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CoVimmune COVID-19 Immunity Calculator: Web Application Development and Validation Study

JMIR Formative Research 2025年 9卷 e59467页

作者： Slotkin, Rebecca Kyriakides, Tassos C. Yu, Vinni Chen, Xien Kundu, Anupam Gupta, Shaili Department of Medicine Yale School of Medicine West Haven CT United States Cooperative Studies Program Coordinating Center VA CT Healthcare System West Haven CT United States Yale School of Public Health Yale University New Haven CT United States Department of Computer Science Yale University New Haven CT United States Yale Center for Analytical Sciences Yale School of Public Health New Haven CT United States Veterans Healthcare System of Connecticut West Haven CT United States

Background: This study illustrates the development of a simple web-based application, which demonstrates the relationship between serum anti-SARS-CoV-2 S1/receptor-binding domain immunoglobulin G (IgG) and anti-SARS-CoV-2 neutralizing antibody (nAb) half-maximal inhibitory concentration (IC50) titers in a vaccinated US adult population and compares them to prior data on nAb titers at different time points after vaccination. Objective: The objective of this study is to create an easily accessible calculator that uses the results of commercially available anti-SARS-CoV-2 serum IgG to approximate the underlying ability to neutralize SARS-CoV-2. Methods: Our web-based application leveraged two previously published datasets. One dataset demonstrated a robust correlation between nAb and serum IgG. The other dataset measured nAb titers at specific time periods over a year-long interval following a messenger RNA vaccination primary series and booster vaccine dose. Clinical factors that were statistically significant on a forward linear regression model examining the prediction of nAb from serum IgG were incorporated in the application tool. Results: By combining the datasets described above, we developed a publicly available web-based application that allows users to enter a serum IgG value and determine their estimated nAb titer. The application contextualizes the estimated nAb titer with the theoretical distance from the corresponding vaccine-mediated antibody protection. Using the clinical variables that had a significant impact on how well IgG values predict nAb titers, this application allows for a patient-centered, nAb titer prediction. Conclusions: This application offers an example of how we might bring the advances made in scientific research on protective antibodies post-SARS-CoV-2 vaccination into the clinical sphere with practical tools. © Rebecca Slotkin, Tassos C Kyriakides, Vinni Yu, Xien Chen, Anupam Kundu, Shaili Gupta.

关键词： COVID-19 immunity immunoglobulin G neutralizing antibody patient-centered care SARS-CoV-2 vaccination vaccine hesitancy vaccine timing web application

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Improving debris flow evacuation alerts in Taiwan using machine learning

arXiv

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arXiv 2022年

作者： Tsai, Yi-Lin Irvin, Jeremy Chundi, Suhas Ng, Andrew Y. Field, Christopher B. Kitanidis, Peter K. Department of Civil and Environmental Engineering Stanford University StanfordCA United States Department of Computer Science Stanford University StanfordCA United States Woods Institute for the Environment Stanford University StanfordCA United States Interdisciplinary Environmental Studies Program Stanford University StanfordCA United States Department of Earth System Science Stanford University StanfordCA United States Institute for Computational and Mathematical Engineering Stanford University StanfordCA United States

Taiwan has the highest susceptibility to and fatalities from debris flows worldwide. The existing debris flow warning system in Taiwan, which uses a time-weighted measure of rainfall, leads to alerts when the measure exceeds a predefined threshold. However, this system generates many false alarms and misses a substantial fraction of the actual debris flows. Towards improving this system, we implemented five machine learning models that input historical rainfall data and predict whether a debris flow will occur within a selected time. We found that a random forest model performed the best among the five models and outperformed the existing system in Taiwan. Furthermore, we identified the rainfall trajectories strongly related to debris flow occurrences and explored trade-offs between the risks of missing debris flows versus frequent false alerts. These results suggest the potential for machine learning models trained on hourly rainfall data alone to save lives while reducing false alerts. Copyright © 2022, The Authors. All rights reserved.

关键词： Rain

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Integrative Engineer's Work Model: An Analysis Using Structural Equation Modelling

SSRN

引用

SSRN 2022年

作者： Rosdi, Mohd Farhan Mat Hussain, Eizah Mat Yasir, Ahmad Shah Hizam Md. Abdullah, Azlina Khoiry, Muhammad Azry School of Computer Science and Engineering Taylor's University Selangor Subang Jaya47500 Malaysia Malay Academic Studies University of Malaya Kuala Lumpur50603 Malaysia Rabdan Academy Abu Dhabi114646 United Arab Emirates Anthropology and Sociology Program Center for Research in Development Social and Environmental Studies Faculty of Social Sciences and Humanities Universiti Kebangsaan Malaysia Selangor Bangi43600 Malaysia Faculty of Engineering & Built Environment National University of Malaysia Selangor Bangi43600 Malaysia

This study analyzes the impacts of engineering-specific job demands on an engineer's professional commitment. This study utilized survey of 504 engineers in Malaysia. Structural equation modelling is used to test the hypothesized model. The result shows engineer's job demands and job resources have significantly impacted psychological well-being and job strain. Professional commitment is influenced by job strain and psychological well-being. The findings also indicate that addressing the "demand for technical knowledge" and "financial resources" is critical to achieving professional commitment. Result is useful for engineering managers and engineers in leading and planning routine work in an engineering organization. © 2022, The Authors. All rights reserved.

关键词： Engineers

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Digital Audio Watermarking by Amplitude Embedding System 15th

Digital Audio Watermarking by Amplitude Embedding System

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15th International Conference on Intelligent Information Hiding and Multimedia Signal Processing, IIH-MSP 2019, held in conjunction with the 12th International Conference on Frontiers of Information Technology, Applications and Tools, FITAT 2019

作者： Lin, Meng-Ju Zhao, Ming Chen, Shuo-Tsung Chen, Ching-Ju Department of Applied Mathematics Tunghai University No. 1727 Sec.4 Taiwan Boulevard Taichung Taiwan40704 Taiwan School of Computer Science Yangtze University Jingzhou CityHubei Province China College of Future Bachelor Program in Interdisciplinary Studies National Yunlin University of Science and Technology TaiwanYunlin64002 Taiwan National Yunlin University of Science and Technology TaiwanYunlin64002 Taiwan

ISBN: (纸本)9789811397134

This paper proposed an amplitude embedding system for digital audio watermarking in the wavelet domain. In this paper, the relationship between the watermarked coefficients and the original coefficients is first presented and then amplitude-based embedding rules are combined into an amplitude-based embedding system that incorporates a system state. For the embedding in this system, the information includes synchronization codes and the watermarks are embedded into the DWT lowest frequency sub-band coefficients which can be described by a matrix form. Moreover, the SNR is rewritten as a performance index which is a quadratic form. Then, a nonlinear function connecting the performance index and the embedding system is derived. Accordingly, an optimization-based embedding system is proposed. Finally, the Karush–Kuhn–Tucker (KKT) Theorem is used to obtain the optimal solution, which is an important formula for watermarking. In addition, the hidden information can be extracted without knowledge of the original audio. In the experiments, the performance of the proposed system is tested and the results verify the high SNR and strong robustness against multimedia signal processing or malicious attacks. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Embeddings

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Digital Audio Watermarking by Quantization Embedding System 15th

Digital Audio Watermarking by Quantization Embedding System

引用

作者： Chen, Ching-Ju Zhao, Ming Chen, Shuo-Tsung Lin, Meng-Ju College of Future Bachelor Program in Interdisciplinary Studies National Yunlin University of Science and Technology DouliuYunlin Taiwan64002 Taiwan School of Computer Science Yangtze University Jingzhou CityHubei Province China Department of Applied Mathematics Tunghai University No. 1727 Sec. 4 Taiwan Boulevard TaichungTaiwan40704 Taiwan National Yunlin University of Science and Technology DouliuYunlin Taiwan64002 Taiwan

ISBN: (纸本)9789811397134

This paper designs a digital audio watermarking scheme using a quantization embedding system in the wavelet domain. In this paper, the relationship between the watermarked coefficients and the original coefficients is first presented and then the quantization-based embedding rules are combined into a quantization-based embedding system that incorporates a system state. For the embedding in this system, the information includes synchronization codes and the watermarks are embedded into the DWT lowest frequency sub-band coefficients, which can be described by a matrix form. Moreover, the SNR is rewritten as a performance index which is a quadratic form. Then, a nonlinear function connecting the performance index and the embedding system is derived. Accordingly, an optimization-based embedding system is proposed. Finally, the Lagrange Principle is used to obtain the optimal solution which is an important formula for watermarking. In addition, the hidden information can be extracted without knowledge of the original audio. In the experiments, the performance of the proposed system is tested and the results verify the high SNR and strong robustness against multimedia signal processing or malicious attacks. © 2020, Springer Nature Singapore Pte Ltd.

关键词： Audio watermarking

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DTCMS: Dynamic traffic congestion management in Social Internet of Vehicles (SIoV)

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Internet of Things (Netherlands) 2021年 16卷

作者： Roopa, M.S. Ayesha Siddiq, S. Buyya, Rajkumar Venugopal, K.R. Iyengar, S.S. Patnaik, L.M. Department of Computer Science and Engineering University Visvesvaraya College of Engineering Bangalore University Bengaluru 560-001 India Cloud Computing and Distributed Systems Laboratory School of Computing and Information Systems University of Melbourne Melbourne 3053 VIC Australia Bangalore University Bengaluru 560-001 India Department of Computer Science and Engineering Florida International University Miami 33199 FL United States Consciousness Studies Program National Institute of Advanced Studies Indian Institute of Science Bengaluru 560-012 India

With the augmentation of traffic exponentially, we observe that traffic congestion does not guarantee road safety or enhance the driving experience. In the recent past, Social Internet of Vehicles (SIoV), a social network paradigm permits social relationships among every vehicle in the network or with any road infrastructure to render a radically useful environment. SIoV is beneficial for the drivers, in improving road safety, avoiding mishaps, and providing a friendly-driving experience. In this paper, we propose a traffic scheduling algorithm to gain the maximum throughput for the flow of vehicles at a road intersection with the formation of social relationships among the vehicles and with the Road Side Units (RSUs). The algorithm estimates the flow rate of vehicles for lanes at the intersections exploiting the volume of traffic moving through the given road. A condition matrix is designed for the consistent movement of traffic considering different routes on the road segments. Social relationships are devised on various aspects of travel needs for a safe, agile, and better driving experience. Simulation results illustrate the efficacy of the proposed scheme with high traffic throughput, service rate and reduce the total travelling time, delay time, and average waiting time in comparison with Dynamic Throughput Maximization Framework and Adaptive Traffic Control Algorithm. © 2020 Elsevier B.V.

关键词： Dynamic traffic control Social Internet of Vehicles (SIoV) Social relationships Traffic congestion management

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Decision Support Systems Selection of Soang Superior Brood Using Weighted Product (WP) and Simple Additive Weighting (SAW) Method 4

Decision Support Systems Selection of Soang Superior Brood U...

引用

4th International Conference on Energy, Environment, Epidemiology and Information System, ICENIS 2019

作者： Ramadiani Kurniawan, Reynaldi Kridalaksana, Awang Harsa Jundillah, Muhammad Labib Faculty of Computer Science and Information Technology Mulawarman University Samarinda Indonesia Magister Program of Information System School of Post Graduate Studies Diponegoro University Semarang Indonesia

Gurame Soang Latin name Osphronomus Labirynthici gouramy including fish, that as the fish have gills and breathing apparatus in the form of additional gills (Labyrinth). One important factor in fish farming Soang Gurame is holding elections. Superior brood has characteristics identical, to distinguish it needs to experience since it is quite difficult. Some of the assessment factors in selecting a superior brood that could be considered in the cultivation of the fish farmers Gurame Soang as ideal weight, physical disability, movement of fish, the shape of the head, and the body color. All of these factors combined to get an assessment that could help the decision making process fish Gurame Soang superior sires. This study used two methods that have selected the calculation accuracy of the decision-making process. The method used is the Weighted Product and Simple Additive weighting. The results of the research that has been done, it can be concluded the total number of alternative Gurame Soang superior sires data as many as 10 fish, and obtained the results of testing the level of accuracy by using the results of data from a breeder Gurame Soang superior sires, Method of Weighted Product got an accuracy of 80% and methods Simple Additive weighting got an accuracy of 60%. © The Authors, published by EDP sciences, 2019.

关键词： Fish

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Experimental implementation of an efficient test of quantumness

arXiv

引用

arXiv 2022年

作者： Lewis, Laura Zhu, Daiwei Gheorghiu, Alexandru Noel, Crystal Katz, Or Harraz, Bahaa Wang, Qingfeng Risinger, Andrew Feng, Lei Biswas, Debopriyo Egan, Laird Vidick, Thomas Cetina, Marko Monroe, Christopher Institute for Quantum Information and Matter Department of Computing and Mathematical Sciences California Institute of Technology CA91125 United States Division of Physics Mathematics and Astronomy California Institute of Technology CA91125 United States Joint Quantum Institute Departments of Physics and Electrical and Computer Engineering University of Maryland College ParkMD20742 United States Joint Center for Quantum Information and Computer Science NIST University of Maryland College ParkMD20742 United States IonQ Inc. College ParkMD20740 United States Departments of Electrical and Computer Engineering University of Maryland College ParkMD20742 United States Institute for Theoretical Studies ETH Zürich CH 8001 Switzerland Duke Quantum Center Department of Physics Duke University DurhamNC27708 United States Department of Electrical and Computer Engineering Duke University DurhamNC27708 United States Chemical Physics Program Institute for Physical Science and Technology University of Maryland College ParkMD20742 United States

A test of quantumness is a protocol where a classical user issues challenges to a quantum device to determine if it exhibits non-classical behavior, under certain cryptographic assumptions. Recent attempts to implement such tests on current quantum computers rely on either interactive challenges with efficient verification, or non-interactive challenges with inefficient (exponential time) verification. In this paper, we execute an efficient non-interactive test of quantumness on an ion-trap quantum computer. Our results significantly exceed the bound for a classical device’s success. Copyright © 2022, The Authors. All rights reserved.

关键词： Qubits

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Perceptual and semantic maps in individual humans share structural features that predict creative abilities

Communications psychology

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Communications psychology 2025年第1期3卷 30页

作者： Johannes P-H Seiler Jonas Elpelt Aida Ghobadi Matthias Kaschube Simon Rumpel Institute of Physiology Focus Program Translational Neurosciences University Medical Center of the Johannes Gutenberg University Mainz Mainz Germany. johseile@uni-mainz.de. Frankfurt Institute for Advanced Studies Frankfurt am Main Germany. Institute of Computer Science Goethe University Frankfurt Frankfurt am Main Germany. Institute of Physiology Focus Program Translational Neurosciences University Medical Center of the Johannes Gutenberg University Mainz Mainz Germany. Institute of Physiology Focus Program Translational Neurosciences University Medical Center of the Johannes Gutenberg University Mainz Mainz Germany. sirumpel@uni-mainz.de.

Building perceptual and associative links between internal representations is a fundamental neural process, allowing individuals to structure their knowledge about the world and combine it to enable efficient and creative behavior. In this context, the representational similarity between pairs of represented entities is thought to reflect their associative linkage at different levels of sensory processing, ranging from lower-order perceptual levels up to higher-order semantic levels. While recently specific structural features of semantic representational maps were linked with creative abilities of individual humans, it remains unclear if these features are also shared on lower level, perceptual maps. Here, we address this question by presenting 148 human participants with psychophysical scaling tasks, using two sets of independent and qualitatively distinct stimuli, to probe representational map structures in the lower-order auditory and the higher-order semantic domain. We quantify individual representational features with graph-theoretical measures and demonstrate a robust correlation of representational structures in the perceptual auditory and semantic modality. We delineate these shared representational features to predict multiple verbal standard measures of creativity, observing that both, semantic and auditory features, reflect creative abilities. Our findings indicate that the general, modality-overarching representational geometry of an individual is a relevant underpinning of creative thought.

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Efficient Breast Cancer Diagnosis from Complex Mammographic Images Using Deep Convolutional Neural Network

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Computational intelligence and neuroscience 2023年第1期2023卷 7717712页

作者： Hameedur Rahman Tanvir Fatima Naik Bukht Rozilawati Ahmad Ahmad Almadhor Abdul Rehman Javed Department of Computer Games Development Faculty of Computing and AI Air University E9 Islamabad Pakistan. Department of Computer Science Faculty of Computing and AI Air University E9 Islamabad Pakistan. Diagnostic Imaging and Radiotherapy Program Therapeutic and Investigation Studies Faculty of Health Sciences University Kebangsaan Malaysia Kuala Lumpur Malaysia. Department of Computer Engineering and Networks College of Computer and Information Sciences Jouf University Sakaka 72388 Saudi Arabia. Department of Cyber Security Air University Islamabad Pakistan. Department of Electrical and Computer Engineering Lebanese American University Byblos Lebanon.

Medical image analysis places a significant focus on breast cancer, which poses a significant threat to women's health and contributes to many fatalities. An early and precise diagnosis of breast cancer through digital mammograms can significantly improve the accuracy of disease detection. computer-aided diagnosis (CAD) systems must analyze the medical imagery and perform detection, segmentation, and classification processes to assist radiologists with accurately detecting breast lesions. However, early-stage mammography cancer detection is certainly difficult. The deep convolutional neural network has demonstrated exceptional results and is considered a highly effective tool in the field. This study proposes a computational framework for diagnosing breast cancer using a ResNet-50 convolutional neural network to classify mammogram images. To train and classify the INbreast dataset into benign or malignant categories, the framework utilizes transfer learning from the pretrained ResNet-50 CNN on ImageNet. The results revealed that the proposed framework achieved an outstanding classification accuracy of 93%, surpassing other models trained on the same dataset. This novel approach facilitates early diagnosis and classification of malignant and benign breast cancer, potentially saving lives and resources. These outcomes highlight that deep convolutional neural network algorithms can be trained to achieve highly accurate results in various mammograms, along with the capacity to enhance medical tools by reducing the error rate in screening mammograms.

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