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How to design the biofeedback training for the rehabilitation of PTSD patients?

How to design the biofeedback training for the rehabilitatio...

2023 IEEE Ural-Siberian Conference on Computational Technologies in Cognitive science, Genomics and Biomedicine, CSGB 2023

作者： Bazanova, Olga Zakharov, Alexander Larkova, Irina Maryanovskaya, Tatiana Melnikov, Andrey Ermolaeva, Sargylana Nikolenko, Ekaterina Shirolapov, Igor The Research Institute of Molecular Biology and Biophysics Laboratory of Computer Systems of Biofeedback Dolgoprudny Russia The Moscow Institute of Physics and Technology Educational and Scientific Center for Humanities and Social Science Novosibirsk Russia Research Institute of Neurosciences Samara State Medical University Samara Russia Lugansk Republican Center for Emergency Medical Care and Disaster Medicine Laboratory of Psychophysiological Support Lugansk Russia Novosibirsk National Research State University Mechanic-Mathematic Department Novosibirsk Russia The Russian University of Sport «gtsolifk» Department of Physiology Moscow Russia The Moscow Institute of Physics and Technology Master's Degree in Applied Data Analysis in the Medical Field Dolgoprudny Russia Federal State Budgetary Scientific Institution Scientific Research Institute of Neurosciences and Medicine Department of Clinical Neuroscience Behavior and Neurotechnology Novosibirsk Russia

ISBN: (纸本)9798350307979

Rationale for this review is the pressing medical and social problem of the posttraumatic stress disorder (PTSD) treatment. It is known that biofeedback technology is one of the most effective methods of treatment and rehabilitation for emotional profile disorders. In order to develop biofeedback aimed to PTSD rehabilitation, we conducted a literature search on this problem. However, it appears that at the moment there is not enough unambiguous data on this type of biofeedback design. The pathogenesis of PTSD is closely related to impaired efficiency of sensorimotor integration (SMI). The effectiveness of therapy for psychosomatic disorders in patients with PTSD can be increased by restoring normal sensorimotor integration. The review examines various autonomic, electrophysiological and postural markers of destroyed sensorimotor integration (SMI) in individuals with PTSD. We have found that the most informative indicators of SMI in norm include: an increase in EEG power in the individually determined high-frequency alpha subrange, a decrease in the speed of body sway and energy demands to maintain a vertical posture, and a decrease in EMG activity of muscles not involved in cognitive or psychomotor performance. We intend to use these indicators in diagnostic purposes and to develop neurofeedback technology for SMI recovery in patients with PTSD. © 2023 IEEE.

关键词： Electroencephalography

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Nature vs. Nurture in Precision Education: Insights of Parents and the Public

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AJOB Empirical Bioethics 2022年第2期13卷 79-88页

作者： Sabatello, Maya Martin, Bree Corbeil, Thomas Lee, Seonjoo Link, Bruce G. Appelbaum, Paul S. Center for Precision Medicine and Genomics Department of Medicine and Division of Ethics Department of Medical Humanities and Ethics Columbia University New York NY United States Division of General Pediatrics Boston Children’s Hospital Boston MA United States Division of Mental Health Data Science New York State Psychiatric Institute New York NY United States Department of Biostatistics and Psychiatry Columbia University Medical Center New York NY United States New York State Psychiatric Institute New York NY United States School of Public Policy University of California Riverside CA United States Center for Research on Ethical Legal & Social Implications of Psychiatric Neurologic & Behavioral Genetics Department of Psychiatry Columbia University New York United States

Background: The philosophical debate about the roles of nature versus nurture in human flourishing is not new. But the rise of precision education—a growing field of research that encourages the use of genetic data to inform educational trajectory and interventions to better meet student needs—has renewed historical and ethical concerns. A major worry is that “genetic hype” may skew public perceptions toward a deterministic perception of the child’s educational trajectory, regardless of the child’s capacities, and underestimation of environmental factors affecting educational outcomes. We tested this hypothesis with parents and adults from the general public in the US. Methods: A newly developed computerized implicit association test (IAT) to assess automatic associations between genetics or environments and student behaviors that are associated with educational achievement was administered to samples of parents of children below 21 years old (n = 450) and adults from the general public (n = 419). The samples were representative of the adult US population and adjusted to oversample Black/African American participants. An overall D score for participants’ IATs (range: [-2, 2]) was calculated on the basis of the speed of participants’ responses. Results: The mean IAT score for both samples indicated stronger association between the quality of being a good student and environment rather than genetics (parents: mean=-0.146, t = -6.56, p < 0.001;general public: mean = -0.249, t = -9.45, p < 0.0001). Younger participants from the general public showed a stronger association between genetics and educational success than middle-aged participants (β = -0.301, p = 0.006). Conclusion: The views of parents and the general public on behavioral genetics and education are complex but call for investment in creating educational environments that are supportive of student success. Future research is needed to understand differences across age groups and to explore views of other sta

关键词： behavioral genetics environment implicit association test precision education

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Explainability and transparency in the realm of digital humanities: toward a historian XAI

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International Journal of Digital humanities 2023年第2期5卷 299-331页

作者： El-Hajj, Hassan Eberle, Oliver Merklein, Anika Siebold, Anna Shlomi, Noga Büttner, Jochen Martinetz, Julius Müller, Klaus-Robert Montavon, Grégoire Valleriani, Matteo Max Planck Institute for the History of Science Berlin Germany BIFOLD – Berlin Institute for the Foundations of Learning and Data Berlin Germany Machine Learning Group Technische Universität Berlin Berlin Germany German Center for Art History Paris (DFK Paris) Paris France The Cohn Institute for the History and Philosophy of Science and Ideas Faculty of Humanities Tel-Aviv University Tel-Aviv Israel Department of Artificial Intelligence Korea University Seoul South Korea Max Planck Institute for Informatics Saarbrüken Germany Department of Mathematics and Computer Science Freie Universität Berlin Berlin Germany

The recent advancements in the field of Artificial Intelligence (AI) translated to an increased adoption of AI technology in the humanities, which is often challenged by the limited amount of annotated data, as well as its heterogeneity. Despite the scarcity of data it has become common practice to design increasingly complex AI models, usually at the expense of human readability, explainability, and trust. This in turn has led to an increased need for tools to help humanities scholars better explain and validate their models as well as their hypotheses. In this paper, we discuss the importance of employing Explainable AI (XAI) methods within the humanities to gain insights into historical processes as well as ensure model reproducibility and a trustworthy scientific result. To drive our point, we present several representative case studies from the Sphaera project where we analyze a large, well-curated corpus of early modern textbooks using an AI model, and rely on the XAI explanatory outputs to generate historical insights concerning their visual content. More specifically, we show that XAI can be used as a partner when investigating debated subjects in the history of science, such as what strategies were used in the early modern period to showcase mathematical instruments and machines.

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Entity perception of Two-Step-Matching framework for public opinions

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Journal of Safety science and Resilience 2020年第1期1卷 36-43页

作者： Ren-De Li Hao-Tian Ma Zi-Yi Wang Qiang Guo Jian-Guo Liu Library and Research Center of Computer Systems Science University of Shanghai for Science and TechnologyShanghai 200093PR China School of Accountancy and Shanghai Key Laboratory of Financial Information Technology Shanghai University of Finance and EconomicsShanghai 200433PR China School of Humanities Shanghai University of Finance and EconomicsShanghai 200433PR China Institute of Sina WRD Big Data Shanghai 201204PR China

Entity perception of ambiguous user comments is a critical problem of target identification for huge amount of public *** this paper,a Two-Step-Matching method is proposed to identify the precise target entity from multiple entities ***,potential entities are extracted by BiLSTM-CRF model and characteristic words by TF-IDF model from public ***,the first matching is implemented between potential entities and an official business directory by Jaro-Winkler distance ***,in order to find the pre-cise one,an industry-characteristic dictionary is developed into the second matching *** precise entity is identified according to the count of characteristic words matching to industry-characteristic *** addition,associated rate(global indicator)and accuracy rate(sample indicator)are defined for evaluation of matching *** results for three data sets of public opinions about major public health events show that the highest associated rate and accuracy rate arrive at 0.93 and 0.95,averagely enhanced by 32%and 30%above the case of using the first matching process *** framework provides the method to find the true target entity of really wanted expression from public opinions.

关键词： Entity perception BiLSTM-CRF model Jaro-Winkler distance algorithm User comments Public opinions

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Molecular Dynamics and Machine Learning Unlock Possibilities in Beauty Design—A Perspective

arXiv

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arXiv 2024年

作者： Xu, Yuzhi Ni, Haowei Zhao, Fanyu Gao, Qinhui Zhao, Ziqing Chang, Chia-Hua Huo, Yanran Hu, Shiyu Zhang, Yike Grovu, Radu He, Min Zhang, John Z.H. Wang, Yuanqing Simons Center for Computational Physical Chemistry New YorkNY10003 United States Department of Chemistry New York University New YorkNY10003 United States Shanghai Frontiers Science Center of Artificial Intelligence and Deep Learning NYU-ECNU Center for Computational Chemistry NYU Shanghai Shanghai200062 China Department of Digital Humanities King’s College London Strand LondonWC2R 2LS United Kingdom Division of Cardiology The First Affiliated Hospital of Nanjing Medical University Nanjing210029 China Internal Medicine Department Rhode Island Hospital Brown Univerisity Health ProvidenceRI02903 United States Xbiome Inc. CambridgeMA01451 United States Center for Data Science New York University New YorkNY10004 United States

Computational molecular design—the endeavor to design molecules, with various missions, aided by machine learning and molecular dynamics approaches, has been widely applied to create valuable new molecular entities, from small molecule therapeutics to protein biologics. In the small data regime, physics-based approaches model the interaction between the molecule being designed and proteins of key physiological functions, providing structural insights into the mechanism. When abundant data has been collected, a quantitative structure-activity relationship (QSAR) can be more directly constructed from experimental data, from which machine learning can distill key insights to guide the design of the next round of experiment design. Machine learning methodologies can also facilitate physical modeling, from improving the accuracy of force fields and extending them to unseen chemical spaces, to more directly enhancing the sampling on the conformational spaces. We argue that these techniques are mature enough to be applied to not just extend the longevity of life, but the beauty it manifests. In this perspective, we review the current frontiers in the research & development of skin care products, as well as the statistical and physical toolbox applicable to addressing the challenges in this industry. Feasible interdisciplinary research projects are proposed to harness the power of machine learning tools to design innovative, effective, and inexpensive skin care products. © 2024, CC BY.

关键词： Molecular dynamics

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Audio Segmentation Techniques and Applications Based on Deep Learning

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Scientific Programming 2022年第1期2022卷

作者： Aggarwal, Shruti Vasukidevi, G. Selvakanmani, S. Pant, Bhaskar Kaur, Kiranjeet Verma, Amit Binegde, Geleta Negasa Department of Computer Science and Engineering Thapar University Punjab Patiala147004 India Department of Science and Humanities R.M.K. College of Engineering and Technology R.S.M. Nagar Tamil Nadu Puduvoyal India Department of Artificial Intelligence and Data Science Velammal Institute of Technology Velammal Knowledge Park Tamil Nadu Chennai India Department of Computer Science and Engineering Graphic Era Deemed to be University Bell Road Clement Town Uttarakhand Dehradun248002 India University Center for Research and Development Chandigarh University Punjab Ajitgarh India Department of Computer Science College of Engineering and Technology Mettu University Metu Ethiopia

Audio processing has become an inseparable part of modern applications in domains ranging from health care to speech-controlled devices. In automated audio segmentation, deep learning plays a vital role. In this article, we are discussing audio segmentation based on deep learning. Audio segmentation divides the digital audio signal into a sequence of segments or frames and then classifies these into various classes such as speech recognition, music, or noise. Segmentation plays an important role in audio signal processing. The most important aspect is to secure a large amount of high-quality data when training a deep learning network. In this study, various application areas, citation records, documents published year-wise, and source-wise analysis are computed using Scopus and Web of science (WoS) databases. The analysis presented in this paper supports and establishes the significance of the deep learning techniques in audio segmentation. Copyright © 2022 Shruti Aggarwal et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

关键词： Speech recognition

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Enabling a Massive data Collection for Hotel Receptionist Chatbot Using a Crowdsourcing Information System

Enabling a Massive Data Collection for Hotel Receptionist Ch...

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International Conference on Information Management and Technology (ICIMTech)

作者： Reval Levannoza Rizky Fauzi Latif Syafira Indah Nurkafianti Kristianus Oktriono Devina Chandra Kurniawan Wiharja Tjeng Wawan Cenggoro School of Computer Science Bina Nusantara University Jakarta Indonesia Language Center Tourism Destination Faculty of Humanities Bina Nusantara University Jakarta Indonesia Language Center Industrial Engineering Faculty of Humanities Bina Nusantara University Jakarta Indonesia Faculty of Humanities Bina Nusantara University Jakarta Indonesia Bioinformatics and Data Science Research Center School of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9781728170718

ISBN: (纸本)9781728170725

With the heavy utilization of deep learning, modern chatbot systems require massive training dataset to achieve their peak performance. Without exception, the development of chatbot for the hotel receptionist tasks also demands a massive training dataset. Unfortunately, laborious effort and hefty time are needed to manually collect a dataset with that size. Therefore, an information system is needed to assist the dataset collection. In regards to solve the problem, this research contributes in developing the information system that enables a massive data collection for training a hotel receptionist chatbot in a reasonable time. In detail, the contribution of this research are twofold: (1) developing a realiable crowdsourcing information system design to collect and store the dataset for training hotel receptionist chatbot; and (2) developing a user experience that can stimulate the crowdworkers to provide more data.

关键词： Crowdsourcing Computer science Training Task analysis Natural language processing Information management

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The use of human mobility data on infectious disease control: Covid-19 as an example

Taiwan Journal of Public Health

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Taiwan Journal of Public Health 2023年第2期42卷 148-152页

作者： Fu, Han Chan, Ta-Chien Wu, Chieh-Yin Wen, Tzai-Hung Lan, Chih-Chan Chou, Mei-Fang Lim, Chen-Fatt Lee, Wei-Sen Chen, Wei-Jen Liu, Yu-Lun Cheng, Hao-Yuan Lin, Bo-Cheng Kuo, Fei-Ying Lin, Yu-Xuan Tsai, Yi-Chen Chang, Ning Lin, Hsien-Ho Chang, Hsiao-Han Department of Infectious Disease Epidemiology London School of Hygiene & Tropical Medicine Taiwan Center for Humanities and Social Sciences Academia Sinica Taiwan College of Public Health National Taiwan University Taiwan Department of Geography Environment and Resources National Taiwan University Taiwan Far EasTone Telecommunications Government and Enterprise Big Data Application Department Taiwan National Disaster Prevention and Relief Science and Technology Center Taiwan National Institutes of Health Taiwan Centers for Disease Control Ministry of Health and Welfare Taiwan Department of Real Estate and Urban and Rural Environment National Taipei University Taiwan National Tsing Hua University School of Science Technology and Management Taiwan Institute of Systems Neuroscience National Tsing Hua University Taiwan Institute of Bioinformatics and Structural Biology National Tsing Hua University Taiwan

Human mobility data are used to evaluate the effectiveness of crowd control measures and delineate geographical zones and other epidemic prevention decisions for the COVID-19 epidemic. This application experience also revealed the challenges faced by the application of human mobility data in infectious disease research and practice. For example, there is no available public data and its usage regulations and empirical data to support the research results of the relationship between human movement and epidemic. Moreover, the three parties - data provider, researcher, and practical worker - have no approach to communicating with each other. It is suggested that in the future, a tripartite collaboration mode can be developed in which major domestic telecommunications companies provide, the National Disaster Prevention center handles and maintains, and the government and research institutions apply to the National Disaster Prevention center for use;establish a complete data platform and strengthen instant communication and cooperation channels. © 2023, Taiwan Public Health Association. All rights reserved.

关键词： Big data COVID-19 Human mobility data Infectious disease control

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Arabic translation and validation of the clinician administered Staden schizophrenia anxiety rating scale (S-SARS)

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Heliyon 2024年第21期10卷 e39792页

作者： Fekih-Romdhane, Feten Al Mouzakzak, Fadila Abilmona, Ghinwa Moustafa, Ahmed Dahdouh, Oussama Hallit, Souheil Tunis El Manar University Faculty of Medicine of Tunis Tunis Tunisia The Tunisian Center of Early Intervention in Psychosis Department of psychiatry “Ibn Omrane” Razi hospital 2010 Manouba Tunisia Faculty of Science Lebanese University Fanar Lebanon School of Psychology Faculty of Society and Design Bond University Gold Coast QLD Australia Department of Human Anatomy and Physiology the Faculty of Health Sciences University of Johannesburg South Africa Centre for Data Analytics Bond University Gold Coast QLD Australia Research Department Psychiatric Hospital of the Cross P.O. Box 60096 Jal Eddib Lebanon School of Medicine and Medical Sciences Holy Spirit University of Kaslik P.O. Box 446 Jounieh Lebanon Psychology Department College of Humanities Effat University Jeddah 21478 Saudi Arabia Applied Science Research Center Applied Science Private University Amman Jordan

Background: Research on anxiety in patients with schizophrenia of Arab origin is surprisingly scarce, particularly given that expressions of both psychotic disorders and anxiety disorders can be largely shaped by cultural factors. This study proposes to complement previous research by exploring the psychometric characteristics of an Arabic translation of the Staden Schizophrenia Anxiety Rating Scale (S-SARS) in chronic, remitted patients diagnosed with schizophrenia. As the Arabic version of the Generalized Anxiety Disorder 7-Item Scale (GAD-7) has not been previously validated in Arabic in patients with schizophrenia, this study had as a secondary aim to investigate the psychometric properties of this scale before its use. Method: This cross-sectional study was performed over a period of three months (August–October 2023). A total of 177 chronic inpatients diagnosed with schizophrenia (63.3 % males) who were remitted and clinically stable participated in the study. Results: Confirmatory factor analyses showed that all 10 items loaded onto a single factor and had high factor loading values between .53 and .81. The reliability of the S-SARS in its Arabic version was excellent as attested by a McDonald's omega and a Cronbach's alpha coefficients of .90 and .89, respectively. The score of Arabic S-SARS correlated positively with the GAD-7 scores (r = .55;p < .001), thus supporting good convergent validity. As for discriminant validity, findings showed positive correlations between S-SARS and depression scores as assessed using the Calgary Depressive Symptoms Scale. In addition, the Arabic S-SARS correlated negatively with general functioning, further supporting the good validity and clinical relevance of the scale. Finally, measurement invariance was established in the sex subsamples (males vs. females) at the scalar, metric and configural levels, with females showing more anxiety than males. Conclusion: Findings suggest that the Arabic S-SARS holds good psychometric p

关键词： Anxiety Arabic Psychometric properties S-SARS Schizophrenia Validation

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Investigating Crime Harm in Low and Downward Crime Contexts: A Spatio-Temporal Analysis of the Japanese Crime Harm Index

SSRN

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SSRN 2022年

作者： Ohyama, Tomoya Hanyu, Kazunori Tani, Masayuki Nakae, Momoka Center for Data-driven Science & Artificial Intelligence Tohoku University 41 Kawauchi Aoba-ku Miyagi Sendai980-8576 Japan College of Humanities & Sciences Nihon University 3-25-40 Sakurajosui Setagaya-ku Tokyo156-8550 Japan Ministry of Justice of Japan 1-1-1 KasumigasekiChiyoda-ku Tokyo100-8977 Japan National Police Agency of Japan 2-1-2 Kasumigaseki Chiyoda-ku Tokyo100-8974 Japan

The Cambridge Crime Harm Index (CCHI), which evaluates the harmful impact of crime on the society, as well as attributes the more severe crimes, thereby identifying the areas in a city that are truly harmed by crime. Although this index facilitates informed urban policy, its effectiveness in settings such as that of Japan, in which the rate of violent crimes is low, and where crime occurrence is generally infrequent, remains unclear. Here, the Japanese CHI was analyzed by examining the criminal offense data of 77 jurisdictions in central Tokyo over 10 years (2010–2019). The pre-weighted counts and post-weighted harm were compared to examine the correlations and time-series changes between them, as well as their differences via different indicators, such as the Gini coefficient and Moran's I statistic. Additionally, space-time scans and principal component regressions were employed to determine the specific characteristics of the jurisdictions where harm accumulates. The result indicated that although the temporal and spatial variability of harm was higher than that of its counts, the tendency of high-harm jurisdictions to cluster was lower. Further, the implications of our findings, particularly regarding the socioeconomic factors that were revealed by the regression analysis, to urban policymakers were also discussed. © 2022, The Authors. All rights reserved.

关键词： Crime

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