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Simple Summary: Investigating strategies to mitigate weaning stress in rabbits holds considerable relevance for the rabbit breeding industry. Epigallocatechin gallate (EGCG), the predominant polyphenol in green tea, is recognized for its extensive health benefits. This study aimed to investigate the impact of dietary supplementation with EGCG on the antioxidant status, immune response, and intestinal microbiota in post-weaning rabbits. The results indicated that EGCG could effectively alleviate oxidative stress induced by weaning, as evidenced by enhanced antioxidant capacity, reduced peroxide generation, increased antioxidant enzymatic activity, improved intestinal morphology, decreased intestinal inflammation, and modulated intestinal microbiota flora. This information is essential for rabbit breeders seeking effective methods to mitigate post-weaning stress. This study was conducted to investigate the impact of EGCG on antioxidant stress, immune response, and intestinal microbiota flora in post-weaning rabbits. A total of 144 40 d Ira rabbits (equally divided by sex), were randomly allocated to six treatments. with five groups receiving doses of 200, 400, 600, 800, and 1000 mg/kg of EGCG, while one group served as a control without EGCG. Over 48 days, this study the assessed growth performance, antioxidant capacity, immune system, intestinal morphology, and cecal microbiota in the rabbits. The results showed that EGCG did not affect growth performance; however, significant linear and quadratic correlations were observed between the MDA, T-AOC, and GSH-Px activities in the liver and jejunum (p < 0.05). Quadratic effects were observed for the spleen and thymus indexes and serum IgG levels with increasing EGCG dosages (p < 0.05). Additionally, positive linear and quadratic effects were found on the ileal villus height and the villus height/crypt depth ratio. The relative abundances of Euryarchaeota, Patescibacteria, and Synergistota were significantly enriched in rabbits fed with high dosages (600–1000 mg/kg) of EGCG. Conclusively, the addition of large doses of EGCG (400–800 mg/kg) can effectively suppress oxidative stress and alleviate weaning stress, thereby contributing to the protection of post-weaning rabbits. [ABSTRACT FROM AUTHOR]

Simple Summary: Probiotics have a range of effects on poultry industry, including improving production performance, inhibiting or mitigating pathogenic infections, enhancing antioxidant capacity, reducing toxic effects, and improving the intestinal environment of poultry. They have significant potential for use as an ideal alternative to antibiotics in poultry farming. The purpose of this research was to evaluate the effect of solid fermentation products of Lactobacillus plantarum, Candida utilis, and Bacillus coagulans on the growth characteristics of broilers and the prevention of avian colibacillosis. The findings indicate that solid fermentation products can enhance the growth characteristics, immune function, and intestinal morphology of broilers. Additionally, it can optimize the abundance of microflora in the cecum and prevent avian colibacillosis, which is caused by avian pathogenic Escherichia coli (APEC). This study investigates the impact of the solid-state fermentation products of Lactobacillus plantarum, Candida utilis, and Bacillus coagulans (LCBs) on the growth characteristics, immune function, intestinal morphology, cecum microbial community, and prevention of avian colibacillosis in broilers. One hundred and twenty Hyland Brown broilers (aged one day) were divided randomly into three groups (four replicates of ten broilers per group). (1) The CON group was fed a basal diet. (2) The MOD group was fed a basal diet. On day 40, APEC strain SX02 (1.1 × 105 CFU/g) was administered to the breasts of chickens in this group. (3) The LCBs group was fed a basal diet supplemented with fermentation products (98.5% basal diet + 0.5% Lactobacillus plantarum and Candida utilis solid-state fermentation products + 1.0% Bacillus coagulans solid-state fermentation products). On day 40, the LCBs group received the same treatment as the MOD group. The experiment lasted 43 days. This study found that the average daily gain (ADG) of the LCBs group was significantly higher than that of the MOD group (p < 0.05), indicating that LCBs can significantly increase the ADG of broilers and improve the feed conversion ratio. Furthermore, compared to the MOD group, the heart bacterial load was significantly reduced in the LCBs group (p < 0.05), and the lesions less severe in the heart, liver, and jejunum were observed (p < 0.05). Additionally, the detection of intestinal flora showed a significant increase in the abundance of beneficial bacteria in the cecum of the LCBs group, while the number of Escherichia coli and Shigella decreased significantly. In conclusion, the solid fermentation of Lactobacillus plantarum, Candida utilis, and Bacillus coagulans can improve the growth performance of broilers while also protecting against avian pathogenic Escherichia coli infection. This demonstrates the potential usefulness of these LCBs in feed production. [ABSTRACT FROM AUTHOR]

Over the past few years, there has been a surge in research attention towards tasks involving graph data, largely due to the impressive performance demonstrated by graph neural networks (GNNs) in handling such information. Currently, out-of-distribution (OOD) detection in graphs is a hot research topic. The goal of graph OOD detection is to identify nodes or new graphs that differ from the training data distribution, primarily in terms of attributes and structures. OOD detection is crucial for enhancing the stability, security, and robustness of models. In various applications, such as biological networks and financial fraud, graph OOD detection can help models identify anomalies or unforeseen situations, thereby enabling appropriate responses. In node-level OOD detection, existing models typically only consider first-order neighbors. This paper introduces graph diffusion to the OOD detection task for the first time, proposing the HOOD model, a graph diffusion-based OOD node detection algorithm. Specifically, the original graph is processed through graph diffusion to obtain a new graph that can directly capture high-order neighbor information, overcoming the limitation that message passing must go through first-order neighbors. The new graph is then sparsified using a top-k approach. Based on entropy information, regularization is employed to ensure the uncertainty of OOD nodes, thereby giving these nodes higher scores and enabling the model to effectively detect OOD nodes while ensuring the accuracy of in-distribution node classification. Experimental results demonstrate that the HOOD model outperforms existing methods in both node classification and OOD detection tasks on multiple benchmarks, highlighting its robustness and effectiveness. [ABSTRACT FROM AUTHOR]

Dendritic cells (DCs) serve as key regulators in tumor immunity, with activated DCs potentiating antitumor responses through the secretion of pro-inflammatory cytokines and the expression of co-stimulatory molecules. Most current studies focus on the relationship between DC subgroups and clear-cell renal-cell carcinoma (ccRCC), but there is limited research on the connection between DCs and ccRCC from the perspective of immune activation. In this study, activated DC genes were identified in both bulk and single-cell RNA-seq data. A prognostic model related to activated DCs was constructed using univariate, multivariate Cox regression and LASSO regression. The prognostic model was validated in three external validation sets: GSE167573, ICGC, and E-MTAB-1980. The prognostic model consists of five genes, PLCB2, XCR1, IFNG, HLA-DQB2, and SMIM24. The expression of these genes was validated in tissue samples using qRT-PCR. Stratified analysis revealed that the prognostic model was able to better predict outcomes in advanced ccRCC patients. The risk scores were associated with tumor progression, tumor mutation burden, immune cell infiltration, and adverse outcomes of immunotherapy. Notably, there was a strong correlation between the expression of the five genes and the sensitivity to JQ1, a BET inhibitor. Molecular docking indicated high-affinity binding of the proteins encoded by these genes with JQ1. In conclusion, our study reveals the crucial role of activated DCs in ccRCC, offering new insights into predicting immune response, targeted therapy effectiveness, and prognosis for ccRCC patients. [ABSTRACT FROM AUTHOR]

A tendency to increase the number of acquired remote sensing images and to make their average size larger has been observed. To manage such data, compression is needed, and lossy compression is often preferable. Since lossy compression introduces distortions, this results in worse classification and object detection. Therefore, lossy compression must be controlled, i.e., the introduced distortions must be under a certain limit. The distortions and the limit can be characterized by different metrics (quantitative criteria). Here, we consider the case of using the HaarPSI metric, which has a very high correlation with visual quality and human attention (saliency map), for three-channel optical band images compressed by the better portable graphics (BPG) encoder, one of the best modern compression techniques. We analyze a two-step procedure of providing a desired visual quality and show its peculiarities for the modes 4:4:4, 4:2:2, and 4:2:0 of image compression. We show how the HaarPSI metric relates to other known metrics of image visual quality and thresholds of distortion visibility. It is demonstrated that the two-step procedure provides about three times better accuracy in providing the desired visual quality compared to the fixed setting of parameter Q that controls compression for the BPG encoder. The provided accuracy is close to the reachable limit determined by the integer value setting of the Q parameter. We also briefly analyze the influence of compression on the classification accuracy of real-life remote sensing data. [ABSTRACT FROM AUTHOR]

Structural graph clustering is a data analysis technique that groups nodes within a graph based on their connectivity and structural similarity. The Structural graph clustering SCAN algorithm, a density-based clustering method, effectively identifies core points and their neighbors within areas of high density to form well-defined clusters. However, the clustering quality of SCAN heavily depends on the input parameters, ϵ and μ , making the clustering results highly sensitive to parameter selection. Different parameter settings can lead to significant differences in clustering results, potentially compromising the accuracy of the clusters. To address this issue, a novel structural graph clustering algorithm based on the adaptive selection of density peaks is proposed in this paper. Unlike traditional methods, our algorithm does not rely on external parameters and eliminates the need for manual selection of density peaks or cluster centers by users. Density peaks are adaptively identified using the generalized extreme value distribution, with consideration of the structural similarities and interdependencies among nodes, and clusters are expanded by incorporating neighboring nodes, enhancing the robustness of the clustering process. Additionally, a distance-based structural similarity method is proposed to re-cluster noise nodes to the correct clusters. Extensive experiments on real and synthetic graph datasets validate the effectiveness of our algorithm. The experiment results show that the ADPSCAN has a superior performance compared with several state-of-the-art (SOTA) graph clustering methods. [ABSTRACT FROM AUTHOR]

An optimal spatio-temporal hybrid model (STHM) based on wavelet transform (WT) is proposed to improve the sensitivity and accuracy of detecting slowly evolving faults that occur in the early stage and easily submerge with noise in complex industrial production systems. Specifically, a WT is performed to denoise the original data, thus reducing the influence of background noise. Then, a principal component analysis (PCA) and the sliding window algorithm are used to acquire the nearest neighbors in both spatial and time dimensions. Subsequently, the cumulative sum (CUSUM) and the mahalanobis distance (MD) are used to reconstruct the hybrid statistic with spatial and temporal sequences. It helps to enhance the correlation between high-frequency temporal dynamics and space and improves fault detection precision. Moreover, the kernel density estimation (KDE) method is used to estimate the upper threshold of the hybrid statistic so as to optimize the fault detection process. Finally, simulations are conducted by applying the WT-based optimal STHM in the early fault detection of the Tennessee Eastman (TE) process, with the aim of proving that the fault detection method proposed has a high fault detection rate (FDR) and a low false alarm rate (FAR), and it can improve both production safety and product quality. [ABSTRACT FROM AUTHOR]

To address the limitations of existing graph contrastive learning methods, which fail to adaptively integrate feature and topological information and struggle to efficiently capture multi-hop information, we propose an adaptive multi-view parallel graph contrastive learning framework (AMPGCL). It is an unsupervised graph representation learning method designed to generate task-agnostic node embeddings. AMPGCL constructs and encodes feature and topological views to mine feature and global topological information. To encode global topological information, we introduce an H-Transformer to decouple multi-hop neighbor aggregations, capturing global topology from node subgraphs. AMPGCL learns embedding consistency among feature, topology, and original graph encodings through a multi-view contrastive loss, generating semantically rich embeddings while avoiding information redundancy. Experiments on nine real datasets demonstrate that AMPGCL consistently outperforms thirteen state-of-the-art graph representation learning models in classification accuracy, whether in homophilous or non-homophilous graphs. [ABSTRACT FROM AUTHOR]

The tumor microenvironment (TME) is crucial in tumor development, metastasis, and response to immunotherapy. DNA methylation can regulate the TME without altering the DNA sequence. However, research on the methylation-driven TME in clear-cell renal cell carcinoma (ccRCC) is still lacking. In this study, integrated DNA methylation and RNA-seq data were used to explore methylation-driven genes (MDGs). Immune scores were calculated using the ESTIMATE, which was employed to identify TME-related genes. A new signature connected with methylation-regulated TME using univariate, multivariate Cox regression and LASSO regression analyses was developed. This signature consists of four TME-MDGs, including AJAP1, HOXB9, MYH14, and SLC6A19, which exhibit high methylation and low expression in tumors. Validation was performed using qRT-PCR which confirmed their downregulation in ccRCC clinical samples. Additionally, the signature demonstrated stable predictive performance in different subtypes of ccRCC. Risk scores are positively correlated with TMN stages, immune cell infiltration, tumor mutation burden, and adverse outcomes of immunotherapy. Interestingly, the expression of four TME-MDGs are highly correlated with the sensitivity of first-line drugs in ccRCC treatment, especially pazopanib. Molecular docking indicates a high affinity binding between the proteins and pazopanib. In summary, our study elucidates the comprehensive role of methylation-driven TME in ccRCC, aiding in identifying patients sensitive to immunotherapy and targeted therapy, and providing new therapeutic targets for ccRCC treatment. [ABSTRACT FROM AUTHOR]

With escalating human activities and the substantial emissions of greenhouse gases, global warming intensifies. This phenomenon has led to increased occurrences of various extreme hydrological events, precipitating significant changes in lakes and rivers across the Qinghai Tibet Plateau. Therefore, accurate information extraction about and delineation of water bodies are crucial for lake monitoring. This paper proposes a methodology based on the Normalized Difference Water Index (NDWI) and Gumbel distribution to determine optimal segmentation thresholds. Focusing on Qinghai Lake, this study utilizes multispectral characteristics from the US Landsat satellite for analysis. Comparative assessments with seven alternative methods are conducted to evaluate accuracy. Employing the proposed approach, information about water bodies in Qinghai Lake is extracted over 38 years, from 1986 to 2023, revealing trends in area variation. Analysis indicates a rising trend in Qinghai Lake's area following a turning point in 2004. To investigate this phenomenon, Pearson correlation analysis of temperature and precipitation over the past 38 years is used and unveils the fact that slight precipitation impacts on area and that there is a positive correlation between temperature and area. In conclusion, this study employs remote sensing data and statistical analysis to comprehensively investigate mechanisms driving changes in Qinghai Lake's water surface area, providing insights into ecological shifts in lake systems against the backdrop of global warming, thereby offering valuable references for understanding and addressing these changes. [ABSTRACT FROM AUTHOR]

Large language models (LLMs) have demonstrated remarkable capabilities in natural language processing tasks, including conversation, in-context learning, reasoning, and code generation. This paper explores the potential application of LLMs in radiological information systems (RIS) and assesses the impact of integrating LLMs on RIS development and human–computer interaction. We present ChatUI-RIS, a prototype chat-based user interface that leverages LLM capabilities to enhance RIS functionality and user experience. Through an exploratory study involving 26 medical students, we investigate the efficacy of natural language dialogue for learning and operating RIS. Our findings suggest that LLM integration via a chat interface can significantly improve operational efficiency, reduce learning time, and facilitate rapid expansion of RIS capabilities. By interacting with ChatUI-RIS using natural language instructions, medical students can access and retrieve radiology information in a conversational manner. The LLM-powered chat interface not only streamlines user interactions, but also enables more intuitive and efficient navigation of complex RIS functionalities. Furthermore, the natural language processing capabilities of LLMs can be harnessed to automatically generate code snippets and database queries, accelerating RIS development and customization. Preliminary observations indicate that integrating LLMs in RIS has the potential to revolutionize user interface design, enhance system capabilities, and ultimately improve the overall user experience for radiologists and medical professionals. [ABSTRACT FROM AUTHOR]

Building extraction plays an important role in urban information analysis, which is helpful for urban planning and disaster monitoring. With the improvement of SAR resolution, rich detailed information in urban areas is revealed, but the discretized features also pose challenges for object detection. This paper addresses the problem of individual high-rise building extraction based on single high-resolution SAR image. Different from previous methods that require building facades to be presented in specific appearances, the proposed method is suitable for extraction of various types of high-rise buildings. After analyzing the SAR images of many types of high-rise buildings, we establish a unified high-rise building part model, on the basis of a scattering mechanism of building structures, to describe the facade characteristics of high-rise buildings, including a facade regularity part, facade bright line part, double bounce part, and their spatial topological relationships. A three-level high-rise building extraction framework, named HRBE-PM, is proposed based on the high-rise building part model. At the pixel level, a modified spot filter is used to extract bright spots and bright lines of different scales simultaneously to obtain salient features. At the structure level, building parts are generated based on the salient features according to semantic information. At the object level, spatial topological information between parts is introduced to generate building hypotheses. We define two indicators, completeness and compactness, to comprehensively evaluate each building hypothesis and select the optimal ones. After postprocessing, the final high-rise building extraction results are obtained. Experiments on two TerraSAR-X images show that the high-rise building extraction precision rate of the HRBE-PM method is above 85.29%, the recall rate is above 82.95%, and the F1-score is above 0.87. The results indicate that the HRBE-PM method can accurately extract individual high-rise buildings higher than 24 m in most dense scenes, regardless of building types. [ABSTRACT FROM AUTHOR]

The stabilization mechanism of soil organic matter (SOM) has received considerable attention. It is widely accepted that mineral sorption/protection is important for SOM stabilization. However, it remains unclear which organic carbon component is beneficial for mineral protection. We collected soil samples from a paddy field (TP) to compare with natural soil (NS). To illustrate the behavior of different SOM pools and their protection by particles, we separated the soils into different particle-size fractions and then removed the active minerals using an acid mixture (1 M HCl/10% HF). The different carbon pools were analyzed using stable carbon isotopes and lipid biomarkers. Our study showed that acid treatment evidently increased the extractability of free lipids, usually over 60%, which confirmed the predominant role of minerals in SOM protection. For NS, the δ13C values increased with decreasing soil particle sizes and soil depths, indicating that 13C-enriched SOM was selectively preserved. However, this trend disappeared after cultivation, which was mainly attributed to the combined effects of the input of 13C-depleted fresh SOM and decomposition of the preserved 13C-enriched SOM. Meanwhile, based on the degradation parameters of the overall lipid biomarkers, SOM showed higher degradation states in clay and silt fractions than in the sand fraction before cultivation. It is possible that the small particle-size fractions could selectively absorb highly degraded SOM. The clay-associated SOM showed a low degradation state, but its carbon content was low after cultivation. We propose that the previously protected SOM was degraded after cultivation and was replaced by relatively fresh SOM, which should be carefully monitored during SOM management. [ABSTRACT FROM AUTHOR]

In this study, the traditional mini split Hopkinson tension bar (SHTB) was enhanced for the dynamic mechanical performance testing of single fiber/resin interface of composites. Single Aramid III fibers were modified using a polyamine modification treatment. Quasi-static and dynamic tensile tests of modified single Aramid III fibers were conducted using an electronic tensile testing machine and mini SHTB. The test results indicated that the surface modification employing the Catechol-Tetraethylenepentamine (Cat-TEPA) approach had a negligible effect on the tensile mechanical properties of single Aramid III fibers. The microdroplet method was introduced to measure the dynamic interfacial shear strength (IFSS) of Aramid III fiber/waterborne polyurethane resin using a mini SHTB. The dynamic shear test results revealed an increase in the dynamic shear strength of the modified Aramid III fiber/resin interface from 36.16 MPa to 41.51 MPa. Furthermore, the Scanning Electron Microscope (SEM) photography of the modified single Aramid III fiber after debonding exhibited regular grid structures on the debonding area, which can prevent debonding between the single fiber and the microdroplet, thereby enhancing interfacial shear performance. [ABSTRACT FROM AUTHOR]

Pesticides are widely detected in large quantities in the environment, posing an ecological threat to the human body and ecology. Semiconductor nanomaterials such as nano-titania (nTiO2) have strong photocatalytic degradation efficiency for pollutants. However, the wide bandgap and limited light absorption range inhibit nano-titania's practical application. Therefore, nTiO2 was modified by Fe3+ doping using the microwave hydrothermal method to improve its photocatalytic performance in this study. Fe-nTiO2 doped with a 1.0% mass ratio was used due to its high photocatalytic performance. Its maximum degradation efficiencies for ACE and ATZ under a 20 W xenon lamp were 88% and 88.5%, respectively. It was found that Fe3+ doping modification distorted the spatial morphology of nTiO2 and shortened the bandgap to facilitate the photocatalytic reaction. The electron paramagnetic resonance results showed that the reactive radicals (1O2, ·OH) produced by photogenerated electrons (e−) and holes (h+) of Fe-nTiO2 were the main active species in the degradation of ACE and ATZ. Additionally, the application of Fe-nTiO2 significantly enhanced the growth of lettuce under sunlight; the degradation efficiencies of ACE and ATZ in lettuce were 98.5% and 100%, respectively. This work provides new insights into the removal of organic contaminants by photocatalysts under sunlight in agriculture. [ABSTRACT FROM AUTHOR]

At present, the production of the majority of valuable chemicals is dependent on the microbial fermentation of carbohydrate substrates. However, direct competition is a potential problem for microbial feedstocks that are also used within the food/feed industries. The use of alternative carbon sources, such as acetate, has therefore become a research focus. As a common organic acid, acetate can be generated from lignocellulosic biomass and C1 gases, as well as being a major byproduct in microbial fermentation, especially in the presence of an excess carbon source. As a model microorganism, Escherichia coli has been widely applied in the production of valuable chemicals using different carbon sources. Recently, several valuable chemicals (e.g., succinic acid, itaconic acid, isobutanol, and mevalonic acid) have been investigated for synthesis in E. coli using acetate as the sole carbon source. In this review, we summarize the acetate metabolic pathway in E. coli and recent research into the microbial production of chemical compounds in E. coli using acetate as the carbon source. Although microbial synthetic pathways for different compounds have been developed in E. coli, the production titer and yield are insufficient for commercial applications. Finally, we discuss the development prospects and challenges of using acetate for microbial fermentation. [ABSTRACT FROM AUTHOR]

With the widespread application and functional complexity of deep neural networks (DNNs), the demand for training samples is increasing. This elevated requirement also extends to DNN-based SAR object detection. Most public SAR object detection datasets are oriented to marine targets such as ships, while data sets oriented to land targets are relatively rare, though they are an effective way to improve the land object detection capability of deep models through SAR sample generation. In this paper, a synthesis generation collaborative SAR sample augmentation framework is proposed to achieve flexible and diverse high-quality sample augmentation. First, a semantic-layout-guided image synthesis strategy is proposed to generate diverse detection samples. The issues of object location rationality and object layout diversity are also addressed. Meanwhile, a pix2pixGAN network guided by layout maps is utilized to achieve diverse background augmentation. Second, a progressive training strategy of diffusion models is proposed to achieve semantically controllable SAR sample generation to further improve the diversity of scene clutter. Finally, a sample cleaning method considering distribution migration and network filtering is employed to further improve the quality of detection samples. The experimental results show that this semantic synthesis generation method can outperform existing sample augmentation methods, leading to a comprehensive improvement in the accuracy metrics of classical detection networks. [ABSTRACT FROM AUTHOR]

The self-purification capacity of semi-closed bays is closely related to the exchange process of open sea water. In recent years, with the enhancement of human development activities, environmental problems such as eutrophication, weak hydrodynamics, and poor water exchange capacity have appeared in the bays. In this paper, the water exchange time and flow field in Jiaozhou Bay (JZB) were investigated using the environmental fluid dynamics code with a coupled dye module. Specifically, Jiaozhou Bay was divided into seven zones to explore the effect mechanism of a monsoon on the water exchange process. A detailed analysis was performed on the current water exchange status in the highly polluted northeastern region of the bay and its influence on the surrounding areas. Based on the definition of the average residence time and considering the effect of the tracer release moment, the distribution of the water exchange time in the bay under three circumstances was obtained. Results showed that the timing of the tracer release exerted minimal influence on the average residence time. The water exchange process was influenced by a combination of astronomical and meteorological factors. The overall exchange capacity of the bay was strongest under the impact of a winter monsoon and tides, followed by a summer monsoon and tides, and the weakest exchange occurred under the influence of tides alone. Moreover, both summer and winter monsoons greatly facilitated water exchange in the heavily polluted northeastern region. However, pollutants from this region had a significant impact on surrounding areas during a summer monsoon. Changes in the structure and intensity of residual flow fields were the primary causes of exchange rate discrepancies. [ABSTRACT FROM AUTHOR]

Aiming to overcome the depletion of fossil fuels and serious environmental pollution, biofuels such as isobutanol have garnered increased attention. Among different synthesis methods, the microbial fermentation of isobutanol from raw substrate is a promising strategy due to its low cost and environmentally friendly and optically pure products. As an important component of lignocellulosics and the second most common sugar in nature, xylose has become a promising renewable resource for microbial production. However, bottlenecks in xylose utilization limit its wide application as substrates. In this work, an isobutanol synthetic pathway from xylose was first constructed in E. coli MG1655 through the combination of the Ehrlich and Dahms pathways. The engineering of xylose transport and electron transport chain complexes further improved xylose assimilation and isobutanol production. By optimizing xylose supplement concentration, the recombinant E. coli strain BWL4 could produce 485.35 mg/L isobutanol from 20 g/L of xylose. To our knowledge, this is the first report related to isobutanol production using xylose as a sole carbon source in E. coli. Additionally, a glucose–xylose mixture was utilized as the carbon source. The Entner–Doudorof pathway was used to assimilate glucose, and the Ehrlich pathway was applied for isobutanol production. After carefully engineering the recombinant E. coli, strain BWL9 could produce 528.72 mg/L isobutanol from a mixture of 20 g/L glucose and 10 g/L xylose. The engineering strategies applied in this work provide a useful reference for the microbial production of isobutanol from xylose or glucose–xylose mixture. [ABSTRACT FROM AUTHOR]

A novel clay-coated mesh was fabricated via a simple brush-coating method without the use of special equipment, chemical reagents, and complex chemical reactions and operation processes. Possessing superhydrophilicity and underwater superoleophobicity, the clay-coated mesh can be used for efficiently separating various light oil/water mixtures. The clay-coated mesh also exhibits excellent reusability, maintaining a high separation efficiency of 99.4% after 30 repeated separations of the kerosene/water mixture. [ABSTRACT FROM AUTHOR]

Biochar modification has received significant research attention due to its attractive and fruitful rewards in improving biochar performances. However, the determinants of modified biochars' stability and the ability of aged modified biochars to remove heavy metals have not been comprehensively evaluated. Therefore, three commonly used functional groups of modified biochars (5% and 10% H2O2-modified (BCH5 and BCH20); 25% and 65% HNO3-modified (BCA25 and BCA65); and amino-modified (BCN), were prepared in this study to explore their stability and the Cd(II) removal performance of aged functional groups modified biochars was studied. The results showed that the O/C ratio is not sensitive enough to predict the stability of functional groups modified biochars, which was commonly used to evaluate pristine biochar (BC0); instead, -COOH content is crucial for modified biochar stability (r = −0.99, r = −0.91, p < 0.05). BCA65 displayed the highest less prone to oxidation property, which indicated that the high surface charges and uniform surface determined the less prone to oxidation ability of the functionally modified biochars. The order of the stability of functionally modified biochars was HNO3-modified > H2O2-modified > amino-modified. After oxidation, the surface charges and pores were significantly reduced, and the Cd2+ adsorption mechanism of modified biochar changed from multilayer adsorption to monolayer adsorption, which led to a reduction in overall Cd(II) removal. The maximum adsorption capacities of BCA65 were reduced from 18.15 mg·g−1 to 4.86 mg·g−1 after oxidation, particularly. In the design and preparation of modified biochar, the long-term stability of the structure and function of modified biochar and its sustainable application in the environment should be considered while improving the heavy metal removal performance of biochars. [ABSTRACT FROM AUTHOR]

For many years, metamaterial absorbers have received much attention in a wide range of application fields. There is an increasing need to search for new design approaches that fulfill more and more complex tasks. According to the specific application requirements, design strategy can vary from structure configurations to material selections. A new combination of a dielectric cavity array, dielectric spacer, and gold reflector as a metamaterial absorber is proposed and theoretically studied in this work. The complexity of the dielectric cavities leads to a more flexible optical response than traditional metamaterial absorbers. It gives a new dimension of freedom for a real three-dimensional metamaterial absorber design. [ABSTRACT FROM AUTHOR]

The biodegradation path and mechanism of wood varies depending on diverse fungi and tree species, as fungi possess selectivity in degradation of versatile wood components. This paper aims to clarify the actual and precise selectivity of white and brown rot fungi and the biodegradation effects on different tree species. Softwood (Pinus yunnanensis and Cunninghamia lanceolata) and hardwood (Populus yunnanensis and Hevea brasiliensis) were subjected to a biopretreating process by white rot fungus Trametes versicolor, and brown rot fungi Gloeophyllum trabeum and Rhodonia placenta with various conversion periods. The results showed that the white rot fungus Trametes versicolor had a selective biodegradation in softwood, which preferentially convert wood hemicellulose and lignin, but cellulose was retained selectively. Conversely, Trametes versicolor achieved simultaneous conversion of cellulose, hemicellulose and lignin in hardwood. Both brown rot fungi species preferentially converted carbohydrates, but R. placenta had a selectivity for the conversion of cellulose. In addition, morphological observation showed that the microstructures within wood changed significantly, and the enlarged pores and the improved accessibility could be beneficial for the penetration and accessibility of treating substrates. The research outcomes could serve as fundamental knowhows and offer potentials for effective bioenergy production and bioengineering of bioresources, and provide a reference for further application of fungal biotechnology. [ABSTRACT FROM AUTHOR]

The molecular mechanisms underlying unexplained recurrent implantation failure (RIF) remain unclear. This study aimed at identifying potential biomarkers, exploring relevant signaling pathways, and analyzing the contribution of immune cell infiltration in RIF. Microarray expression datasets were extracted from the Gene Expression Omnibus database to perform bioinformatic analyses. The results showed that ten hub genes may predict RIF with high specificity and sensitivity (area under the curve = 1.000). Protein–protein interaction analysis revealed close interactions between the hub genes and the endometrial receptivity array. The real-time quantitative polymerase chain reaction further validated three potential biomarkers (RAB32, TRIB2, and FAM155B). Functional enrichment analyses indicated that immune pathways were significantly downregulated and lipid metabolism pathways were significantly upregulated in RIF compared with the controls. Significant negative correlations were observed between fatty acid biosynthesis and the immune pathways. Immune cell infiltration, including those in CD56dim natural killer, dendritic, Th1, Th2, and regulatory T cells, as well as macrophages, was significantly reduced in RIF compared with the controls used herein. This study may provide a novel perspective on the diagnosis and treatment of RIF. [ABSTRACT FROM AUTHOR]

The corrugated steel plate shear wall (CSPSW) has high strength, ductility, and energy dissipation capacity and can be used as the lateral force-resisting system of multi-story and high-rise buildings. The vertical load transmitted by the upper floor and frame columns may inevitably act on the corrugated steel plate shear wall. However, the influence of the gravity load on the performance of the corrugated steel shear wall is not considered in most studies. To investigate the behavior of corrugated steel plate shear walls considering the actual gravity load, four scaled SPSWs under lateral and vertical loading were tested. The specimens' failure mode, envelope curves, and hysteretic curves were analyzed. A numerical simulation model was established based on the validation of the experimental test on the SPSWs. The results showed that the hysteresis curves of the test were consistent with those of the simulation results. Finally, parametric analysis was conducted on the SPSWs with different types of infill plates, height-to-thickness ratio, and gravity loads. [ABSTRACT FROM AUTHOR]

Pain is a common clinical symptom among patients. Although various opioid analgesics have been developed, their side effects hinder their application. This study aimed to develop a novel opioid analgesic, HAGD (H-Tyr-D-AIa-GIy-Phe-NH2), with limited side effects. In vivo studies on mouse models as well as in vitro studies on Chinese hamster ovary (CHO) cells expressing human mu, delta, or kappa opioid receptors (CHOhMOP, CHOhDOP, and CHOhKOP, respectively) and human sperm were conducted. Compared with subcutaneous morphine (10 mg/kg), subcutaneous HAGD (10 mg/kg) produced equipotent or even greater antinociception with a prolonged duration by activating mu/delta opioid receptors in preclinical mouse pain models. The analgesic tolerance, rewarding effects (i.e., conditioned place preference and acute hyperlocomotion), and gastrointestinal transit inhibition of HAGD were significantly reduced compared with those of morphine. Both HAGD and morphine exhibited a withdrawal response and had no impacts on motor coordination. In CHOhMOP and CHOhDOP, HAGD showed specific and efficient intracellular Ca2+ stimulation. HAGD had minimal impact on human sperm motility in vitro, whereas 1 × 10−7 and 1 × 10−8 mol/L of morphine significantly declined sperm motility at 3.5 h. Overall, HAGD may serve as a promising antinociceptive compound. [ABSTRACT FROM AUTHOR]

Missing data is a common and inevitable phenomenon. In practical applications, the datasets usually contain noises for various reasons. Most of the existing missing data imputing algorithms are affected by noises which reduce the accuracy of the imputation. This paper proposes a noise-aware missing data multiple imputation algorithm NPMI in static data. Different multiple imputation models are proposed according to the missing mechanism of data. Secondly, the method to determine the imputation order of multivariablesmissing is given. A random sampling consistency algorithm is proposed to estimate the initial values of the parameters of the multiple imputation model to reduce the influence of noise data and improve the algorithm's robustness. Experiments on two real datasets and two synthetic datasets verify the accuracy and efficiency of the proposed NPMI algorithm, and the results are analyzed. [ABSTRACT FROM AUTHOR]

Background: Breast cancer (BRCA) is one of the most common cancers in women worldwide and a leading cause of death from malignancy. This study was designed to identify a novel biomarker for prognosticating the survival of BRCA patients. Methods: The prognostic potential of eukaryotic translation initiation factor 4 gamma 1 (EIF4G1) was assessed using RNA sequencing (RNA-seq) data from The Cancer Genome Atlas (TCGA) and Gene Expression Omnibus (GEO) as training cohort and validation set, respectively. The functional enrichment analysis of differentially expressed genes (DEGs) was performed. The relationship between EIF4G1 and tumor microenvironment (TME) was analyzed. Immunotherapy responses were explored by the immunophenoscores (IPS) and tumor immune dysfunction and exclusion (TIDE) score. The Connectivity Map (CMap) was used to discover potentially effective therapeutic molecules against BRCA. Immunohistochemistry (IHC) was applied to compare the protein levels of EIF4G1 in normal and cancer tissues and to verify the prognostic value of EIF4G1. Results: BRCA patients with increased expression of EIF4G1 had a shorter overall survival (OS) in all cohorts and results from IHC. EIF4G1-related genes were mainly involved in DNA replication, BRCA metastasis, and the MAPK signaling pathway. Infiltration levels of CD4+-activated memory T cells, macrophages M0, macrophages M1, and neutrophils were higher in the EIF4G1 high-expression group than those in the EIF4G1 low-expression group. EIF4G1 was positively correlated with T cell exhaustion. Lower IPS was revealed in high EIF4G1 expression patients. Five potential groups of drugs against BRCA were identified. Conclusion: EIF4G1 might regulate the TME and affect BRCA metastasis, and it is a potential prognostic biomarker and therapeutic target for BRCA. [ABSTRACT FROM AUTHOR]

Aims: Krüppel-like Factor 9 (KLF9) is a transcription factor that regulates multiple disease processes. Studies have focused on the role of KLF9 in the redox system. In this study, we aimed to explore the effect of KLF9 on diabetic cardiomyopathy. Methods and Results: Cardiac-specific overexpression or silencing of KLF9 in C57BL/6 J mice was induced with an adeno-associated virus 9 (AAV9) delivery system. Mice were also subjected to streptozotocin injection to establish a diabetic cardiomyopathy model. In addition, neonatal rat cardiomyocytes were used to assess the possible role of KLF9 in vitro by incubation with KLF9 adenovirus or small interfering RNA against KLF9. To clarify the involvement of peroxisome proliferator-activated receptors (PPARγ), mice were subjected to GW9662 injection to inhibit PPARγ. KLF9 was upregulated in the hearts of mice with diabetic cardiomyopathy and in cardiomyocytes. In addition, KLF9 overexpression in the heart deteriorated cardiac function and aggravated hypertrophic fibrosis, the inflammatory response and oxidative stress in mice with diabetic cardiomyopathy. Conversely, cardiac-specific silencing of KLF9 ameliorated cardiac dysfunction and alleviated hypertrophy, fibrosis, the cardiac inflammatory response and oxidative stress. In vitro, KLF9 silencing in cardiomyocytes enhanced inflammatory cytokine release and oxidative stress; KLF9 overexpression increased these detrimental responses. Moreover, KLF9 was found to regulate the transcription of PPARγ, which suppressed the expression and nuclear translocation of nuclear Factor E2-related Factor 2 (NRF2). In mice injected with a PPARγ inhibitor, the protective effects of KLF9 knockdown on diabetic cardiomyopathy were counteracted by GW9662 injection. Conclusions: KLF9 aggravates cardiac dysfunction, the inflammatory response and oxidative stress in mice with diabetic cardiomyopathy. KLF9 may become a therapeutic target for diabetic cardiomyopathy. [ABSTRACT FROM AUTHOR]

Medical applications of nanotechnology are promising in creating efficient and targeted therapies. However, so far, nanodrug design has not taken into consideration possible effects on human microbiota. The beneficial functions of bacteria could be stimulated by nanodrugs while negative effects on beneficial bacteria could cause risks to human health. Here, simulated intestinal fluid (IF) was optimized for culturing a human commensal and probiotic bacterial strain, Lactobacillus casei, to study the effects of medically relevant NPs—Ag and hyaluronic acid-coated Au NPs (HA-Au NPs)—in conditions pertinent to the gastrointestinal tract. When cultivated either aerobically or anaerobically, the specific growth rates of L. casei were ~0.2 h−1 in IF and ~0.4 h−1 in the standard medium of lactobacilli (MRS). Ag NPs inhibited the growth of L. casei in IF at lower concentrations (EC50 ~ 65 and 15 mg/L in aerobic and anaerobic conditions, respectively) than in MRS (EC50 > 100 mg/L), likely caused by differences in the composition of the two media and different intrinsic growth rates of bacteria in IF and MRS. Ag NP dissolution in IF and MRS did not explain the differences in growth inhibition, implying NP-specific effects. HA-Au NPs were not growth-inhibitory to L. casei up to 250 mg/L. Still, both NPs at sub-growth-inhibitory concentrations suppressed the expression of bacteriocin genes in L. casei, suggesting an inhibitory effect of NPs on the probiotic properties of L. casei, i.e., its competitiveness in microbial communities. However, HA-Au NPs did not appear to affect or even stimulated the immunomodulatory properties of L. casei in human intestinal epithelial cells. Thus, medically relevant NPs at low, sub-bacteriostatic levels can affect the metabolism of beneficial human bacteria and potentially induce changes in the microbiota and immune signaling. [ABSTRACT FROM AUTHOR]

TFIIIA is a zinc-finger transcription factor that is involved in post-transcriptional regulation during development. Here, the BcTFIIIA gene was isolated from pak choi. Sequence analysis showed that BcTFIIIA encodes 383 amino acids (aa) with an open reading frame (ORF) of 1152 base pairs (bp). We investigated the subcellular location of BcTFIIIA and found the localized protein in the nucleus. BcTFIIIA was suppressed when the pak choi was infected by the turnip mosaic virus (TuMV). The BcTFIIIA mRNA expression level in a resistant variety was higher than that in a sensitive variety, as determined by qRT-PCR analysis. Yeast two hybrid (Y2H) assay and bimolecular fluorescence complementation (BiFC) suggested that BcTFIIIA interacts with TuMV CP and VPg in vivo, respectively, and in vitro. A virus-induced gene silencing (VIGS) experiment showed that the silencing of BcTFIIIA gene expression in pak choi promoted the accumulation of TuMV. These results suggest that BcTFIIIA negatively regulates viral infection through the interaction with TuMV CP and VPg. [ABSTRACT FROM AUTHOR]

In this study, we attempted to eliminate atmospheric fog and aerosol particles by strong sound waves. The action of sound waves created an air disturbance, and the oscillation of the local air caused the micron-sized aerosol droplet particles to move. To provide guidance of the characteristics of the effective sound waves, this study numerically simulated aerosol droplet agglomeration under the action of sound waves, which was solved by coupling computational fluid dynamics (CFD) and discrete element methods (DEMs) as a typical two-phase flow problem in this study. The movements of aerosol droplet particles were simulated, as well as their agglomeration. The evolution process of the average particle size and the number of multimers were obtained, and the influence of different sound frequencies, sound pressure level (SPL), and particle spacing on agglomeration were studied. It was found that the promotion effect of low-frequency sound waves on aerosol droplet agglomeration was significantly higher than that of high-frequency sound waves, and the sound wave promotion effect of high SPLs was better than that of low SPL. In addition, the concept of the average agglomeration time required to quantify the acoustic agglomeration speed was proposed, and it was found to be positively correlated with sound frequency and particle spacing, while being negatively correlated with SPL. [ABSTRACT FROM AUTHOR]

High-voltage electrostatic field (HVEF) as an emerging green technology is just at the beginning of its use in meat products and by-products processing. In this study, we employed duck oil to produce duck-oil-based diacylglycerol (DAG), termed DDAG. Three different DDAG volume concentrations (0, 20%, and 100%) of hybrid duck oils, named 0%DDAG, 20%DDAG, and 100%DDAG, respectively, were used to investigate their thermal oxidation stability in high-voltage electrostatic field heating and ordinary heating at 180 ± 1 ℃. The results show that the content of saturated fatty acids and trans fatty acids of the three kinds of duck oils increased (p < 0.05), while that of polyunsaturated fatty acids decreased (p < 0.05) from 0 h to 8 h. After heating for 8 h, the low-field nuclear magnetic resonance showed that the transverse relaxation time (T21) of the three oils decreased (p < 0.05), while the peak area ratio (S21) was increased significantly (p < 0.05). The above results indicate that more oxidation products were generated with heating time. The peroxide value, the content of saturated fatty acids, and the S21 increased with more DAG in the duck oil, which suggested that the oxidation stability was likely negatively correlated with the DAG content. Moreover, the peroxide value, the content of saturated fatty acids and trans fatty acids, and the S21 of the three concentrations of duck oils were higher (p < 0.05) under ordinary heating than HVEF heating. It was concluded that HVEF could restrain the speed of the thermal oxidation reaction occurring in the duck oil heating and be applied in heating conditions. [ABSTRACT FROM AUTHOR]

Polarimetric Interferometric Synthetic Aperture Radar (PolInSAR) has many useful applications, especially in forest areas. With the development of SAR miniaturization technology, researchers can install PolInSAR on small unmanned aerial vehicles (UAV), which can reduce flight costs. Limited by size and power, UAV-borne SAR usually works in a high-frequency band, which restricts its application to such things as vegetation height inversion. While on the other hand, the high resolution acquired under a short wavelength promises its application in urban areas. However, there are fewer studies on the application of PolInSAR in urban areas compared with that in forest areas. In this paper, we propose a processing method for a Ku-band multi-rotor-UAV-borne PolInSAR and provide a preliminary analysis of height inversion results on its data from the Fudan campus in Shanghai. We obtain the digital surface model (DSM) of different polarization modes and the DSM of polarimetric interferometry optimal decomposition in this area, whose RMSE is 2.88 m. On this basis, the elevation inversion results of targets such as buildings, lampposts, and trees are compared and analyzed. We preliminarily explore and analyze the reasons for the different results of different targets. To this end, we propose a mathematical derivation of the relationship between the interferometric phase between PolInSAR and InSAR of Pauli decomposition. We also perform a simulation to analyze the relationship between the phase center height of Pauli decomposition and PolInSAR under different cases. It provides a reference for the application of small UAV-borne PolInSAR in urban areas. [ABSTRACT FROM AUTHOR]

This paper deals with providing the desired quality in the Better Portable Graphics (BPG)-based lossy compression of color and three-channel remote sensing (RS) images. Quality is described by the Mean Deviation Similarity Index (MDSI), which is proven to be one of the best metrics for characterizing compressed image quality due to its high conventional and rank-order correlation with the Mean Opinion Score (MOS) values. The MDSI properties are studied and three main areas of interest are determined. It is shown that quite different quality and compression ratios (CR) can be observed for the same values of the quality parameter Q that controls compression, depending on the compressed image complexity. To provide the desired quality, a modified two-step procedure is proposed and tested. It has a preliminary stage carried out offline (in advance). At this stage, an average rate-distortion curve (MDSI on Q) is obtained and it is available until the moment when a given image has to be compressed. Then, in the first step, an image is compressed using the starting Q determined from the average rate-distortion curve for the desired MDSI. After this, the image is decompressed and the produced MDSI is calculated. In the second step, if necessary, the parameter Q is corrected using the average rate-distortion curve, and the image is compressed with the corrected Q. Such a procedure allows a decrease in the MDSI variance by around one order after two steps compared to variance after the first step. This is important for the MDSI of approximately 0.2–0.25 corresponding to the distortion invisibility threshold. The BPG performance comparison to some other coders is performed and examples of its application to real-life RS images are presented. [ABSTRACT FROM AUTHOR]

Classical swine fever (CSF) is a severe disease that has caused serious economic losses for the global pig industry and is widely prevalent worldwide. In recent decades, CSF has been effectively controlled through compulsory vaccination with a live CSF vaccine (C strain). It has been successfully eradicated in some countries or regions. However, the re-emergence of CSF in Japan and Romania, where it had been eradicated, has brought increased attention to the disease. Because the traditional C-strain vaccine cannot distinguish between vaccinated and infected animals (DIVA), this makes it difficult to fight CSF. The emergence of marker vaccines is considered to be an effective strategy for the decontamination of CSF. This paper summarizes the progress of the new CSF marker vaccine and provides a detailed overview of the vaccine design ideas and immunization effects. It also provides a methodology for the development of a new generation of vaccines for CSF and vaccine development for other significant epidemics. [ABSTRACT FROM AUTHOR]

In order to evaluate the potential differences between 3-Ac-DON and 15-Ac-DON in the human intestinal microbial metabolism, human fecal samples were anaerobically cultured in vitro. Quantitative fecal microbiota characteristics were obtained by 16S rRNA sequencing, and the data revealed several genera that may be relevant for the transformation of the acetylated DONs. Significant differences in the level of 3-Ac-DON and 15-Ac-DON conversion were observed among microbiota from different human individuals. 3-Ac-DON could be rapidly hydrolyzed; a ten-fold difference was observed between the highest and lowest in vitro conversion after 4 h. However, 15-Ac-DON was not fully transformed in the 4 h culture of all the individual samples. In all cases, the conversion rate of 3-Ac-DON was higher than that of 15-Ac-DON, and the conversion rate of 3-Ac-DON into DON varied from 1.3- to 8.4-fold that of 15-Ac-DON. Based on in vitro conversion rates, it was estimated that 45–452 min is required to convert all 3-Ac-DON to DON, implying that deacetylation of 3-Ac-DON is likely to occur completely in all human individuals during intestinal transit. However, for conversion of 15-Ac-DON, DON formation was undetectable at 4 h incubation in 8 out of the 25 human samples, while for 7 of these 8 samples conversion to DON was detected at 24 h incubation. The conversion rates obtained for these seven samples indicated that it would take 1925–4805 min to convert all 15-Ac-DON to DON, while the other 17 samples required 173–734 min. From these results it followed that for eight of the 25 individuals, conversion of 15-Ac-DON to DON was estimated to be incomplete during the 1848 min intestinal transit time. The results thus indicate substantial interindividual as well as compound specific differences in the deconjugation of acetylated DONs. A spearman correlation analysis showed a statistically significant relationship between deconjugation of both acetyl-DONs at 4 h and 24 h incubation. Based on the in vitro kinetic parameters and their scaling to the in vivo situation, it was concluded that for a substantial number of human individuals the deconjugation of 15-Ac-DON may not be complete upon intestinal transit. [ABSTRACT FROM AUTHOR]

A novel encryption algorithm called the chained phase-controlled operation (CPCO) is presented in this paper, inspired by CNOT operation, which indicates a stronger correlation among message states and each message state depending on not only its corresponding key but also other message states and their associated keys. Thus, it can prevent forgery effectively. According to the encryption algorithm CPCO and the classical dual signature protocols, a quantum dual signature scheme based on coherent states is proposed in this paper. It involves three participants, the customer Alice, the merchant Bob and the bank Trent. Alice expects to send her order message and payment message to Bob and Trent, respectively. It is required that the two messages must be linked to guarantee the payment is paid for the corresponding order. Thus, Alice can generate a quantum dual signature to achieve the goal. In detail, Alice firstly signs her two messages with the shared secret key. Then She connects the two signatures into a quantum dual signature. Finally, Bob and Trent severally verify the signatures of the order message and the payment message. Security analysis shows that our scheme can ensure its security against forgery, repudiation and denial. In addition, simulation experiments based on the Strawberry Fields platform are performed to valid the feasibility of CPCO. Experimental results demonstrate that CPCO is viable and the expected coherent states can be acquired with high fidelity, which indicates that the encryption algorithm of the scheme can be implemented on quantum devices effectively. [ABSTRACT FROM AUTHOR]

One decisive problem of short text classification is the serious dimensional disaster when utilizing a statistics-based approach to construct vector spaces. Here, a feature reduction method is proposed that is based on two-stage feature clustering (TSFC), which is applied to short text classification. Features are semi-loosely clustered by combining spectral clustering with a graph traversal algorithm. Next, intra-cluster feature screening rules are designed to remove outlier feature words, which improves the effect of similar feature clusters. We classify short texts with corresponding similar feature clusters instead of original feature words. Similar feature clusters replace feature words, and the dimension of vector space is significantly reduced. Several classifiers are utilized to evaluate the effectiveness of this method. The results show that the method largely resolves the dimensional disaster and it can significantly improve the accuracy of short text classification. [ABSTRACT FROM AUTHOR]

Word embeddings are effective intermediate representations for capturing semantic regularities between words in natural language processing (NLP) tasks. We propose sentiment-aware word embedding for emotional classification, which consists of integrating sentiment evidence within the emotional embedding component of a term vector. We take advantage of the multiple types of emotional knowledge, just as the existing emotional lexicon, to build emotional word vectors to represent emotional information. Then the emotional word vector is combined with the traditional word embedding to construct the hybrid representation, which contains semantic and emotional information as the inputs of the emotion classification experiments. Our method maintains the interpretability of word embeddings, and leverages external emotional information in addition to input text sequences. Extensive results on several machine learning models show that the proposed methods can improve the accuracy of emotion classification tasks. [ABSTRACT FROM AUTHOR]

A new aliphatic acid, compound 1, together with six known metabolites, including nonactic acid (2), homononactic acid (3), ethyl homononactate (4), homononactylhomononactate (5), valinomycin (6), and cyclo-(Pro-Leu) (7), was isolated from the culture broth of Streptomyces sp. BM-8, an actinobacterial strain isolated from the feces of Equus quagga. The structures of these compounds were established by analyses of spectroscopic data, including 1D and 2D nuclear magnetic resonance spectra (NMR), as well as by HR-ESI-MS spectrometry and chemical derivative analyses. Additionally, a serial analogue of nonactic acid and homononacticacid (8–21) was synthesized. The cytotoxicity of 1–21 wastested against a panel of cancer cell lines, such as HT-29, MCF-7, A375 and K562, with MTT assay. In addition, the cytotoxicity tests revealed that 1 was less cytotoxic toward a panel of cancerous cells, as compared with valinomycin (6). [ABSTRACT FROM AUTHOR]

Object localization is an important application of remote sensing images and the basis of information extraction. The acquired accuracy is the key factor to improve the accuracy of object structure information inversion. The floating roof oil tank is a typical cylindrical artificial object, and its top cover fluctuates up and down with the change in oil storage. Taking the oil tank as an example, this study explores the localization by combining the traditional feature parameter method and convolutional neural networks (CNNs). In this study, an improved fast radial symmetry transform (FRST) algorithm called fast gradient modulus radial symmetry transform (FGMRST) is proposed and an approach based on FGMRST combined with CNN is proposed. It effectively adds the priori of circle features to the calculation process. Compared with only using CNN, it achieves higher precision localization with fewer network layers. The experimental results based on SkySat data show that the method can effectively improve the calculation accuracy and efficiency of the same order of magnitude network, and by increasing the network depth, the accuracy still has a significant improvement. [ABSTRACT FROM AUTHOR]

Polarimetric Interferometric Synthetic Aperture Radar (PolInSAR) can improve interferometric coherence and phase quality, which has good application potential. With the development of the Mini-SAR system, Unmanned Aerial Vehicle borne (UAV-borne) PolInSAR systems became a reality. However, UAV-borne PolInSAR is easily affected by air currents and other factors, which may cause large motion errors and polarization distortion inevitably exists. However, there are few pieces of research which are about motion compensation residual error (MCRE) and polarization distortion effects on PolInSAR. Though the effects of MCRE on Interferometric SAR (InSAR) and polarization distortion on PolInSAR were studied, respectively, these two parts are independently modeled and analyzed. In this paper, a model that simultaneously considers the effects of these two kinds of errors is proposed, and simulation results are given to validate the model. Then, a quantitative analysis based on a real Quadcopter UAV PolInSAR system is performed according to the model, which is valuable for system design and practical application of the UAV-borne PolInSAR system. [ABSTRACT FROM AUTHOR]

Senecavirus A (SVA), formerly known as Seneca Valley virus (SVV), causes vesicular symptoms in adult pigs and acute death of neonatal piglets. This pathogen has emerged in major swine producing countries around the world and caused significant economic losses to the pig industry. Thus, it is necessary to develop strategies to prevent and control SVA infection. Herein, an SVA strain (named GD-ZYY02-2018) was isolated from a pig herd with vesicular symptoms in Guangdong province of China in 2018. The present study aimed to carry out the phylogenetic analysis of the GD-ZYY02-2018 strain, determine its pathogenicity in finishing pigs, and assess the protective efficacy of the inactivated GD-ZYY02-2018 strain against virus challenge. The results of phylogenetic analysis showed that the SVA GD-ZYY02-2018 strain belonged to the USA-like strains and had a close genetic relationship with recent Chinese SVA strains. Animal challenge experiment showed that 100-day-old pigs inoculated intranasally with SVA GD-ZYY02-2018 strain developed vesicular lesion, low fever, viremia, and virus shedding in feces. The immunization challenge experiment showed that pigs vaccinated with inactivated GD-ZYY02-2018 strain could produce a high titer of anti-SVA neutralizing antibody and no vesicular lesion, fever, viremia, and virus shedding in feces was observed in vaccinated pigs after challenge with GD-ZYY02-2018 strain, indicating that inactivated GD-ZYY02-2018 could protect finishing pigs against the challenge of homologous virus. In conclusion, preliminary results indicated that inactivated GD-ZYY02-2018 could be used as a candidate vaccine for in-depth research and might be conducive to the prevention and control of SVA infection. [ABSTRACT FROM AUTHOR]

Lossy compression is widely used to decrease the size of multichannel remote sensing data. Alongside this positive effect, lossy compression may lead to a negative outcome as making worse image classification. Thus, if possible, lossy compression should be carried out carefully, controlling the quality of compressed images. In this paper, a dependence between classification accuracy of maximum likelihood and neural network classifiers applied to three-channel test and real-life images and quality of compressed images characterized by standard and visual quality metrics is studied. The following is demonstrated. First, a classification accuracy starts to decrease faster when image quality due to compression ratio increasing reaches a distortion visibility threshold. Second, the classes with a wider distribution of features start to "take pixels" from classes with narrower distributions of features. Third, a classification accuracy might depend essentially on the training methodology, i.e., whether features are determined from original data or compressed images. Finally, the drawbacks of pixel-wise classification are shown and some recommendations on how to improve classification accuracy are given. [ABSTRACT FROM AUTHOR]

Correction: Xixi, Li., et al. The Plastidial Glyceraldehyde-3-Phosphate Dehydrogenase Is Critical for Abiotic Stress Response in Wheat. Int. J. Mol. [Extracted from the article]

To create an intelligent surface region of interests (ROI) 3D quantitative inspection strategy a reality in the continuous casting (CC) production line, an improved 3D laser image scanning system (3D-LDS) was established based on binocular imaging and deep-learning techniques. In 3D-LDS, firstly, to meet the requirements of the industrial application, the CCD laser image scanning method was optimized in high-temperature experiments and secondly, we proposed a novel region proposal method based on 3D ROI initial depth location for effectively suppressing redundant candidate bounding boxes generated by pseudo-defects in a real-time inspection process. Thirdly, a novel two-step defects inspection strategy was presented by devising a fusion deep CNN model which combined fully connected networks (for defects classification/recognition) and fully convolutional networks (for defects delineation). The 3D-LDS' dichotomous inspection method of defects classification and delineation processes are helpful in understanding and addressing challenges for defects inspection in CC product surfaces. The applicability of the presented methods is mainly tied to the surface quality inspection for slab, strip and billet products. [ABSTRACT FROM AUTHOR]

The structural stability, electronic structures, mechanical properties and Debye temperature of W-TM (TM = Cr, Cu, Fe, Mn, Mo and Ni, respectively) alloys have been investigated by first principles method. The lattice constant, cell volume, formation energy and cohesive energy of W-TM alloys are calculated. W-TM alloys still maintain bcc lattice, and have no structural phase transformation. It is shown that W-Mo and W-Mn alloys have better alloying ability with strong interactions between W and Mo/Mn atoms. However, the alloying ability of W-Cu, W-Fe, W-Cr and W-Ni is poor, and there is a weak chemical interaction between W and Cu/Cr/Fe/Ni atoms. Using the optimized lattice, the elastic constants are calculated, and the elastic moduli and other mechanical parameters are derived. Results show that the mechanical strength of W-TM alloys is lower than that of pure W, especially W-Cu and W-Ni alloys. However, the B/G ratio and Poisson's ratio of W-TM alloys are higher than that of pure W, indicating that TM alloying can significantly improve the ductility of pure W. The metallicity of pure W can be enhanced by doping Fe or Mn, while doping Cr, Cu, Mo and Ni reduces the metallicity of pure W, of which W-Cu alloy has worst metallicity. [ABSTRACT FROM AUTHOR]

Plastidial glyceraldehyde-3-phosphate dehydrogenase (GAPDH, GAPCp) are ubiquitous proteins that play pivotal roles in plant metabolism and are involved in stress response. However, the mechanism of GAPCp's function in plant stress resistance process remains unclear. Here we isolated, identified, and characterized the TaGAPCp1 gene from Chinese Spring wheat for further investigation. Subcellular localization assay indicated that the TaGAPCp1 protein was localized in the plastid of tobacco (Nicotiana tobacum) protoplast. In addition, quantitative real-time PCR (qRT-PCR) unraveled that the expression of TaGAPCp1 (GenBank: MF477938.1) was evidently induced by osmotic stress and abscisic acid (ABA). This experiment also screened its interaction protein, cytochrome b6-f complex iron sulfite subunit (Cyt b6f), from the wheat cDNA library using TaGAPCp1 protein as a bait via the yeast two-hybrid system (Y2H) and the interaction between Cyt b6f and TaGAPCp1 was verified by bimolecular fluorescence complementation assay (BiFC). Moreover, H2O2 could also be used as a signal molecule to participate in the process of Cyt b6f response to abiotic stress. Subsequently, we found that the chlorophyll content in OE-TaGAPCp1 plants was significantly higher than that in wild type (WT) plants. In conclusion, our data revealed that TaGAPCp1 plays an important role in abiotic stress response in wheat and this stress resistance process may be completed by H2O2-mediated ABA signaling pathway. [ABSTRACT FROM AUTHOR]