results show that our approach obtains much better BLEU score compared to various baselines.Furthermore, human judgment shows that MTA-LSTM has the ability to generate essays that are not only coherent but also closely related to the input topics.

This paper investigates the finite-time stabilization problem for interval type-2 T-S fuzzy systems with norm-bounded uncertainties and time-varying delays. A static output feedback controller is designed to guarantee the finite-time stability of closed-loop fuzzy control systems. Data packet loss is assumed to exist in the feedback transmission channel, and a novel delay product-type Lyapunov–Krasovskii function is constructed for deriving the delay-dependent stabilization conditions. These conditions can be denoted by linear matrix inequalities, according to matrix decoupling techniques and inequality constriction methods. The information of the upper and lower membership functions is integrated into the stabilization conditions using a membership function-dependent analysis method to reduce conservativeness. The simulation results demonstrate the effectiveness of the proposed finite-time control method.

Abstract The vacuolar protein sorting 33B (VPS33B) was rarely reported in malignant tumors. In this research, we demonstrated that overexpression of VPS33B inhibited proliferation and chemoresistance to fluorouracil (5-FU) in nasopharyngeal carcinoma (NPC) in vivo and in vitro. Mechanistic analysis confirmed that overexpression of VPS33B modulated EGFR/PI3K/AKT/c-Myc/P53 signaling to arrest the cell cycle at G1/S phase. In addition, miR-133a-3p, a tumor-suppressive miRNA, was induced by P53 and directly targeted the EGFR/PI3K/AKT/c-Myc/P53 signaling and thus formed a negative feedback loop. Furthermore, another tumor suppressor, NESG1, interacted with VPS33B by colocalizing in the cytoplasm. The knockdown of NESG1 reversed the inhibitory effects of the overexpression of VPS33B in NPC cells by downregulating the PI3K/AKT/c-Jun-mediated transcription repression. Surprisingly, VPS33B was downregulated in the nicotine-treated and LMP-1-overexpressing NPC cells by targeting PI3K/AKT/c-Jun-mediated signaling. In addition, patients with higher VPS33B expression had a longer overall survival. Our study is the first to demonstrate that VPS33B is negatively regulated by LMP-1 and nicotine and thus suppresses the proliferation of NPC cells by interacting with NESG1 to regulate EGFR/PI3K/AKT/c-Myc/P53/miR-133a-3p signaling in NPC cells.

Abstract In this study, we present novel molecular mechanisms by which FOXO1 functions as a tumor suppressor to prevent the pathogenesis of nasopharyngeal carcinoma (NPC). First, we observed that FOXO1 not only controlled tumor stemness and metastasis, but also sensitized NPC cells to cisplatin (DDP) in vitro and in vivo. Mechanistic studies demonstrated that FOXO1-induced miR-200b expression through the GSK3β/β-catenin/TCF4 network-mediated stimulation of ZEB1, which reduced tumor stemness and the epithelial–mesenchymal transition (EMT) signal. Furthermore, we observed FOXO1 interaction with MYH9 and suppression of MYH9 expression by modulating the PI3K/AKT/c-Myc/P53/miR-133a-3p pathway. Decreased MYH9 expression not only reduced its interactions with GSK3β, but also attenuated TRAF6 expression, which then decreased the ubiquitin-mediated degradation of GSK3β protein. Increased GSK3β expression stimulated the β-catenin/TCF4/ZEB1/miR-200b network, which increased the downstream tumor stemness and EMT signals. Subsequently, we observed that chemically synthesized cinobufotalin (CB) strongly increased FOXO1-induced DDP chemosensitivity by reducing MYH9 expression, and the reduction in MYH9 modulated GSK3β/β-catenin and its downstream tumor stemness and EMT signal in NPC. In clinical samples, the combination of low FOXO1 expression and high MYH9 expression indicated the worst overall survival rates. Our studies demonstrated that CB potently induced FOXO1-mediated DDP sensitivity by antagonizing its binding partner MYH9 to modulate tumor stemness in NPC.

In the current work, a series of experiments were carried out under low and normal temperature conditions (0 and 20 °C) to research the influence of low temperature on the performance of lithium-ion batteries (LIBs). Besides this, a commercial insulation material (IM) was employed to research its effect on preventing damage in a battery exposed to low temperature. Based on the experimental results, it was found that the battery exhibited a higher temperature increase at low ambient temperature due to the larger internal resistance of the battery at low temperature, which resulted in greater heat generation. It was also observed that the low temperature caused the uniformity of the battery to deteriorate as a result of temperature and voltage differences, and the uniformity became poorer with increasing cycle rate. Moreover, the capacity decay rate of the battery was demonstrated to be greatly accelerated by the low temperature. According to the morphological changes of the battery components, the structure of the electrode materials and separator was damaged under low temperature conditions. Finally, the results show that the IM had a significant effect on warming the battery up; therefore, a much better discharge performance and slower decay rate of the battery were achieved. Furthermore, the performance of the IM was found to be related to its thickness.

Salmonella selectively colonizes into the hypoxic tumor region and exerts antitumor effects via multiple mechanisms, while the tumor colonized Salmonella recruits host neutrophils into the tumor, presenting a key immunological restraint to compromise the Salmonella efficacy. Here, we develop a combinatorial strategy by employing silver nanoparticles (AgNPs) to improve the efficacy and biosafety of Salmonella. The AgNPs were decorated with sialic acid (SA) to allow selective recognition of L-selectin on neutrophil surfaces, based on which the tumor-homing of AgNPs was achieved by neutrophil infiltration in the Salmonella colonized tumor. The tumor-targeting AgNPs exert the functions of (1) local depletion of neutrophils in tumors to boost the efficacy of Salmonella, (2) direct killing tumor cells via L-selectin-mediated intracellular delivery, and (3) clearing the residual Salmonella after complete tumor eradication to minimize the side effects. With a single tail vein injection of such combination treatment, the tumor was eliminated with high biosafety, resulting in a superior therapeutic outcome.

Although the thermal behaviors including thermal instability of nitrocellulose (NC) and its mixtures with some humectants have been comprehensively examined previously in the literature, their combustion characteristics have not been systematically studied. To address the issue, the combustion properties of NC with alcohol humectants are investigated by the means of the ISO 5660 cone calorimeter. Two kinds of NC-humectant mixtures with 30 wt.% isopropanol and 30 wt.% ethanol, respectively, were employed as samples. The tests were conducted under different external radiations, ranging from 0–15 kW/m2. The experimental results indicate that the external radiation positively influences the peak heat release rate (HRR) intensity and the maximum mass loss rate (MLR), while the total heat release (THR) decreases with the elevated external radiation. Comparatively, the sample with isopropanol exhibits a higher fire risk, characterized by the higher peak HRR, THR and maximum MLR. Auxiliary investigating methods, including Scanning Electron Microscopy and Differential Scanning Calorimeter-Thermal Gravimetric Analysis, were applied to examine the micro structure and thermal behavior of NC-humectant mixtures. The results helped to explain the burning characteristics observed in the cone calorimeter tests.

Abstract A sustainable and green route to access diverse functionalized ketones via dehydrogenative–dehydrative cross‐coupling of primary and secondary alcohols is demonstrated. This borrowing hydrogen approach employing a pincer N‐heterocyclic carbene Mn complex displays high activity and selectivity. A variety of primary and secondary alcohols are well tolerant and result in satisfactory isolated yields. Mechanistic studies suggest that this reaction proceeds via a direct outer‐sphere mechanism and the dehydrogenation of the secondary alcohol substrates plays a vital role in the rate‐limiting step.

Abstract The degeneration of dopaminergic neurons is a major contributor to the pathogenesis of mid‐brain disorders. Clinically, cell therapeutic solutions, by increasing the neurotransmitter dopamine levels in the patients, are hindered by low efficiency and/or side effects. Here, a strategy using electromagnetized nanoparticles to modulate neural plasticity and recover degenerative dopamine neurons in vivo is reported. Remarkably, electromagnetic fields generated by the nanoparticles under ultrasound stimulation modulate intracellular calcium signaling to influence synaptic plasticity and control neural behavior. Dopaminergic neuronal functions are reversed by upregulating the expression tyrosine hydroxylase, thus resulting in ameliorating the neural behavioral disorders in zebrafish. This wireless tool can serve as a viable and safe strategy for the regenerative therapy of the neurodegenerative disorders.

Abstract Antisense long non-coding RNAs (antisense lncRNAs), transcribed from the opposite strand of genes with either protein coding or non-coding function, were reported recently to play a crucial role in the process of tumor onset and development. Functionally, antisense lncRNAs either promote or suppress cancer cell proliferation, migration, invasion, and chemoradiosensitivity. Mechanistically, they exert their regulatory functions through epigenetic, transcriptional, post-transcriptional, and translational modulations. Simultaneously, because of nucleotide sequence complementarity, antisense lncRNAs have a special role on its corresponding sense gene. We highlight the functions and molecular mechanisms of antisense lncRNAs in cancer tumorigenesis and progression. We also discuss the potential of antisense lncRNAs to become cancer diagnostic biomarkers and targets for tumor treatment.

Abstract Spintronic devices are considered a possible solution for the hardware implementation of artificial synapses and neurons, as a result of their non‐volatility, high scalability, complementary metal‐oxide‐semiconductor transistor compatibility, and low power consumption. As compared to ferromagnets, ferrimagnet‐based spintronics exhibits equivalently fascinating properties that have been witnessed in ultrafast spin dynamics, together with efficient electrical or optical manipulation. Their applications in neuromorphic computing, however, have still not been revealed, which motivates the present experimental study. Here, by using compensated ferrimagnets containing Co 0.80 Gd 0.20 with perpendicular magnetic anisotropy, it is demonstrated that the behavior of spin‐orbit torque switching in compensated ferrimagnets could be used to mimic biological synapses and neurons. In particular, by using the anomalous Hall effect and magneto‐optical Kerr effect imaging measurements, the ultrafast stimulation of artificial synapses and neurons is illustrated, with a time scale down to 10 ns. Using experimentally derived device parameters, a three‐layer fully connected neural network for handwritten digits recognition is further simulated, based on which, an accuracy of more than 93% could be achieved. The results identify compensated ferrimagnets as an intriguing candidate for the ultrafast neuromorphic spintronics.

Major space companies are developing satellite mega-constellations to provide global Internet coverage and services. Limited battery capacity is one of the biggest obstacles on mega-constellations due to the restricted weight and volume of satellites. Massive Internet packet routing tasks pose a big challenge to the energy system in such mega constellations. Incorrect use of satellite batteries during routing phases may significantly increase the energy consumption and cause node failure quickly. Existing state-of-the-art works on energy-saving routing for satellite networks paid much attention on traffic distribution and end-to-end delay issues. However, these methodologies were using many real-time network information for optimization which is not practical in mega-constellations. Note also that these works did not consider energy efficiency and guaranteed end-to-end delay simultaneously. In this paper, we propose a novel deep reinforcement learning based energy-efficient routing protocol called DRL-ER, which avoids the battery energy imbalance of constellations and can also guarantee a required bounded end-to-end delay. In DRL-ER, satellites can learn a routing policy that will balance energy usage among satellites. Extensive simulation results show that our proposed DRL-ER protocol reduces the energy consumption of satellites in average by more than 55% compared to the current state-of-the-art work, and prolongs the lifetime of constellations significantly.

The coiled-coil domain containing protein members have been well documented for their roles in many diseases including cancers.However, the function of the coiled-coil domain containing 65 (CCDC65) remains unknown in tumorigenesis including gastric cancer.Methods: CCDC65 expression and its correlation with clinical features and prognosis of gastric cancer were analyzed in tissue.The biological role and molecular basis of CCDC65 were performed via in vitro and in vivo assays and a various of experimental methods including co-immunoprecipitation (Co-IP), GST-pull down and ubiquitination analysis et al.Finally, whether metformin affects the pathogenesis of gastric cancer by regulating CCDC65 and its-mediated signaling was investigated.Results: Here, we found that downregulated CCDC65 level was showed as an unfavourable factor in gastric cancer patients.Subsequently, CCDC65 or its domain (a.a.130-484) was identified as a significant suppressor in GC growth and metastasis in vitro and in vivo.Molecular basis showed that CCDC65 bound to ENO1, an oncogenic factor has been widely reported to promote the tumor pathogenesis, by its domain (a.a.130-484) and further promoted ubiquitylation and degradation of ENO1 by recruiting E3 ubiquitin ligase FBXW7.The downregulated ENO1 decreased the binding with AKT1 and further inactivated AKT1, which led to the loss of cell proliferation and EMT signal.Finally, we observed that metformin, a new anti-cancer drug, can significantly induce CCDC65 to suppress ENO1-AKT1 complex-mediated cell proliferation and EMT signals and finally suppresses the malignant phenotypes of gastric cancer cells.Conclusion: These results firstly highlight a critical role of CCDC65 in suppressing ENO1-AKT1 pathway to reduce the progression of gastric cancer and reveals a new molecular mechanism for metformin in suppressing gastric cancer.Our present study provides a new insight into the mechanism and therapy for gastric cancer.

Metal hydride complexes are key intermediates for N-alkylation of amines with alcohols by the borrowing hydrogen/hydrogen autotransfer (BH/HA) strategy. Reactivity tuning of metal hydride complexes could adjust the dehydrogenation of alcohols and the hydrogenation of imines. Herein we report ruthenium(ii) complexes with hetero-bidentate N-heterocyclic carbene (NHC)-phosphine ligands, which realize smart pathway selection in the N-alkylated reaction via reactivity tuning of [Ru-H] species by hetero-bidentate ligands. In particular, complex 6cb with a phenyl wingtip group and BArF- counter anion, is shown to be one of the most efficient pre-catalysts for this transformation (temperature is as low as 70 °C, neat conditions and catalyst loading is as low as 0.25 mol%). A large variety of (hetero)aromatic amines and primary alcohols were efficiently converted into mono-N-alkylated amines in good to excellent isolated yields. Notably, aliphatic amines, challenging methanol and diamines could also be transformed into the desired products. Detailed control experiments and density functional theory (DFT) calculations provide insights to understand the mechanism and the smart pathway selection via [Ru-H] species in this process.

An example of homogeneous Mo-catalyzed direct N-alkylation of anilines or nitroarenes with alcohols is presented. The DFT aimed design suggested the easily accessible bis-NHC-Mo(0) complex features a strong hydride-donating ability, achieving effective N-alkylation of anilines or challenging nitroarenes with alcohols. The enhanced hydride-donating strategy should be useful in designing highly active systems for borrowing hydrogen transformations.

Feline infectious peritonitis (FIP) is a systemic, potentially fatal viral disease. The objectives of this study were to review clinical and laboratory features and treatment of cats highly suspected of FIP in Wuhan, China. The clinical records of 127 cats highly suspected of FIP were reviewed for history, clinical signs, physical findings, and diagnostic test results. Sex, neutering status, breed, age, and month of onset of disease were compared with the characteristics of the clinic population. Age and neutering status were significantly correlated with FIP-suspicion. Sex, breed and onset month were not associated with FIP. There were many more FIP-suspected cases in cats in young cats or male intact cats. Effusion was observed in 85.8% of the FIP-suspected cats. Increased serum amyloid A (SAA) and lymphopenia were common laboratory abnormalities in the FIP cases. Furthermore, 91.7% of the cats highly suspected of FIP had an albumin/globulin (A/G) ratio < 0.6, while 85.3% had an A/G ratio < 0.5. The mortality rate for FIP-suspected cats was 67%, and six submitted cases were confirmed by FIP-specific immunohistochemistry. Of the 30 cats treated with GS-441524 and/or GC376, 29 were clinically cured. The study highlights the diverse range of clinical manifestations by clinicians in diagnosing this potentially fatal disease. A/G ratio and SAA were of higher diagnostic value. GS-441524 and GC376 were efficient for the treatment of FIP-suspected cats.

The development of an effective and inexpensive electrocatalyst for the oxygen evolution reaction (OER) is the key to achieve high hydrogen production since water splitting has sluggish OER kinetics. Herein, a composite of nickel-rich nickel nitride (NR-Ni3N) with graphitic carbon nitrides (GCNs) was prepared for the electrocatalytic OER, showing a low overpotential of ∼290 mV, a small Tafel slope of ∼70 mV dec–1 at 10 mA cm–2 current density, and low loss of activity after 36 h of test in an alkaline electrolyte, outperforming the pure Ni3N and even the noble catalyst RuO2. The characterization results revealed that the defective GCNs can promote the generation of a Ni-rich region in Ni3N in the nitridation process, and the high conductivity of the formed robust Ni–Ni3N heterojunction and its strong synergistic effect with GCNs explain the excellent OER electrocatalytic performances of NR-Ni3N/GCNs. This work provides a novel feasible strategy for the development of highly active OER electrocatalysts.