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Mitochondrial Complex Mutants Can Modulate Responses to Stresses Associated with Reduced Water Availability

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SSRN

SSRN 2023年

作者： Zsigmond, Laura Alexandra Juhász-Erdélyi, Annabella Valkai, Ildikó Alexa, Dávid Rigó, Gábor Kant, Kamal Szepesi, Ágnes Fiorani, Fabio Körber, Niklas Kovács, László Szabados, László Institute of Plant Biology HUN-REN Biological Research Centre Szeged Hungary Department of Plant Biology Faculty of Science and Informatics University of Szeged Szeged Hungary Institut für Bio- und Geowissenschaften Forschungszentrum Jülich GmbH Jülich Germany Nunhems - BASF Vegetable Seeds Department of Data Science and Technology Roermond Netherlands

Mitochondria are important sources of energy in plants and are implicated in coordination of a number of metabolic and physiological processes including stabilization of redox balance, synthesis and turnover of several metabolites, and control of programmed cell death. Mitochondrial electron transport chain (mETC) is the backbone of the energy producing process which can influence other processes as well. Accumulating evidence suggests that mETC can affect responses to environmental stimuli and modulate tolerance to extreme conditions such as drought or salinity. Screening for stress responses of 13 Arabidopsis mitochondria-related T-DNA insertion mutants, we identified ndufs8.2-1 which has an increased ability to withstand osmotic and oxidative stresses compared to wild type plants. Insertion in ndufs8.2-1 disrupted the gene that encodes the NADH dehydrogenase [ubiquinone] fragment S subunit 8 (NDUFS8) subunit of Complex I of mETC. ndufs8.2-1 tolerated reduced water availability, retained photosynthetic activity and recovered from severe water stress with higher efficiency compared to wild type plants. Several mitochondrial functions were altered in the mutant including oxygen consumption, ROS production, ATP and ADP content as well as activities of genes encoding alternative oxidase 1A (AOX1A) and various alternative NAD(P)H dehydrogenases (ND). Our results suggest, that certain mETC components such as NDUFS8.2 are implicated in redox and energy homeostasis which can modulate responses to stresses associated with reduced water availability. © 2023, The Authors. All rights reserved.

关键词： Mitochondria

Multimodal E-Commerce Product Classification Using Hierarchical Fusion

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arXiv 2022年

作者： Tashu, Tsegaye Misikir Fattouh, Sara Kiss, Péter Horváth, Tomáš Department of Data Science and Engineering Faculty of Informatics ELTE - Eötvös Loránd University Pazmány Péter sétány 1/C Budapest1117 Hungary Faculty of Science Institute of Computer Science Pavol Jozef Šafárik University Jesenná 5 Košice040 01 Slovakia College of Informatics Kombolcha Institute of Technology Wollo University Kombolcha208 Ethiopia

In this work, we present a multi-modal model for commercial product classification, that combines features extracted by multiple neural network models from textual (CamemBERT and FlauBERT) and visual data (SE-ResNeXt-50), using simple fusion techniques. The proposed method significantly outperformed the unimodal models' performance and the reported performance of similar models on our specific task. We did experiments with multiple fusing techniques and found, that the best performing technique to combine the individual embedding of the unimodal network is based on combining concatenation and averaging the feature vectors. Each modality complemented the shortcomings of the other modalities, demonstrating that increasing the number of modalities can be an effective method for improving the performance of multi-label and multimodal classification problems. © 2022, CC BY.

关键词： Electronic commerce

Gamefication of Youth's Career Guidance Self-Identification

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Gamefication of Youth's Career Guidance Self-Identification

2022 International Conference on Smart Information Systems and Technologies, SIST 2022

作者： Poliakov, Mykyta Mezzane, Daoud Terenchuk, Svitlana Riabchun, Yuliia Rusnak, Patrik Biloshchytska, Svitlana Kyiv National University Of Construction And Architecture Department Of Information Technology Design And Applied Mathematics Kyiv Ukraine Inovative Materials Energy And Sustainable Devellopment Laboratpry Cadi Ayyad University Marrakech Morocco Kyiv National University Of Construction And Architecture Department Of Information Technology Kyiv Ukraine University Of Zilina Faculty Of Management Science And Informatics Zilina Slovakia Astana It University Department Of Computer Technology And Data Nur-Sultan Kazakhstan

ISBN: (数字)9781665467902

ISBN: (纸本)9781665467902

The work is devoted to solving the youth's professional orientation problem in modern conditions of limited offline communication. The urgency of development of new methods and tools of adolescents' professional orientation, which are based on modern information technologies, is shown. The research's focus is aimed at the introduction of computer game technologies in the work of career guidance centers, pre-university departments of colleges and higher education institutions. The expediency and effectiveness of the existing professional orientation computer game tasks usage in career guidance work with youth who need decision support at the stage of choosing a future profession are substantiated. It is shown that in the conditions of virtual reality the estimate reliability of personal qualities for compliance with a certain professional activity depends on the selection of game tasks. A clear criterion for automatic measurement of activity interest in professional activity, which depends on the task selection time, is proposed. There are fragments of computer game tasks that allow a person to self-estimate their ability to perform activities in different situations and professional relationships without communicating with career counselors and psychologists. © 2022 IEEE.

关键词： Computer games

Multimodal Feature Extraction for Memes Sentiment Classification

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arXiv 2022年

作者： Ouaari, Sofiane Tashu, Tsegaye Misikir Horváth, Tomáš Department of Data Science and Engineering Faculty of Informatics ELTE - Eötvös Loránd University Pazmány Péter sétány 1/C Budapest1117 Hungary Institute of Computer Science Faculty of Science Pavol Jozef Šafárik University Jesenná 5 Košice040 01 Slovakia College of Informatics Kombolcha Institute of Technology Wollo University Kombolcha208 Ethiopia

In this study, we propose feature extraction for multimodal meme classification using Deep Learning approaches. A meme is usually a photo or video with text shared by the young generation on social media platforms that expresses a culturally relevant idea. Since they are an efficient way to express emotions and feelings, a good classifier that can classify the sentiment behind the meme is important. To make the learning process more efficient, reduce the likelihood of overfitting, and improve the generalizability of the model, one needs a good approach for joint feature extraction from all modalities. In this work, we proposed to use different multimodal neural network approaches for multimodal feature extraction and use the extracted features to train a classifier to identify the sentiment in a meme. © 2022, CC BY.

关键词： Computer vision

Micromechanics Simulations Coupling the *** Software Library With a Parallel FETI-DP Solver 26th

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Micromechanics Simulations Coupling the *** Software Library...

26th International Conference on Domain Decomposition Methods, 2020

作者： Köhler, S. Rheinbach, O. Sandfeld, S. Institut für Numerische Mathematik und Optimierung Fakultät für Mathematik und Informatik Technische Universität Bergakademie Freiberg Akademiestr. 6 Freiberg09596 Germany Forschungszentrum Jülich Wilhelm-Johnen-Straße Jülich52428 Germany Chair of Materials Data Science and Materials Informatics Faculty 5 RWTH Aachen University Aachen52072 Germany

ISBN: (纸本)9783030950248

We consider adaptive finite elements, using the open source finite element library *** [1], and an implementation [11] of the FETI-DP (Finite Element Tearing and Interconnecting Dual–Primal) method based on PETSc, for the solution of problems from dislocation micromechanics. The library *** is well known for its adaptive finite element approach based on hanging node constraints. The parallel data structures in *** are meant to be used with global parallel matrices, which are assembled across the interface. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.

关键词： Composite micromechanics

Adaptability of Existing Feasibility Tools for Clinical Study Research data Platforms

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Adaptability of Existing Feasibility Tools for Clinical Stud...

68th Annual Meeting of the German Association of Medical informatics, Biometry, and Epidemiology: science. Close to People, GMDS 2023

作者： Witte, Marie-Louise Schoneberg, Anne Hanss, Sabine Lablans, Martin Vehreschild, Janne Krefting, Dagmar Department of Medical Informatics University Medical Center Göttingen Germany German Centre for Cardiovascular Research Partner Site Göttingen Germany German Cancer Research Center Heidelberg Germany Cdpmi Medical Faculty Mannheim Heidelberg University Germany Department i of Internal Medicine University Hospital Cologne Germany German Centre for Infection Research Partner Site Bonn-Cologne Germany Department Ii for Internal Medicine University Hospital Frankfurt Germany Campus Institute Data Science Georg-August-University Göttingen Germany

ISBN: (纸本)9781643684284

Introduction: The increasing need for secondary use of clinical study data requires FAIR infrastructures, i.e. provide findable, accessible, interoperable and reusable data. It is crucial for data scientists to assess the number and distribution of cohorts that meet complex combinations of criteria defined by the research question. This so-called feasibility test is increasingly offered as a self-service, where scientists can filter the available data according to specific parameters. Early feasibility tools have been developed for biosamples or image collections. They are of high interest for clinical study platforms that federate multiple studies and data types, but they pose specific requirements on the integration of data sources and data protection. Methods: Mandatory and desired requirements for such tools were acquired from two user groups - primary users and staff managing a platform's transfer office. Open Source feasibility tools were sought by different literature search strategies and evaluated on their adaptability to the requirements. Results: We identified seven feasibility tools that we evaluated based on six mandatory properties. Discussion: We determined five feasibility tools to be most promising candidates for adaption to a clinical study research data platform, the Clinical Communication Platform, the German Portal for Medical Research data, the Feasibility Explorer, Medical Controlling, and the Sample Locator. © 2023 The authors and IOS Press.

关键词： User interfaces

Mobility-aware Seamless Service Migration and Resource Allocation in Multi-edge IoV Systems

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arXiv 2025年

作者： Chen, Zheyi Huang, Sijin Min, Geyong Ning, Zhaolong Li, Jie Zhang, Yan College of Computer and Data Science Fuzhou University Fuzhou350116 China Engineering Research Center of Big Data Intelligence Ministry of Education Fujian Key Laboratory of Network Fuzhou350002 China Computing and Intelligent Information Processing [Fuzhou University Fuzhou350116 China Department of Computer Science Faculty of Environment Science and Economy University of Exeter ExeterEX4 4QF United Kingdom School of Communications and Information Engineering Chongqing University of Posts and Telecommunications Chongqing400065 China Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai200240 China Department of Informatics University of Oslo Oslo0316 Norway

Mobile Edge Computing (MEC) offers low-latency and high-bandwidth support for Internet-of-Vehicles (IoV) applications. However, due to high vehicle mobility and finite communication coverage of base stations, it is hard to maintain uninterrupted and high-quality services without proper service migration among MEC servers. Existing solutions commonly rely on prior knowledge and rarely consider efficient resource allocation during the service migration process, making it hard to reach optimal performance in dynamic IoV environments. To address these important challenges, we propose SR-CL, a novel mobility-aware seamless Service migration and Resource allocation framework via Convex-optimization-enabled deep reinforcement Learning in multi-edge IoV systems. First, we decouple the Mixed Integer Nonlinear Programming (MINLP) problem of service migration and resource allocation into two sub-problems. Next, we design a new actor-critic-based asynchronous-update deep reinforcement learning method to handle service migration, where the delayed-update actor makes migration decisions and the one-step-update critic evaluates the decisions to guide the policy update. Notably, we theoretically derive the optimal resource allocation with convex optimization for each MEC server, thereby further improving system performance. Using the real-world datasets of vehicle trajectories and testbed, extensive experiments are conducted to verify the effectiveness of the proposed SR-CL. Compared to benchmark methods, the SR-CL achieves superior convergence and delay performance under various scenarios. Copyright © 2025, The Authors. All rights reserved.

关键词： Convex optimization

A Literature Review of Machine Learning Techniques for Dance Recognition and Robotic Vision

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A Literature Review of Machine Learning Techniques for Dance...

Robotics and Technologies for Industrial Automation (ROBOTHIA), IEEE International Conference on

作者： Lee Wei San Samuel-Soma M. Ajibade Muhammed Basheer Jasser Adefemi Ayodele Babatunde Adedotun Ajayi Mbiatke Anthony Bassey Department of Data Science and Artificial Intelligence Faculty of Engineering and Technology Sunway University Selangor Darul Ehsan Malaysia Research Centre for Nanomaterials and Energy Technology (RCNMET) Faculty of Engineering and Technology Sunway University Selangor Malaysia Research Centre for Human-Machine Collaboration (HUMAC) Faculty of Engineering and Technology Sunway University Petaling Jaya Selangor Malaysia University of East London London UK Department of Cyber security Faculty of Computing & Informatics Ladoke Akintola University of Technology Ogbomoso Nigeria Department of Business Administration Universiti Tun Hussein Onn Malaysia Batu Pahat Malaysia

ISBN: (数字)9798350356755

ISBN: (纸本)9798350356762

Image recognition, powered by machine learning (ML), has significantly advanced applications in both dance movement recognition and robotic vision. This review examines key ML techniques, including Convolutional Neural Networks (CNNs), Deep Neural Networks (DNNs), Self-Organizing Maps (SOMs), and Long Short-Term Memory (LSTM) networks, alongside pose estimation methods like OpenPose and Part Affinity Fields (PAFs). These techniques enhance dance classification, real-time feedback, and motion analysis, with OpenPose + LSTMs and PAFs + LSTMs demonstrating the highest accuracy. Notwithstanding progress, obstacles such as high computational costs, data dependency, and real-time implementation challenges persist. Beyond dance, these methods are critical in robotic vision, intelligent automation, and industrial image processing, enabling autonomous robotic navigation, defect detection in manufacturing, and AI-driven motion tracking. By leveraging human movement analysis for robotics, ML improves human-robot interaction, robotic-assisted rehabilitation, and industrial automation. Despite progress, challenges such as high computational demands, data dependency, and real-time constraints remain. This review explores future directions, including multimodal data fusion, hybrid AI models, and real-time optimization, bridging the gap between AI-driven motion systems and intelligent automation to enhance adaptability and efficiency across domains.

关键词： Intelligent automation Humanities Solid modeling Image recognition Accuracy Service robots Robot sensing systems Real-time systems Robots Long short term memory

Implicit Neural Representation in Medical Imaging: A Comparative Survey

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arXiv 2023年

作者： Molaei, Amirali Aminimehr, Amirhossein Tavakoli, Armin Kazerouni, Amirhossein Azad, Bobby Azad, Reza Merhof, Dorit School of Computer Engineering Iran University of Science and Technology Tehran Iran School of Electrical Engineering Iran University of Science and Technology Tehran Iran South Dakota State University BrookingsSD United States Faculty of Electrical Engineering and Information Technology RWTH Aachen University Aachen Germany Institute of Image Analysis and Computer Vision Faculty of Informatics and Data Science University of Regensburg Regensburg Germany Fraunhofer Institute for Digital Medicine MEVIS Bremen Germany

Implicit neural representations (INRs) have gained prominence as a powerful paradigm in scene reconstruction and computer graphics, demonstrating remarkable results. By utilizing neural networks to parameterize data through implicit continuous functions, INRs offer several benefits. Recognizing the potential of INRs beyond these domains, this survey aims to provide a comprehensive overview of INR models in the field of medical imaging. In medical settings, numerous challenging and ill-posed problems exist, making INRs an attractive solution. The survey explores the application of INRs in various medical imaging tasks, such as image reconstruction, segmentation, registration, novel view synthesis, and compression. It discusses the advantages and limitations of INRs, highlighting their resolution-agnostic nature, memory efficiency, ability to avoid locality biases, and differentiability, enabling adaptation to different tasks. Furthermore, the survey addresses the challenges and considerations specific to medical imaging data, such as data availability, computational complexity, and dynamic clinical scene analysis. It also identifies future research directions and opportunities, including integration with multimodal imaging, real-time and interactive systems, and domain adaptation for clinical decision support. To facilitate further exploration and implementation of INRs in medical image analysis, we have provided a compilation of cited studies along with their available open-source implementations on GitHub. Finally, we aim to consistently incorporate the most recent and relevant papers regularly. © 2023, CC BY.

关键词： Medical imaging