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Insight into the liver dysfunction in COVID-19 patients: Molecular mechanisms and possible therapeutic strategies

World Journal of Gastroenterology 2023年第14期29卷 2064-2077页

作者： Naina Khullar Jasvinder Singh Bhatti Satwinder Singh Bhawana Thukral P Hemachandra Reddy Gurjit Kaur Bhatti Department of Zoology Mata Gujri CollegeFatehgarh Sahib 140407PunjabIndia Laboratory of Translational Medicine and Nanotherapeutics Department of Human Genetics and Molecular MedicineSchool of Health SciencesCentral University of PunjabBathinda 151401PunjabIndia Department of Computer Science and Technology Central University of PunjabBathinda 151401PunjabIndia Department of Nutrition and Dietetics University Institute of Applied Health SciencesChandigarh UniversityMohali 140413PunjabIndia Department of Internal Medicine Texas Tech University Health Sciences CenterLubbockTX 79430United States Department of Medical Lab Technology University Institute of Applied Health SciencesChandigarh UniversityMohali 140413PunjabIndia

As of June 2022,more than 530 million people worldwide have become ill with coronavirus disease 2019(COVID-19).Although COVID-19 is most commonly associated with respiratory distress(severe acute respiratory syndrome),metaanalysis have indicated that liver dysfunction also occurs in patients with severe *** studies revealed distinctive patterning in the receptors on the hepatic cells that helps in viral invasion through the expression of angiotensinconverting enzyme *** has also been reported that in some patients with COVID-19,therapeutic strategies,including repurposed drugs(mitifovir,lopinavir/ritonavir,tocilizumab,etc.)triggered liver injury and cholestatic *** proven indicators support cytokine storm-induced hepatic *** there are 1.5 billion patients with chronic liver disease worldwide,it becomes imperative to critically evaluate the molecular mechanisms concerning hepatotropism of COVID-19 and identify new potential *** review also designated a comprehensive outlook of comorbidities and the impact of lifestyle and genetics in managing patients with COVID-19.

关键词： COVID-19 Liver damage Pharmacotherapy Cytokine storm Molecular mechanisms

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LaCo: Large Language Model Pruning via Layer Collapse

arXiv

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arXiv 2024年

作者： Yang, Yifei Cao, Zouying Zhao, Hai Department of Computer Science and Engineering Shanghai Jiao Tong University China Key Laboratory of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering Shanghai Jiao Tong University China Shanghai Key Laboratory of Trusted Data Circulation and Governance in Web3 China

Large language models (LLMs) based on transformer are witnessing a notable trend of size expansion, which brings considerable costs to both model training and inference. However, existing methods such as model quantization, knowledge distillation, and model pruning are constrained by various issues, including hardware support limitations, the need for extensive training, and alterations to the model internal structure. In this paper, we propose a concise layer-wise structured pruner called Layer Collapse (LaCo), in which rear model layers collapse into a prior layer, enabling a rapid reduction in model size while preserving the model structure. Comprehensive experiments show that our method maintains an average task performance of over 80% at pruning ratios of 25-30%, significantly outperforming existing state-of-the-art structured pruning methods. We also conduct post-training experiments to confirm that the LaCo effectively inherits the parameters of the original model. Additionally, we perform ablation studies on various settings of LaCo. Finally, we discuss our motivation from the perspective of layer-wise similarity and evaluate the performance of the pruned LLMs across various pruning ratios Copyright © 2024, The Authors. All rights reserved.

关键词： Digital elevation model

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UMAP and Tree Physiology Optimization for Effective Water Quality Management in Consumer Electronics

UMAP and Tree Physiology Optimization for Effective Water Qu...

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2025 IEEE International Conference on Consumer Electronics, ICCE 2025

作者： Gupta, Brij B. Gaurav, Akshat Bansal, Shavi Wu, Jinsong Arya, Varsha Chui, Kwok Tai Department of Computer Science and Information Engineering Asia University Taichung413 Taiwan University of Economics and Human Science Warsaw Poland Ronin Institute MontclairNJ United States Insights2Techinfo India Department of Electrical Engineering Universidad de Chile Chile Hong Kong

ISBN: (纸本)9798331521165

Leveraging UMAP for feature selection and Tree Physiology Optimization (TPO) for hyperparameter tuning, we proposed model for efficient water quality control in consumer electronics. We balanced the data with SMOTE from a Kaggle water quality dataset and using UMAP to find important characteristics. The TPO method then was used to maximize the parameters of the deep learning model. With an eye on few false positives, our algorithm was very accurate in spotting clean water. Still, the confusion matrix shows that there are difficulties precisely identifying dangerous water. © 2025 IEEE.

关键词： Reliability

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Semantics-Controlled Gaussian Splatting for Outdoor Scene Reconstruction and Rendering in Virtual Reality

arXiv

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arXiv 2024年

作者： Schieber, Hannah Young, Jacob Langlotz, Tobias Zollmann, Stefanie Roth, Daniel Erlangen Germany Department of Computer Science University of Otago Dunedin New Zealand Technical University of Munich Human-Centered Computing and Extended Reality Lab TUM University Hospital Orthopedics and Sports Orthopedics Germany

Advancements in 3D rendering like Gaussian Splatting (GS) allow novel view synthesis and real-time rendering in virtual reality (VR). However, GS-created 3D environments are often difficult to edit. For scene enhancement or to incorporate 3D assets, segmenting Gaussians by class is essential. Existing segmentation approaches are typically limited to certain types of scenes, e.g., "circular" scenes, to determine clear object boundaries. However, this method is ineffective when removing large objects in non-"circling" scenes such as large outdoor scenes. We propose Semantics-Controlled GS (SCGS), a segmentationdriven GS approach, enabling the separation of large scene parts in uncontrolled, natural environments. SCGS allows scene editing and the extraction of scene parts for VR. Additionally, we introduce a challenging outdoor dataset, overcoming the "circling" setup. We outperform the state-of-the-art in visual quality on our dataset and in segmentation quality on the 3D-OVS dataset. We conducted an exploratory user study, comparing a 360-video, plain GS, and SCGS in VR with a fixed viewpoint. In our subsequent main study, users were allowed to move freely, evaluating plain GS and SCGS. Our main study results show that participants clearly prefer SCGS over plain GS. We overall present an innovative approach that surpasses the state-of-the-art both technically and in user experience. © 2024, CC BY.

关键词： Virtual environments

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Structural and functional neural correlates of sensorimotor deficits in progression of hepatic encephalopathy

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Magnetic Resonance Letters 2025年第2期5卷 1-10页

作者： Sha, Guanchen Liu, Yuefan Cao, Yutong Zhang, Qi Zhang, Yining Chen, Yuanyuan Fan, Qiuyun Cheng, Yue Department of Biomedical Engineering College of Precision Instruments and Optoelectronics Engineering Tianjin University Tianjin300072 China Tianjin Key Laboratory of Brain Science and Neuroengineering Tianjin300072 China Academy of Medical Engineering and Translational Medicine Tianjin University Tianjin300072 China Department of Medical Imaging Tianjin First Central Hospital Tianjin300192 China Haihe Laboratory of Brain-Computer Interaction and Human-Machine Integration Tianjin300392 China State Key Laboratory of Advanced Medical Materials and Devices Tianjin300072 China

Hepatic encephalopathy (HE) is a neurological condition that occurs as a complication of liver dysfunction that involves sensorimotor symptoms in addition to cognitive and behavioral changes, particularly in cases of severe liver disease or cirrhosis. Previous studies have reported spatially distributed structural and functional abnormalities related to HE, but the exact relationship between the structural and functional alterations with respect to disease progression remains unclear. In this study, we performed surface-based cortical thickness comparisons and functional connectivity (FC) analyses between three cross-sectional groups: healthy controls (HC, N = 51), patients with minimal hepatic encephalopathy (MHE, N = 50), patients with overt hepatic encephalopathy (OHE, N = 51). In addition to the distributed cortical thinning that is extensively thought to be associated with cognitive decline in HE, we found significant cortical thickening in the left parahippocampal gyrus cortex in the OHE group (p © 2025 The Authors

关键词： Diseases

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Network Properties Analysis in Stroke Patients Based on the resting-state EEG 23

Network Properties Analysis in Stroke Patients Based on the ...

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Proceedings of the 2023 10th International Conference on Biomedical and Bioinformatics Engineering

作者： Zhongpeng Wang Jinxiang Nan Yijie Zhou Long Chen Shuang Liu Minpeng Xu Qi Li Dong Ming Academy of Medical Engineering and Translational Medicine Tianjin University China and Haihe Laboratory of Brain-computer Interaction and Human-machine Integration China Academy of Medical Engineering and Translational Medicine Tianjin University China Academy of Medical Engineering and Translational Medicine Tianjin University China and Department of Rehabilitation Tianjin Hospital China

ISBN: (纸本)9798400708343

In recent years, the researches on brain networks in stroke patients based on EEG signals have attracted attention. Few of them have investigated the specific patterns of FCs across metrics. In this paper, we focus on the lesion properties of common brain regions under different network metrics. Phase synchronization indexes (PSI) between EEG channels were calculated to construct graph theory networks in the Alpha and Beta bands for stroke patients and healthy controls. Network metrics degree, clustering coefficient, and local efficiency were utilized to characterize brain network differences between groups. The results revealed that in Alpha band, patients were characterized by a lower clustering coefficient and exhibited lower global efficiency and lower degree in the Beta band. Regionally, the motor cortex and parietal cortex were identified as common impaired regions across all network metrics, performing weaker capacity for information transfer and integration, which may explain their motor disability. The findings of our study will play an important role in motor evaluation after stroke.

关键词： Electroencephalography (EEG) graph theory phase synchronization index (PSI) stroke

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Prediction of Parkinson’s disease based on artificial neural networks using speech datasets

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Journal of Ambient Intelligence and humanized Computing 2023年第10期14卷 13571-13584页

作者： Liu, Wei Liu, Jierong Peng, Tao Wang, Guojun Balas, Valentina Emilia Geman, Oana Chiu, Hung-Wen School of Information and Communication Engineering Hainan University Hainan Haikou570228 China School of Computer Science and Cyber Engineering Guangzhou University Guangdong Guangzhou510006 China College of Biomedical Information and Engineering Hainan Medical University Street Hainan Haikou571199 China Department of Automation and Applied Informatics Aurel Vlaicu University of Arad Arad310130 Romania Department of Health and Human Development Stefan cel Mare University of Suceava Suceava720229 Romania Graduate Institute of Biomedical Informatics Taipei Medical University Taipei Taiwan

Parkinson’s disease (PD) is a progressive disorder of the nervous system that affects movement. Early prediction of PD can increase the chances of earlier intervention and delay the onset of the disease. Vocal impairment is one of the most important signs in the early stages of PD. Therefore, PD detection based on speech analysis and vocal patterns has attracted significant attention recently. In this paper, we propose a vowel-based artificial neural network (ANN) model for PD prediction based on single vowel phonation. Firstly, we propose a novel multi-layer neural network based on speech features to predict PD. The speech samples from 48 PD patients and 20 healthy individuals are processed into four types: vowel, number, word, and short sentence. Secondly, we establish ANN models with single-type speech samples versus combinations of multi-type speech samples, respectively. Comparative experiments demonstrate that the single-type vowel model is superior to other single-type models as well as multi-type models. Finally, we build a vowel-based ANN model for PD prediction and evaluate its performance. Extensive experiments demonstrate that the proposed model has a prediction accuracy of 91%, sensitivity of 99%, specificity of 82%, and area under the receiver operating characteristic curve (AUC) of 91%, which is superior to the performance of previous methods. Overall, this study demonstrates that the proposed model can provide good classification accuracy for predicting PD and can improve the rate of early diagnosis. © 2022, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Network layers

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Preface: Security and safety in artificial intelligence

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Security and Safety 2024年第4期3卷 4-5页

作者： Hao Zhang Yu-Gang Jiang Claudio Melchiorri Gerhard Rigoll Department of Control Science and Engineering Tongji UniversityShanghai 200092China Shanghai Institute of Intelligent Science and Technology Shanghai 201210China School of Computer Science Fudan UniversityShanghai 200433China Department of Electrical Electronic and Information EngineeringUniversity of BolognaBologna 40136Italy Institute for Human-Machine Communication Technical University of MunichMunich 80539Germany

This special topic centers on cutting-edge advancements in the security and safety of artificial intelligence(AI),with a focus on critical applications across domains such as autonomous systems,federated learning,and network *** rapid evolution of AI algorithms,enabled by advances in hardware and software,has led to transformative applications but also revealed significant vulnerabilities and security risks.

关键词： artificial hardware autonomous

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Profiles in brain type in programming performance for non-vocational courses 10th

Profiles in brain type in programming performance for non-vo...

引用

10th International Conference in Methodologies and Intelligent Systems for Technology Enhanced Learning, MIS4TEL 2020

作者： Solitro, Ugo Brondino, Margherita Bonafini, Roberto Pasini, Margherita Department of Computer Science and Department of Human Sciences University of Verona Verona Italy

ISBN: (纸本)9783030525378

Learning a programming language and solving problems in an algorithmic way is a hard task for many students. A better comprehension of the psychological characteristics involved in this process is needed to reduce these difficulties, implementing teaching methodologies sensitive to these aspects. In this study, we analyse the relationship between cognitive styles, inside the theoretical framework of the empathizing–systemizing (E–S) theory, and performance, also considering the role of sex. In fact, E-S theory states the difference in male and female mind, the first one more empathy-oriented, the second one more oriented at understanding systems. A sample of 56 students attending a course of programming in an Applied Mathematics with a relevant practical activity enhanced with a submission system and supported by a few tutors was involved in the study. We defined profiles of students based on their scores in EQ and SQ, and on their sex, using a cluster analysis. 4 clusters were found: 1. female students with low level of SQ and high level of EQ;2. female students with high level of both SQ and EQ;3. male students, with low level of EQ and high level of;4. male students with low level of both SQ and EQ. A first exploration of the relation of profiles with the learning performance is described. © The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2020.

关键词： Students

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A Novel Approach to Social Sustainability with Machine Learning and the Best Worst Method in Manufacturing 1

A Novel Approach to Social Sustainability with Machine Learn...

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1st International Conference on Advanced Computing and Emerging Technologies, ACET 2024

作者： Yogi, Kottala Sri Franklin Jino, R.E. Dankan Gowda, V. Murthy, C. Ravindra Prasad, Veduri Veera Srinivas, Ved Hyderabad Symbiosis International University Symbiosis Institute of Business Management Department of Operations Pune India V.S.B. Engineering College Department of Information Technology Tamilnadu Karur India Bms Institute of Technology and Management Department of Electronics and Communication Engineering Karnataka Bangalore India Mohan Babu University School of Engineering Department of Ece Andhra Pradesh Tirupati India Aditya College of Engineering and Technology Department of Computer Science & Engineering Andhra Pradesh Surampalem India Thiagarajar School of Management Department of Human Resources Tamil Nadu Madurai India

ISBN: (纸本)9798350367720

This paper is aimed at presenting a novel approach for enhancing the measurement of social sustainability in manufacturing domain with the help of ML with BWM. Social sustainability when dealing with manufacturing is part of the four sustainability pillars that seeks to address aspects such as;welfare of workers, social organization, and practice within the firm. This is why the conventional tools may not sufficiently inform on the right combination of the said aspects. The information from the big data is then processed by the means of ML to disclose the patterns illuminating the stance influences and BWM is integrated to analyze specialists' insight the power of evolving influential aspects of stance. They are useful in minimizing the time as well as the energy required in the formulation of the decisions because the details and correlations needed are already provided. It is illustrated with the help of an example in the manufacturing setting and significant improvements in the values of the social sustainability indices compared to the classical approach. From these conclusions, it is possible to indicate the prospects for the integration of ML and BWM as the authors' contribution to tackling the problem of social sustainability in the manufacturing sector. © 2024 IEEE.

关键词： Smart manufacturing

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