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Investigating the Psychological Outcomes Through Yoga for Stress Reduction Using Machine Learning and Statistical Techniques

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SN Computer science 2024年第8期5卷 1-14页

作者： Gupta, Apurva Kadyan, Virender Telles, Shirley Machine Intelligence Research Center School of Computer Science University of Petroleum and Energy Studies Uttarakhand Dehradun India Patanjali Research Foundation Uttarakhand Haridwar India

Yoga has become crucial mode of intervention in enhancing mental health through empirical and data-supported methodologies. This study investigates the effects of yoga interventions after cognitive task on physiological and psychological parameters, specifically blood pressure (BP) and State-Trait Anxiety Inventory (STAI) scores, using optimized machine learning techniques. The primary objective was to analyze and predict how different yoga practices impact individual health outcomes through stress reduction. The initial phase involved collecting baseline data on BP and STAI parameters from participants before and after interventions. The various machine learning algorithms were employed to model the data, with a focus on their performance in predicting changes in BP and anxiety levels as measured by the STAI. In like manner, subsequent analysis using DT and RF models demonstrated promising results in terms of accuracy, with RF and DT particularly effective in handling the complex patterns in the combined BP and STAI data. Further, the Artificial Bee Colony algorithm was applied to optimize the hyper-parameters of the DT and RF models. The optimized models, termed BP-STAI Combined-Optimized DT and BP-STAI Combined-Optimized RF, achieved accuracies of 69.90% and 75.43%, respectively. These results highlight a significant improvement over the non-optimized models and underscore the effectiveness of combining physiological and psychological data in predictive analytics. The findings provide valuable insights into cognitive-driven stress reduction and the broader implications of employing advanced data-driven approaches in health and wellness research. © The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. 2024.

关键词： Blood pressure (BP) Machine learning Optimization State-Trait Anxiety Inventory (STAI) Yoga Interventions

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The cranial base and midface characteristics in apert and Crouzon syndrome: A 3-dimensional analysis of morphological variations

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Journal of Cranio-Maxillofacial Surgery 2025年第7期53卷 855-864页

作者： Zheng, Lantian Hariri, Firdaus Ramli, Norlisah Mohd Abdullah, Norli Anida Department of Oral and Maxillofacial Clinical Sciences Faculty of Dentistry Universiti Malaya Malaysia Department of Biomedical Imaging Faculty of Medicine Universiti Malaya Malaysia Mathematics Division Centre for Foundation Studies in Science Universiti Malaya Malaysia Center for Data Analytics Consultancy and Services Faculty of Science Universiti Malaya Malaysia

The craniofacial morphology in patients with syndromic craniosynostosis varies from one spectrum to another. Our study aims to explore the craniofacial morphology and growth pattern in patients with Apert and Crouzon syndrome. This study involved 39 computed tomographic scans of skull (Apert = 11, Crouzon = 10, Control = 18), divided into 2 age subgroups. The non-parametric Mann-Whitney U test was performed to investigate the morphological characteristics between Apert, Crouzon and Control groups. The length of the middle cranial fossa decreased in both syndromes, but clivus length increased slightly in Apert syndrome and decreased in Crouzon syndrome. In Apert syndrome, midface height and width were control, and in Crouzon, the posterior height and width were slightly shorter, and the anterior side was control. The length of the midface was shortened in particular the upper segment. Zygomatic bone length and height as well as zygomatic arch length were developed close to control with a rotation in Apert syndrome. The zygomatic bones and arch in Crouzon syndrome were shortened in length and control in height without a rotation. The contributions of maxillary, zygomatic, and palatal deformities to midface malformation vary between two syndromes. Moreover, there was uneven severity of maxillary and zygomatic developmental deformities in both syndromes. © 2025 European Association for Cranio-Maxillo-Facial Surgery

关键词： Apert syndrome Cranial base Crouzon syndrome Midface Morphology

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A comparative evaluation of augmented reality and virtual reality on chemistry experiment learning in higher level education

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Multimedia Tools and Applications 2024年 1-40页

作者： Lam, Meng Chun Majid, Nazatul Aini Abd Hassan, Nurul Izzaty Mobarak, Nadhratun Naiim Tan, Siok Yee Hashim, Harwati Liew, Sook Yee Soon, Daniel Abidin, Rimaniza Zainal Suwadi, Nur Asylah Mixed Reality and Pervasive Computing Lab Center for Artificial Intelligence Technology Faculty of Information Science & Technology Universiti Kebangsaan Malaysia Bangi43600 Malaysia Department of Chemical Sciences Faculty of Science and Technology Universiti Kebangsaan Malaysia Selangor Bangi43600 Malaysia Centre of Innovation in Teaching and Learning Faculty of Education Universiti Kebangsaan Malaysia Bangi43600 Malaysia Chemistry Division Centre for Foundation Studies in Science Universiti Malaya Kuala Lumpur50603 Malaysia Center for Software Technology and Management Faculty of Information Science & Technology Universiti Kebangsaan Malaysia Bangi43600 Malaysia

In the constantly evolving landscape of higher education, integrating cutting-edge technologies has become crucial for enhancing learning experiences. As advancements in Augmented Reality (AR) and Virtual Reality (VR) continue to redefine educational paradigms, it is essential to understand their unique contributions to Chemistry education. The objective of this study is to assess the impact of AR and VR technology on knowledge acquisition, performance, user acceptance, and motivation. This was achieved through a comparative analysis of AR and VR mobile applications in a learning environment for chemistry experiments. The evaluation involved three main phases: pre-test, post-test and exchange phase. A total of 32 participants were recruited for the between-subject evaluation. Each group completed demographic forms and knowledge tests to ensure balanced representation. Afterwards, the participants were required to complete the knowledge test and questionnaire in the post-test. While in the exchange phase, it was held to acquire participants’ preferences on the best application to conduct chemistry experiments. The results reveal significant findings for both groups, indicating that AR and VR applications offer enhanced learning experiences. The results showed significant improvements in knowledge acquisition for both AR and VR groups, with both AR and VR groups demonstrating a substantial increase in knowledge scores in the post-test phase. Notably, the AR score was 44% better than the VR group in the post-test phase. In addition, the participants expressed significantly greater satisfaction with AR than with VR, implying a higher level of comfort and contentment with AR technology for conducting chemistry experiments. © The Author(s), under exclusive licence to Springer science+Business Media, LLC, part of Springer Nature 2024.

关键词： Virtual environments

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Building imaginary-time thermal field theory with artificial neural networks

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Chinese Physics C 2024年第10期48卷 23-30页

作者： Tian Xu Lingxiao Wang Lianyi He Kai Zhou Yin Jiang Physics Department Beihang University37 Xueyuan RdBeijing 100191China Shanghai Research Center for Theoretical Nuclear Physics National Natural Science Foundation of ChinaFudan UniversityShanghai 200438China Department of Physics Tsinghua UniversityBeijing 100084China School of Science and Engineering The Chinese University of Hong KongShenzhenShenzhen 518172China Frankfurt Institute for Advanced Studies Ruth-Moufang-Str.160438 Frankfurt am MainGermany

In this paper,we introduce a novel approach in quantum field theories to estimate actions using artificial neural networks(ANNs).The actions are estimated by learning system configurations governed by the Boltzmann factor,e^(-s),at different temperatures within the imaginary time formalism of thermal field ***,we focus on the 0+1 dimensional quantum field with kink/anti-kink configurations to demonstrate the feasibility of the ***-mixture autoregressive networks(CANs)enable the construction of accurate effective actions with tractable probability density *** numerical results demonstrate that this methodology not only facilitates the construction of effective actions at specified temperatures but also adeptly estimates the action at intermediate temperatures using data from both lower and higher temperature *** capability is especially valuable for detailed exploration of phase diagrams.

关键词： artificial neural network imaginary-time thermal field theory effective model probability estimation

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AI for organic and polymer synthesis

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science China Chemistry 2024年第8期67卷 2461-2496页

作者： Xin Hong Qi Yang Kuangbiao Liao Jianfeng Pei Mao Chen Fanyang Mo Hua Lu Wen-Bin Zhang Haisen Zhou Jiaxiao Chen Lebin Su Shuo-Qing Zhang Siyuan Liu Xu Huang Yi-Zhou Sun Yuxiang Wang Zexi Zhang Zhunzhun Yu Sanzhong Luo Xue-Feng Fu Shu-Li You Center of Chemistry for Frontier Technologies Department of ChemistryZhejiang UniversityHangzhou 310027China Center of Basic Molecular Science Department of ChemistryTsinghua UniversityBeijing 100084China Guangzhou National Laboratory Guangzhou 510005China Center for Quantitative Biology Academy for Advanced Interdisciplinary StudiesPeking UniversityBeijing 100871China State Key Laboratory of Molecular Engineering of Polymers Department of Macromolecular ScienceFudan UniversityShanghai 200433China School of Materials Science and Engineering Peking UniversityBeijing 100871China Beijing National Laboratory for Molecular Sciences Center for Soft Matter Science and EngineeringKey Laboratory of Polymer Chemistry and Physics of Ministry of EducationCollege of Chemistry and Molecular EngineeringPeking UniversityBeijing 100871China AI for Science(AI4S)-Preferred Program Shenzhen Graduate SchoolPeking UniversityShenzhen 518055China State Key Laboratory of Chemical Biology Shanghai Institute of Organic ChemistryUniversity of Chinese Academy of SciencesChinese Academy of SciencesShanghai 200032China Department of Chemical Sciences National Natural Science Foundation of ChinaBeijing 100085China State Key Laboratory of Organometallic Chemistry Shanghai Institute of Organic ChemistryChinese Academy of SciencesShanghai 200032China

Recent years have witnessed the transformative impact from the integration of artificial intelligence with organic and polymer synthesis. This synergy offers innovative and intelligent solutions to a range of classic problems in synthetic chemistry. These exciting advancements include the prediction of molecular property, multi-step retrosynthetic pathway planning, elucidation of the structure-performance relationship of single-step transformation, establishment of the quantitative linkage between polymer structures and their functions, design and optimization of polymerization process, prediction of the structure and sequence of biological macromolecules, as well as automated and intelligent synthesis platforms. Chemists can now explore synthetic chemistry with unprecedented precision and efficiency, creating novel reactions, catalysts, and polymer materials under the datadriven paradigm. Despite these thrilling developments, the field of artificial intelligence(AI) synthetic chemistry is still in its infancy, facing challenges and limitations in terms of data openness, model interpretability, as well as software and hardware support. This review aims to provide an overview of the current progress, key challenges, and future development suggestions in the interdisciplinary field between AI and synthetic chemistry. It is hoped that this overview will offer readers a comprehensive understanding of this emerging field, inspiring and promoting further scientific research and development.

关键词： organic synthesis polymer synthesis machine learning prediction chemical database automated synthesis

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Review of: Joshua Zimmerman, Pilsudski: Founding Father of Modern Poland, Cambridge, MA, Harvard University Press, 2022, 640 pages, Hardcover: ISBN 9780674984271, $39.95

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studies in East European Thought 2023年第2期77卷 415-417页

作者： Koczanowicz, Tadeusz Swiss National Science Foundation Mobility Postdoc Transregional Center for Democratic Studies The New School for Social Research New York USA

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Effects of friction stir processing and nano-hydroxyapatite on the microstructure,hardness,degradation rate and in-vitro bioactivity of WE43 alloy for biomedical applications

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Journal of Magnesium and Alloys 2024年第1期12卷 209-224页

作者： Bo Wu Farazila Yusof Fuguo Li Huan Miao A.R.Bushroa Mohd Ridha Bin Muhamad Irfan Anjum Badruddin Mahmoud Z.Ibrahim Department of Mechanical Engineering Faculty of EngineeringUniversiti MalayaKuala Lumpur 50603Malaysia Centre of Advanced Manufacturing and Material Processing(AMMP Centre) Universiti MalayaKuala Lumpur 50603Malaysia Center of Foundation studies in Science Universiti MalayaKuala Lumpur 50603Malaysia State Key Laboratory of Solidification Processing School of Materials Science and EngineeringNorthwestern Polytechnical UniversityXi’an 710072China Mechanical Engineering Department College of EngineeringKing Khalid UniversityAbha 61421Saudi Arabia Design and Production Engineering Faculty of EngineeringAin Shams UniversityCairo 11517Egypt

Nowadays,magnesium alloys are emerging in biomedical implants for their similar properties to natural ***,the rapid degradation of magnesium alloys in biological media hinders successful *** of microstructure,as well as reinforcement particles can significantly improve the degradation *** this work,multi-pass friction stir processing(FSP)was proposed to synthesize WE43/nano-hydroxyapatite(n HA)surface composite,the microstructure,reinforced particle distribution,micro-hardness,corrosion behavior and in-vitro bioactivity were *** subsequent FSP passes of WE43 alloy and WE43/n HA composite refined the grain size which was reduced by 94.29%and 95.92%(2.63 and 1.88μm,respectively)compared to base metal after three *** resulted in increasing the microhardness by 120%(90.86 HV0.1)and 135%(105.59 HV0.1)for the WE43 and WE43-n HA,*** is found that increasing FSP passes improved the uniform distribution of n HA particles within the composite matrix which led to improved corrosion resistance and less degradation *** corrosion rate of the FSPed WE43/n HA composite after three passes was reduced by 38.2%(4.13 mm/year)and the degradation rate was reduced by 69.7%(2.87 mm/y).This is attributed to secondary phase(Mg24Y5and Mg41Nd5)particle fragmentation and redistribution,as well as a homogeneous distribution of n ***,the growing Ca-P and Mg(OH)2layer formed on the surface represented a protective layer that reduced the degradation *** wettability test revealed a relatively hydrophilic surface with water contact angle of 49.1±2.2°compared to 71.2±2.1°for base ***,biomineralization test showed that apatite layer grew after immersion 7d in simulated body fluid with atomic ratio of Ca/P 1.60 approaching the stoichiometric ratio(1.67)indicating superior bioactivity of FSPed WE43/n HA composite after three *** results raise that the grain refinement by FSP and introduction of n HA partic

关键词： Friction stir processing Magnesium-based composite Nano-hydroxyapatite Corrosion behavior In-vitro bioactivity

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Analysis of critical raw materials policy for electrical and electronic equipment: Planning for a truly circular economy

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Resources Policy 2024年 99卷

作者： Vafeas, N.A. Slezak, P. Hitzman, M.W. Science Foundation Ireland Centre for Research in Applied Geosciences School of Earth Science O'Brien Centre for Science University College Dublin Ireland Idaho National Lab Center for Advanced Energy Studies 955 MK Simpson Blvd Idaho FallsID83401 United States

The European Union's objectives under the Green and Digital transitions, are contingent on the decarbonisation of essential sectors such as energy, transportation, and communications. At present, the EU does not have sufficient identified mineral resources, nor processing capacity, to supply many of its strategically defined materials. The success of these objectives hinges on the EU's ability to secure a stable and consistent supply of critical raw materials (CRM). Using a systematic three-part assessment of mandated and non-mandated EU policies, European Commission communications, and a review of CRM, the findings reveal that despite efforts to enhance local supply and diversify foreign sources of CRM, there is a lack of cross-sector coherence across social, economic, and technical aspects of recycling. This is further exacerbated by inefficient retention of waste-hosted critical raw materials. Failure to adopt integrative policy measures may result in the EU's continued dependency on undiversified foreign sources for its supply of critical raw materials, thereby compromising its strategic autonomy as well as the goals of the Green and Digital transitions. Improved design of electrical and electronic equipment and processing of waste from these products could conceivably provide a mechanism for a continuous and retained supply of critical raw materials, culminating in a potentially significant resource stream for the Union. The EU can improve resource efficiency, reduce its dependence on imports, and facilitate a truly circular economy by adopting a comprehensive and symbiotic policy framework that quantifies material resources in waste and that recognises the product design stage as an integral facet of the product recycling stage, herein referred to as "forwardcycling". © 2024 Elsevier Ltd

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Facial Asymmetry Classification in Neurological Disorders: Integrating Computer Vision and Machine Learning for Improved Patient Care 8

Facial Asymmetry Classification in Neurological Disorders: I...

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8th IEEE International Forum on Research and Technologies for Society and Industry Innovation, RTSI 2024

作者： Ranjan, Pratik Lasala, Angelo Ruscelli, Anna Lina Sahu, Sujit Kumar Guarín, Diego L. Moccia, Sara Castoldi, Piero Micera, Silvestro Bandini, Andrea School of Advanced Studies University of Camerino Italy The BioRobotics Institute Scuola Superiore Sant'Anna Pisa Italy TeCIP Institute Health Science Interdisciplinary Center Scuola Superiore Sant'Anna Pisa Italy TeCIP Institute Scuola Superiore Sant'Anna Pisa Italy University of Florida Department of Applied Physiology and Kinesiology Department of Biomedical Engineering GainesvilleFL United States The BioRobotics Institute Health Science Interdisciplinary Center Scuola Superiore Sant'Anna Pisa Italy Epfl Bertarelli Foundation in Translational Neuroengineering Geneva Switzerland

ISBN: (纸本)9798350362138

Facial gestures and movements play a critical role in communicating, eating, and expressing emotions, making the assessment of oro-facial functions vital in clinical practice. Neurological conditions such as stroke and facial palsy significantly impact these movements, necessitating accurate differentiation for appropriate diagnosis. This paper proposes an automated approach to classifying facial asymmetry in stroke and peripheral facial paralysis, leveraging computer vision and machine learning algorithms. Using public datasets like the Toronto NeuroFace and Massachusetts Eye and Ear Infirmary (MEEI), we employed facial landmark localization, comprehensive feature extraction, and classification techniques to discern subtle variations in facial movements and expressions across different conditions. Our approach achieved promising results, with accuracy up to 88% to distinguish facial impairments due to stroke and facial palsy. Tasks such as lip spreading, blinking, and eyebrow-raising demonstrated high accuracy, aligning with previous findings. Our study lays the groundwork for improving the diagnosis and treatment of oro-facial impairments using machine learning, with potential applications in clinical and emergency settings to enhance patient care and diagnostic accuracy. © 2024 IEEE.

关键词： Diagnosis

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Banana Disease Recognition Using Deep Learning Based Method Combined With Attention Mechanism

Banana Disease Recognition Using Deep Learning Based Method ...

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International Conference on Computer and Information Technology (ICCIT)

作者： Tahmina Hoque Norli Anida Abdullah Muhammad Asif Hasan Najiah Mohd Sadali School of Science Engineering and Technology East Delta University Chattogram Bangladesh Mathematics Division Center for Foundation Studies in Science University of Malaya Kuala Lumpur Malaysia Centre for Research in Biotechnology for Agriculture (CEBAR) Universiti Malaya Kuala Lumpur Malaysia

ISBN: (数字)9798331519094

ISBN: (纸本)9798331519100

In numerous Asian countries, bananas are a key component of international trade and a significant source of foreign exchange earnings. However, the banana agriculture sector faces a substantial challenge due to disease affecting banana leaves. These diseases significantly affect the sector by reducing both the quality and quantity of the produce. To address this problem, this study proposes a convolutional neural network (CNN) model, enhanced with a spatial attention mechanism as an augmented module for identifying diseases in banana leaves. We compiled a dataset of 5,583 images, from real-life instances and the Mendeley database, divided into 13 classes representing different banana leaf diseases. During preprocessing, a deep convolutional generative adversarial network (DCGAN) was utilized to augment the image samples, thereby addressing the problem of uneven data distribution. In our comparative analysis, we assessed several well-known pre-trained models employing transfer learning and fine-tuning techniques, alongside a vision transformer model VIT32. The experimental results were promising: the proposed model achieved an accuracy of 96.37% indicating its efficacy in classifying various types of banana leaf diseases on this multiclass dataset.

关键词： Deep learning Training Attention mechanisms Accuracy Computational modeling Transfer learning Graph neural networks Data models Convolutional neural networks Diseases

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