Catalogue Search | MBRL
Are you sure you want to remove the book from the shelf?
{{itemTitle}}
52,351
result(s) for
"Yu, Yan"
Sort by:
Multi-feature deep learning framework for predicting CO adsorption mechanisms at metal oxide interfaces: a transformer-based approach
This study presents a novel multi-feature deep learning framework that integrates Transformer architecture with readily computable molecular descriptors to predict CO adsorption mechanisms at single metal oxide interfaces. The framework employs specialized encoders for structural, electronic, and kinetic descriptors, utilizing cross-feature attention mechanisms to capture the multifaceted nature of catalytic processes. Unlike traditional approaches requiring expensive DFT calculations, our method uses empirical descriptors and pre-computed parameters that can be rapidly obtained for practical catalyst screening applications. Comprehensive evaluation across seven distinct metal oxide systems demonstrates superior performance over traditional machine learning methods, achieving mean absolute errors below 0.12 eV for adsorption energy prediction and correlation coefficients exceeding 0.92. Systematic ablation studies reveal the hierarchical importance of different data modalities, with structural information providing the most critical contribution. Case studies on CeO₂, TiO₂, and ZnO validate the model’s capability to distinguish material-specific mechanisms and provide mechanistic insights consistent with experimental observations. The multi-feature approach successfully predicts coverage-dependent effects, surface termination influences, and defect-mediated processes, establishing a foundation for data-driven catalyst design and mechanism elucidation in sustainable catalysis applications.
Journal Article
Enhanced dust emission following large wildfires due to vegetation disturbance
Large wildfires reduce vegetation cover and soil moisture, leaving the temporally degraded landscapes an emergent source of dust emission. However, the global extent of post-fire dust events and their influencing factors remain unexplored. Using satellite measurements of active fires, aerosol abundance, vegetation cover and soil moisture from 2003 to 2020, here we show that 54% of the examined ~150,000 global large wildfires are followed by enhanced dust emission, producing substantial dust loadings for days to weeks over normally dust-free regions. The occurrence and duration of post-fire dust emission is controlled primarily by the extent of precedent wildfires and resultant vegetation anomalies and modulated secondarily by pre-fire drought conditions. The intensifying wildfires and drying soils during the studying period have made post-fire dust events one day longer, especially over extratropical forests and grasslands. With the predicted intensification of regional wildfires and concurrent droughts in the upcoming decades, our results indicate a future enhancement of sequential fire and dust extremes and their societal and ecological impacts.
Enhanced dust emissions are associated with more than half of the global large wildfire events occurring between 2003 and 2020, according to analyses of satellite measurements of aerosol abundance following more than 150,000 global wildfires.
Journal Article
عبارات \غامضة\ عن الصين : مقالات في الجغرافيا البشرية
هذا الكتاب هو الجزء الأول من سلسلة كتب \"الحكمة الصينية\" ويأتي تحت عنوان (عبارات \"غامضة\" عن الصين : مقالات في الجغرافيا البشرية)، وجمع بين دفتيه ما مجموعة أربعة عشر مصطلحا متعلقا بالجغرافيا البشرية، ومن بينها \"الأقاليم التسعة\"، \"العالم\"، \"النهر الأصفر\"، \"سور الصين العظيم\"، \"المدينة\"، \"و\"العاصمة\"، وغيرها، ويتمثل الغرض الرئيسي للكتاب في تعريف الأطفال بالجغرافيا الصينية التقليدية، وتعميم معارف الجغرافيا البشرية في نفس الوقت، وهو الأمر الذي يترك الأطفال يستكشفون المعنى الثقافي وراء المصطلحات والمفردات الشائعة.
Book
Cervical squamous cell carcinoma-secreted exosomal miR-221-3p promotes lymphangiogenesis and lymphatic metastasis by targeting VASH1
Cancer-secreted exosomal miRNAs are emerging mediators of cancer-stromal cross-talk in the tumor environment. Our previous miRNAs array of cervical squamous cell carcinoma (CSCC) clinical specimens identified upregulation of miR-221-3p. Here, we show that miR-221-3p is closely correlated with peritumoral lymphangiogenesis and lymph node (LN) metastasis in CSCC. More importantly, miR-221-3p is characteristically enriched in and transferred by CSCC-secreted exosomes into human lymphatic endothelial cells (HLECs) to promote HLECs migration and tube formation in vitro, and facilitate lymphangiogenesis and LN metastasis in vivo according to both gain-of-function and loss-of-function experiments. Furthermore, we identify vasohibin-1 (VASH1) as a novel direct target of miR-221-3p through bioinformatic target prediction and luciferase reporter assay. Re-expression and knockdown of VASH1 could respectively rescue and simulate the effects induced by exosomal miR-221-3p. Importantly, the miR-221-3p-VASH1 axis activates the ERK/AKT pathway in HLECs independent of VEGF-C. Finally, circulating exosomal miR-221-3p levels also have biological function in promoting HLECs sprouting in vitro and are closely associated with tumor miR-221-3p expression, lymphatic VASH1 expression, lymphangiogenesis, and LN metastasis in CSCC patients. In conclusion, CSCC-secreted exosomal miR-221-3p transfers into HLECs to promote lymphangiogenesis and lymphatic metastasis via downregulation of VASH1 and may represent a novel diagnostic biomarker and therapeutic target for metastatic CSCC patients in early stages.
Journal Article
Reciprocity, evolution, and decision games in network and data science
\"Learn how to analyze and manage evolutionary and sequential user behaviors in modern networks, and how to optimize network performance by using indirect reciprocity, evolutionary games, and sequential decision-making. Understand the latest theory without the need to go through the details of traditional game theory. With practical management tools to regulate user behavior and simulations and experiments with real data sets, this is an ideal tool for graduate students and researchers working in networking, communications, and signal processing\"-- Provided by publisher.
Book
RASP 4: Ancestral State Reconstruction Tool for Multiple Genes and Characters
With the continual progress of sequencing techniques, genome-scale data are increasingly used in phylogenetic studies. With more data from throughout the genome, the relationship between genes and different kinds of characters is receiving more attention. Here, we present version 4 of RASP, a software to reconstruct ancestral states through phylogenetic trees. RASP can apply generalized statistical ancestral reconstruction methods to phylogenies, explore the phylogenetic signal of characters to particular trees, calculate distances between trees, and cluster trees into groups. RASP 4 has an improved graphic user interface and is freely available from http://mnh.scu.edu.cn/soft/blog/RASP (program) and https://github.com/sculab/RASP (source code).
Journal Article
Metabolomics Signatures in Type 2 Diabetes: A Systematic Review and Integrative Analysis
Abstract
Objective
Metabolic signatures have emerged as valuable signaling molecules in the biochemical process of type 2 diabetes (T2D). To summarize and identify metabolic biomarkers in T2D, we performed a systematic review and meta-analysis of the associations between metabolites and T2D using high-throughput metabolomics techniques.
Methods
We searched relevant studies from MEDLINE (PubMed), Embase, Web of Science, and Cochrane Library as well as Chinese databases (Wanfang, Vip, and CNKI) inception through 31 December 2018. Meta-analysis was conducted using STATA 14.0 under random effect. Besides, bioinformatic analysis was performed to explore molecule mechanism by MetaboAnalyst and R 3.5.2.
Results
Finally, 46 articles were included in this review on metabolites involved amino acids, acylcarnitines, lipids, carbohydrates, organic acids, and others. Results of meta-analysis in prospective studies indicated that isoleucine, leucine, valine, tyrosine, phenylalanine, glutamate, alanine, valerylcarnitine (C5), palmitoylcarnitine (C16), palmitic acid, and linoleic acid were associated with higher T2D risk. Conversely, serine, glutamine, and lysophosphatidylcholine C18:2 decreased risk of T2D. Arginine and glycine increased risk of T2D in the Western countries subgroup, and betaine was negatively correlated with T2D in nested case-control subgroup. In addition, slight improvements in T2D prediction beyond traditional risk factors were observed when adding these metabolites in predictive analysis. Pathway analysis identified 17 metabolic pathways may alter in the process of T2D and metabolite-related genes were also enriched in functions and pathways associated with T2D.
Conclusions
Several metabolites and metabolic pathways associated with T2D have been identified, which provide valuable biomarkers and novel targets for prevention and drug therapy.
Journal Article