Nan Lu

Electrochemical impedance spectroscopy (EIS) is an efficient and non-destructive test for analyzing the bioelectrochemical processes of microbial fuel cells (MFCs). The key factors limiting the output performance of an MFC can be identified by quantifying the contribution of its various internal parts to the total impedance. However, little attention has been paid to the measurement conditions and diagrammatic processes of the EIS for MFC. This review, starting with the analysis of admittance of bioelectrode, introduces conditions for the EIS measurement and summarizes the representative equivalent circuit plots for MFC. Despite the impedance from electron transfer and diffusion process, the effect of unnoticeable capacitance obtained from the Nyquist plot on MFCs performance is evaluated. Furthermore, given that distribution of relaxation times (DRT) is an emerging method for deconvoluting EIS data in the field of fuel cell, the application of DRT-analysis to MFC is reviewed here to get insight into bioelectrode reactions and monitor the biofilm formation. Generally, EIS measurement is expected to optimize the construction and compositions of MFCs to overcome the low power generation.

Malignant tumours are a serious threat to human health. Traditional chemotherapy has achieved breakthrough improvements but also has significant detrimental effects, such as the development of drug resistance, immunosuppression, and even systemic toxicity. Photothermal therapy (PTT) is an emerging cancer therapy. Under light irradiation, the phototherapeutic agent converts optical energy into thermal energy and induces the hyperthermic death of target cells. To date, numerous photothermal agents have been developed. Prussian blue (PB) nanoparticles are among the most promising photothermal agents due to their excellent physicochemical properties, including photoacoustic and magnetic resonance imaging properties, photothermal conversion performance, and enzyme-like activity. By the construction of suitably designed PB-based nanotherapeutics, enhanced photothermal performance, targeting ability, multimodal therapy, and imaging-guided cancer therapy can be effectively and feasibly achieved. In this review, the recent advances in PB-based photothermal combinatorial therapy and imaging-guided cancer therapy are comprehensively summarized. Finally, the potential obstacles of future research and clinical translation are discussed.

The analysis by Shapiro et al. (1969) of a two-dimensional peristaltic pump at small Reynolds number and with long wavelengths is extended to include a Newtonian peripheral layer adjacent to the wall to simulate the effect of a coating in physiological flows. An earlier analysis by Shukla et al. (1980) violates mass conservation because of an incorrect deduction of the interface shape. We present a detailed analysis of the effect of the peripheral layer on the fluid motions, the pumping characteristics, and the phenomena of reflux and trapping. For prescribed wall motion, a peripheral layer more viscous than the inner fluid improves pumping performance, while a less-viscous outer layer degrades performance. Even a very thin peripheral layer may substantially reduce pumping if the viscosity in this layer is very low relative to the inner region. The effects of the peripheral layer on reflux and trapping depend on the conditions which are held fixed while making the comparison. However, the general trend with decreasing peripheral-layer viscosity is towards an overall decrease in trapping, a decrease in reflux with fixed total volume flow rate, but an increase in reflux with fixed pressure head.

It is well known that ocean ambient noise levels in the frequency range from a few hundred hertz to several tens of kilohertz are well correlated with wind speed. A physical mechanism that could account for some of this sound generation is the production of bubble clouds by breaking waves. A simple laboratory study of the sound generated by a column of bubbles is reported here. From measurements of the various characteristics of this column, good evidence is obtained that the bubbles within the column are vibrating in a collective mode of oscillation. Based upon an assumption of collective oscillations, analytical calculations of the predicted frequency of vibration of this column as well as the dependence of this frequency on such parameters as bubble population and column geometry agree closely with the measured values. These results give evidence that the bubble plumes generated by breaking waves can be a strong source of relatively low frequency (< 1 kHz) ambient noise.

By means of an effective equation model for the propagation of pressure waves in a bubbly liquid, the normal modes of oscillation of regions of bubbly liquid in an otherwise pure liquid are calculated for some simple geometries. It is shown that the frequencies of oscillation of such bubble clouds can be much lower than those of the constituent bubbles in isolation and fall well within the range where substantial wind-dependent noise is observed in the ocean. A comparison with some experimental data strongly supports the theoretical results.< <ETX xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">&gt;</ETX>

The present study aimed to test the moderating effect of gender on the relationship between social capital and life satisfaction among older adults in urban China. A quota sampling method was used to select 456 older adults aged 60 and older from 16 local communities in Suzhou city in 2015. Hierarchical multiple regression was employed to test the proposed models. The associations between family social capital and life satisfaction were higher among older men than women. Trust and helping others were stronger predictors of older women’s life satisfaction than their male counterparts. Citizenship activities affected life satisfaction among older men only. The findings highlight the important role of social capital in sustaining and/or improving life satisfaction among both older women and men. Policy and intervention implications are discussed.

High-RH-favored multiphase reactions can significantly change the chemical composition of fine particles and thereby modify their physicochemical properties.

Poor properties and high concentrations of heavy metals are still major concerns of successful application of animal manure-derived biochar into the environment. This work thus proposed to add chlorine-based additives (Cl-additives, i.e., CaCl2, MgCl2, KCl, NaCl, and PVC, 50 g Cl/ kg) to improve biochar properties and enhance heavy metal volatilization during swine manure pyrolysis. The results showed that the addition of CaCl2 could improve the retention of carbon (C) by up to 13.1% during pyrolysis, whereas other Cl-additives had little effect on it. Moreover, CaCl2 could enhance the aromaticity of biochar, as indicated by lower H/C ratio than raw biochar. Pretreatment with CaCl2, MgCl2 and PVC reduced phosphorus (P) solubility but increased its bioavailability via the formation of chlorapatite (Ca5(PO4)3Cl). The CaCl2 was more effective for enhancing the volatilization efficiency of heavy metals than other Cl-additives, except for Pb that tended to react with the generated Ca5(PO4)3Cl to form more stable and less volatile Pb5(PO4)3Cl. However, high pyrolysis temperature (900℃) was essential for CaCl2 to simultaneously decrease the bioavailability of heavy metals. Our results indicated that co-pyrolysis of swine manure with CaCl2 is a promising strategy to increase C retention, P bioavailability, and volatilization of heavy metals, and, at higher temperature, reduce the bioavailability of biochar-born heavy metals.

This study tested the relationship between grandparent-grandchild family capital and self-rated health of older rural Chinese adults and the mediating role of the grandparent-parent relationship in terms of grandparent-grandchild family capital and self-rated health.Data were derived from a random sample of 1,027 adults aged 60 and older who were interviewed in the rural Chaohu region in 2009. Structural equation modeling was used to examine the direct effect of grandparent-grandchild family capital in terms of relations with the first child's family on self-rated health among respondents, as well as the mediating effect of the grandparent-parent relationship.The results showed the direct effect of grandparent-grandchild family capital on self-rated health of older rural Chinese adults. The grandparent-parent relationship had a partial mediation effect on the relationship between grandparent-grandchild family capital and self-rated health of respondents.Grandparent-grandchild family capital had a unique direct effect on the self-rated health of older rural Chinese adults, enriching our theoretical understanding of sources of family capital and their impacts in a collectivist cultural context that emphasizes intergenerational interaction and exchange. The findings also highlighted the mediation effects of grandparent-parent relationships on the relationship between grandparent-grandchild family capital and self-rated health of older rural Chinese adults, supporting the "grandchild-as-linkage" hypothesis in understanding the social determination of self-rated health in China.

The single-layer Molybdenum disulfide (MoS2) was subtracted by using pulsed lasers with different parameters. The machining results were tested by optical microscopy, Raman spectrum, photoluminescent (PL) spectrum, scanning electron microscopy (SEM), and atomic force microscopy (AFM), indicating that the femtosecond laser machining has a better boundary effect than the nanosecond laser. Molecular dynamics (MD) were used to simulate the subtractive manufacturing effect and thermal transfer under different pulse widths and energy conditions. It has been proved that the short-width pulsed laser is more suitable for patterning MoS2. During the MD simulation, wrinkles and defects were found during the laser machining of long-width pulsed laser. The band structure of MoS2 was calculated by density functional theory (DFT) to investigate the effect of different wrinkle and defect conditions on the nonlinear laser absorption. The effect of defects on MoS2 thermal transfer was explored by plasma construction defects. The energy transfer during long-width pulsed laser machining was obtained. This work provides fundamental understanding of laser patterning and machining of MoS2 for future device applications.

As China’s urbanization process deepens, more and more residents of small and medium-sized cities are moving to large cities, and the number of left-behind children is increasing. In this paper, using data from the China Education Panel Survey (CEPS), a nationally representative survey sample, we examine the well-being of left-behind children with urban household registration at the junior high school level and the causal effects of parental migration on their well-being. Research findings indicate that children who are left behind in urban areas are at a disadvantage in most aspects of their well-being compared to urban non-left-behind children. We examine the determinants of urban household registration for left-behind children. Children in families with lower socioeconomic status, more siblings, and poorer health were more likely to be left behind. In addition, our counterfactual framework reveals that, on average, staying behind negatively impacts the well-being of urban children, based on the propensity score matching (PSM) method. Compared to non-migrant children, left-behind children had significantly lower physical health, mental health, cognitive ability, academic performance, school affiliation, and relationships with their parents.

Leaves are crucial for maintaining plant growth and development via photosynthesis, and their function is simultaneously regulated by a suite of phenotypic traits. Although much is known about the genetic architecture of individual leaf traits, unraveling the genetic basis of complex leaf morphology remains a challenge. Based on the functional correlation and coordination of multi-traits, we divided 15 leaf morphological traits into three modules, comprising size (area, length, width, and perimeter), shape (leaf lobes, aspect ratio, circularity, rectangularity, and the relevant ratios), and color (red, green, and blue) for an ornamental tree species, Catalpa bungei. A total of 189 significant single-nucleotide polymorphisms were identified in the leaves of C. bungei: 35, 82, and 76 in the size, shape, and color modules, respectively. Four quantitative trait loci were common between the size and shape modules, which were closely related according to phenotype correlation, genetic mapping, and mRNA analysis. The color module was independent of them. Synergistic changes in the aspect ratio, leaf lobe, and circularity suggest that these traits could be the core indicators of the leaf shape module. The LAS and SRK genes, associated with leaf lobe and circularity, were found to function in plant defense mechanisms and the growth of leaves. The associations between the SRK and CRK2 genes and the leaf lobe and circularity traits were further verified by RT-qPCR. Our findings demonstrate the importance of integrating multi-trait modules to characterize leaf morphology and facilitate a holistic understanding of the genetic architecture of intraspecific leaf morphology diversity.

To improve the mental health rehabilitation effect of college students, this paper combines the self-regulated music psychotherapy method to study the effect of mental health rehabilitation intervention on college students. Moreover, this paper continuously detects psychological stress based on heart rate variability and successfully realizes the continuous detection of psychological stress in exams by using a short time scale and effective heart rate variability characteristics. In addition, this paper evaluates the effect by establishing a psychological rehabilitation model and mathematical statistics methods. Finally, the effectiveness of the mental health rehabilitation method for college students, rooted in self-regulated music psychotherapy, was validated through both practical experimentation and simulation studies. The findings from both the real-world application and the simulated environment consistently demonstrated positive outcomes, affirming the robustness and efficacy of the proposed approach.

The emission and scattering of sound from bubble clouds is studied theoretically. It is shown that clouds having a size and air content similar to what might be expected as a consequence of the breaking of ocean waves can oscillate at frequencies as low as 100 Hz and below. Thus cloud oscillations may furnish an explanation of the substantial amount of low-frequency wind-dependent oceanic ambient noise observed experimentally. Detailed results for the backscattering from bubble clouds—particularly at low grazing angles—are also presented and shown to be largely compatible with oceanic data. Although the cloud model used here is idealized (a uniform hemispherical cloud under a plane water free-surface), it is shown that the results are relatively robust in terms of bubble size, distribution, and total air content. A similar insensitivity to cloud shape is found in a companion paper [Sarkar and Prosperetti, J. Acoust. Soc. Am. 93, XXX (1993)].

The present study aimed to determine the bidirectional relationship between cognitive function and the loss hierarchy of activities of daily living (ADL) among older adults in China.Data were derived from the Longitudinal Study on Family Caregivers for Frail Older Adults Aged 75 or Above in Shanghai (2010-2013).Community-dwelling older adults and their primary caregivers were invited to participate in this research.The inclusion criteria for the older adults were as follows: (a) have a Shanghai urban household registration status, (b) be 75 years old or older, (c) have no fewer than two limitations in ADLs or equivalent, and (d) have one primary caregiver aged 18 years or older. 469 older adults cared by their spouses or children were included in the final analytical sample of this research.Cognitive function was assessed using the Chinese version of the Short Portable Mental Status Questionnaire and ADLs were measured by self-reports of having difficulty or needing help with basic daily activities.Cognitive function in 2010 was a significant predictor of intermediate loss of ADLs in 2013 (β=-0.13, p<0.05) and late loss of ADLs in 2013 (β=-0.17, p<0.01). The loss hierarchy of ADLs among older adults was not shown to be significant as a risk factor of cognitive function in 2013.Practitioners are encouraged to adopt the ADL loss hierarchy as a supplementary needs assessment tool to make the social service delivery process more effective, economical and tailored. Cognitive function change monitoring programmes and services providing education on nutrition and encouraging social participation of older individuals were also helpful in promoting the quality of life of the older adults.

The freeway plays an essential role in intercity transportation, due to its safety, convenience and efficiency. To ensure the gradually networked freeway system to operate smoothly and efficiently, the connective reliability evaluation become extremely important. Applying the complex network approach, the improved evaluation indicators of complex network, such as structural degree, betweenness and shortest path length are defined respectively to reflect the freeway network's structural properties firstly. Secondly, a measurement considering the effective paths number is proposed to evaluate freeway network's connective reliability. Finally, based on the freeway network in Shandong Province (SFN), which is the largest scale freeway network in eastern China, those evaluation indicators are calculated, and the freeway network's connective reliability are evaluated under different scenarios. The nodes with high structural betweenness must be given more protection so as to improve the reliability of the SFN under random attack The structural properties and reliability analysis of freeway networks are helpful for road planning and unexpected major events control.

The size and shape of the foveal avascular zone (FAZ) have a strong positive correlation with several vision-threatening retinovascular diseases. The identification, segmentation and analysis of FAZ are of great significance to clinical diagnosis and treatment. We presented an adaptive watershed algorithm to automatically extract FAZ from retinal optical coherence tomography angiography (OCTA) images. For the traditional watershed algorithm, “over-segmentation” is the most common problem. FAZ is often incorrectly divided into multiple regions by redundant “dams”. This paper analyzed the relationship between the “dams” length and the maximum inscribed circle radius of FAZ, and proposed an adaptive watershed algorithm to solve the problem of “over-segmentation”. Here, 132 healthy retinal images and 50 diabetic retinopathy (DR) images were used to verify the accuracy and stability of the algorithm. Three ophthalmologists were invited to make quantitative and qualitative evaluations on the segmentation results of this algorithm. The quantitative evaluation results show that the correlation coefficients between the automatic and manual segmentation results are 0.945 (in healthy subjects) and 0.927 (in DR patients), respectively. For qualitative evaluation, the percentages of “perfect segmentation” (score of 3) and “good segmentation” (score of 2) are 99.4% (in healthy subjects) and 98.7% (in DR patients), respectively. This work promotes the application of watershed algorithm in FAZ segmentation, making it a useful tool for analyzing and diagnosing eye diseases.

Traditional vine variety identification methods usually rely on the sampling of vine leaves followed by physical, physiological, biochemical and molecular measurement, which are destructive, time-consuming, labor-intensive and require experienced grape phenotype analysts. To mitigate these problems, this study aimed to develop an application (App) running on Android client to identify the wine grape automatically and in real-time, which can help the growers to quickly obtain the variety information. Experimental results showed that all Convolutional Neural Network (CNN) classification algorithms could achieve an accuracy of over 94% for twenty-one categories on validation data, which proves the feasibility of using transfer deep learning to identify grape species in field environments. In particular, the classification model with the highest average accuracy was GoogLeNet (99.91%) with a learning rate of 0.001, mini-batch size of 32 and maximum number of epochs in 80. Testing results of the App on Android devices also confirmed these results. Keywords: deep learning, mobile phone, grapevine cultivar, vine leaf image, identification, Vitis vinifera L. DOI: 10.25165/j.ijabe.20211405.6593 Citation: Liu Y X, Shen L, Su J Y, Lu N, Fang Y L, Liu F, et al. Development of a mobile application for identification of grapevine (Vitis vinifera L.) cultivars via deep learning. Int J Agric & Biol Eng, 2021; 14(5): 172–179.

Retinal segmentation is a prerequisite for quantifying retinal structural features and diagnosing related ophthalmic diseases. Canny operator is recognized as the best boundary detection operator so far, and is often used to obtain the initial boundary of the retina in retinal segmentation. However, the traditional Canny operator is susceptible to vascular shadows, vitreous artifacts, or noise interference in retinal segmentation, causing serious misdetection or missed detection. This paper proposed an improved Canny operator for automatic segmentation of retinal boundaries. The improved algorithm solves the problems of the traditional Canny operator by adding a multi-point boundary search step on the basis of the original method, and adjusts the convolution kernel. The algorithm was used to segment the retinal images of healthy subjects and age-related macular degeneration (AMD) patients; eleven retinal boundaries were identified and compared with the results of manual segmentation by the ophthalmologists. The average difference between the automatic and manual methods is: 2-6 microns (1-2 pixels) for healthy subjects and 3-10 microns (1-3 pixels) for AMD patients. Qualitative method is also used to verify the accuracy and stability of the algorithm. The percentage of "perfect segmentation" and "good segmentation" is 98% in healthy subjects and 94% in AMD patients. This algorithm can be used alone or in combination with other methods as an initial boundary detection algorithm. It is easy to understand and improve, and may become a useful tool for analyzing and diagnosing eye diseases.

Supervised federated learning (FL) enables multiple clients to share the trained model without sharing their labeled data. However, potential clients might even be reluctant to label their own data, which could limit the applicability of FL in practice. In this paper, we show the possibility of unsupervised FL whose model is still a classifier for predicting class labels, if the class-prior probabilities are shifted while the class-conditional distributions are shared among the unlabeled data owned by the clients. We propose federation of unsupervised learning (FedUL), where the unlabeled data are transformed into surrogate labeled data for each of the clients, a modified model is trained by supervised FL, and the wanted model is recovered from the modified model. FedUL is a very general solution to unsupervised FL: it is compatible with many supervised FL methods, and the recovery of the wanted model can be theoretically guaranteed as if the data have been labeled. Experiments on benchmark and real-world datasets demonstrate the effectiveness of FedUL. Code is available at https://github.com/lunanbit/FedUL.

Cryoprotectants, such as sorbitol and dimethyl sulfoxide, are widely used to stabilize the culture solution in cryopreservation, which is necessary for the application of somatic embryogenesis technique in conifer vegetative propagation. However, limited information is available about the molecular mechanism of the osmotic-responses induced by cryoprotectants in conifer species. Use Norway spruce (Picea abies (L.) Karst.) embryogenic tissues (ETs), cryoprotectant pretreatment (CPT) methods T3 and T6 (T3 with low regrowth rate; T6 with high regrowth rate) were selected out of eight CPTs for further analyses based on their similar solution thermal stability but distinct survival rate after cryopreservation. High dose of initial sorbitol (>=0.3 M) induced G1 to G2 cell cycle shift. While, extensive necrosis was detected after low dose of initial sorbitol (=<0.2 M) CPT. 27 RNA-seq libraries (untreated control, T3 or T6 pretreated 4 h, 24 h, 48 h and before freezing) were sequenced using Illumina sequencing platform. The RNA-seq data emphasized the importance of the early molecular responses induced by cryoprotectants. Differently expressed (DE) genes (DEGs) were enriched in cell wall modification, cell cycle regulation and oxidation reaction categories. DE transcription factors (TFs) in T3 vs T6 were enriched in MYB, AP2/ERF, NAC and WRKY families. PaMYB11, one of the hub genes in the early stage, was knockdown by RNA interference (RNAi) to verify our RNA-seq data. The PaMYB11 up-regulation was shown to be necessary for the survival of the ETs under CPT. Our study provides novel knowledge of the stimulus molecular responses to CPT in spruce ETs, which could guide the development of more efficient procedure for cryopreservation in conifers and further expand their industrial applications.

The small nuclear ribonucleoprotein 200 kDa (SNRNP200) gene plays a key role in the maturation of pre-message RNA (pre-mRNA) splicing with the indication for the etiology of retinitis pigmentosa (RP). Gene recognition can facilitate the diagnosis of these patients for better clinical management, treatment and counseling. This study aimed to outline the causative mutation in a Chinese family and the pathogenic mechanism of this SNRNP200 mutation in RP. Eighteen individuals from the affected family underwent a complete ophthalmic examination. Whole exome sequencing (WES) was conducted to identify the pathogenic variant in the proband, which was then confirmed by Sanger sequencing. Expression of the SNRNP200 transcript in zebrafish was identified via whole mount in situ hybridization. Morpholino oligonucleotide (MO) and SNRNP200 wild and mutant mRNA were injected into zebrafish embryos followed by analyses of the systemic changes and retinal phenotypes using immunofluorescence. Heterozygous SNRNP200 c.C6088T (p.Arg2030Cys) mutation was ascertained in two members of this family: the proband and his father (II-2). Overexpression of SNRNP200 Arg2030Cys , but not SNRNP200 WT caused systemic deformities in the wild-type zebrafish embryos with the retina primarily injured, and significantly increased death rates in the morphant embryos, in which the orthologous zebrafish SNRNP200 gene was blocked. In conclusion, this study reports a novel heterozygous SNRNP200 c.C6088T mutation, which is evidenced to cause RP via a dominant-negative effect.

Abstract This paper systematically analyses the application status and advantages of steel corrugated plate and it’s composite structure technology in domestic and foreign infrastructure construction, such as in the tunnel fields. From the aspects of Engineering characteristics, environment and energy saving, etc. We put forward the research ideas, development prospects and application ideas of steel corrugated plate technology in the field of infrastructure.

Contaminations frequently occur in bacterial cultures, which significantly affect the reproducibility and reliability of the results from whole-genome sequencing (WGS). Decontaminated WGS data with clean reads is the only desirable source for detecting possible variants correctly. Improvements in bioinformatics are essential to analyze the contaminated WGS dataset. Existing pipelines usually contain contamination detection, decontamination, and variant calling separately. The efficiency and results from existing pipelines fluctuate since distinctive computational models and parameters are applied. It is then promising to develop a bioinformatical tool containing functions to discriminate and remove contaminated reads and improve variant calling from clean reads. In this study, we established a Python-based pipeline named CleanSeq for automatic detection and removal of contaminating reads, analyzing possible genome variants with proper verifications via local re-alignments. The application and reproducibility are proven in either simulated, publicly available datasets or actual genome sequencing reads from our experimental evolution study in Escherichia coli. We successfully obtained decontaminated reads, called out all seven consistent mutations from the contaminated bacterial sample, and derived five colonies. Collectively, the results demonstrated that CleanSeq could effectively process the contaminated samples to achieve decontaminated reads, based on which reliable results (i.e., variant calling) could be obtained.

Cavitationlike bubble collapses and the bursting of floating bubbles have been proposed in the literature as sources of oceanic ambient noise at kilohertz frequencies. The first process is shown to be physically impossible in the oceanic environment. The noise produced by the second mechanism is estimated and shown to be too weak to be of any significance.

A simple model of a small bubble floating at the surface of a liquid before bursting is considered. The oscillations of this system are studied by means of a Lagrangian method. It is found that two fundamentally different modes exist. The surface mode has low frequency and does not change appreciably the volume of the immersed part of the bubble: As a consequence, its efficiency as a source of sound in the water is very limited. The volume mode has a much higher frequency and is a more efficient radiator in the water, although it may be hard to excite. Both modes behave as monopole sources in the air. It is therefore predicted that an oscillating floating bubble is a much more intense source of sound in the air than in the liquid. This conclusion seems to be supported by experimental observations.

The MIP Timing Detector will provide additional timing capabilities for detection of minimum ionizing particles (MIPs) at CMS during the High Luminosity LHC era, improving event reconstruction and pileup rejection. The central portion of the detector, the Barrel Timing Layer (BTL), will be instrumented with LYSO:Ce crystals and Silicon Photomultipliers (SiPMs) providing a time resolution of about 30 ps at the beginning of operation, and degrading to 50-60 ps at the end of the detector lifetime as a result of radiation damage. In this work, we present the results obtained using a 120 GeV proton beam at the Fermilab Test Beam Facility to measure the time resolution of unirradiated sensors. A proof-of-concept of the sensor layout proposed for the barrel region of the MTD, consisting of elongated crystal bars with dimensions of about 3 x 3 x 57 mm$^3$ and with double-ended SiPM readout, is demonstrated. This design provides a robust time measurement independent of the impact point of the MIP along the crystal bar. We tested LYSO:Ce bars of different thickness (2, 3, 4 mm) with a geometry close to the reference design and coupled to SiPMs manufactured by Hamamatsu and Fondazione Bruno Kessler. The various aspects influencing the timing performance such as the crystal thickness, properties of the SiPMs (e.g. photon detection efficiency), and impact angle of the MIP are studied. A time resolution of about 28 ps is measured for MIPs crossing a 3 mm thick crystal bar, corresponding to an MPV energy deposition of 2.6 MeV, and of 22 ps for the 4.2 MeV MPV energy deposition expected in the BTL, matching the detector performance target for unirradiated devices.

Purpose The purpose of this paper is to construct a new algorithm of program procedure for medical grey relational method based on SAS software. Design/methodology/approach Based on the SAS environment, the authors construct a new algorithm of program procedure through the following methods: the construction data set, confirmation of the comparison sequence and reference sequence, the original data transformation, calculation of the grey relational coefficient of reference sequence and comparison sequence and calculating the correlation. Findings The results show that the novel algorithm of program procedure for medical grey relational method based on SAS software satisfies the properties properly. It also fully confirmed the biggest advantage of the grey relational analysis is that its requirements are not too high for the amount of data, and it does not need to follow the typical distribution. Originality/value The paper succeeds in constructing a novel algorithm of program procedures for medical grey relational method and providing a valuable tool for solving similar problems.

Fatty acids increase ATP-binding cassette ABC transporter A12 (ABCA12) levels via an increase in peroxisome proliferator-activated receptor β/δ (PPAR β/δ). Promoting lipid transport to lamellar granules has been suggested to improve epidermal barrier function in patients with dry skin.We investigated whether mevalonolactone (MVL) produced by Saccharomycopsis fibuligera improves dry skin by promoting ABCA12 expression and the amount of free fatty acids in epidermal keratinocytes.We examined whether MVL increases ABCA12 mRNA and protein levels and the amount of Nile red-positive lipids in cultured epidermal keratinocytes and in a three-dimensional epidermal model by cell staining. Promotion of fatty acid production by MVL was analyzed by liquid chromatography-mass spectrometry. We also evaluated whether MVL addition increases PPAR β/δ mRNA expression in cultured keratinocytes. Based on the results, a randomized controlled trial was conducted in which milky lotions containing MVL and placebo were applied to dry facial skin of healthy female volunteers in winter.MVL increased ABCA12 mRNA and protein levels and lamellar granule number and size. Fatty acid analysis revealed that MVL elevated myristic acid, palmitic acid, and palmitoleic acid levels as well as PPAR β/δ mRNA expression. In human tests, milky lotions containing MVL were shown to significantly improve transepidermal water loss (TEWL) in the stratum corneum compared to placebo.The results suggest that MVL increases fatty acid uptake and ABCA12, promotes fatty acid transport to lamellar granules, and improves epidermal barrier function in dry skin through increased expression of PPAR β/δ.

Mercury (Hg) and arsenic (As) are toxic and harmful heavy metals, with exceedance rates of 1.6% and 2.7%, respectively, in soils across China. Compared to soils contaminated with Hg or As alone, co-contaminated soils pose complex environmental risks and are difficult to remediate. Biochar is widely used as a soil amendment to adsorb and immobilize pollutants such as heavy metals. However, only a few studies have explored the efficiency of biochars produced from different crop straws to reduce the bioavailability of heavy metals in co-contaminated soils, and the effects on soil biological properties are often overlooked. The aim of this study was to investigate changes to the physicochemical properties, enzyme activities, and heavy metal bioavailability of an industrial soil co-contaminated with Hg and As upon the addition of different biochars from reed, cassava, and rice straws (REB, CAB, and RIB, respectively). The soil was amended with 1% biochar and planted with spinach in pots for 30 days. RIB was more effective than REB and CAB in increasing the soil pH, organic matter content, and cation exchange capacity. RIB and CAB exhibited similar positive effects on the soil dehydrogenase, catalase, invertase, and urease activities, which were higher than those of REB. The exchangeable fraction of both metals decreased upon biochar addition, and the residual fraction showed the opposite trend. All biochar amendments reduced the bioconcentration factors of heavy metals (especially Hg) in plants and decreased the metal bioavailability in soil. RIB is the optimal amendment for the stabilization of soil co-contaminated with Hg and As.

To test the effect of pre-curing time on the impact resistance of reactive powder concrete (RPC), RPC specimens were cured in a steam curing box at a temperature of 70 °C for 72 h with pre-curing times of 18, 24, and 30 h. At 28 days, the low-speed impact test was carried out on RPC specimens with a Ceast9350 drop weight impact system at an impact rate of 5 m/s and impact energy of 140 J. The variation curves of the impact force and displacement of RPC specimens with impact times were obtained. The results show that the impact resistance of RPC specimens improved with the increased pre-curing time, implying that appropriate pre-curing time (30 h in this case) can improve RPC mechanical properties. At the same time, combined with x-ray diffraction, scanning electron microscope imaging of hydration products, and the energy dispersion spectroscopy test, the influence mechanism of pre-curing time on the impact resistance of RPC is analyzed from the microstructure standpoint. The results show that appropriate pre-curing time can make the hydration of cement form finer particles and make the hardened paste form a protective structure to reduce the damage of steam curing in the strength development process. Through multiscale homogenization calculation via the Mori–Tanaka scheme, it can be seen that RPC’s stiffness increases with the prolonged pre-curing time. Optimizing pre-curing time is conducive to improving the mechanical properties of RPC specimens.

A model of a bubble cloud based on a set of averaged equations is used to study the acoustic emission and scattering properties of these objects. From a study of the normal modes of the cloud, it is inferred that the lowest modes have a frequency much lower than that of the individual bubbles. This indicates that clouds of bubbles can radiate at such low frequencies if these modes are excited. The results of some scattering calculations at different wavelengths are also shown as a function of the incidence and scattering angles. [Work supported by ONR.]

Alternative investments, such as hedge funds, venture capital, and private equity, can improve portfolio performance, especially for long-term institutional and high net worth individual investors. Difficulties arise when rebalancing a portfolio that includes alternative investments due to the nature of the commitments. Transaction costs can be sizable and money flows are restricted by illiquid markets, covenants, and related restrictions. Following a review of the pros and cons of including alternative investments in a traditional portfolio, the authors show the intrinsic advantages of a multi-period asset allocation strategy and present an optimizing approach for addressing transaction costs.

The goal of this paper is to explore a method for virus inactivation based on ultrasonic treatment, and on this basis, to explore the synergistic effect of methylene blue as a sonosensitizer in virus inactivation. The titer of human parainfluenza virus type 3 (HPIV3), Autographacaliforinica nuclear polyhedrosis virus carried a green fluorescent reporter gene (AcNPV-GFP) and Enterovirus group D 68 (EV-D68) were determined by plaque assays or TCID50 methods after treatment by MB combined with illumination (MB photochemical, MBP) or ultrasonic excitation. Different ultrasonic power and time, MB concentration gradient were set to determine the best anti-viral combination. For the enveloped virus HPIV3 and AcNPV-GFP, pure ultrasonic or MBP treatment could reduce viral titer more than 104，and ultrasonic combined with MB could completely inactivate HPIV3 and AcNPV-GFP in 5min while traditional MBP methods could only reduce viral titer about 10X. For the non-enveloped virus EV-D68, pure ultrasonic or MBP treatment only reduced the viral titer about 102, but ultrasonic combined with MB treatment could reduce the viral titer about 103 in 5min and completely inactive EV-D68 in 10min (reduced 105). Compared with MBP method and pure ultrasonic inactivation, ultrasonic combined with MB has better inactivation effect on either enveloped or non-enveloped viruses, and the appropriate combination of parameters is expected to be a new blood transfusion transmitted virus inactivation method.

The retirement and relocation of urban industrial enterprises has led to the retirement of a large number of contaminated sites.Aiming at the problem that the data related to the contaminated site comes from many different sources and has different structures, and it is difficult to explore the potential correlation between the data through the existing management methods, this paper proposes a knowledge map construction method for multi-source heterogeneous data of the contaminated site.According to the different structures of contaminated site data, we use the knowledge construction theory to select appropriate entity recognition, relationship recognition and knowledge fusion methods to extract various types of information of contaminated sites and establish semantic networks.The knowledge map constructed for a contaminated site in Northeast China contains 3840 contaminated site entities including site information, enterprise information and soil information, and the corresponding association relationship is 4768.Practice has proved that the proposed knowledge map construction method can effectively and intuitively represent the potential association relationship between contaminated site data, and provide corresponding technical support and decision-making information for the relevant departments of contaminated site restoration and management.

The mechanism is investigated for cascade benz annulation of phenyl)prop-2-yn-1-yl)benzamide catalyzed by Ag(I).The oxonium-ion generation and water nucleophilic addition induces ring opening hydroxylation, dual ketonization giving 1,5-diketone intermediate.Mediated by acid, the intramolecular cyclization, water elimination affords β-naphthol, from which the nucleophilic cyclization dehydration provides desired product naphthooxazole.The side reaction of acid-activated 5-exo-dig cyclization is accompanied by synergetic synchronous hydrolysis yielding indenone.The promotion of Ag(I) lies in the absolute energy and activation barrier decrease of oxonium-ion generation and water nucleophilic addition.The mediation of acid exists in intramolecular cyclization, nucleophilic cyclization dehydration and 5-exo-dig cyclization.The solvent influence of acid is smaller than Ag(I) from the reduction degree.These results are supported by Multiwfn analysis on FMO of specific TSs and MBO value of vital bonding, breaking.

Food security is an important basis for national security. This paper makes a comprehensive analysis of the concept change of food security, the current situation of domestic food security, the policy orientation and the important problems faced by food security in the new era, with a view to further understanding the development direction and measures to ensure national food security in the future.

Agricultural non-point source pollution is an important problem at present. By analyzing the amount and intensity of fertilizer application and the proportion of different types of fertilizer application in the past 10 years, the paper makes clear that the excessive application of fertilizer and the imbalance of fertilizer structure are the main causes of agricultural non-point source pollution.

With the development of today's society, the contact between countries is getting closer and closer. People in different countries use different languages. It is very important to enable people in different countries to solve the first communication barrier and solve the language problem. In this environment, the technology of machine translation is becoming more and more mature. Relying on machine translation, people can not only understand the literature of different countries and regions, but also help complete the basic daily work. Moreover, the efficiency of machine translation is also higher than that of manual translation, which can not only save human resources, but also speed up the work efficiency and greatly improve the speed of social development. Similarly, there is the amount of data with the improvement of technology, so it is particularly important to apply data mining algorithms to design a model that can meet the needs of machine translation and its quality evaluation in the era of big data. This paper makes some research on the machine translation quality evaluation model based on the data mining algorithm. Based on the basic attributes of the algorithm and the background significance of machine translation, the quality evaluation model is obtained through relevant experimental simulation. By analyzing the experimental data, it can be seen that the machine translation quality evaluation model can basically meet the needs.

Optical coherence tomography (OCT) attenuation imaging is a technique that uses the optical attenuation coefficient (OAC) to distinguish the types or pathological states of tissues and has been increasingly used in basic research and clinical diagnosis. With the increasing application of swept-source OCT, scholars are increasingly inclined to explore deep tissues. Unfortunately, the accuracy of OAC calculation when exploring deep tissues has yet to be improved. Existing methods generally have the following problems: overestimation error, underestimation error, severe fluctuation, or stripe artifacts in the OAC calculation of the OCT tail signal. The main reason for this is that the influence of the noise floor on the OCT weak signal at the tail-end is not paid enough attention. The noise floor can change the attenuation pattern of the OCT tail signal, which can lead to severe errors in the OAC. In this paper, we proposed a Kalman filter-based OAC optimal algorithm to solve this problem. This algorithm can not only eliminate the influence of the noise floor, but can also effectively protect the weak signal at the tail-end from being lost. The OAC of deep tissues can be calculated accurately and stably. Numerical simulation, phantom, and in vivo experiments were tested to verify the algorithm’s effectiveness in this paper. This technology is expected to play an essential role in disease diagnosis and in the evaluation of the effectiveness of treatment methods.

It is necessary to find effective methods for ecosystem stability quantification that can forewarn massive collapses of ecosystem structure and inform ecosystem management. Multiple ecosystem stability metrics (ESMs) have been proposed and increasingly employed to quantify terrestrial ecosystem stability. However, their sensitivity in depicting stability changes in diverse terrestrial ecosystems has not been thoroughly examined. Here, we evaluated 11 commonly suggested ESMs using two vegetation indices (normalized difference vegetation index and enhanced vegetation index) and examined their responses to the aridity (defined as ratio of precipitation to potential evapotranspiration) gradient in diverse African biomes. The four temporal ESMs (temporal autoregressive coefficient, detrended fluctuation indicator, spectrum density ratio, and conditional heteroskedasticity) showed increasing trends with aridity, indicating decreasing ecosystem stability with increasing aridity in some biomes. However, all spatial ESMs and other temporal ESMs were not sensitive in detecting changes in ecosystem stability with aridity. The ESMs derived from normalized difference vegetation index and enhanced vegetation index exhibited inconsistencies in some cases, suggesting the influence of the adopted variables on ESM performance. Our results revealed that temporal metrics based on the critical slowing down phenomenon can be used to evaluate ecosystem stability in African terrestrial biomes. Quantification of ecosystem stability can be improved by selecting sensitive metrics and appropriate variables for specific biomes.

The components of nighttime sap flow (En), including transpiration (Et) and stem recharge (Er), played an important role for the water balances and drought adaptation of plant communities in water limited regions. However, the quantitative and controlling factors on En components are unclear. This study used the heat balance method to measure sap flow density for V. negundo on the Loess Plateau for a normal precipitation year (2021) and a wetter year (2022). The results showed that the mean values of Et and Er were 1.65 and 0.31 g h-1cm-2 in the two years, respectively, and the two variables were both higher in the wetter year. The mean contribution of Et to En was 81.83%, indicating that the En was almost used for Et. Although vapor pressure deficit (VPD), air temperature (Ta) and soil water content (SWC) were significantly correlated with Et and Er on hourly time scale, they explained a small fraction of the variance in Et on daily time scale. The Er was little affected by meteorological and SWC factors on daily time scale. On the diurnal course, Et and Er initial both declined after sundown because of decreasing VPD and Ta, and Et was significantly higher than the value of Er. However, the two variables increased when VPD was nearly zero and Ta decreasing, and Er was higher than Et, which indicated that Er was affected by circadian regulation and driving the occurrence of Et. Er increased the predawn stem water potential and daytime transpiration which could alleviate the effect of dry condition on predawn carbon fixation. It is suggested that Et and Er would increase in response to increasing nighttime air temperature to adapt future climate change, which would influence the water balance process and plant survival in water limited regions.

Abstract An experimental area of different profile configurations was established in Meixian County, Baoji City, Shaanxi Province. In the experiment, loamy loess was selected as cultivable layer and two types of soil thickness of 40cm (plot1, plot3, plot5) and 60cm (plot2, plot4, plot6) were designed, in which the transition layer of plot1 and plot2 were fine sand, the transition layer of plot3 and plot4 were loamy loess, and the transition layer of plot5 and plot6 were clay. Results showed that the soil particles were mainly composed of silt loam and silt. Soil particles were basically distributed in the range of 2 ~ 50µm. The fractal dimension D of soil volume in each treatment was in the range of 2.229 ~ 2.484, and there was a significant positive correlation between soil clay particle and soil silt particle content ( P &lt; 0.01 ). Fractal dimension D of soil volume in the experimental area was significantly positively correlated with soil organic matter, total nitrogen and silt particle content ( P &lt; 0.01 ), and significantly negatively correlated with soil gravel particle content ( P &lt; 0.05 ); Therefore, it can be concluded that the soil texture can be better improved when the covering type is loamy loess, the soil thickness is 40cm and the transition layer is fine sand.

Purpose: The purpose of this study was to investigate the association between foveal vessels and retinal thickness in individuals with diabetic retinopathy (DR) and control subjects, and to reveal foveal avascular zone (FAZ) growth in early individuals with DR. Methods: The regions with a thickness less than 60 µm were marked from the intima thickness maps and named FAZThic. The avascular zones extracted from the deep vascular plexus were designated as FAZAngi. The boundary of the two FAZ forms a ring region, which we called FAZRing. The FAZ growth rate was defined as the ratio of the FAZRing area to the FAZThic area. Thirty healthy controls and 30 individuals with mild nonproliferative DR were recruited for this study. Results: The FAZThic area in individuals with mild DR and control subjects showed similar distribution. The FAZAngi area in individuals with mild DR are higher than that in control subjects on the whole, but there was no significant difference (P > 0.05). The FAZRing area in individuals with mild DR was significantly higher than that in control subjects (P < 0.001). However, there is still a small amount of overlap data between the two groups. For the FAZ growth rate, the individuals with mild DR were also significantly larger than the control subjects (P < 0.001). But there were no overlapping data between the two groups. Conclusions: The growth of FAZ in individuals with mild DR can be inferred by comparing FAZAngi with FAZThic. This method minimizes the impact of individual variations and helps researchers to understand the progression mechanism of DR more deeply.

Lu <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2(1-x)</sub> Y <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2x</sub> SiO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">5</sub> (LYSO) crystals readout by a silicon photomultiplier (SiPM) will be used in the barrel timing layer of a precision timing detector for the Compact Muon Solenoid (CMS) experiment at the High-Luminosity Large Hadron Collider (HL-LHC). This detector is expected to be exposed up to 5-Mrad γ-ray dose, 2.5×10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">13</sup> charged hadrons/cm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> , and 3×10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">14</sup> n <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">eq</sub> /cm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> at the HL-LHC for 10 years of operation. We present results of the photocurrent in LYSO+SiPM packages induced by Co- 60 γ-rays and Cf-252 neutrons of the expected dose rate and neutron flux, respectively. The γ-ray-induced readout noise is about 30 keV, which is negligible when compared to the 4.2-MeV signal from the minimum ionization particle signals. The neutron-induced readout noise is about 7 keV, which is more than a factor of 4 smaller than that from the γ-rays.

In this article, a radiation model is proposed to estimate the emission of the pantograph arc. An improved least-square regression analysis method is given for studying the pantograph arc characteristics at various sites on electrified railways and at various train speeds. The radiation model and the improved least-square method were both validated using the test data. The impact of arc on the airport instrument landing system (ILS) was investigated using electromagnetic wave propagation theory and the signal-to-noise ratio requirement of the ILS. We deduced the position limit of the articulated neutral section (ANS) and verified it through experiments. This research provides a theoretical foundation and technological methodology for civil aviation and high-speed railway electromagnetic compatibility studies as well as helps for airport site selection and high-speed railway route planning.

Left ventricular hypertrophy (LVH) has been classified separately as an independent risk factor for hypertension. However, comparisons between different body size indices and left ventricular hypertrophy (LVH) in hypertensive populations have not been reported yet. In this study, we enrolled 4,639 hypertensive patients from rural China. Anthropometric indices and cardiovascular disease risk factor variables were measured and analyzed using Spearman’s correlation, logistic regression, and receiver operating characteristic (ROC) curve analyses. Patients in the highest quartile of body size indices were more likely to have left ventricular hypertrophy than those in the lowest quartile; these indices were BMI (adjusted OR: 3.55, 95% CI: 2.90; 4.35), WC (adjusted OR: 2.23, 95% CI: 1.84; 2.70), WHR (adjusted OR: 1.44, 95% CI: 1.18; 1.75), and WHtR (adjusted OR: 3.23, 95% CI: 2.62; 3.99). The areas under the ROC curves of BMI (AUC: 0.628, 95% CI: 0.612; 0.644), WHtR (AUC: 0.628, 95% CI: 0.560; 0.593), WHR (AUC: 0.530, 95% CI: 0.513; 0.547), and WC (AUC: 0.576, 95% CI: 0.513; 0.547) were all above 0.5, which indicated that the four anthropometric indicators may be associated with LVH. The four anthropometric indicators of obesity were identified as risk factors for LVH. Weight control might help reduce the risk of left ventricular hypertrophy.

Under distribution shift (DS) where the training data distribution differs from the test one, a powerful technique is importance weighting (IW) which handles DS in two separate steps: weight estimation (WE) estimates the test-over-training density ratio and weighted classification (WC) trains the classifier from weighted training data. However, IW cannot work well on complex data, since WE is incompatible with deep learning. In this paper, we rethink IW and theoretically show it suffers from a circular dependency: we need not only WE for WC, but also WC for WE where a trained deep classifier is used as the feature extractor (FE). To cut off the dependency, we try to pretrain FE from unweighted training data, which leads to biased FE. To overcome the bias, we propose an end-to-end solution dynamic IW that iterates between WE and WC and combines them in a seamless manner, and hence our WE can also enjoy deep networks and stochastic optimizers indirectly. Experiments with two representative types of DS on three popular datasets show that our dynamic IW compares favorably with state-of-the-art methods.

This article studies and discusses the cheating phenomenon that may occur in the application of the online examination system one by one, and provides corresponding prevention strategies. Based on the two major aspects of the camera's candidate status recognition and the machine's operation behavior identification, the research and analysis are carried out, and the anti-cheating detection system is designed according to each prevention requirement to realize a highly anti-cheating invigilator system. The system provides assistance to improve the quality of online examination and actively promotes the development of Internet plus education.

Reasonable logistics distribution plan can not only reduce distribution costs, but also be conducive to energy saving and emissions reduction. This study aims to optimize logistics distribution plan with the minimum energy consumption as objective. Firstly, as for the time-dependent vehicle routing problem with time windows (TDVRPTW), considering the effect of total vehicle weight and travel speed on energy consumption factor, an optimization function is proposed to minimize the fuel consumption during delivery; secondly, based on the road network and traffic information, the ant colony algorithm is used to solve the TDVRPTW to optimize the distribution plan; finally, experiments are designed to evaluate the effectiveness of the proposed optimization method, and the results show that, compared to the existing optimization approach, the proposed method can effectively reduce the energy consumption of delivery vehicles by about 12.76%.

Children with facial deformity always encounter social adaption problems and psychological problems in the process of contacting with the outside world. Facial deformity and negative social feedback will contribute to the formation of abnormal self-concept which leads to the inferiority complex, isolation feelings and some other adverse psychological states. In order to resist the bad influence from stereotyping reaction, they will form abnormal psychological defense mechanism. Family environment, academic background of parents, type of deformity and cosmetic repairing are considered as most important influence factors to the psychological development of children with facial deformity, but the special mechanism and extent is not yet clear. The therapy for the deformed mentality has been improved from usual interventions to the generally applied evidence-based psychosocial therapy. The latest research has been focused on the modular approach to therapy for children with anxiety, depression, or conduct problems (MATCH), which has been proved more useful than the former therapy. (Int Rev Ophthalmol, 2016, 40: 206-212) Key words: facial deformity; psychological problems

Poor properties and high concentrations of heavy metals have become major concerns of animal manure-derived biochar application in environment. The effect of adding chlorinating agents (CaCl2 , MgCl2 , KCl, NaCl, and PVC, 50 g (Cl)/ kg) on biochar properties and heavy metal volatilization during swine manure pyrolysis was investigated. The addition of CaCl2 could improve the retention of C by up to 54.22% in biochar during pyrolysis, other chloride additives had little effect on C retention. Moreover, CaCl2 could enhance the aromaticity of biochar. Pretreatment with CaCl2 , MgCl2 , and PVC reduced phosphorus availability via the formation of chlorapatite (Ca5(PO4 )3 Cl. The CaCl2 was more effective for enhancing the volatilization efficiency of heavy metals than other Cl-donors, expect for Pb. However, higher pyrolysis temperature was essential to simultaneously decrease the heavy metals bioavailability. Our results indicated that the pretreatment of swine manure with CaCl2 was a promising strategy to increase carbon retention and the volatilization of heavy metals during pyrolysis.

Recent years have witnessed a great success of supervised deep learning, where predictive models were trained from a large amount of fully labeled data. However, in practice, labeling such big data can be very costly and may not even be possible for privacy reasons. Therefore, in this paper, we aim to learn an accurate classifier without any class labels. More specifically, we consider the case where multiple sets of unlabeled data and only their class priors, i.e., the proportions of each class, are available. Under this problem setup, we first derive an unbiased estimator of the classification risk that can be estimated from the given unlabeled sets and theoretically analyze the generalization error of the learned classifier. We then find that the classifier obtained as such tends to cause overfitting as its empirical risks go negative during training. To prevent overfitting, we further propose a partial risk regularization that maintains the partial risks with respect to unlabeled datasets and classes to certain levels. Experiments demonstrate that our method effectively mitigates overfitting and outperforms state-of-the-art methods for learning from multiple unlabeled sets.

Abstract Purpose: To analyze the distribution of fibrovascular proliferative membrane (FVPM) in proliferative diabetic retinopathy (PDR) patients that need treated with pars plana vitrectomy (PPV), and to evaluate the outcomes separately. Methods: Retrospective review of consecutive 25-G PPV cases operated for PDR between September 2018 and April 2020. All FVPMs were outlined and assigned to three groups: arcade type, juxtapapillary type and central type. General characteristics, operation-related variables, best-corrected visual acuity (BCVA) 12 month postoperative and complications were recorded. , All patients were followed up for over one year Results: In total, 93 eyes were recruited. Among them, the FVPMs distribution of nasotemporal and inferiosuperioral were significantly different (both p &lt; 0.01), with 87 (93.55%) FVPMs located in the nasal hemispheres, and 67 (72.04%) in the inferior hemispheres. The eyes with a central FVPM required the longest operation time, with silicon oil used in most patients, generally combined with tractional retinal detachment (RD) and rhegmatogenous RD, as well as the worst postoperative best-corrected visual acuity and the highest rates of recurrent RD and iatrogenic retinal break formation (all p &lt; 0.05). Conclusion: FVPMs were more commonly found in the nasal and inferior mid-peripheral retina in addition to the area of arcade vessels. Performing 25-G PPV for treating PDR eyes with a central FVPM had a relatively worse prognosis.

Recent years have witnessed a great success of supervised deep learning, where predictive models were trained from a large amount of fully labeled data. However, in practice, labeling such big data can be very costly and may not even be possible for privacy reasons. Therefore, in this paper, we aim to learn an accurate classifier without any class labels. More specifically, we consider the case where multiple sets of unlabeled data and only their class priors, i.e., the proportions of each class, are available. Under this problem setup, we first derive an unbiased estimator of the classification risk that can be estimated from the given unlabeled sets and theoretically analyze the generalization error of the learned classifier. We then find that the classifier obtained as such tends to cause overfitting as its empirical risks go negative during training. To prevent overfitting, we further propose a partial risk regularization that maintains the partial risks with respect to unlabeled datasets and classes to certain levels. Experiments demonstrate that our method effectively mitigates overfitting and outperforms state-of-the-art methods for learning from multiple unlabeled sets.

A nucleus-specific RNAi nanoplatform was developed by Xu et al. for targeted regulation of nuclear lncRNA function and effective cancer therapy. This nanoplatform could respond to the endosomal pH to expose NTPA/siRNA complexes for the nucleus-specific siRNA delivery, leading to a significant inhibition of nuclear lncNEAT2 expression and tumor growth.

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This Technical Memorandum (TM) summarizes the Fermilab Test Beam operations for FY2017. It is one of a series of annual publications intended to gather information in one place. In this case, the information concerns the individual experiments that ran at FTBF and are listed in Table 1. Each experiment section was prepared by the relevant authors, and was edited for inclusion in this summary.

In the ultra-dense network scenario, a joint power allocation scheme is proposed to maximize the sum rate of user-centric overlapped virtual cell systems. The optimal power allocation is firstly modeled with hierarchical framework and decomposed into two subproblems: power splitting and virtual power allocation, then it is solved by the alternating iteration between the two subproblems. The power splitting is obtained by an SLNR (signal to leakage plus noise ratio)-based algorithm with the introducing of Lagrangian function, and virtual power allocation is achieved by a binary iterative water-filling algorithm. As the power splitting coefficient takes the form of eigenvector which maximizes SLNR, a balanced effect on signal enhancement and interference reduction is achieved. Simulation results show that the proposed algorithm is superior to conventional power allocation algorithms in performance, as it effectively reduces interference and increases the sum rate of the system.

Paradoxical embolism is often accompanied by pulmonary embolism (PE). It can occur in the same time with PE, also can occur after PE. When right atrial pressure is higher than left atrium pressure during pulmonary hypertension, the thrombus enters into the left cardiac system through the oval hole at the level of the atrium, which leads to systemic arterial embolism. It is previously considered as a rare disease. With the understanding of thromboembolic diseases, it is not rare to find paradoxical embolism. In this paper, the current status of paradoxical embolism and treatment strategies will be reviewed. Key words: Venous thromboembolism; Pulmonary embolism; Paradoxical embolism; Foramen ovale, patent; Therapy

The barrel timing layer for the CMS HL-LHC precision timing detector will be constructed using LYSO+SiPM modules. The barrel in HL-LHC beam intensities is expected to be exposed under an ionization dose rate of up to 200 rad/h and a neutron flux of up to 3×10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">6</sup> neq/cm <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sup> /s. We present results from measurements of photocurrent in the LYSO+SiPM packages induced by Co-60 γ-rays and Cf-252 neutrons. The γ-ray induced readout noise is found to be about 30 keV, which is negligible compared to the 4.2 MeV signal from minimum ionization particles. The neutron induced noise is about 7 keV, which is more than a factor of 4 smaller than that from the ionization dose.

Table S4. Genotypic data of CfSUS identified in the associated population. (XLSX 30 kb)

Table S1. Phenotype of associated population. (XLSX 19 kb)

One possible source of ambient noise in the ocean is clouds of bubbles generated by a variety of mechanisms at the sea surface and extending down to depths of several meters [A. Prosperetti, J. Acoust. Soc. Am. 83, 1042–1054 (1988)]. Experimental evidence exists [Yoon et al., J. Acoust. Soc. Am. (1990)] that demonstrates that the sound generated by a cloud of bubbles is characteristic of the gross features of the cloud itself. From the analysis of underwater acoustic emissions of these “collective oscillations,” the numerous modes of vibration of a column of bubbles were studied, including a variety of boundary conditions, and these results compared against theoretical predictions. Because of the excellent agreement that exists between predicted and measured acoustic characteristics of the bubble-filled column, it appears that the theory for describing such collective oscillations is becoming firmly established. [Work supported by ONR and ONT.]

At HEP experiments, processing billions of records of structured numerical data can be a bottleneck in the analysis pipeline.This step is typically more complex than current query languages allow, such that numerical codes are used.As highly parallel computing architectures are increasingly important in the computing ecosystem, it may be useful to consider how accelerators such as GPUs can be used for data analysis.Using CMS and ATLAS Open Data, we implement a benchmark physics analysis with GPU acceleration directly in Python based on efficient computational kernels using Numba/LLVM, resulting in an order of magnitude throughput increase over a pure CPUbased approach.We discuss the implementation and performance benchmarks of the physics kernels on CPU and GPU targets.We demonstrate how these kernels are combined to a modern ML-intensive workflow to enable efficient data analysis on high-performance servers and remark on possible operational considerations.

Nan Lu#, Yongchuan Li#, Jiajia Lu, Fan Zhang and Aimin Chen* Author Affiliations Department of Orthopaedic surgery, Shanghai Changzheng Hospital, Second Military Medical University, China #These authors are equally contributed to this work Received: November 23, 2020 | Published: January 19, 2021 Corresponding author: Aimin Chen, Department of Orthopaedic surgery, Shanghai Changzheng Hospital, Second Military Medical University, China DOI: 10.26717/BJSTR.2021.33.005369

&amp;lt;p&amp;gt;Vertical measurements of aerosol physical-chemical properties have important significance for better addressing the environment and climate effects of atmospheric aerosol. Traditional in-situ vertical observations of those properties are mainly based on aircraft platforms which are costly and restrictive, and not applicable for near-ground (&amp;lt;500 m) measurements. Within the boundary layer, tethered balloon and unmanned aerial vehicle (UAV) are ideal observation platforms but cannot carry heavy online aerosol instruments due to payload limitations. In this study, a new lightweight airborne aerosol sampling system is developed for tethered balloon and UAV platform. The system can collect airborne aerosol samples at up to 12 heights with conductive bags, and the samples can be analyzed later by online instruments such as aerosol mass spectrometer and single particle soot photometer (SP2). During an intensive field campaign conducted in Lhasa in summer of 2020, the new developed system was applied together with a SP2 to determine the vertical profile of refractory black carbon (rBC) mixing state. Preliminary results show that most rBC containing particles are external mixture and the proportion of internally mixed rBC increases with height. The vertical profiles of rBC mixing state are affected by surface emissions, the development of atmospheric boundary layer and meteorological conditions.&amp;lt;/p&amp;gt;

Traditional vine variety identification methods usually rely on the sampling of vine leaves followed by physical, physiological, biochemical and molecular measurement, which are destructive, time-consuming, labor-intensive and require experienced grape phenotype analysts. To mitigate these problems, this study aimed to develop an application (App) running on Android client to identify the wine grape automatically and in real-time, which can help the growers to quickly obtain the variety information. Experimental results showed that all Convolutional Neural Network (CNN) classification algorithms could achieve an accuracy of over 94% for twenty-one categories on validation data, which proves the feasibility of using transfer deep learning to identify grape species in field environments. In particular, the classification model with the highest average accuracy was GoogLeNet (99.91%) with a learning rate of 0.001, mini-batch size of 32 and maximum number of epochs in 80. Testing results of the App on Android devices also confirmed these results. Keywords: deep learning, mobile phone, grapevine cultivar, vine leaf image, identification, Vitis vinifera L. DOI: 10.25165/j.ijabe.20211405.6593 Citation: Liu Y X, Shen L, Su J Y, Lu N, Fang Y L, Liu F, et al. Development of a mobile application for identification of grapevine (Vitis vinifera L.) cultivars via deep learning. Int J Agric & Biol Eng, 2021; 14(5): 172–179.

The Lixia River area in Jiangsu Province is a typical plain river network area in the lower reaches of the Jianghuai Plain. The water system in the area is characterized by strong artificial control, close upstream and downstream connections, and slow flow of water. In this study, we use the coupled model of hydrology, hydrodynamics and water quality of the river network in the Lixia River area to simulate the changes of water quality and hydrodynamic conditions of the regional river network under different joint scheduling schemes, and analyze the effect of different schemes on improving the regional water environment. Considering the different conditions of diversion control, drainage control, starting time and river section connectivity, a total of five water transfer schemes were set up to simulate and analyze the effect of water environment improvement during the non-flood season. Through the analysis of regional water quality representative sites, the effect of water transfer on the improvement of the water environment in different areas of the hinterland is different, with a significant effect in the south of the study area, most of the indicators of water quality after the transfer of water to reach the national water quality standard and significantly better than the current water quality as well as the results in the middle area. The reduction of COD, BOD5 organic pollutant concentration in the north of the study area has a certain role, but does not have the improvement of N, P nutrient pollution function. The region-wide water transfer simulation experiments can provide technical support for the attempt of optimal scheduling of water environment under the watershed management system, taking the watershed as a unit and breaking the administrative division.

Bright and fast LYSO:Ce crystals with SiPM readout are used for the barrel timing layer of the CMS MIP timing detector project at the HL-LHC. A thermal electric cooler is mounted on SiPMs to mitigate the expected high dark counting rate. The SiPM temperature will be controlled at -35 °C (238 K) during beam on to reduce the dark counting rate, and at a high temperature, such as 25 °C (298 K) during beam off to facilitate thermal annealing. We report photo-luminescence spectra measured at 213, 238, and 295 K for four LYSO bars from different vendors. No significant variation in both intensity and decay time was observed. The results demonstrate that LYSO:Ce crystals work well down to -60 °C.

A key assumption in supervised learning is that training and test data follow the same probability distribution. However, this fundamental assumption is not always satisfied in practice, e.g., due to changing environments, sample selection bias, privacy concerns, or high labeling costs. Transfer learning (TL) relaxes this assumption and allows us to learn under distribution shift. Classical TL methods typically rely on importance-weighting -- a predictor is trained based on the training losses weighted according to the importance (i.e., the test-over-training density ratio). However, as real-world machine learning tasks are becoming increasingly complex, high-dimensional, and dynamical, novel approaches are explored to cope with such challenges recently. In this article, after introducing the foundation of TL based on importance-weighting, we review recent advances based on joint and dynamic importance-predictor estimation. Furthermore, we introduce a method of causal mechanism transfer that incorporates causal structure in TL. Finally, we discuss future perspectives of TL research.

The literature contains substantial evidence that oceanic ambient noise is wind dependent over a broad frequency range [G. Wenz, J. Acoust. Soc. Am. 34, 1936 (1962)]. The nature of the source of low-frequency acoustic emissions is still unknown, although a correlation with breaking waves points toward the possibility, suggested by one of the authors [A. Prospererti, J. Acoust. Soc. Am. 84, 1042 (1988)], that the collective oscillations of bubble clouds may be involved. Studies, both experimental and theoretical, are reported on for the noise generated by a column of bubbles that is self excited into oscillation. By varying parameters such as column height, void fraction, size of bubbles, etc., the applicability of a theory that presumes the bubbles are undergoing collective oscillations can be critically challenged. The theory survives the test in all respects. This will lead to future studies on the more general problem of oceanic ambient noise. [Work supported by ONR and KOSEF (SWY).]