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People readily identify interactions based on resource transfer, such as giving. In the present study, we examine whether adults bind two agents in an interactive unit even if one caused the other to gain a resource indirectly — i.e., as a side effect of pursuing another outcome. Across five behavioral and EEG experiments, we found convergent signatures of social binding (change sensitivity and alpha-band suppression) when adults were presented with an action resulting in the collateral gain of a resource for a passive agent. No binding was observed when the action caused the collateral loss of the agent's pre-existing possession, revealing an asymmetry in how gains and losses are perceived to affect agents. Together, these findings suggest that adults interpret actions resulting in the provision of material gains as interactive, even when these are indirectly brought about.

Recent evidence suggests that infants interpret giving as indicative of a relationship based on reciprocal exchange. Monitoring such a relationship requires tracking its participants irrespective of the role they occupy in a given interaction, as these are assumed to alternate over time. We explored this hypothesis in a label-mapping paradigm by testing whether 14-month-olds interpreted a trained label as referring to the features of an agent pointed at (a stable identity-tagging information) or to the action role it carried out (a temporary information). Across four eye-tracking experiments, infants consistently mapped the trained label onto the agent's features, when the agent gave a resource to someone. Superficial similar actions not resulting in social transfer (i.e., disposing of an object) did not induce such mapping. These findings suggest that the observation of giving highlighted identity-preserving information over transitory action roles, possibly due to the relational assumptions this action engendered.

In the pursuit of novel catalyst development to address pressing environmental concerns and energy demand, conventional design and optimization methods often fall short due to the complexity and vastness of the catalyst parameter space. The advent of Machine Learning (ML) has ushered in a new era in the field of catalyst optimization, offering potential solutions to the shortcomings of traditional techniques. However, existing methods fail to effectively harness the wealth of information contained within the burgeoning body of scientific literature on catalyst synthesis. To address this gap, this study proposes an innovative Artificial Intelligence (AI) workflow that integrates Large Language Models (LLMs), Bayesian optimization, and an active learning loop to expedite and enhance catalyst optimization. Our methodology combines advanced language understanding with robust optimization strategies, effectively translating knowledge extracted from diverse literature into actionable parameters for practical experimentation and optimization. In this article, we demonstrate the application of this AI workflow in the optimization of catalyst synthesis for ammonia production. The results underscore the workflow's ability to streamline the catalyst development process, offering a swift, resource-efficient, and high-precision alternative to conventional methods., Comment: 31 pages, 7 figures

Graph Neural Networks (GNNs) have achieved notable success in various applications over graph data. However, recent research has revealed that real-world graphs often contain noise, and GNNs are susceptible to noise in the graph. To address this issue, several Graph Structure Learning (GSL) models have been introduced. While GSL models are tailored to enhance robustness against edge noise through edge reconstruction, a significant limitation surfaces: their high reliance on node features. This inherent dependence amplifies their susceptibility to noise within node features. Recognizing this vulnerability, we present DEGNN, a novel GNN model designed to adeptly mitigate noise in both edges and node features. The core idea of DEGNN is to design two separate experts: an edge expert and a node feature expert. These experts utilize self-supervised learning techniques to produce modified edges and node features. Leveraging these modified representations, DEGNN subsequently addresses downstream tasks, ensuring robustness against noise present in both edges and node features of real-world graphs. Notably, the modification process can be trained end-to-end, empowering DEGNN to adjust dynamically and achieves optimal edge and node representations for specific tasks. Comprehensive experiments demonstrate DEGNN's efficacy in managing noise, both in original real-world graphs and in graphs with synthetic noise., Comment: PAKDD 2024, the code is available at https://github.com/TaiHasegawa/DEGNN

Exemplar-Free Class Incremental Learning is a highly challenging setting where replay memory is unavailable. Methods relying on frozen feature extractors have drawn attention recently in this setting due to their impressive performances and lower computational costs. However, those methods are highly dependent on the data used to train the feature extractor and may struggle when an insufficient amount of classes are available during the first incremental step. To overcome this limitation, we propose to use a pre-trained text-to-image diffusion model in order to generate synthetic images of future classes and use them to train the feature extractor. Experiments on the standard benchmarks CIFAR100 and ImageNet-Subset demonstrate that our proposed method can be used to improve state-of-the-art methods for exemplar-free class incremental learning, especially in the most difficult settings where the first incremental step only contains few classes. Moreover, we show that using synthetic samples of future classes achieves higher performance than using real data from different classes, paving the way for better and less costly pre-training methods for incremental learning.

The solvation capacity of dispersion solvents plays a crucial role in the solution processing of metal halide perovskites. For instance, N,N-dimethylformamide (DMF), a widely used dispersion solvent, possesses high solvation capacity but often generates suboptimal film quality due to slow crystallization kinetics. We propose using low-solvation binary cosolvents (nitrile-and ether-type solvents) to achieve a balance between solvation (i.e., sufficient solubility of precursors) and desolvation (i.e., rapid crystallization of films) pro-cesses during perovskite synthesis. The polarity and hydrogen -bonding property of these cosolvents synergistically enhance their solvation capacity, facilitating perovskite precursor dissolution. Moreover, the low-solvation cosolvents accelerate the crystalliza-tion of well-defined intermediate films, yielding higher-quality pe-rovskites than those synthesized with DMF. The optimized modules achieved an active-area efficiency of 22.27%, with a certified aper-ture-area efficiency of 16.10% and corresponding active-area effi-ciency of 20.75%. This research on solvation regulation provides universal guidelines for innovatively preparing high-quality halide perovskites.

The metallicity enrichment history (MEH) of a galaxy is determined by its star formation history (SFH) and the gas cycling process. In this paper, we construct a chemical evolution model that is regulated by the SFH of the system. In this SFH-regulated model, the evolution of all other variables, including the MEH, can be determined by the SFH. We test this model on six locally isolated dwarf galaxies covering three dwarf types that were observed by the Local Cosmology from Isolated Dwarfs (LCID) project. The SFHs and MEHs of these LCID galaxies have been measured from the deep color-magnitude diagrams that are down to the main sequence turn-offs stars. With simple assumptions of the star formation law and the mass-dependent outflows, our SFH-regulated model successfully reproduces the MEHs of all six LCID galaxies from their SFHs, with only one free parameter, the wind efficiency $\eta \sim 1.0$, for all six galaxies. This model provides a physically motivated link that directly connects the SFH and MEH of a galaxy, which will be useful to accommodate into the state-of-the-art stellar population synthesis models to help relieve the nuisance of the heavy degeneracy between the ages and metallicities of the stellar populations., Comment: 18 pages, 5 figures, accepted for publication in ApJ

Self-rationalizing models that also generate a free-text explanation for their predicted labels are an important tool to build trustworthy AI applications. Since generating explanations for annotated labels is a laborious and costly pro cess, recent models rely on large pretrained language models (PLMs) as their backbone and few-shot learning. In this work we explore a self-training approach leveraging both labeled and unlabeled data to further improve few-shot models, under the assumption that neither human written rationales nor annotated task labels are available at scale. We introduce a novel dual-teacher learning framework, which learns two specialized teacher models for task prediction and rationalization using self-training and distills their knowledge into a multi-tasking student model that can jointly generate the task label and rationale. Furthermore, we formulate a new loss function, Masked Label Regularization (MLR) which promotes explanations to be strongly conditioned on predicted labels. Evaluation on three public datasets demonstrate that the proposed methods are effective in modeling task labels and generating faithful rationales., Comment: ACL Findings 2023

Vulnerability detection is a critical problem in software security and attracts growing attention both from academia and industry. Traditionally, software security is safeguarded by designated rule-based detectors that heavily rely on empirical expertise, requiring tremendous effort from software experts to generate rule repositories for large code corpus. Recent advances in deep learning, especially Graph Neural Networks (GNN), have uncovered the feasibility of automatic detection of a wide range of software vulnerabilities. However, prior learning-based works only break programs down into a sequence of word tokens for extracting contextual features of codes, or apply GNN largely on homogeneous graph representation (e.g., AST) without discerning complex types of underlying program entities (e.g., methods, variables). In this work, we are one of the first to explore heterogeneous graph representation in the form of Code Property Graph and adapt a well-known heterogeneous graph network with a dual-supervisor structure for the corresponding graph learning task. Using the prototype built, we have conducted extensive experiments on both synthetic datasets and real-world projects. Compared with the state-of-the-art baselines, the results demonstrate promising effectiveness in this research direction in terms of vulnerability detection performance (average F1 improvements over 10\% in real-world projects) and transferability from C/C++ to other programming languages (average F1 improvements over 11%).

Spectral-type subspace clustering algorithms have shown excellent performance in many subspace clustering applications. The existing spectral-type subspace clustering algorithms either focus on designing constraints for the reconstruction coefficient matrix or feature extraction methods for finding latent features of original data samples. In this paper, inspired by graph convolutional networks, we use the graph convolution technique to develop a feature extraction method and a coefficient matrix constraint simultaneously. And the graph-convolutional operator is updated iteratively and adaptively in our proposed algorithm. Hence, we call the proposed method adaptive graph convolutional subspace clustering (AGCSC). We claim that by using AGCSC, the aggregated feature representation of original data samples is suitable for subspace clustering, and the coefficient matrix could reveal the subspace structure of the original data set more faithfully. Finally, plenty of subspace clustering experiments prove our conclusions and show that AGCSC outperforms some related methods as well as some deep models., Comment: Accepted by CVPR 2023

The star-forming clumps in star-bursting dwarf galaxies provide valuable insights into the understanding of the evolution of dwarf galaxies. In this paper, we focus on five star-bursting dwarf galaxies featuring off-centered clumps in the Mapping Nearby Galaxies at Apache Point Observatory (MaNGA) survey. Using the stellar population synthesis software FADO, we obtain the spatially-resolved distribution of the star formation history, which allows us to construct the $g$-band images of the five galaxies at different ages. These images can help us to probe the evolution of the morphological structures of these galaxies. While images of stellar population older than 1 Gyr are typically smooth, images of stellar population younger than 1 Gyr reveal significant clumps, including multiple clumps which appear at different locations and even different ages. To study the evolutionary connections of these five galaxies to other dwarf galaxies before their star-forming clumps appear, we construct the images of the stellar populations older than three age nodes, and define them to be the images of the "host" galaxies. We find that the properties such as the central surface brightness and the effective radii of the hosts of the five galaxies are in between those of dwarf ellipticals (dEs) and dwarf irregulars (dIrrs), with two clearly more similar to dEs and one more similar to dIrrs. Among the five galaxies, 8257-3704 is particularly interesting, as it shows a previous starburst event that is not quite visible from its $gri$ image, but only visible from images of the stellar population at a few hundred million years. The star-forming clump associated with this event may have appeared at around 600 Myr and disappeared at around 40 Myr., Comment: 21 pages, 16 figures, accepted for publication in RAA

Text-attributed graphs (TAGs) are prevalent in various real-world scenarios, where each node is associated with a text description. The cornerstone of representation learning on TAGs lies in the seamless integration of textual semantics within individual nodes and the topological connections across nodes. Recent advancements in pre-trained language models (PLMs) and graph neural networks (GNNs) have facilitated effective learning on TAGs, garnering increased research interest. However, the absence of meaningful benchmark datasets and standardized evaluation procedures for TAGs has impeded progress in this field. In this paper, we propose CSTAG, a comprehensive and diverse collection of challenging benchmark datasets for TAGs. The CS-TAG datasets are notably large in scale and encompass a wide range of domains, spanning from citation networks to purchase graphs. In addition to building the datasets, we conduct extensive benchmark experiments over CS-TAG with various learning paradigms, including PLMs, GNNs, PLM-GNN co-training methods, and the proposed novel topological pre-training of language models. In a nutshell, we provide an overview of the CS-TAG datasets, standardized evaluation procedures, and present baseline experiments. The entire CS-TAG project is publicly accessible at https://github.com/sktsherlock/TAG-Benchmark.

The ability to detect macroscopic changes is important for probing the behaviors of experimental many-body systems from the classical to the quantum realm. Although abrupt changes near phase boundaries can easily be detected, subtle macroscopic changes are much more difficult to detect as the changes can be obscured by noise. In this study, as a toy model for detecting subtle macroscopic changes in many-body systems, we try to differentiate scalar field samples at varying temperatures. We compare different methods for making such differentiations, from physics method, statistics method, to AI method. Our finding suggests that the AI method outperforms both the statistical method and the physics method in its sensitivity. Our result provides a proof-of-concept that AI can potentially detect macroscopic changes in many-body systems that elude physical measures., Comment: 10 pages, 3 figures

Sleep stage classification is crucial for detecting patients' health conditions. Existing models, which mainly use Convolutional Neural Networks (CNN) for modelling Euclidean data and Graph Convolution Networks (GNN) for modelling non-Euclidean data, are unable to consider the heterogeneity and interactivity of multimodal data as well as the spatial-temporal correlation simultaneously, which hinders a further improvement of classification performance. In this paper, we propose a dynamic learning framework STHL, which introduces hypergraph to encode spatial-temporal data for sleep stage classification. Hypergraphs can construct multi-modal/multi-type data instead of using simple pairwise between two subjects. STHL creates spatial and temporal hyperedges separately to build node correlations, then it conducts type-specific hypergraph learning process to encode the attributes into the embedding space. Extensive experiments show that our proposed STHL outperforms the state-of-the-art models in sleep stage classification tasks.

Graph neural network (GNN) has gained increasing popularity in recent years owing to its capability and flexibility in modeling complex graph structure data. Among all graph learning methods, hypergraph learning is a technique for exploring the implicit higher-order correlations when training the embedding space of the graph. In this paper, we propose a hypergraph learning framework named LFH that is capable of dynamic hyperedge construction and attentive embedding update utilizing the heterogeneity attributes of the graph. Specifically, in our framework, the high-quality features are first generated by the pairwise fusion strategy that utilizes explicit graph structure information when generating initial node embedding. Afterwards, a hypergraph is constructed through the dynamic grouping of implicit hyperedges, followed by the type-specific hypergraph learning process. To evaluate the effectiveness of our proposed framework, we conduct comprehensive experiments on several popular datasets with eleven state-of-the-art models on both node classification and link prediction tasks, which fall into categories of homogeneous pairwise graph learning, heterogeneous pairwise graph learning, and hypergraph learning. The experiment results demonstrate a significant performance gain (average 12.5% in node classification and 13.3% in link prediction) compared with recent state-of-the-art methods.

Class-incremental learning aims to learn new classes in an incremental fashion without forgetting the previously learned ones. Several research works have shown how additional data can be used by incremental models to help mitigate catastrophic forgetting. In this work, following the recent breakthrough in text-to-image generative models and their wide distribution, we propose the use of a pretrained Stable Diffusion model as a source of additional data for class-incremental learning. Compared to competitive methods that rely on external, often unlabeled, datasets of real images, our approach can generate synthetic samples belonging to the same classes as the previously encountered images. This allows us to use those additional data samples not only in the distillation loss but also for replay in the classification loss. Experiments on the competitive benchmarks CIFAR100, ImageNet-Subset, and ImageNet demonstrate how this new approach can be used to further improve the performance of state-of-the-art methods for class-incremental learning on large scale datasets., Comment: Best paper award at 1st Workshop on Visual Continual Learning, ICCV 2023

Metabolism is vital to cellular function and tissue homeostasis during human lung development. In utero, embryonic pluripotent stem cells undergo endodermal differentiation toward a lung progenitor cell fate that can be mimicked in vitro using induced human pluripotent stem cells (hiPSCs) to study genetic mutations. To identify differences between wild-type and surfactant protein B (SFTPB)-deficient cell lines during endoderm specification toward lung, we used an untargeted metabolomics approach to evaluate the developmental changes in metabolites. We found that the metabolites most enriched during the differentiation from pluripotent stem cell to lung progenitor cell, regardless of cell line, were sphingomyelins and phosphatidylcholines, two important lipid classes in lung development. The SFTPB mutation had no metabolic impact on early endodermal lung development. The identified metabolite signatures during lung progenitor cell differentiation may be utilized as biomarkers for normal embryonic lung development.

Belle II is an experiment operating at the intensity frontier. Over the next decades, it will record the decay of billions of bottom mesons, charm hadrons, and tau leptons produced in 10 GeV electron-positron collisions at the SuperKEKB high-luminosity collider at KEK. These data, collected in low-background and kinematically known conditions, will allow us to measure hundreds of parameters that test the standard model (SM) and probe for the existence of new particles, at mass scales orders of magnitudes higher than those studied at the energy frontier. We project our sensitivities for measurements that are of primary relevance and where Belle II will be unique or world leading for data corresponding to 1 to 50 ab-1. Belle II will uniquely probe non-SM contributions in sensitive b -> qqbar s decays and charmless b -> qqbar d(u) decays, semileptonic b -> s nu nubar and s tau+ \tau- decays, fully leptonic b -> ell nu decays, and select c -> u processes. Belle II will lead exploration of non-SM physics in b -> c tau nu and b -> s gamma decays and will most precisely determine the quark-mixing parameters |Vub| and |Vcb|. Belle II will measure many parameters in tau physics to precisions that will be world leading for the foreseeable future, including the electric and magnetic dipole moments, branching fractions for charged-lepton-flavor-violating decays, and quantities that test lepton-flavor universality. Belle II will perform unique searches for dark-sector particles with masses in the MeV--GeV range. We will also pursue a broad spectroscopy program for conventional and multiquark c cbar and b bbar states and provide essential inputs to sharpen the interpretation of muon magnetic-anomaly results. Our exploration of uncharted regions of non-SM parameter space with high precision will reveal non-SM particles or set stringent constraints on their existence, guiding future endeavors., Comment: 48 pages, 15 figures. The document has been confidentially distributed to Snowmass conveners since March 2022, but only now is distributed on arxiv due to Belle II collaboration authorship restrictions following the Ukraine situation

Increased wealth and per capita energy use have transformed lives and shaped societies, but energy poverty remains a global challenge. Previous research has shown positive relationships among metrics of health and happiness and economic indices such as income and gross domestic product and between energy use and human development. To our knowledge, however, no comprehensive assessment has examined to what extent energy use may limit national-level trends in such metrics. We analyze the maximum global performance of nine health, economic, and environmental metrics by country, determining which metrics increase with per capita energy use and which show thresholds or plateaus in maximum performance. Across the dataset, eight of nine metrics, including life expectancy, infant mortality, happiness, food supply, and access to basic sanitation services, improve steeply and then plateau at levels of average primary annual energy consumption between 10 and 75 GJ person−1 computed nationally (five metrics plateau between 10 and 30 GJ person−1). One notable exception is air quality (energy threshold of 125 GJ person−1 across 133 countries). Averaged across metrics, the 10 countries (with at least seven metrics) showing the best performance given their per capita primary energy use are Malta, Sri Lanka, Cuba, Albania, Iceland, Finland, Bangladesh, Norway, Morocco, and Denmark. If distributed equitably, today's average global energy consumption of 79 GJ person−1 could, in principle, allow everyone on Earth to realize 95% or more of maximum performance across all metrics (and assuming no other limiting factors). Dozens of countries have average per capita energy use below this 79 GJ energy sufficiency threshold, highlighting the need to combat energy poverty. Surprisingly, our analysis also suggests that reduced per capita primary energy consumption could in principle occur in many higher energy-consuming countries with little or no loss in health, happiness, or other outcomes, r

Research on solvent chemistry, particularly for halide perovskite intermediates, has been advancing the development of perovskite solar cells (PSCs) toward commercial applications. A predictive understanding of solvent effects on the perovskite formation is thus essential. This work systematically discloses the relationship among the basicity of solvents, solvent-contained intermediate structures, and intermediate-to-perovskite alpha-FAPbI(3) evolutions. Depending on their basicity, solvents exhibit their own favorite bonding selection with FA(+) or Pb2+ cations by forming either hydrogen bonds or coordination bonds, resulting in two different kinds of intermediate structures. While both intermediates can be evolved into alpha-FAPbI(3) below the delta-to-alpha thermodynamic temperature, the hydrogen-bond-favorable kind could form defect-less alpha-FAPbI(3) via sidestepping the break of strong coordination bonds. The disclosed solvent gaming mechanism guides the solvent selection for fabricating high-quality perovskite films and thus high-performance PSCs and modules.

INTRODUCTION: Genomic alterations in the juxtamembrane exon 14 splice sites in NSCLC lead to increased MET stability and oncogenesis. We present the largest cohort study of MET Exon 14 (METex14) using whole transcriptome sequencing. METHODS: A total of 21,582 NSCLC tumor samples underwent complete genomic profiling with next-generation sequencing of DNA (592 Gene Panel, NextSeq, whole exome sequencing, NovaSeq) and RNA (NovaSeq, whole transcriptome sequencing). Clinicopathologic information including programmed death-ligand 1 and tumor mutational burden were collected and RNA expression for mutation subtypes and MET amplification were quantified. Immunogenic signatures and potential pathways of invasion were characterized using single-sample gene set enrichment analysis and mRNA gene signatures. RESULTS: A total of 533tumors (2.47%) with METex14 were identified. The most common alterations were point mutations (49.5%) at donor splice sites. Most alterations translated to increased MET expression, with MET co-amplification resulting in synergistic increase in expression (q < 0.05). Common coalterations were amplifications of MDM2 (19.0% versus 1.8% wild-type [WT]), HMGA2 (13.2% versus 0.98% WT), and CDK4 (10.0% versus 1.5% WT) (q < 0.05). High programmed death-ligand 1 > 50% (52.5% versus 27.3% WT, q < 0.0001) and lower proportion of high tumor mutational burden (>10 mutations per megabase, 8.3% versus 36.7% WT, p < 0.0001) were associated with METex14, which were also enriched in both immunogenic signatures and immunosuppressive checkpoints. Pathways associated with METex14 included angiogenesis and apical junction pathways (q < 0.05). CONCLUSIONS: METex14 splicing alterations and MET co-amplification translated to higher and synergistic MET expression at the transcriptomic level. High frequencies of MDM2 and CDK4 co-amplifications and association with multiple immunosuppressive checkpoints and angiogenic pathways provide insight into

Liqi Zhu,1,2 Zhihao Wu,1,2 Chen Zhu,1,2 Jun Yin,1,2 Yuzheng Huang,3,4 Jie Feng,5 Quan Zhang1,2 1Institute of Comparative Medicine, College of Veterinary Medicine, Yangzhou University, Yangzhou, Jiangsu, 225009, People’s Republic of China; 2Jiangsu Co-Innovation Center for Prevention and Control of Important Animal Infectious Diseases and Zoonoses, Yangzhou University, Yangzhou, Jiangsu, 225009, People’s Republic of China; 3National Health Commission Key Laboratory of Parasitic Disease Control and Prevention, Jiangsu Provincial Key Laboratory on Parasite and Vector Control Technology, Jiangsu Institute of Parasitic Diseases, Wuxi, Jiangsu Province, 214064, People’s Republic of China; 4Public Health Research Center, Jiangnan University, Wuxi, Jiangsu Province, 214122, People’s Republic of China; 5Shanghai Laboratory Animal Research Center, Shanghai Quality Monitoring Center of Laboratory Animals, Shanghai, 201203, People’s Republic of ChinaCorrespondence: Quan Zhang, Institute of Comparative Medicine, College of Veterinary Medicine, Yangzhou University, Yangzhou, People’s Republic of China, Tel +86 138-1584-1244, Email zquan@yzu.edu.cnObjective: IL-17 is a key regulator of the inflammatory response, and as such, it is involved in the constraint and clearance of pathogens. The mechanism of IL-17 in the pathogenesis of inflammatory bowel disease (IBD) caused by microbial infection is still unclear. Helicobacter hepaticus infection can induce colitis in many mouse strains, and thus, it has been widely used in the study of IBD pathogenesis.Methods: In this study, male C57BL/6, BALB/c, Il-10−/−, and Il-17a−/− mice were infected with H. hepaticus for several weeks. Histopathology, H. hepaticus colonization and distribution, expression of inflammatory cytokines and lysozyme, and distribution of mucus in proximal colon were examined.Results: The colonic colonization of H. hepaticus was abnormally high in Il-17a−/− mice. H. hepaticus infection caused on

Yaning Li,1 Junfang Nie,1 Jie Dai,1 Jun Yin,1 Binbin Huang,1 Jia Liu,1 Guoguang Chen,1 Lili Ren1,2 1School of Pharmacy, Nanjing Tech University, Nanjing, People’s Republic of China; 2Department of Microbiology and Immunology, Stanford University, Stanford, CA, USACorrespondence: Guoguang Chen; Lili Ren, School of Pharmacy, Nanjing Tech University, Nanjing, People’s Republic of China, Tel +86-2558-139-416, Email ggchen@njtech.edu.cn; renlili@njtech.edu.cnPurpose: Nanotechnology has been widely used in antitumor research. The complex physiological environment has brought significant challenges to the field of antitumor micelles. The ideal micelles must not only have an invisible surface to extend the circulation time but must also enhance the retention of drugs and cellular internalization at the tumor.Methods: A graded response micelle (RPPssD@IR780/DOC) was designed to self-assemble by cRGD-poly(β-amino esters)-polyethylene glycol-ss-distearoyl phosphatidylethanolamine (cRGD-PBAE-PEG-ss-DSPE) loaded with docetaxel (DOC) and IR-780 iodide (IR780). The micelles were designed to allow the PEG shell to prolong the blood circulation time in the body and effectively accumulate in the tumor. Subsequently, the acidic microenvironment of the tumor could transform the PBAE to hydrophilic, thereby increasing the size of micelles and exposing cyclic Arg-Gly-Asp (cRGD) peptides to increase the retention and cellular internalization of micelles in the tumor. After tumor cells had captured micelles, the high expression of glutathione in the cells prompted the release of DOC and IR780. Subsequently, the IR780 was stimulated by an 808-nm laser to generate local heat and reactive oxygen species (ROS) to synergize with DOC to treat the tumor.Results: In vitro and in vivo experimental results suggested that RPPssD@IR780/DOC was a potential photochemical effective for the treatment of tumors with non-negligible antitumor activity and good biocompatibility.Co

Gas accretion is an important process in the evolution of galaxies, but it has limited direct observational evidences. In this paper, we report the detection of a possible ongoing gas accretion event in a Blue Compact Dwarf (BCD) galaxy, MaNGA 8313-1901, observed by the Mapping Nearby Galaxies and Apache Point Observatory (MaNGA) program. This galaxy has a distinct off-centered blue clump to the northeast (the NE clump) that shows low metallicity and enhanced star-formation. The kinematics of the gas in the NE clump also seems to be detached from the host BCD galaxy. Together with the metallicity drop of the NE clump, it suggests that the NE clump likely has an external origin, such as the gas accretion or galaxy interaction, rather than an internal origin, such as an \hii~complex in the disk. After removing the underlying host component, we find that the spectrum of the "pure" clump can match very well with a modeled spectrum containing a stellar population of the young stars ($\le 7$ Myr) only. This may imply that the galaxy is experiencing an accretion of cold gas, instead of a merger event involving galaxies with significant pre-existing old stars. We also find signs of another clump (the SW clump) at the south-west corner of the host galaxy, and the two clumps may share the same origin of gas accretion., Comment: 17 pages, 10 figures, accepted for publication in ApJ

Siamese networks are widely used for remote sensing change detection tasks. A vanilla siamese network has two identical feature extraction branches which share weights, these two branches work independently and the feature maps are not fused until about to be sent to a decoder head. However we find that it is critical to exchange information between two feature extraction branches at early stage for change detection task. In this work we present Mutual-Attention Siamese Network (MASNet), a general siamese network with mutual-attention plug-in, so to exchange information between the two feature extraction branches. We show that our modification improve the performance of siamese networks on multi change detection datasets, and it works for both convolutional neural network and visual transformer., Comment: XXIV ISPRS Congress

Feng Su,1,&ast; Yong Fang,1,&ast; Jinjie Yu,1 Tian Jiang,1 Siyun Lin,1 Shaoyuan Zhang,1 Lu Lv,2 Tao Long,2 Huiwen Pan,2 Junqing Qi,2 Qiang Zhou,3 Weifeng Tang,4 Guowen Ding,2 Liming Wang,5 Lijie Tan,1 Jun Yin1 1Department of Thoracic Surgery, Zhongshan Hospital of Fudan University, Shanghai, People’s Republic of China; 2Department of Cardiothoracic Surgery, Affiliated People’s Hospital of Jiangsu University, Jiangsu, People’s Republic of China; 3Department of Thoracic Surgery, Sichuan Cancer Hospital & Institute, Sichuan, People’s Republic of China; 4Department of Cardiothoracic Surgery, Nanjing Drum Tower Hospital, Jiangsu, People’s Republic of China; 5Department of Respiratory, Shanghai Xuhui Central Hospital, Shanghai, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Jun Yin; Lijie Tan, Zhongshan Hospital of Fudan University, 180 Fenglin road, Xuhui District, Shanghai, 200032, People’s Republic of China, Email jun_yin@fudan.edu.cn; tan.lijie@zs-hospital.sh.cnBackground: The σ 1A subunit of the adaptor protein 1 (AP1S1) participates in various intracellular transport pathways, especially the maintenance of copper homeostasis, which is pivotal in carcinogenesis. It is therefore rational to presume that AP1S1 might also be involved in carcinogenesis. In this hospital-based case-control study, we investigated the genetic susceptibility to ESCC in relation to SNPs of AP1S1 among Chinese population.Methods: A database containing a total of 1303 controls and 1043 ESCC patients were retrospectively studied. The AP1S1 SNPs were analyzed based on ligation detection reaction (LDR) method. Then, the relationship between ESCC and SNPs of AP1S1 was determined with a significant crude P< 0.05. Then the logistic regression analysis was used for the calculation for adjusted P in the demographic stratification comparison if a significant difference was observed in the previous step.Results: AP1S1 rs77387

Da-Ming Xu,1,&ast; Ze-Wen Zhang,2,&ast; Jing-Xing Yi,3 Long Xie,3 Wen-Jun Yu,2 Jin-Feng Qiu,4 Cheng-Wei Xu,5 Chun-Ling He,6 Xian-Ru Xu,7 Jun Yin3 1Division of Urological Surgery, The Second Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong Province, People’s Republic of China; 2Division of Hematology, The Second Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong Province, People’s Republic of China; 3Department of Clinical Laboratory Medicine, The Second Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong Province, People’s Republic of China; 4Division of Respirology, The Second Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong Province, People’s Republic of China; 5Department of Blood Purification, The Second Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong Province, People’s Republic of China; 6Department of Pathology, The Second Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong Province, People’s Republic of China; 7Division of Inventional Ultrasonic Therapeutics, The Second Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong Province, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Jun Yin, Department of Clinical Laboratory Medicine, The Second Affiliated Hospital of Shantou University Medical College, Dongxia Road North, Shantou, Guangdong Province, 515041, People’s Republic of China, Tel +86 754 8891 5950, Email jyin@stu.edu.cnBackground: Adult chronic immune thrombocytopenia (chronic ITP) is a common autoimmune hemorrhagic disease characterized by decreased platelet production and increased platelet destruction, leading to thrombocytopenia. In this study, Ca2+, calnexin (CNX) and calreticulin (CRT) within platelets from adult patients with chronic ITP were investigated.Methods: Platelets were isolat

The gut microbiome is a microbial ecosystem which expresses 100 times more genes than the human host and plays an essential role in human health and disease pathogenesis. Since most intestinal microbial species are difficult to culture, next generation sequencing technologies have been widely applied to study the gut microbiome, including 16S rRNA, 18S rRNA, internal transcribed spacer (ITS) sequencing, shotgun metagenomic sequencing, metatranscriptomic sequencing and viromic sequencing. Various software tools were developed to analyze different sequencing data. In this review, we summarize commonly used computational tools for gut microbiome data analysis, which extended our understanding of the gut microbiome in health and diseases.

Metal-halide perovskites have rapidly emerged as one of the most promising materials of the 21st century, with many exciting properties and great potential for a broad range of applications, from photovoltaics to optoelectronics and photocatalysis. The ease with which metal-halide perovskites can be synthesized in the form of brightly luminescent colloidal nanocrystals, as well as their tunable and intriguing optical and electronic properties, has attracted researchers from different disciplines of science and technology. In the last few years, there has been a significant progress in the shape-controlled synthesis of perovskite nanocrystals and understanding of their properties and applications. In this comprehensive review, researchers having expertise in different fields (chemistry, physics, and device engineering) of metal-halide perovskite nanocrystals have joined together to provide a state of the art overview and future prospects of metal-halide perovskite nanocrystal research.

The focus of this work is to study the gas entrainment and mold flux entrapments during the ingot filling process based on physical and numerical modelling. The formation of the free surface was investigated in the uphill teeming method, which illustrates a dynamic change at a quasi-steady state. The influence of several turbulent models on the result was studied. The Reynolds stress turbulence model predictions show a good agreement to the experimental result compared to predictions using k-ԑ based turbulence models. It was found that the Weber number at the free surface is smaller than 12.3, when the inlet velocity is 0.5 m·s-1. This indicates a minor chance for mold flux entrapments, based on previously reported results. In order to reach a calm free surface using an even high inlet velocity, the side teeming process is proposed. A rotational flow field was found to be generated in the side teeming process, due to the horizontal teeming of the molten steel. A vortex cannot be found in the side teeming process because of the weak strength of the swirling flow. However, surface disturbances can be seen close to the wall of the mold, but they are small and vanish at lower teeming velocities. An optimization of the filling angles in the side teeming process was studied to reduce and eliminate the surface disturbances at the edge of the mold. The result showed that the 90 degrees filling angle results in a calm free surface without surface disturbances. Therefore, this design is recommended to use in the ingot casting process. The trumpet was also studied in this work to better understand the gas entrainment phenomenon. Water model experiments were carried out to measure the gas entrainment rate during a quasi-steady. Numerical simulations were performed and the results showed a good agreement to the experimental results. The formation of a big bubble was observed at the bend, which is due to the generation of a low-pressure region. Finally, an angled runner design w, I traditionell götgjutning fylls götet uppifrån vilket orsakar stänk, exponering mot atmosfär samt neddragning av flux. Dessa nackdelar kan reduceras genom att gjuta underifrån med en metod som kallas “uphill teeming”. Däremot, tillkommer även en del nackdelar med denna gjutningsmetod som t.ex. infångning av gas och stänk initialt i processen. Dessa nackdelar orsakar icke-metalliska inneslutningar som är kritiska för kvalitén av den slutliga stålprodukten. I detta arbete studeras infångning av gas och flux under uphill teeming metoden med hjälp av numeriska samt fysikaliska modeller. Den dynamiska ändringen av den fria ytan som uppstår under uphill teeming metoden studerades med hjälp av Reynold stress turbulens modellen. Jämfört med k-e turbulens modellen så visade denna modell en bättre similaritet till de fysikaliska experimenten. Det konstaterades att Weber­numret vid den fria ytan är mindre än 12,3 när inloppshastigheten är 0,5m·s-1 vilket indikerar att systemet har låg risk för neddragning av flux. För att uppnå en stilla flytande fri yta med höga inloppshastigheter så föreslogs sidofyllning. Sidofyllning skapade ett svagt rotationsflöde pga. horisontell fyllning längs tangenten på götformen. Rotationsflödet var inte tillräckligt starkt föra att generera en vortex under fyllningsprocessen. Däremot observerades små störningar längs kokillens vägg som försvann med lägre fyllningshastighet. Olika sidofyllnings vinklar studerades för att optimera mot en lugn fri yta utan störningar längs kokillens väggar. En vinkel på 90 grader visade bäst resultat med 0% risk vid den fria ytan och rekommenderas därför till götgjutningsprocessen. För att studera infångning av gas inkluderades även fyllningskanalerna till kokillen i en fysikalisk samt kvasi stationär numerisk vattenmodell med fokus på infångningshastighet. Simuleringarna visade bra similaritet till de fysikaliska experimenten och det observerades formning av stora bubblor pga. lågt tryck i vissa regioner i kanale

The flow pattern affects the interaction between the mold flux and liquid steel,especially during the initial entry of liquid steel into the mold. Strong turbulencecan cause mold flux entrapments during the ingot casting process. If thishappens, nonmetallic inclusions are generated, which decreases the quality ofthe final product. Herein, the side teeming process is introduced as an alternativeto the traditional uphill teeming process to decrease mold flux entrapments. Bothphysical experiments and mathematical modeling are conducted to study the freesurface. Specifically, the Weber number is also evaluated to predict the possibilityof mold flux entrapments at the free surface. The results show that a calmer freesurface is formed in the side teeming process compared with the uphill teemingprocess. Also, the results show that the Reynolds stress model is more suitable topredict the free surface compared with the realizable k–ε model. The presentfindings strongly suggest that an implementation of a side teeming processwould be an effective way of reducing the risk for mold flux entrapments., QC 20210527

Incidental radiation exposure to the heart during lung cancer radiotherapy is associated with radiation-induced heart disease and increased rates of mortality. By considering the respiratory-induced motion of the heart it is possible to create a radiotherapy plan that results in a lower overall cardiac dose. This approach is challenging using current clinical practices: manual contouring of the heart is time consuming, and subject to inter- and intra-observer variability. In this work, we investigate the feasibility of our previously developed, atlas-based, automatic heart segmentation tool to delineate the heart in four-dimensional x-ray computed tomography (4D-CT) images. We used a dataset comprising 19 patients receiving radiotherapy for lung cancer, with 4D-CT imaging acquired at 10 respiratory phases and with a maximum intensity projection image generated from these. For each patient, one of four experienced radiation oncologists contoured the heart on each respiratory phase image and the maximum intensity image. Automatic segmentation of the heart on these same patient image sets was achieved using a leave-one-out approach, where for each patient the remaining 18 were used as an atlas set. The consistency of the automatic segmentation relative to manual contouring was evaluated using the Dice similarity coefficient (DSC) and mean absolute surface-to-surface distance (MASD). The DSC and MASD are comparable to inter-observer variability in clinically acceptable whole heart delineations (average DSC > 0.93 and average MASD < 2.0 mm in all the respiratory phases). The comparison between automatic and manual delineations on the maximum intensity images produced an overall mean DSC of 0.929 and a mean MASD of 2.07 mm. The automatic, atlas-based segmentation tool produces clinically consistent and robust heart delineations and is easy to implement in the routine care of lung cancer patients.

Multidentate molecular additives are widely used to passivate perovskite, yet the role of chelate effect is still unclear. Here, the authors investigate a wide range of additives with different coordination number and functional moieties to establish correlation between coordination affinity and perovskite crystallisation dynamics. Molecular additives are widely utilized to minimize non-radiative recombination in metal halide perovskite emitters due to their passivation effects from chemical bonds with ionic defects. However, a general and puzzling observation that can hardly be rationalized by passivation alone is that most of the molecular additives enabling high-efficiency perovskite light-emitting diodes (PeLEDs) are chelating (multidentate) molecules, while their respective monodentate counterparts receive limited attention. Here, we reveal the largely ignored yet critical role of the chelate effect on governing crystallization dynamics of perovskite emitters and mitigating trap-mediated non-radiative losses. Specifically, we discover that the chelate effect enhances lead-additive coordination affinity, enabling the formation of thermodynamically stable intermediate phases and inhibiting halide coordination-driven perovskite nucleation. The retarded perovskite nucleation and crystal growth are key to high crystal quality and thus efficient electroluminescence. Our work elucidates the full effects of molecular additives on PeLEDs by uncovering the chelate effect as an important feature within perovskite crystallization. As such, we open new prospects for the rationalized screening of highly effective molecular additives., Funding Agencies|ERC Starting GrantEuropean Research Council (ERC) [717026]; Swedish Energy Agency EnergimyndighetenSwedish Energy Agency [48758-1, 44651-1]; Swedish Research Council VRSwedish Research Council; NanoLund; Swedish Government Strategic Research Area in Materials Science on Functional Materials at Linkoping University [2009-00971]; National Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC) [91833303, 61974098, 62005126]; National Key Research and Development Program [2016YFA0201900]; Jiangsu High Educational Natural Science Foundation [18KJA430012]; 111 ProgramMinistry of Education, China - 111 Project; Collaborative Innovation Center of Suzhou Nano Science and Technology; Collaborative Innovation Center of Suzhou Nano Science Technology; Research Foundation - Flanders (FWO)FWO [12Y7218N, 12Y7221N, G098319N]; KU Leuven Research FundKU Leuven [C14/19/079, 201806920071, 201906830040, 201608530162, 201806460021]; China Scholarship CouncilChina Scholarship Council

High turbulence at the liquid steel-mold flux interface can result in mold flux entrapments, which can generate non-metallic inclusions during the ingot casting process. Those non-metallic inclusions are detrimental to the final steel quality. The teeming process during ingot casting is typically carried out using the uphill teeming method. The authors propose a novel alternative method using a side teeming process, which decreases turbulence at the free surface. In order to define the optimum operational conditions, a 3-D mathematical model was developed to investigate the effect of the filling angle on the motion of the free surface and the resulting shear stresses during the teeming process. The investigated filling angles were: 0, 30, 45, 60 and 90 degrees. The present findings suggest that using the filling angle of 90 degrees between the mold and the runner would be an effective way of reducing the number of inclusions due to mold flux entrapments and refractory wear., QC 20210527

The gas entrainment can influence surface disturbances during the filling in the uphill ingot teeming process. Surface disturbances can result in mold flux entrapments, leading to the generation of non-metallic inclusions which are detrimental to the final steel quality. A three-dimension simulation was conducted to study the gas entrainment during the filling process. Furthermore, a water model experiment was also carried out to validate the results from the numerical simulations. The results showed a good agreement between the numerical and physical models. Moreover, the formation of a big bubble can be observed at the bend between the trumpet and the horizontal runner, and between the horizontal runner and the vertical runner. The sizes of the big bubble fluctuate during the teeming process. The current study gives a specific overview of the gas entrainment phenomenon during the initial filling of the uphill teeming process., QC 20210527

This study examined the relationship between career mentoring and work engagement from the mentor perspective, by estimating work meaningfulness as a mediator. The research model used quantitative survey data from 309 employees who mentored their junior colleagues in the on-the-job training programmes of Japanese companies. The results demonstrated that career mentoring had an indirect effect on the work engagement of mentors by enhancing the psychological meaningfulness of their work. In addition, learning goal orientation positively influenced career mentoring; this may subsequently facilitate the work engagement by increasing the perception of the meaning of work. Learning-oriented individuals who act as mentors find psychological meaningfulness in their work, which in turn enhances their work engagement. By setting acceptable meaningful goals for mentoring programmes, practitioners can minimize the negative outcomes of mentoring. The results contribute to the existing literature by examining how mentoring experiences affect the behaviour of mentors.

Gangliosides are sialic acid-containing glycosphingolipids that have been found in the cell membranes of all vertebrates. Their important biological functions are contributed by both the glycan and the ceramide lipid components. GM3 is a major ganglioside and a precursor for many other more complex gangliosides. To obtain structurally diverse GM3 gangliosides containing various sialic acid forms and different fatty acyl chains in low cost, an improved process was developed to chemically synthesize lactosyl sphingosine from an inexpensive l-serine derivative. It was then used to obtain GM3 sphingosines from diverse modified sialic acid precursors by an efficient one-pot multienzyme sialylation system containing Pasteurella multocida sialyltransferase 3 (PmST3) with in situ generation of sugar nucleotides. A highly effective chemical acylation and facile C18-cartridge purification process was then used to install fatty acyl chains of varying lengths and different modifications. The chemoenzymatic method represents a powerful total synthetic strategy to access a library of structurally defined GM3 gangliosides to explore their functions.

Accessing large numbers of structurally diverse glycans and derivatives is essential to functional glycomics. We showed a general tolerance of galactosyltransferases toward uridine-diphosphate-galactosamine (UDP-GalN), which is not a commonly used sugar nucleotide donor. The property was harnessed to develop a two-step chemoenzymatic strategy for facile synthesis of novel and divergent N-acetylgalactosamine (GalNAc)-glycosides and derivatives in preparative scales. The discovery and the application of the new property of existing glycosyltransferases expand their catalytic capabilities in generating novel carbohydrate linkages, thus prompting the synthesis of diverse glycans and glycoconjugates for biological studies.

While recent years have witnessed remarkable progress in the feature representation of visual tracking, the problem of feature misalignment between the classification and regression tasks is largely overlooked. The approaches of feature extraction make no difference for these two tasks in most of advanced trackers. We argue that the performance gain of visual tracking is limited since features extracted from the salient area provide more recognizable visual patterns for classification, while these around the boundaries contribute to accurately estimating the target state. We address this problem by proposing two customized feature extractors, named polar pooling and extreme pooling to capture task-specific visual patterns. Polar pooling plays the role of enriching information collected from the semantic keypoints for stronger classification, while extreme pooling facilitates explicit visual patterns of the object boundary for accurate target state estimation. We demonstrate the effectiveness of the task-specific feature representation by integrating it into the recent and advanced tracker RPT. Extensive experiments on several benchmarks show that our Customized Features based RPT (RPT++) achieves new state-of-the-art performances on OTB-100, VOT2018, VOT2019, GOT-10k, TrackingNet and LaSOT., Comment: the authors hold different opinions on whether or not to public the paper

Da-Ming Xu,1,&ast; Qian Li,2,&ast; Jing-Xing Yi,3,&ast; Xin-Jian Cai,3 Long Xie,3 Wei Fang,3 Jin-Feng Qiu,4 Cheng-Wei Xu,5 Chun-Ling He,6 Xian-Ru Xu,7 Jie-Song Xu,8 Jun Yin2,3 1Division of Urological Surgery, Second Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, People’s Republic of China; 2Division of Hematology, Second Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, People’s Republic of China; 3Department of Clinical Laboratory Medicine, Second Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, People’s Republic of China; 4Division of Respirology, Second Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, People’s Republic of China; 5Department of Blood Purification, Second Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, People’s Republic of China; 6Department of Pathology, Second Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, People’s Republic of China; 7Division of Interventional Ultrasonic Therapeutics, Second Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, People’s Republic of China; 8Department of Electroencephalogram, Second Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Jun YinDepartment of Clinical Laboratory Medicine and Division of Hematology, Second Affiliated Hospital of Shantou University Medical College, Dongxia Road North, Shantou, Guangdong Province, 515041, People’s Republic of ChinaTel +86 754 8891 5950Email jyin@stu.edu.cnObjective: In order to evaluate the effect of dyslipidemia on cellular or humoral immunity in patients, changes in the absolute number of lymphocyte subsets were detected.Methods: Flow cytometry was applied to determine the absolute value of lymphocyte subsets: B

Ming Li,1,&ast; Da-Ming Xu,1,&ast; Shu-Bin Lin,1 Zheng-Liang Yang,1 Teng-Yu Xu,1 Jin-Huan Yang,1 Ze-Xin Lin,1 Ze-Kai Huang,1 Jun Yin2,3 1Division of Urological Surgery, Second Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, People’s Republic of China; 2Division of Hematology, Second Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, People’s Republic of China; 3Department of Clinical Laboratory Medicine, Second Affiliated Hospital of Shantou University Medical College, Shantou, Guangdong, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Jun YinDepartment of Clinical Laboratory Medicine and Division of Hematology, The Second Affiliated Hospital of Shantou University Medical College, Dongxia Road North, Shantou, Guangdong Province, 515041, People’s Republic of ChinaTel +86 754 8891 5950Email jyin@stu.edu.cnObjective: To investigate the immune profiles in benign prostatic hyperplasia, changes in the absolute number of lymphocyte subsets and the proportion of T lymphocyte subsets were detected.Methods: Absolute value of lymphocyte subsets in peripheral blood (T, B and NK cells) and the proportion of T lymphocyte (native CD4+ T cell, memory CD4+ T cell, CD8+CD28+ T cell, CD8+CDDR+ T cells and CD8+CD38+ T cell) were measured by flow cytometry.Results: The absolute values of CD3+ T cell (972.55± 330.31 vs 1757.99± 439.38), CD4+ T cell (656.43± 252.39 vs 899.30± 262.10), and CD8+ T cell (301.97± 147.76 vs 728.45± 230.34) in patients with benign prostatic hyperplasia were significantly reduced (all P< 0.05). There was no significant difference in NK cell (285.58± 182.84 vs 528.92± 208.17) and B cell (186.66± 86.62 vs 334.17± 130.46). The proportion of naive CD4+ T cell (3.75± 0.50 vs 8.54± 1.61) in T lymphocyte subsets in patients with BPH was significantly reduced (P< 0.05). There was no significant difference in memory CD4+ T cell (87

The Visual Object Tracking challenge VOT2021 is the ninth annual tracker benchmarking activity organized by the VOT initiative. Results of 71 trackers are presented; many are state-of-the-art trackers published at major computer vision conferences or in journals in recent years. The VOT2021 challenge was composed of four sub-challenges focusing on different tracking domains: (i) VOT-ST2021 challenge focused on short-term tracking in RGB, (ii) VOT-RT2021 challenge focused on "real-time" short-term tracking in RGB, (iii) VOT-LT2021 focused on long-term tracking, namely coping with target disappearance and reappearance and (iv) VOT-RGBD2021 challenge focused on long-term tracking in RGB and depth imagery. The VOT-ST2021 dataset was refreshed, while VOT-RGBD2021 introduces a training dataset and sequestered dataset for winner identification. The source code for most of the trackers, the datasets, the evaluation kit and the results along with the source code for most trackers are publicly available at the challenge website(1).

Lingwen Ying,1,&ast; Yong Zhang,2,&ast; Jun Yin,1,&ast; Yufei Wang,1 Wei Lu,1 Wei Zhu,1 Yuqian Bao,1 Jian Zhou1 1Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital; Shanghai Clinical Center for Diabetes; Shanghai Diabetes Institute; Shanghai Key Laboratory of Diabetes Mellitus, Shanghai, 200233, People’s Republic of China; 2Department of Immunology and Microbiology, Shanghai Jiao Tong University, School of Medicine, Shanghai, People’s Republic of China&ast;These authors contributed equally to this workCorrespondence: Jian ZhouDepartment of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, 600 Yishan Road, Shanghai, 200233, People’s Republic of ChinaTel +86-21-64369181Fax +86-21-64368031Email zhoujian@sjtu.edu.cnPurpose: We aimed to explore the immunological characteristics and cytokine profile of the initial stage of type 1 diabetes.Patients and Methods: In total, 123 age- and sex-matched subjects with newly diagnosed classic type 1 diabetes mellitus (T1ADM), fulminant type 1 diabetes mellitus (FT1DM), and normal glucose tolerance (NGT) were enrolled. Serum cytokine levels were measured using Milliplex MAP multifactor detection.Results: There was a significant increase in the levels of transforming growth factor β (TGFβ 1) and TGFβ 2 and decrease in programmed death-1 (PD-1), PD ligand 1 (PD-L1), pro-inflammatory cytokines, and anti-inflammatory cytokines in type 1 diabetes patients compared with the NGT subjects (all P < 0.05). There was no significant difference in C-reactive protein (CRP) and blood routine indicators between the two groups. Type 1 diabetes was further divided into T1ADM and FT1DM subgroups. FT1DM patients had much higher CRP levels than T1ADM patients (4.90 [0.95– 26.05] mg/L vs 0.39 [0.20– 0.74] mg/L, P < 0.01). Blood routine results showed that the number of leukocytes was significantly increased in FT1D

Lingli Cai,* Cheng Li,* Yufei Wang, Yifei Mo, Jun Yin, Xiaojing Ma Department of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital; Shanghai Clinical Center for Diabetes; Shanghai Diabetes Institute; Shanghai Key Laboratory of Diabetes Mellitus, Shanghai, People’s Republic of China*These authors contributed equally to this workCorrespondence: Jun Yin; Xiaojing MaDepartment of Endocrinology and Metabolism, Shanghai Jiao Tong University Affiliated Sixth People’s Hospital, 600 Yishan Road, Shanghai, 200233, People’s Republic of ChinaTel +86-21-64369181Fax +86-21-64368031Email yinjun@sjtu.edu.cn; maxiaojing@sjtu.edu.cnAim: Growth differentiation factor 15 (GDF15) is closely related to obesity. This study aimed to explore the influence of weight loss intervention on serum GDF15 levels and the relationship between GDF15 and metabolism.Materials and Methods: Forty-four overweight and obese adults either adopted a low-carbohydrate diet or performed moderate-to-vigorous exercise for 3 weeks. Weekly follow-ups were conducted to measure body composition, glucose and lipid metabolism and serum GDF15 levels.Results: After 3 weeks of intervention, body weight, fat mass and waist circumference in both groups decreased (P < 0.05). No significant change in GDF15 levels was observed in the two groups. Among all the subjects, 10 of them (22.7%, group of Down) showed a decrease in GDF15 and 34 (77.3%, group of Up) showed an increase in GDF15 after the intervention. We found that GDF15 increased significantly with the follow-up time in the UP group and waist circumference, fasting serum insulin (FINS), homeostasis model assessment of insulin resistance (HOMA-IR) and triglycerides (TG) decreased (P for trend < 0.05). However, no significant differences in all parameters were detected in Down group. In addition, GDF15 was elevated between 30 mins and 120 mins in a 75-g oral glucose tolerance

The generation of nonmetallic inclusions due to mold flux entrapment is detrimental for the final steel quality in the uphill teeming process. Herein, physical and mathematical modeling using a full-scale mold is conducted to investigate the change of the hump height and the surface height at the free surface during filling. Moreover, the Weber number is also studied to analyze the tendency of mold flux entrapment at the free surface. The results show that the Reynolds stress model can predict the hump height more accurately compared with the k − ε-based turbulence models. In addition, the result shows that a lower filling rate can result in a lower hump height as well as less fluctuations of the hump and surface heights. Furthermore, the Weber number for the low flow rate case is lower than 12.3, which indicates a small or no risk for mold flux entrapment. The present findings suggest that a reduction in velocity in the mold entrance region are an effective means of reducing the risk of mold flux entrapment., QC 20210505