Yang Wang

In the present work, the microstructure of the melt-spun Al 90 Ce 10 alloy has been characterized using X-ray diffraction and transmission electron microscopy together with energy-dispersive spectrometry. It has been found that the microstructure of the melt-spun Al 90 Ce 10 alloy is composed of the amorphous phase, f -Al, f -Al 11 Ce 3 , Al 3 Ce and unidentified phases, quite different from that of the ingot-like alloy consisting of coarse primary f -Al- f -Al 11 Ce 3 dendrites embedded in the f -Al- f -Al 11 Ce 3 eutectic matrix. Moreover, the amorphous phase is dominant in the melt-spun Al 90 Ce 10 alloy according to the XRD and TEM results. Al 3 Ce particles, less than 100 nm in size, are dispersed in the partial amorphous phase. Polygonal f -Al 11 Ce 3 crystals embedded in the f -Al matrix are also observed. The presence of the hexagonal, kite-like and petal-like intermetallic particles surrounded by the amorphous phase indicates that there exist micro-inhomogeneous structures in the Al 90 Ce 10 melt. These results demonstrate that the overheating of the melt has a significant effect on the amorphization of the Al 90 Ce 10 alloy

The COVID-19 pandemic caused widespread disruption as governments took actions to limit the spread of the virus. Measures such as physical distancing and lockdowns changed living conditions, leading to challenges such as social isolation and reduced connectedness. This study explores COVID-19’s impact on adolescents’ well-being, emphasising family social capital, which refers to supportive adult-child relationships that foster well-being and enhance remote learning. Quantitative data was collected through an online survey from August 2022 to August 2023, involving 4008 students and 3511 parents. Semi-structured interviews with six students and their parents (either the mother or the father) provided in-depth insights into the perceived role of family social capital in shaping adolescents’ well-being during quarantine. Quantitative data revealed that parental education level significantly influenced adolescents’ self-reported well-being and resilience, and family income influenced parents’ perceptions of their children’s well-being. Qualitative data highlighted the importance of strong family bonds, effective parent-child relationships, and robust family support in mitigating the adverse effects of prolonged home quarantine. The research also discovered the role of adolescents’ agency in building social capital through web-based communities. The study contributes to understanding Chinese adolescents’ well-being during the COVID-19 pandemic, providing implications for supporting their well-being in the post-pandemic era.

The Scoping Culture and Heritage Capital study was commissioned jointly in November 2021 by the Arts and Humanities Research Council (AHRC) and Department for Digital, Culture, Media and Sport (DCMS). The study was led by Dr Patrycja Kaszynska, Senior Research Fellow at UAL, in partnership with cultural sector partners and policy makers, and collaborating with a team of researchers spanning arts and humanities, heritage science and economics: Dr Sadie Watson and Dr Emma Dwyer from Museum of London Archaeology (MOLA); Prof Diane Coyle, University of Cambridge; Prof Patrizia Riganti and Dr Yang Wang University of Glasgow, Dr Ricky Lawton, Simetrica-Jacobs and Dr Mafalda Dâmaso (UAL). The findings of the scoping study are that the introduction of the CHC framework presents significant opportunities from the point of view of valuing the arts, culture and heritage, as well as policy decision-making as such. However, the scoping exercise shows that developing, operationalising and implementing this framework requires sustained research attention, methods refinement and, crucially, capacity- and capability-building across disciplines and sectors. This is not least because the value of arts, culture and heritage as conceived through the CHC framework is an inter- and trans-disciplinary concept. The scoping study is accompanied by a AHRC/DCMS funding call for new research informed by the project’s recommendations.

A link prediction model for weighted networks based on Dempster–Shafer evidence theory and the influence of common neighbours is proposed in this paper. First, three types of future common neighbours and their topological structures are proposed. Second, the concepts of endpoint weight influence, link weight influence, and high-strength node influence are introduced. Then, the similarity based on the impacts of current common neighbours and FCNs is defined, respectively. Finally, the two similarity indices are fused by the DS evidence theory. This model effectively integrates multisource information and completely exploits the influence of all CCNs and FCNs on similarity. Experiments are performed on 9 real and 40 simulation-weighted datasets, and these findings are compared with several classic algorithms. Results show that the proposed method has higher precision than other methods, which can achieve good performance in link prediction in weighted networks.

Ontologies, as the term is used in informatics, are structured vocabularies comprised of human- and computer-interpretable terms and relations that represent entities and relationships. Within informatics fields, ontologies play an important role in knowledge and data standardization, representation, integra- tion, sharing and analysis. They have also become a foundation of artificial intelligence (AI) research. In what follows, we outline the Coronavirus Infectious Disease Ontology (CIDO), which covers multiple areas in the domain of coronavirus diseases, including etiology, transmission, epidemiology, pathogenesis, diagnosis, prevention, and treatment. We emphasize CIDO development relevant to COVID-19.

COVID-19 often manifests with different outcomes in different patients, highlighting the complexity of the host-pathogen interactions involved in manifestations of the disease at the molecular and cellular levels. In this paper, we propose a set of postulates and a framework for systematically understanding complex molecular host-pathogen interaction networks. Specifically, we first propose four host-pathogen interaction (HPI) postulates as the basis for understanding molecular and cellular host-pathogen interactions and their relations to disease outcomes. These four postulates cover the evolutionary dispositions involved in HPIs, the dynamic nature of HPI outcomes, roles that HPI components may occupy leading to such outcomes, and HPI checkpoints that are critical for specific disease outcomes. Based on these postulates, an HPI Postulate and Ontology (HPIPO) framework is proposed to apply interoperable ontologies to systematically model and represent various granular details and knowledge within the scope of the HPI postulates, in a way that will support AI-ready data standardization, sharing, integration, and analysis. As a demonstration, the HPI postulates and the HPIPO framework were applied to study COVID-19 with the Coronavirus Infectious Disease Ontology (CIDO), leading to a novel approach to rational design of drug/vaccine cocktails aimed at interrupting processes occurring at critical host-coronavirus interaction checkpoints. Furthermore, the host-coronavirus protein-protein interactions (PPIs) relevant to COVID-19 were predicted and evaluated based on prior knowledge of curated PPIs and domain-domain interactions, and how such studies can be further explored with the HPI postulates and the HPIPO framework is discussed.

Current COVID-19 pandemic and previous SARS/MERS outbreaks have caused a series of major crises to global public health. We must integrate the large and exponentially growing amount of heterogeneous coronavirus data to better understand coronaviruses and associated disease mechanisms, in the interest of developing effective and safe vaccines and drugs. Ontologies have emerged to play an important role in standard knowledge and data representation, integration, sharing, and analysis. We have initiated the development of the community-based Coronavirus Infectious Disease Ontology (CIDO). As an Open Biomedical Ontology (OBO) library ontology, CIDO is an open source and interoperable with other existing OBO ontologies. In this article, the general architecture and the design patterns of the CIDO are introduced, CIDO representation of coronaviruses, phenotypes, anti-coronavirus drugs and medical devices (e.g. ventilators) are illustrated, and an application of CIDO implemented to identify repurposable drug candidates for effective and safe COVID-19 treatment is presented.

The current COVID-19 pandemic and the previous SARS/MERS outbreaks of 2003 and 2012 have resulted in a series of major global public health crises. We argue that in the interest of developing effective and safe vaccines and drugs and to better understand coronaviruses and associated disease mechenisms it is necessary to integrate the large and exponentially growing body of heterogeneous coronavirus data. Ontologies play an important role in standard-based knowledge and data representation, integration, sharing, and analysis. Accordingly, we initiated the development of the community-based Coronavirus Infectious Disease Ontology in early 2020. As an Open Biomedical Ontology (OBO) library ontology, CIDO is open source and interoperable with other existing OBO ontologies. CIDO is aligned with the Basic Formal Ontology and Viral Infectious Disease Ontology. CIDO has imported terms from over 30 OBO ontologies. For example, CIDO imports all SARS-CoV-2 protein terms from the Protein Ontology, COVID-19-related phenotype terms from the Human Phenotype Ontology, and over 100 COVID-19 terms for vaccines (both authorized and in clinical trial) from the Vaccine Ontology. CIDO systematically represents variants of SARS-CoV-2 viruses and over 300 amino acid substitutions therein, along with over 300 diagnostic kits and methods. CIDO also describes hundreds of host-coronavirus protein-protein interactions (PPIs) and the drugs that target proteins in these PPIs. CIDO has been used to model COVID-19 related phenomena in areas such as epidemiology. The scope of CIDO was evaluated by visual analysis supported by a summarization network method. CIDO has been used in various applications such as term standardization, inference, natural language processing (NLP) and clinical data integration. We have applied the amino acid variant knowledge present in CIDO to analyze differences between SARS-CoV-2 Delta and Omicron variants. CIDO's integrative host-coronavirus PPIs and drug-target knowledge has also been used to support drug repurposing for COVID-19 treatment. CIDO represents entities and relations in the domain of coronavirus diseases with a special focus on COVID-19. It supports shared knowledge representation, data and metadata standardization and integration, and has been used in a range of applications.

Confucian thought provides guidance on social structure and political governance. It was introduced to Japan as early as the fourth century AD (Anno Domini) and has been deeply imprinted in Japan’s history and culture for thousands of years. This article takes I am a cat as a specific example to analyze the specific Confucian ideas reflected in Japanese relational language. I am a cat is a classic work by the famous modern Japanese satirist Soseki Natsume. From the specific reflection of I am a cat, Japanese relational language includes Confucian concepts of superiority and inferiority, loyalty and filial piety, harmony and gratitude, as well as the concepts of propriety, benevolence and righteousness. It also reflects that Confucian philosophy has penetrated into Japanese related language. In such research, Japanese learners can gain a more intuitive understanding of the impact of Confucianism on modern Japanese relational language to improve the learning effectiveness. It also helps to develop the understanding of the influence of Confucian culture on Japan.

The mechanical environment crucially influences many cell functions 1. However, it remains largely mysterious how mechanical stimuli are transmitted into biochemical signals. Src is known to regulate the integrin-cytoskeleton interaction2, which is essential for the transduction of mechanical stimuli3-5. Using fluorescent resonance energy transfer, here we develop a genetically encoded Src reporter that enables the imaging and quantification of spatio-temporal activation of Src in live cells. We introduced a local mechanical stimulation to human umbilical vein endothelial cells by applying laser-tweezer traction on fibronectin-coated beads adhering to the cells. Using the Src reporter, we observed a rapid distal Src activation and a slower directional wave propagation of Src activation along the plasma membrane. This wave propagated away from the stimulation site with a speed of 18.1 ± 1.7 nm s-1. This force-induced directional and long-range activation of Src was abolished by the disruption of actin filaments or microtubules. Our reporter has thus made it possible to monitor mechanotransduction in live cells with spatio-temporal characterization. We find that the transmission of mechanically induced Src activation is a dynamic process that directs signals via the cytoskeleton to spatial destinations.

Contactin-Associated protein-like 2 is a large multidomain neuronal adhesion molecule implicated in a number of neurological disorders, including epilepsy, schizophrenia, autism spectrum disorder, intellectual disability, and language delay. We reveal here by electron microscopy that the architecture of CNTNAP2 is composed of a large, medium, and small lobe that flex with respect to each other. Using epitope labeling and fragments, we assign the F58C, L1, and L2 domains to the large lobe, the FBG and L3 domains to the middle lobe, and the L4 domain to the small lobe of the CNTNAP2 molecular envelope. Our data reveal that CNTNAP2 has a very different architecture compared with neurexin 1α, a fellow member of the neurexin superfamily and a prototype, suggesting that CNTNAP2 uses a different strategy to integrate into the synaptic protein network. We show that the ectodomains of CNTNAP2 and contactin 2 bind directly and specifically, with low nanomolar affinity. We show further that mutations in CNTNAP2 implicated in autism spectrum disorder arenot segregated but are distributed over the whole ectodomain. The molecular shape and dimensions of CNTNAP2 place constraints on how CNTNAP2 integrates in the cleft of axo-glial and neuronal contact sites and how it functions as an organizing and adhesive molecule.

Analysis of gene expression patterns in gastric cancer can help to identify a comprehensive panel of gene biomarkers for predicting clinical outcomes and to discover potential new therapeutic targets. Here, a multi-step bioinformatics analytic approach was developed to establish a novel prognostic scoring system for GC. We first identified 276 genes that were robustly differentially expressed between normal and GC tissues, of which, 249 were found to be significantly associated with overall survival by univariate Cox regression analysis. The biological functions of 249 genes are related to cell cycle, RNA/ncRNA process, acetylation and extracellular matrix organization. A network was generated for view of the gene expression architecture of 249 genes in 265 GCs. Finally, we applied a canonical discriminant analysis approach to identify a 53-gene signature and a prognostic scoring system was established based on a canonical discriminant function of 53 genes. The prognostic scores strongly predicted patients with GC to have either a poor or good OS. Our study raises the prospect that the practicality of GC patient prognosis can be assessed by this prognostic scoring system.

Background: PPM1G is a nuclear localized serine/threonine phosphatase implicated to be a regulator of chromatin remodeling, mRNA splicing, and DNA damage. However, its in vivo function is unknown. Results: Here we show that ppm1g expression is highly enriched in the central nervous system during mouse and zebrafish development. ppm1g-/- mice were embryonic lethal with incomplete penetrance after E12.5. Rostral defects, including neural tube and craniofacial defects were observed in ppm1g-/- embryos associated with increased cell death in the neural epithelium. In zebrafish, loss of ppm1g also led to neural defects with aberrant neural marker gene expression. Primary fibroblasts from ppm1g-/- embryos failed to grow without immortalization while immortalized ppm1g-/- fibroblasts had increased cell death upon oxidative and genotoxic stress when compared to wild type fibroblasts. Conclusions: Our in vivo and in vitro studies revealed a critical role for PPM1G in normal development and cell survival. © 2013 Wiley Periodicals, Inc.

Using the ER-fMRI technique, the present study was designed to investigate the neural substrates of language switching among second-language learners. Twelve Chinese college students who were learning English were scanned when they performed language switching tasks. Compared to non-switching conditions, language switching elicited greater activation in the right superior prefrontal cortex, left middle and superior frontal cortex, and right middle cingulum and caudate. When the direction of switching was considered, forward switching, but not backward switching, activated several brain regions related to executive functions relative to non-switching conditions. These results suggest that neural correlates of language switching differ depending on the direction of the switch and that there does not seem to be a specific brain area acting as a "language switch". © 2006.

© 2015 IEEE. Over 50% of HIV+ individuals exhibit neurocognitive impairment and subcortical atrophy, but the pattern of brain abnormalities associated with HIV is still poorly understood. Using parametric surface-based shape analyses, we mapped the 3D profile of subcortical morphometry in 63 HIV+ participants and 31 uninfected controls. The thalamus, corpus striatum, hippocampus, amygdala, brainstem, callosum and ventricles were segmented from brain MRIs. To investigate subcortical shape, we analyzed the Jacobian determinant and radial distances for structure surfaces. We also investigated effects of nadir CD4+ T-cell counts, viral load, and illness duration on subcortical morphology. Our results characterize subcortical morphometry in older HIV+ people, where participants showed significant volumetric enlargements in the thalamus, left pallidum and the ventricles while showing a reduction in the callosum. Further, RD maps revealed atrophy of the left thalamus and expansion of the brainstem in HIV. RD and JD maps of the right pallidum identified tissue expansion associated with illness duration while the left pallidum showed anterior atrophy and posterior expansion associated with viral load.

Background: Malaria around the China-Myanmar border is a serious health problem in the countries of South-East Asia. An. minimus is a principle malaria vector with a wide geographic distribution in this area. Malaria is endemic along the boundary between Yunnan province in China and the Kachin State of Myanmar where the local Anopheles community and the malaria transmission vectors have never been clarified. Methods. Adult Anopheles specimens were collected using CDC light traps in four villages along the border of China and Myanmar from May 2012 to April 2013. Morphological and molecular identification of mosquito adults confirmed the species of Anopheles. Blood-meal identification using the female abdomens was conducted using multiplex PCR. For sporozoite detection in An. minimus, sets of 10 female salivary glands were pooled and identified with SSU rDNA using nested PCR. Monthly abundance of An. minimus populations during the year was documented. The diversity of Anopheles and the role of An. minimus on malaria transmission in this border area were analyzed. Results: 4,833 adult mosquitoes in the genus Anopheles were collected and morphologically identified to species or species complex. The Anopheles community is comprised of 13 species, and 78.83% of our total specimens belonged to An. minimus s.l., followed by An. maculatus and the An. culicifacies complex. The quantity of trapped An. minimus in the rainy season of malaria transmission was greater than during the non-malarial dry season, and a peak was found in May 2012. An. minimus fed on the blood of four animals: humans, cattle, pigs and dogs. 1,500 females of An. minimus were pooled into 150 samples and tested for sporozoites: only 1 pooled sample was found to have sporozoites of Plasmodium vivax. Conclusion: Anopheles is abundant with An. minimus being the dominant species and having a high human blood index along the China-Myanmar border. The sporozoites in An. minimus were determined to be Plasmodium vivax with a 0.07-0.7% infection rate. © 2013Yu et al.; licensee BioMed Central Ltd.

This chapter offers an introduction to the field of Generative AI (GenAI), providing critical foundational knowledge on neural networks, deep learning, advanced architectures, and recent innovations propelling this domain. It delineates GenAI as a branch of AI focused on creating novel, coherent content, distinguishing it from discriminative models. Tracing the origins of GenAI, the chapter elucidates the concepts of neural networks, unraveling their components like input layers, hidden layers, and output layers. Backpropagation, which facilitates training through gradient computation, is explained in detail. The chapter progresses to explore deep learning, attributed to increases in compute power and data availability. Techniques like convolutional and recurrent neural networks, which enable feature learning, are highlighted. Advanced architectures like transformers and diffusion models, based on attention mechanisms and reversed diffusion processes, respectively, are analyzed as cutting-edge innovations. The chapter concludes with promising new developments like Hinton’s Forward-Forward algorithm, Meta’s I-JEPA model, privacy-preserving federated learning, and integration of reasoning agents, painting an exciting outlook for the future. Overall, the chapter provides a layered knowledge base, spanning history, techniques, architectures, and innovations in GenAI. With its comprehensive yet accessible approach, it aims to equip readers with a holistic understanding of the foundations propelling GenAI.

This book explores the revolutionary intersection of Generative AI (GenAI) and cybersecurity. It presents a comprehensive guide that intertwines theories and practices, aiming to equip cybersecurity professionals, CISOs, AI researchers, developers, architects and college students with an understanding of GenAI’s profound impacts on cybersecurity. The scope of the book ranges from the foundations of GenAI, including underlying principles, advanced architectures, and cutting-edge research, to specific aspects of GenAI security such as data security, model security, application-level security, and the emerging fields of LLMOps and DevSecOps. It explores AI regulations around the globe, ethical considerations, the threat landscape, and privacy preservation. Further, it assesses the transformative potential of GenAI in reshaping the cybersecurity landscape, the ethical implications of using advanced models, and the innovative strategies required to secure GenAI applications. Lastly, the book presents an in-depth analysis of the security challenges and potential solutions specific to GenAI, and a forward-looking view of how it can redefine cybersecurity practices. By addressing these topics, it provides answers to questions on how to secure GenAI applications, as well as vital support with understanding and navigating the complex and ever-evolving regulatory environments, and how to build a resilient GenAI security program. The book offers actionable insights and hands-on resources for anyone engaged in the rapidly evolving world of GenAI and cybersecurity.

Targeting people living with Human Immunodeficiency Virus, this research examined the prevalence of space-focused stereotypes and their underlying mechanism on behavioral inclinations. Study 1 adopted the explicit nomination and implicit Go/No-Go association tests to explore the existence of space-focused stereotypes of people living with HIV/AIDS. The results demonstrated that space-focused stereotypes were only manifested explicitly with characteristics such as messy, dirty, and gloomy. Study 2 demonstrated a more negative evaluation and community-approaching willingness for communities that include people living with HIV/AIDS than those without HIV/AIDS. Additionally, space-focused stereotypes were found to have an indirect influence on community-approaching willingness; the influence was mediated by both emotional and cognitive factors. These results indicate the deviation of explicit and implicit space-focused stereotypes. More importantly, it revealed that space-focused stereotypes decreased community evaluation and influenced behavioral inclination. This research suggested the existence of space-focused stereotypes on another stigmatized social group. Characteristics of space might be the key to forming space-focused stereotypes.