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It is important to quickly strengthen and repair earthquake-damaged buildings to restore the normal life after earthquake. Therefore, it is necessary to study the seismic performance of widely-used assembled buildings repaired with different approaches. In this paper, two different methods are designed to repair seismically damaged shear walls assembled with grouted sleeves. Based on different damage scenarios, the first method uses high-strength grout to replace damaged concrete, and the second method uses grout jacketing with reinforcement implantation and reinforcing mesh to enhance the damaged cross-section. The repaired walls are compared with the original walls on the damage mode, bearing capacity, ductility, energy dissipation capacity, and stiffness degradation. The test results verify that both repair methods can restore the load-bearing capacity of the assembled shear walls. Further, the seismic performance of the two repaired seismic-damaged shear walls with different axial pressure ratios is analyzed using finite element analysis. The seismic loss indices of the original assembled and the repaired shear walls are calculated using the Park-Ang two-parameter seismic damage model based on the results of the experimental studies and the finite element analysis.

The microbiota–gut–brain axis denotes a two-way system of interactions between the gut and the brain, comprising three key components: (1) gut microbiota, (2) intermediates and (3) mental ailments. These constituents communicate with one another to induce changes in the host's mood, cognition and demeanor. Knowledge concerning the regulation of the host central nervous system by gut microbiota is fragmented and mostly confined to disorganized or semi-structured unrestricted texts. Such a format hinders the exploration and comprehension of unknown territories or the further advancement of artificial intelligence systems. Hence, we collated crucial information by scrutinizing an extensive body of literature, amalgamated the extant knowledge of the microbiota–gut–brain axis and depicted it in the form of a knowledge graph named MMiKG, which can be visualized on the GraphXR platform and the Neo4j database, correspondingly. By merging various associated resources and deducing prospective connections between gut microbiota and the central nervous system through MMiKG, users can acquire a more comprehensive perception of the pathogenesis of mental disorders and generate novel insights for advancing therapeutic measures. As a free and open-source platform, MMiKG can be accessed at http://yangbiolab.cn:8501/ with no login requirement. [ABSTRACT FROM AUTHOR]

In order to solve the poor matching ability between concrete structures of traditional architectural space optimization design methods, it leads to the problem of low space optimization ratio, so based on virtual reality technology, the author proposes a new method for optimizing the space of concrete structure buildings. Using virtual reality technology to improve the basic structure of building space, reorganize the form through the design space, and optimize the design of the concrete structure building space function; based on the test model of virtual reality technology, design the matching method of concrete structure, increase the proportion of building space optimization, and adopt linear buckling method, geometric nonlinear method, and double nonlinear analysis method; the ultimate bearing capacity of steel structures of residential buildings in earthquake areas is tested. Experimental results show that for the simple structure building space, the average optimization ratios are 97.17% and 96.71%, respectively; for the complex structure building space, under the proposed optimization design, the average optimization ratio is maintained at 94.34%, and the error between the stress prediction value of the finite element model and the axial stress obtained by testing is less than 6%. Compared with the traditional space optimization design, in the proposed space optimization design method, the proportion of building space optimization is higher; it can be seen that the virtual reality technology has a better matching effect on the concrete structure, and the accuracy of the ultimate bearing capacity value obtained by prediction is high. [ABSTRACT FROM AUTHOR]

Under seismic loading, the coupling beam not only connects the wall stems together, but also plays a role in energy dissipation and shock absorption. On the basis of a literature review, this paper presents a new type of prefabricated concrete arch coupling beam with steel connectors. The structure of the prefabricated beam and its connection with the wall stems are introduced. The seismic performance of the beam-wall joint is analyzed through experimental research and finite element analysis. The results show that the arch beam effectively improves the shear bearing capacity of the beam-wall connection, thus improves the overall seismic performance of the coupled wall structures. This research provides a useful reference for developing design codes for prefabricated coupling beams. [ABSTRACT FROM AUTHOR]

Post-translational modifications (PTMs) play significant roles in regulating protein structure, activity and function, and they are closely involved in various pathologies. Therefore, the identification of associated PTMs is the foundation of in-depth research on related biological mechanisms, disease treatments and drug design. Due to the high cost and time consumption of high-throughput sequencing techniques, developing machine learning-based predictors has been considered an effective approach to rapidly recognize potential modified sites. However, the imbalanced distribution of true and false PTM sites, namely, the data imbalance problem, largely effects the reliability and application of prediction tools. In this article, we conduct a systematic survey of the research progress in the imbalanced PTMs classification. First, we describe the modeling process in detail and outline useful data imbalance solutions. Then, we summarize the recently proposed bioinformatics tools based on imbalanced PTM data and simultaneously build a convenient website, ImClassi_PTMs (available at lab.malab.cn/∼dlj/ImbClassi_PTMs/), to facilitate the researchers to view. Moreover, we analyze the challenges of current computational predictors and propose some suggestions to improve the efficiency of imbalance learning. We hope that this work will provide comprehensive knowledge of imbalanced PTM recognition and contribute to advanced predictors in the future. [ABSTRACT FROM AUTHOR]

The paper investigates the behavior of glass‐fiber reinforced polymer (GFRP) reinforced concrete columns with integrated steel spirals (hybrid reinforcement). Six concrete columns were tested under eccentric axial loading, resulting in failure due to bending. Columns with outer steel longitudinal bars experienced steel yielding at peak loads, while those with GFRP outer rebars failed due to concrete crushing. The results revealed that using GFRP as outer longitudinal bars led to peak loads 3–10% lower compared to columns with steel rebars. Inner confinement by steel spirals increased the load‐carrying capacity. Additionally, columns with inner tubular steel exhibited greater strength than those with steel spirals, indicating a slightly enhanced confinement effect. A finite element model was developed to analyze structural behavior, considering both material and geometric nonlinearity. The model's accuracy was validated by comparing predictions with test results. Parametric analysis from the nonlinear FE model showed that eccentricity significantly impacted column load‐carrying capacity. Increasing inner confinement area and the number of inner longitudinal bars improved structural stiffness and load‐carrying capacity. Furthermore, a simplified theoretical method was proposed. Comparison between experimental failure loads and theoretical predictions revealed differences within 20%, indicating satisfactory reliability of the proposed method. [ABSTRACT FROM AUTHOR]

Cathode material Li [Li0.2Ni0.2Co0.08Mn0.52−xCux]O2 (x = 0, 0.01, 0.03, 0.05, 0.07) has been synthesized via carbonate coprecipitation method and modified by Cu2+ which was introduced at different stages. The crystal structure features, morphology, and electrochemical properties of the powders are studied in detail using X-ray diffraction spectroscopy, scanning electron microscopy, EDS spectroscopy, and electrochemical measurements. The experimental results show that the electrochemical properties of Li [Li0.2Ni0.2Co0.08Mn0.52−xCux]O2 (x = 0, 0.01, 0.03, 0.05, 0.07) oxides are improved. This is because an appropriate amount of Cu2+ doping increases the lattice spacing of the layered material, reduces the agglomeration of the particles, and improves the uniformity of the particles. Especially in the coprecipitation stage, Cu2+ was introduced and x = 3% showed better rate and cycle performance. The specific discharge capacity at 1C and 2C was 197.28 mAhg−1 and 124.92 mAhg−1, respectively, and cycle returned to 0.1C capacity after 45 cycles, the discharge specific capacity is still up to 261.5 mAhg−1. [ABSTRACT FROM AUTHOR]

In this paper, LiMn1−xMgxPO4·Li3V2(PO4)3/C (x = 0, 0.01, 0.02, 0.03, 0.04, 0.05, 0.06, 0.07, 0.10) and LiMnPO4·Li3V2−yAly(PO4)3/C (y = 0.01, 0.02, 0.03, 0.05, 0.07, 0.10) composite cathode materials for lithium-ion batteries were successfully synthesized by a simple sol-gel method and modified by Mg2+ doped and Al3+ doped. The effects of Mg2+ and Al3+ doping on the microstructure and electrochemical properties of LiMnPO4·Li3V2(PO4)3/C were characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), EDAS energy spectrum analysis (EDS), constant current charge/discharge electrical test, cyclic voltammetry, and electrochemical impedance spectroscopy (EIS). The analysis shows that the electrochemical properties of samples have been greatly improved. The results show that when x = 0.06 and y = 0.02, the material has the best electrochemical performance. Under the voltage range of 2.5–4.5 V, the initial discharge specific capacity at 0.1 C (1 C = 143 mAh g−1) is as high as 148.2 mAh g−1 and 134.4 mAh g−1, respectively. [ABSTRACT FROM AUTHOR]

The samples of xLi3V2(PO4)3·yLiFe0.8Mn0.2PO4/C (x:y = 1:0, 3:1, 1:1, 1:2, 0:1) are facilely prepared via a ball milling-assisted two-step sintering route. According to the results of Rietveld refinement, the xLi3V2(PO4)3·yLiFe0.8Mn0.2PO4/C (x, y ≠ 0) composites are composed of orthorhombic LiFe0.8Mn0.2PO4 and monoclinic L3V2(PO4)3. Electrochemical tests show that the faster reaction kinetics improve the electrochemical properties of the xLi3V2(PO4)3·yLiFe0.8Mn0.2PO4/C (x, y ≠ 0) composites, in which all multiphase composites release more than capacity of 100 mAh g−1 at 2C at the potential range of 2.5-4.5 V. In particular, the diffusion coefficient of lithium ion is in the magnitude of 10−7 to 10−9 cm2 s−1; Li3V2(PO4)3·2LiFe0.8Mn0.2PO4/C shows the highest specific capacity at the rate range of 0.1-2C and exhibits excellent long-term rate performance with capacity retention of 93.4% (relative to the initial discharge capacity) after 280 cycles at the rate of 5C. [ABSTRACT FROM AUTHOR]

Summary Integrative analysis of single-cell RNA-sequencing (scRNA-seq) data with spatial data for the same species and organ would provide each cell sample with a predictive spatial location, which would facilitate biological study. However, publicly available spatial sequencing datasets for specific species and organs are rare and are often displayed in different formats. In this study, we introduce a new web-based scRNA-seq analysis tool, webSCST, that integrates well-organized spatial transcriptome sequencing datasets categorized by species and organs, provides a user-friendly interface for raw single-cell processing with popular integration methods and allows users to submit their raw scRNA-seq data once to obtain predicted spatial locations for each cell type. Availability and implementation webSCST implemented in shiny with all major browsers supported is available at http://www.webscst.com. webSCST is also freely available as an R package at https://github.com/swsoyee/webSCST. [ABSTRACT FROM AUTHOR]

Hot compression of TC8M-1 was carried out under isothermal working conditions with temperature from 1173 K to 1323 K (900 °C to 1050 °C), strain rate from 0.001 to 10/s, and height reduction from 20 to 80 pct (corresponding true strain from 0.22 to 1.61). Constitutive equations were constructed and apparent activation energies of 149.5 and 617.4 kJ/mol were obtained for deformation in the β and upper α/ β phase regions, respectively. Microstructure examination confirmed the dominant role of dynamic recrystallization in the α/ β phase region and that of dynamic recovery in the β phase region, with the occurrence of grain boundary sliding at very low strain rate (0.001/s) in both regions. Based on the dynamic materials model, processing maps were constructed, providing optimal domains for hot working at the temperature of 1253 K (980 °C) and the strain rate of 0.01 to 0.1/s, or at 1193 K to 1213 K (920 °C to 940 °C) and 0.001/s. Moreover, our results indicated that the initial temperature non-uniformity along the specimen axis before compression existed and influenced the strain distribution, which contributed to the abnormal oscillations and/or abrupt rise-up of true stress and inhomogeneous deformation. [ABSTRACT FROM AUTHOR]

Populus deltoides is a fast-growing, large tree and one of the largest North American hardwood trees. In this study, the complete chloroplast (cp) genome sequence of P. deltoides is characterized. The whole cp genome was assembled to 156,867 bp, including a large single copy (LSC) region of 85,534 bp, a small single copy (SSC) region of 16,513 bp and a pair of inverted repeats (IRs) region of 27,410 bp. The base content of the P. deltoides cp genome is A (32.0%), T (31.3%), C (18.0%), and G (18.7%), and AT bases occupy a large proportion of the cp genome. The neighbor-joining phylogenetic analysis with 20 cp genomes from the Salicaceae family showed that P. deltoides is sister to Populus davidiana. These will provide for the evolutionary and biological studies in Salicaceae family. [ABSTRACT FROM AUTHOR]

Salix triandra is a great willow for bees and an excellent choice for living willow structures. In this study, we assembled and annotated the complete chloroplast (cp) genome sequence of S. triandra. The whole cp genome is 155,821 base-pairs (bp) in size, which comprises one small single copy (SSC) region of 16,223 bp and one large single copy (LSC) region of 84,532 bp separated by a pair of inverted repeats (IRs) of 27,533 bp. There are 131 genes, including 86 protein-coding genes, 37 tRNA genes, and 8 rRNA genes. Phylogenetic analysis with the Neighbour-joining method indicates that S. triandra is closely related to S. tetrasperma. The complete cp genome will facilitate the biological studies in the order Malpighiales in future. [ABSTRACT FROM AUTHOR]

In recent years, the application of single-cell transcriptomics and spatial transcriptomics analysis techniques has become increasingly widespread. Whether dealing with single-cell transcriptomic or spatial transcriptomic data, dimensionality reduction and clustering are indispensable. Both single-cell and spatial transcriptomic data are often high-dimensional, making the analysis and visualization of such data challenging. Through dimensionality reduction, it becomes possible to visualize the data in a lower-dimensional space, allowing for the observation of relationships and differences between cell subpopulations. Clustering enables the grouping of similar cells into the same cluster, aiding in the identification of distinct cell subpopulations and revealing cellular diversity, providing guidance for downstream analyses. In this review, we systematically summarized the most widely recognized algorithms employed for the dimensionality reduction and clustering analysis of single-cell transcriptomic and spatial transcriptomic data. This endeavor provides valuable insights and ideas that can contribute to the development of novel tools in this rapidly evolving field., (© The Author(s) 2024. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)

Depression is one of the most prevalent mental disorders today. Over the past decade, there has been considerable attention given to the field of gut microbiota associated with depression. A substantial body of research indicates a bidirectional communication pathway between gut microbiota and the brain. In this review, we extensively detail the correlation between gut microbiota, including Lactobacillus acidophilus and Bifidobacterium longum , and metabolites such as short-chain fatty acids (SCFAs) and 5-hydroxytryptamine (5-HT) concerning depression. Furthermore, we delve into the potential health benefits of microbiome-targeted therapies, encompassing probiotics, prebiotics, and synbiotics, in alleviating depression. Lastly, we underscore the importance of employing a constraint-based modeling framework in the era of systems medicine to contextualize metabolomic measurements and integrate multi-omics data. This approach can offer valuable insights into the complex metabolic host-microbiota interactions, enabling personalized recommendations for potential biomarkers, novel drugs, and treatments for depression., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2024 Wang, Song, Lai, Tang, Dou and Yang.)

Alzheimer's disease (AD) is a severe neurodegenerative disease with slow course of onset and deterioration with time. With the speedup of global aging, AD has become a disease that seriously threatens the physical health of the elderly; therefore, the effective prevention and treatments of AD is an extremely important area of study for researchers and clinicians. Rapid technological developments have promoted the analysis of various kinds of complex data sets using machine learning methods. The common machine learning algorithms, such as Lasso, SVM and Random Forest, are very important in AD research. To help accelerate AD-related research, we review some recent research progress on Alzheimer's disease, including database, image analysis, gene expression, etc., which can provide AD researchers with more comprehensive research methods., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

As a kind of novel non-invasive marker for molecular detection, cell-free DNA (cfDNA) has potential value for the early diagnosis of diseases, prognosis assessment, and efficacy monitoring. The constant developments in molecular biology detection technologies have led to an increase in clinical studies on the use of cfDNA detection methods for patients, and many gratifying outcomes have been achieved. In this review, the contributions of bioinformatics tools to the study of cfDNA are well discussed. The focus of the review is on cfDNA identification signals, cfDNA identification methods, and the relationship of cfDNA with human diseases such as hepatic cancer, lung cancer, end-stage kidney disease, and ischemic stroke. The research significance and existing problems of using cfDNA as a biomarker for diseases are also discussed., (Copyright © 2022 Elsevier Ltd. All rights reserved.)

5-Methylcytosine (m5C) is a well-known post-transcriptional modification that plays significant roles in biological processes, such as RNA metabolism, tRNA recognition, and stress responses. Traditional high-throughput techniques on identification of m5C sites are usually time consuming and expensive. In addition, the number of RNA sequences shows explosive growth in the post-genomic era. Thus, machine-learning-based methods are urgently requested to quickly predict RNA m5C modifications with high accuracy. Here, we propose a noval support-vector-machine (SVM)-based tool, called iRNA-m5C_SVM, by combining multiple sequence features to identify m5C sites in Arabidopsis thaliana. Eight kinds of popular feature-extraction methods were first investigated systematically. Then, four well-performing features were incorporated to construct a comprehensive model, including position-specific propensity (PSP) (PSNP, PSDP, and PSTP, associated with frequencies of nucleotides, dinucleotides, and trinucleotides, respectively), nucleotide composition (nucleic acid, di-nucleotide, and tri-nucleotide compositions; NAC, DNC, and TNC, respectively), electron-ion interaction pseudopotentials of trinucleotide (PseEIIPs), and general parallel correlation pseudo-dinucleotide composition (PC-PseDNC-general). Evaluated accuracies over 10-fold cross-validation and independent tests achieved 73.06% and 80.15%, respectively, which showed the best predictive performances in A. thaliana among existing models. It is believed that the proposed model in this work can be a promising alternative for further research on m5C modification sites in plant., (Copyright © 2020 The Author(s). Published by Elsevier Inc. All rights reserved.)

Populus deltoides is a fast-growing, large tree and one of the largest North American hardwood trees. In this study, the complete chloroplast (cp) genome sequence of P. deltoides is characterized. The whole cp genome was assembled to 156,867 bp, including a large single copy (LSC) region of 85,534 bp, a small single copy (SSC) region of 16,513 bp and a pair of inverted repeats (IRs) region of 27,410 bp. The base content of the P. deltoides cp genome is A (32.0%), T (31.3%), C (18.0%), and G (18.7%), and AT bases occupy a large proportion of the cp genome. The neighbor-joining phylogenetic analysis with 20 cp genomes from the Salicaceae family showed that P. deltoides is sister to Populus davidiana . These will provide for the evolutionary and biological studies in Salicaceae family., Competing Interests: The authors report no conflicts of interest. The authors alone are responsible for the content and writing of the paper., (© 2019 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.)

Salix triandra is a great willow for bees and an excellent choice for living willow structures. In this study, we assembled and annotated the complete chloroplast (cp) genome sequence of S. triandra . The whole cp genome is 155,821 base-pairs (bp) in size, which comprises one small single copy (SSC) region of 16,223 bp and one large single copy (LSC) region of 84,532 bp separated by a pair of inverted repeats (IRs) of 27,533 bp. There are 131 genes, including 86 protein-coding genes, 37 tRNA genes, and 8 rRNA genes. Phylogenetic analysis with the Neighbour-joining method indicates that S. triandra is closely related to S. tetrasperma . The complete cp genome will facilitate the biological studies in the order Malpighiales in future., Competing Interests: The authors report no conflicts of interest. The authors alone are responsible for the content and writing of the paper., (© 2019 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group.)