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Muscle coactivation analysis for neuromuscular control assessment of lower limb stretch-shortening cycle

Gait & Posture 2023年 106卷 S175-S176页

作者： Rodrigues, Carlos Correia, Miguel Abrantes, João Benedetti, Marco Nadal, Jurandir Faculty of Engineering- University of Porto Biomedical Engineering Program Porto Portugal INESC TEC - Institute for Systems and Computer Engineering- Technology and Science C-BER - Centre for Biomedical Engineering Research Porto Portugal Faculty of Engineering- University of Porto Department of Electrical and Computer Engineering Porto Portugal CICANT - Centre for Research in Applied Communication- Culture and New Technologies MovLab - Laboratory of Technologies for Interactions and Interfaces Lisbon Portugal Federal University of Pernambuco Department of Electronic and Systems Recife Brazil Federal University of Rio de Janeiro Biomedical Engineering Program Rio de Janeiro Brazil

IntroductionMuscle stretch-shortening cycle (SSC) is a central mechanism with lower limb muscle contraction immediately preceded by muscle stretch for efficient submaximal activities such as gait and powerful maximal activities such as running and jumping [1,2]. Research questionAlthough muscle SSC can be observed at gait and running its higher expression and accessibility is performed on standard maximum vertical jump (MVJ) with an open issue on neuromuscular control assessment of lower limb muscle SSC [3]. MethodsFor this purpose, we present and applied noninvasive subject specific analysis of lower limb muscle coactivation for selected muscles with higher contribution during MVJ impulse based on corresponding conditioned surface electromyographic signals (sEMG). Selected muscles correspond to lower limb muscles vastus medialis (VM), rectus femoris (RF), vastus lateralis (VL), lateral gastrocnemius (LG) and medial gastrocnemius (MG). Twenty-seven trials were assessed corresponding for each subject to the highest MVJ based on larger flight time with long SSC at countermovement jump (CMJ), short SSC at drop jump (DJ) and squat jump (SJ) with no SSC. Trial sample is composed by a group of six young adult volunteers’ students on sports and physical education degree with the ages (21.5 ± 1.4) years, (76.7 ± 9.3) kg mass and (1.79 ± 0.06) m height. Surface skin was prepared and Aqua-Wet gel Skintact F55 electrodes were applied at bipolar configuration as indicated by SENIAN. VM, RF, VL, LG and MG sEMG linear envelopes were paired plotted with the area under the curves computed as well as the coactivation pairs defined as the common area under the curves normalized to the sum of the corresponding pair individual areas under the curves. Coactivations were compared at CMJ, DJ and SJ as well as among CMJ, DJ and SJ, Fig. 1. ResultsStrongest coactivations with decreasing intensity were detected between VM-RF and LG-MG muscles at CMJ and SJ, whereas at DJ the strongest coacti

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Analysis of user readiness toward ICT usage at small medium enterprise in south tangerang

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Journal of Physics: Conference Series 2018年第1期1007卷

作者： D Napitupulu M Syafrullah R Rahim D. Abdullah MI Setiawan Research Center for Quality System & Testing Technology Indonesian Institute of Sciences Tangerang Selatan Banten Indonesia Program of Master of Computer Science Universitas Budi Luhur Indonesia School of Computer and Communication Engineering Universiti Malaysia Perlis Malaysia Department of Informatics Universitas Malikussaleh Aceh Indonesia Department of Civil Engineering Narotama University Surabaya Indonesia

Utilization of Information and communication Technology (ICT) is still relatively low in the level of SMEs due to various limitations ranging from access to capital, till the marketing network. ICT is present to provide the ability for SMEs in improving the benefits and competitive advantage of the organization. This study aims to determine the level of readiness of SMEs in utilizing technology, especially ICT. The methodology used is a survey to see the technology readiness of 107 SMEs in South Tangerang selected by purposive sampling. The approach used is TRI (Technology Readiness Index) which is the individual perception of technology based on four criteria that is optimism, innovativeness, discomfort and insecurity. The results showed that the optimism and innovativeness variables significantly positively influence the technology readiness while the variables of discomfort and insecurity also significantly positively influence the readiness of ICT.

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Analysis of e-learning implementation readiness based on integrated elr model

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Journal of Physics: Conference Series 2018年第1期1007卷

作者： K Adiyarta D Napitupulu R Rahim D. Abdullah MI Setiawan Program of Master of Computer Scocience Universitas Budi Luhur Indonesia Research Center for Quality System & Testing Technology Indonesian Institute of Sciences Tangerang Selatan Banten Indonesia School of Computer and Communication Engineering Universiti Malaysia Perlis Malaysia Department of Informatics Universitas Malikussaleh Aceh Indonesia Department of Civil Engineering Narotama University Surabaya Indonesia

E-learning nowadays has become a requirement for institutions to support their learning activities. To adopt e-learning, an institution requires a large strategy and resources for optimal application. Unfortunately, not all institutions that have used e-learning got the desired results or expectations. This study aims to identify the extent of the level of readiness of e-learning implementation in institution X. The degree of institutional readiness will determine the success of future e-learning utilization. In addition, institutional readiness measurement are needed to evaluate the effectiveness of strategies in e-learning development. The research method used is survey with questionnaire designed based on integration of 8 best practice ELR (e-learning readiness) model. The results showed that from 13 factors of integrated ELR model being measured, there are 3 readiness factors included in the category of not ready and needs a lot of work. They are human resource (2.57), technology skill (2.38) and content factors (2.41). In general, e-learning implementation in institutions is in the category of not ready but needs some of work (3.27). Therefore, the institution should consider which factors or areas of ELR factors are considered still not ready and needs improvement in the future.

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Cell2Sentence: teaching large language models the language of biology 24

Cell2Sentence: teaching large language models the language o...

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Proceedings of the 41st International Conference on Machine Learning

作者： Daniel Levine Syed Asad Rizvi Sacha Lévy Nazreen Pallikkavaliyaveetil David Zhang Xingyu Chen Sina Ghadermarzi Ruiming Wu Zihe Zheng Ivan Vrkic Anna Zhong Daphne Raskin Insu Han Antonio Henrique De Oliveira Fonseca Josue Ortega Caro Amin Karbasi Rahul M. Dhodapkar David Van Dijk Department of Computer Science Yale University New Haven CT School of Engineering Applied Science University of Pennsylvania Philadelphia PA School of Computer and Communication Sciences Swiss Federal Institute of Technology Lausanne Lausanne Switzerland Department of Computer Science Yale University New Haven CT and Department of Neuroscience Yale School of Medicine New Haven CT Department of Computer Science Yale University New Haven CT and Department of Neuroscience Yale School of Medicine New Haven CT and Wu Tsai Institute Yale University New Haven CT Google and Yale Institute for Foundations of Data Science New Haven CT and Department of Computer Science Yale University New Haven CT and Yale School of Engineering and Applied Science New Haven CT Roski Eye Institute University of Southern California Los Angeles CA and Department of Internal Medicine (Cardiology) Yale School of Medicine New Haven CT Department of Computer Science Yale University New Haven CT and Yale Institute for Foundations of Data Science New Haven CT and Wu Tsai Institute Yale University New Haven CT and Cardiovascular Research Center Yale School of Medicine New Haven CT and Interdepartmental Program in Computational Biology & Bioinformatics Yale University New Haven CT and Department of Internal Medicine (Cardiology) Yale School of Medicine New Haven CT

We introduce Cell2Sentence (C2S), a novel method to directly adapt large language models to a biological context, specifically single-cell transcriptomics. By transforming gene expression data into "cell sentences," C2S bridges the gap between natural language processing and biology. We demonstrate cell sentences enable the fine-tuning of language models for diverse tasks in biology, including cell generation, complex cell-type annotation, and direct data-driven text generation. Our experiments reveal that GPT-2, when fine-tuned with C2S, can generate biologically valid cells based on cell type inputs, and accurately predict cell types from cell sentences. This illustrates that language models, through C2S fine-tuning, can acquire a significant understanding of single-cell biology while maintaining robust text generation capabilities. C2S offers a flexible, accessible framework to integrate natural language processing with transcriptomics, utilizing existing models and libraries for a wide range of biological applications.

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Comparative analysis of machine learning-based approaches for prediction of colon cancer

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AIP Conference Proceedings 2024年第1期2919卷

作者： Shubhangi Bhargava Adarsh Kumar Moolchand Sharma Indu Bharadwaj Victor Hugo C. de Albuquerque Department of Computer Science & Engineering Maharaja Agrasen Institute of Technology Rohini Delhi India Department of Electronics and Communication Engineering Galgotias University Greater Noida Uttar Pradesh India Telecommunication Engineering Program-PPGET Federal Institute of Education Science and Technology of Ceará (IFCE) Fortaleza Ceará Brazil Department of Teleinformatics Engineering Federal University of Ceará Fortaleza/CE Brazil

Colon cancer, along with lung, prostate, and breast cancer, is one of the most common types of cancer globally and is regarded as one of the world’s leading causes of death. In therapy for this common illness, substantial progress has been achieved recently. Adjuvant chemotherapy is effective, specifically in stage III patients, and surgery was tailored for the most outstanding results with the least amount of morbidity. Several novel target-oriented medications are being evaluated, and some of them (cetuximab and bevacizumab, for example) have already shown high activity/efficacy, primarily when used in conjunction with chemotherapy. To get the best results, it is necessary to provide current recommendations for treating these patients in medical trials and daily practices. This research seeks to use a person’s gene expression to determine whether or not they have colon cancer. This information is used by the Logistic Regression, Naive–Bayes Algorithm and Catboost Algorithm to predict human colon cancer. The learning classification dataset included 7457 gene expression levels from 36 patients, 18 of whom were healthy and 18 of whom were malignant.

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Comparison of the Effectiveness of Machine Learning Techniques for the Number of Road Traffic Injuries

Comparison of the Effectiveness of Machine Learning Techniqu...

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International ECTI Northern Section Conference on Electrical, Electronics, computer and Telecommunications engineering (ECTI-NCON)

作者： Wirawan Puttamat Wikanda Phaphan Anuchit Jitpattanakul Chainarong Pianpailoon Sakorn Mekruksavanich Department of Mathematics Faculty of Education Chaiyaphum Rajabhat University Chaiyaphum Thailand Department of Applied Statistics Faculty of Applied Science King Mongkut’s University of Technology North Bangkok Bangkok Thailand Research Group in Statistical Learning and Inference Department of Mathematics Faculty of Applied Science King Mongkut’s University of Technology North Bangkok Bangkok Thailand Intelligent and Nonlinear Dynamic Innovations Research Center Curriculum and Teaching Program (Mathematics) Faculty of Education Sakon Nakhon Rajabhat University Sakon Nakhon Thailand Department of Computer Engineering School of Information and Communication University of Phayao Phayao Thailand

This article aims to compare forecasting techniques with machine learning techniques for predicting the number of people injured in road accidents using data from the Injury Information Collaboration Center, Department of Disease Control, Ministry of Public Health Outpatient Files (OPD) spanning the years 2018 to 2022. The four machine-learning techniques examined in this study include Decision Tree Regression, Random Forest Regression, Support Vector Regression, and Multiple Linear Regression. The data analysis was performed using the R programming language. The results revealed that the Decision Tree Regression technique yielded the most accurate predictions for the number of road traffic injuries, as evidenced by its lowest values of MAE, MSE, and RMSE.

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Optical excitation and detection of neuronal activity

arXiv

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arXiv 2017年

作者： Hu, Chenfei Sam, Richard Shan, Mingguang Nastasa, Viorel Wang, Minqi Kim, Taewoo Gillette, Martha Sengupta, Parijat Popescu, Gabriel Department of Electrical and Computer Engineering University of Illinois at Urbana-Champaign UrbanaIL61801 United States School of Molecular and Cellular Biology University of Illinois at Urbana-Champaign UrbanaIL61801 United States Department of Bioengineering University of Illinois at Urbana-Champaign UrbanaIL61801 United States Department of Cell and Developmental Biology University of Illinois at Urbana-Champaign UrbanaIL61801 United States Neuroscience Program University of Illinois at Urbana-Champaign UrbanaIL61801 United States Beckman Institute for Advanced Science and Technology University of Illinois at Urbana-Champaign UrbanaIL61801 United States College of Information and Communication Engineering Harbin Engineering University Harbin Heilongjiang150001 China National Institute for Laser Plasma and Radiation Physics Magurele Ilfov Bucharest077125 Romania

Optogenetics has emerged as an exciting tool for manipulating neural activity, which in turn, can modulate behavior in live organisms. However, detecting the response to the optical stimulation requires electrophysiology with physical contact or fluorescent imaging at target locations, which is often limited by photobleaching and phototoxicity. In this paper, we show that phase imaging can report the intracellular transport induced by optogenetic stimulation. We developed a multimodal instrument that can both stimulate cells with subcellular spatial resolution and detect optical pathlength changes with nanometer scale sensitivity. We found that optical pathlength fluctuations following stimulation are consistent with active organelle transport. Furthermore, the results indicate a broadening in the transport velocity distribution, which is significantly higher in stimulated cells compared to optogenetically inactive cells. It is likely that this label-free, contactless measurement of optogenetic response will provide an enabling approach to neuroscience. Copyright © 2017, The Authors. All rights reserved.

关键词： Electrophysiology

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Feature Selection in Cross-Project Software Defect Prediction

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Journal of Physics: Conference Series 2020年第2期1569卷

作者： A Saifudin A Trisetyarso W Suparta C H Kang B S Abbas Y Heryadi Informatics Engineering Pamulang University Jalan Raya Puspitek 46 Banten 15310 Indonesia Doctor of Computer Science Program Bina Nusantara University Jalan Kebon Jeruk Raya 27 Jakarta 11530 Indonesia Informatics Department Pembangunan Jaya University Banten Indonesia Department of Electronics and Communication Engineering Kwangwoon University South Korea

Advances in technology have increased the use and complexity of software. The complexity of the software can increase the possibility of defects. Defective software can cause high losses. Fixing defective software requires a high cost because it can spend up 50% of the project schedule. Most software developers don't document their work properly so that making it difficult to analyse software development history data. Software metrics which use in cross-project software defects prediction have many features. Software metrics usually consist of various measurement techniques, so there are possibilities for their features to be similar. It is possible that these features are similar or irrelevant so that they can cause a decrease in the performance of classifiers. In this study, several feature selection techniques were proposed to select the relevant features. The classification algorithm used is Naive Bayes. Based on the analysis using ANOVA, the SBS and SBFS models can significantly improve the performance of the Naïve Bayes model.

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Spatio-temporal assessment of whole-body center of mass coordination on standard maximum vertical jump

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Gait & Posture 2022年 97卷 S208-S209页

作者： Rodrigues, C. Correia, M. Abrantes, J. Rodrigues, B. Nadal, J. Faculty of Engineering- University of Porto Biomedical Engineering Program Porto Portugal INESC TEC - Institute for Systems and Computer Engineering- Technology and Science C-BER - Centre for Biomedical Engineering Research Porto Portugal University of Porto Faculty of Engineering Porto Portugal Lusófona University- CICANT - Centre for Research in Applied Communication- Culture and New Technologies MovLab Laboratory of Technologies for Interactions and Interfaces Lisbon Portugal Federal University of Pernambuco Department of Electronic and Systems Recife Brazil Federal University of Rio de Janeiro Biomedical Engineering Program Rio de Janeiro Brazil

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CubeSat single-photon detector module for investigating in-orbit laser annealing to heal radiation damage

arXiv

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arXiv 2024年

作者： Sultana, Nigar Krynski, Joanna Lim, Jin Gyu Floyd, John Lembeck, Michael Makarov, Vadim Kwiat, Paul Jennewein, Thomas Institute for Quantum Computing University of Waterloo WaterlooONN2L 3G1 Canada Department of Electrical and Computer Engineering University of Waterloo WaterlooONN2L 3G1 Canada Department of Physics and Astronomy University of Waterloo WaterlooONN2L 3G1 Canada University of Illinois Urbana-Champaign ChampaignIL United States Vigo Quantum Communication Center University of Vigo Vigo Spain Quantum Information Science Program Canadian Institute for Advanced Research TorontoONM5G 1Z8 Canada

Single-photon avalanche photodiodes (SPADs) based on silicon are widely considered for quantum satellite communications but suffer from an increasing dark count rate (DCR) due to displacement damage in their active areas induced by proton radiation. When the DCR of SPADs exceeds a certain threshold, they become unusable for quantum communication protocols. Previous laboratory experiments have demonstrated that laser annealing of SPADs’ active area with about 1 W optical power can significantly reduce radiation-induced DCR of synthetically irradiated SPADs. To assess the feasibility of in-orbit laser annealing on constantly irradiated SPADs in low-Earth orbit, we developed a module with a CubeSat form factor capable of both laser and thermal annealing of four silicon SPADs. Here we report the design and ground testing of this module, investigating laser annealing in a simulated space environment. Our results pave the way for an in-orbit trial that may prove this technology useful for future satellite missions with quantum receivers on board. Copyright © 2024, The Authors. All rights reserved.

关键词： Radiation damage

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