检索结果-内蒙古大学图书馆

Filaggrinopathies—FLG/FLG2: Diagnostic Complexities and Immunotherapy

Journal of Investigative Dermatology 2025年第7期145卷 1622-1632页

作者： Nouri, Zahra Biglari, Sajjad Tabatabaiefar, Mohammad Amin Vahidnezhad, Fatemeh Hozhabrpour, Amir March, Michael E. Margolis, David J. Gudjonsson, Johann E. Hakonarson, Hakon Vahidnezhad, Hassan Center for Applied Genomics Children's Hospital of Philadelphia Philadelphia PA United States Department of Genetics and Molecular Biology Isfahan University of Medical Sciences Isfahan Iran Department of Computer Science and Engineering Technology University of Maryland Eastern Shore Princess Anne MD United States Antimicrobial Resistance Research Center Institute of Immunology and Infectious disease Iran University of Medical Sciences Tehran Iran Department of Dermatology University of Pennsylvania Perelman School of Medicine Philadelphia PA United States Department of Dermatology University of Michigan Ann Arbor MI United States Division of Human Genetics Children's Hospital of Philadelphia Philadelphia PA United States Department of Pediatrics University of Pennsylvania Perelman School of Medicine Philadelphia PA United States

FLG and FLG2 proteins are expressed in the outer layers of the epidermis, where they are vital in epidermal differentiation and skin barrier formation. Filaggrinopathies involving dysfunctions in these proteins are associated with a spectrum of phenotypic presentations, from monogenic to multifactorial conditions. This review examines biosynthesis and function of FLG and FLG2 proteins and evaluates their molecular pathogenesis in filaggrinopathies. Moreover, genotype–phenotype correlations are assessed, emphasizing genetic diagnosis complexities and diverse immune dysregulation patterns. Finally, it examines ongoing immunotherapeutic approaches by targeting different cytokines as promising treatment options for filaggrinopathies management. © 2024 The Authors

关键词： Atopic dermatitis FLG FLG2 Inflammatory dermatoses Skin barrier disorders

来源：评论

学校读者我要写书评

暂无评论

Do Text-to-Text Multi-Task Learners Suffer from Task Conflict?

arXiv

引用

arXiv 2022年

作者： Mueller, David Andrews, Nicholas Dredze, Mark Department of Computer Science Johns Hopkins University United States Human Language Technology Center of Excellence Johns Hopkins University United States

Traditional multi-task learning architectures train a single model across multiple tasks through a shared encoder followed by task-specific decoders. Learning these models often requires specialized training algorithms that address task-conflict in the shared parameter updates, which otherwise can lead to negative transfer. A new type of multi-task learning within NLP homogenizes multi-task architectures as a shared encoder and language model decoder, which does surprisingly well across a range of diverse tasks (Raffel et al., 2020). Does this new architecture suffer from task-conflicts that require specialized training algorithms? We study how certain factors in the shift towards text-to-text models affects multi-task conflict and negative transfer, finding that both directional conflict and transfer are surprisingly constant across architectures. © 2022, CC BY.

关键词： Signal encoding

来源：评论

学校读者我要写书评

暂无评论

Mitigating Misleading Chain-of-Thought Reasoning with Selective Filtering

arXiv

引用

arXiv 2024年

作者： Wu, Yexin Zhang, Zhuosheng Zhao, Hai College of Zhiyuan Shanghai Jiao Tong University China School of Electronic Information and Electrical Engineering Shanghai Jiao Tong University China 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

Large language models have manifested remarkable capabilities by leveraging chain-of-thought (CoT) reasoning techniques to solve intricate questions through step-by-step reasoning chains. Despite its success, the efficacy of such reasoning is inherently contingent upon the quality of CoT. However, flawless CoT reasoning cannot be guaranteed due to the presence of indecomposable questions and the potential for erroneous reasoning chains, particularly in the case of small-scale language models. To tackle this challenge, we propose a novel approach called the selective filtering reasoner (SelF-Reasoner) that assesses the entailment relationship between the question and the candidate reasoning chain. Then, we proceed with CoT reasoning when the reasoning chain demonstrates confidence;otherwise, we opt to predict the answer directly. SelF-Reasoner improves the fine-tuned T5 baseline consistently over the scienceQA, ECQA, and LastLetter tasks. Code is available at https://***/LibroWu/SelF-Reasoner. © 2024, CC BY-SA.

关键词： Computational linguistics

来源：评论

学校读者我要写书评

暂无评论

MSA-GCN:Multiscale Adaptive Graph Convolution Network for Gait Emotion Recognition

arXiv

引用

arXiv 2022年

作者： Yin, Yunfei Jing, Li Huang, Faliang Yang, Guangchao Wang, Zhuowei The School of of Computer Science and Technology Chongqing University Chongqing China Guangxi Key Lab of Human-Machine Interaction and Intelligent Decision Nanning Normal University Nanning530001 China Faculty of Engineering and Information Technology University of Technology Sydney Australia

Gait emotion recognition plays a crucial role in the intelligent system. Most of the existing methods recognize emotions by focusing on local actions over time. However, they ignore that the effective distances of different emotions in the time domain are different, and the local actions during walking are quite similar. Thus, emotions should be represented by global states instead of indirect local actions. To address these issues, a novel MultiScale Adaptive Graph Convolution Network (MSA-GCN) is presented in this work through constructing dynamic temporal receptive fields and designing multiscale information aggregation to recognize emotions. In our model, a adaptive selective spatial-temporal graph convolution is designed to select the convolution kernel dynamically to obtain the soft spatiotemporal features of different emotions. Moreover, a Cross-Scale mapping Fusion Mechanism (CSFM) is designed to construct an adaptive adjacency matrix to enhance information interaction and reduce redundancy. Compared with previous state-of-the-art methods, the proposed method achieves the best performance on two public datasets, improving the mAP by 2%. We also conduct extensive ablations studies to show the effectiveness of different components in our methods. Copyright © 2022, The Authors. All rights reserved.

关键词： Emotion Recognition

来源：评论

学校读者我要写书评

暂无评论

Dwi-Based Virtual Mr Elastography Using Generative Model and Application on Liver Fibrosis Staging

SSRN

引用

SSRN 2024年

作者： Sun, Longyu Wang, Yikun Li, Yan Hu, Xumei Mao, Wenyue Sun, Mengting Wang, Zian Yan, Fuhua Li, Ruokun Wang, Chengyan Human Phenome Institute Fudan University Shanghai China Department of Radiology Ruijin Hospital Shanghai Jiao Tong University School of Medicine Shanghai China Institute of Science and Technology for Brain-Inspired Intelligence Fudan University Shanghai China School of Computer Science Fudan University Shanghai China

Background: Liver biopsy is the standard clinical method for diagnosing liver fibrosis. However, the inherent invasiveness of this procedure and the susceptibility to sampling errors introduces specific constraints. Therefore, non-invasive diagnostic techniques need to be developed. This study aimed to assess the reliability and reproducibility of virtual MR Elastography (vMRE) based on Diffusion Weighted Imaging (DWI) and evaluate its effectiveness in diagnosing liver fibrosis. Methods: We proposed a Registration-based Generative Adversarial Network-Convolutional Block Attention Module (RegGAN-CBAM) to synthesize virtual cMap (stiffness) and phiMap (viscosity). The correlation and agreement between the measurements (liver stiffness and viscosity) derived from native MRE (nMRE) and vMRE were assessed using the Spearman correlation coefficient and Bland-Altman analysis. Boxplots compared the fibrosis grading and distribution of cirrhosis between nMRE and vMRE. ROC curves were constructed to assess the diagnostic performance for cirrhosis. Findings: A total of 128 patients were included in this study. All of them had undergone magnetic resonance imaging examinations of the abdomen including MRE and DWI sequences. The RegGAN-CBAM model demonstrated favorable performance in image synthesis and liver stiffness/viscosity estimation. The virtual MRE (both cMap and phiMap) display notable similarity to native MRE in images, along with consistent liver stiffness and viscosity (r = 0.772 for cMap, 0.575 for phiMap, p © 2024, The Authors. All rights reserved.

关键词： Noninvasive medical procedures

来源：评论

学校读者我要写书评

暂无评论

Energy Efficiency Optimization for Full-Duplex D2D Communications Underlaying Distributed Antenna Systems

IEEE Transactions on Green Communications and Networking

引用

IEEE Transactions on Green Communications and Networking 2024年

作者： Liu, Zhan Liao, Zhiyuan Li, Chunquan Zhang, Zhijun Yu, Junzhi Liu, P.X. Hunan University of Humanities Science and Technology School of Information Loudi417000 China Nanchang University School of Information Engineering Nanchang330031 China Jiangxi Provincial Key Laboratory of Intelligent Systems and Human-Machine Interaction Nanchang330031 China South China University of Technology School of Automation Science and Engineering Guangzhou510640 China Peking University State Key Laboratory for Turbulence and Complex Systems Department of Advanced Manufacturing and Robotics College of Engineering Beijing100871 China Carleton University Department of Systems and Computer Engineering OttawaONK1S 5B6 Canada

In this paper, we investigate the total system energy efficiency (EE) of full-duplex (FD) device-to-device (D2D) communications underlaying distributed antenna systems (DAS), where remote access units (RAUs), D2D users (DUs), and cellular users (CUs) are all capable of FD operation. Specifically, we jointly optimize subcarrier assignment and power allocation under the quality of service (QoS) requirements of CUs and DUs and the maximum power constraints of RAUs, CUs, and DUs. In addition, we propose a novel spectrum sharing strategy that allows each subcarrier to be assigned to multiple CUs and/or multiple D2D pairs (DPs) for flexibility. To solve the formulated non-convex optimization problem, we first employ fractional programming to transform the objective function in the optimization problem from the fractional form into the equivalent subtractive form. Then, an efficient iterative resource allocation algorithm is proposed, which needs to solve an inner problem in each iteration. After relaxing the variables and introducing penalty factors, the non-convex inner problem is transformed into a convex problem through the successive convex approximation (SCA) method and solved by iterative algorithm. Simulation results demonstrate that the proposed algorithm can considerably improve the system EE compared to other benchmark schemes. Furthermore, the proposed spectrum sharing strategy is superior to the existing sharing strategies. © 2017 IEEE.

关键词： Convex optimization

来源：评论

学校读者我要写书评

暂无评论

Medical Image Synthesis Workbench Supporting Multiple Modalities with Feature-Level Transforms 1

Medical Image Synthesis Workbench Supporting Multiple Modali...

引用

1st IEEE International Conference on Innovations in High Speed Communication and Signal Processing, IHCSP 2023

作者： Sharma, Nitin Carlos Cotrina-Aliaga, Juan Philip Bhimavarapu, John Kumar Illa, Pavan Jyotiyana, Priya IMS Engineering College Uttar Pradesh India Universidad Privada San Juan Bautista Faculty of Human Medicine Chincha Peru Electronics and Communication Engineering Koneru Lakshmaiah Education Foundation Andhra Pradesh India Vallurupalli Nageswara Rao Vignana Jyothi Institute of Engineering & Technology Department of Information Technology Hyderabad India Jaipur Engineering College and Research Centre Computer Science and Engineering Jaipur India

ISBN: (纸本)9798350345957

Multi-modal In recent years, medical image synthesis has arisen as a holistic analytic strategy that typically employs many transformation methods. When it comes to medicine, multi-modal image synthesis refers to the technique of combining images from several imaging modalities to enhance image quality while maintaining detail. Image processing, computer apparition, pattern acknowledgment, machine knowledge, and artificial intellect are just few of the many cutting-edge fields that fall under the umbrella of medical image synthesis. The synthesis of many medicinal imaging modalities has been used extensively in the clinic to help doctors better understand the lesion. This paper presents the firefly algorithm, a multi-learning model workbench that minimises squared errors and maximises synthesis quality via weighted entropy. MATLAB simulations are used to compare the proposed workbench against state-of-the-art methods in terms of peak signal-to-noise ratio, Mean square error, correlation, and precision. The proposed workbench performs well across the board and requires less computing power. © 2023 IEEE.

关键词： Image enhancement

来源：评论

学校读者我要写书评

暂无评论

Investigating the interaction Experience with Augmented Reality Based Writing Tools 21st

Investigating the Interaction Experience with Augmented Real...

引用

21st International Conference on human-computer interaction, HCI International 2019

作者： Zheng, Wei Yi, Xin Shi, Yuanchun Pervasive Human-Computer Interaction Group Department of Computer Science and Technology Tsinghua University Beijing100084 China

ISBN: (纸本)9783030235277

The contents of this paper include the design methodology of perceptual computing products, the innovative design of the AR writing and its technical feasibility, the writing interactive experience test of different hardware platforms, etc. It has certain reference value for the research work of paperless writing. © Springer Nature Switzerland AG 2019.

关键词： Augmented reality

来源：评论

学校读者我要写书评

暂无评论

Multi-level Gate Feature Aggregation with Spatially Adaptive Batch-Instance Normalization for Semantic Image Synthesis 27th

Multi-level Gate Feature Aggregation with Spatially Adaptive...

引用

27th International Conference on MultiMedia Modeling, MMM 2021

作者： Long, Jia Lu, Hongtao Key Lab of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai China MoE Key Lab of Artificial Intelligence AI Institute Shanghai Jiao Tong University Shanghai China

ISBN: (纸本)9783030678319

In this paper, we focus on the task of generating realistic images given an input semantic layout, which is also called semantic image synthesis. Most of previous methods are based on conditional generative adversarial networks mechanism, which is stacks of convolution, normalization, and non-linearity layers. However, these methods easily generate blurred regions and distorted structures. There are two limits existing: their normalization layers are unable to make a good balance between keeping semantic layout information and geometric changes;and cannot effectively aggregated multi-level feature. To address the above problems, we propose a novel method which incorporates multi-level gate feature aggregation mechanism (GFA) and spatially adaptive batch-instance normalization (SPAda-BIN) for semantic image synthesis. Experiments on several challenging datasets demonstrate the advantage of the proposed method over existing approaches, in terms of both visual fidelity and quantitative metrics. © 2021, Springer Nature Switzerland AG.

关键词： Semantics

来源：评论

学校读者我要写书评

暂无评论

Robust language-based mental health assessments in time and space through social media

arXiv

引用

arXiv 2023年

作者： Mangalik, Siddharth Eichstaedt, Johannes C. Giorgi, Salvatore Mun, Jihu Ahmed, Farhan Gill, Gilvir Ganesan, Adithya V. Subrahmanya, Shashanka Soni, Nikita Clouston, Sean A.P. Schwartz, H. Andrew Department of Computer Science Stony Brook University Stony BrookNY United States Department of Psychology Stanford University StanfordCA United States Institute for Human-Centered A.I. Stanford University CA United States Department of Family Population and Preventive Medicine Renaissance School of Medicine Stony Brook University Stony BrookNY United States Department of Computer and Information Science University of Pennsylvania United States

Compared to physical health, population mental health measurement in the U.S. is very coarse-grained. Currently, in the largest population surveys, such as those carried out by the Centers for Disease Control or Gallup, mental health is only broadly captured through "mentally unhealthy days" or "sadness", and limited to relatively infrequent state or metropolitan estimates. Through the large scale analysis of social media data, robust estimation of population mental health is feasible at much higher resolutions, up to weekly estimates for counties. In the present work, we validate a pipeline that uses a sample of 1.2 billion Tweets from 2 million geo-located users to estimate mental health changes for the two leading mental health conditions, depression and anxiety. We find moderate to large associations between the language-based mental health assessments and survey scores from Gallup for multiple levels of granularity, down to the county-week (fixed effects β = .25 to 1.58;p © 2023, CC BY-SA.

关键词： Cost effectiveness

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：