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Spatial Distribution of Reduced Density of Hard Spheres Near a Hard-Sphere Dimer: Results from Three-Dimensional Ornstein–Zernike Equations Coupled with Several Different Closures and from Grand Canonical Monte Carlo Simulation

SSRN

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SSRN 2023年

作者： Matsuo, Mika Nakamura, Yuka Kinoshita, Masahiro Akiyama, Ryo Department of Chemistry Kyushu University Fukuoka819-0395 Japan Interdisciplinary Program of Biomedical Engineering Assistive Technology and Art and Sports Sciences Faculty of Engineering Niigata University Niigata950-2181 Japan Department of Chemistry Graduate School of Science Chiba University Chiba263-8522 Japan Center for the Promotion of Interdisciplinary Education and Research Kyoto University Kyoto606-8501 Japan

We calculated the spatial distribution of the reduced density and pair distribution function (PDF) of solvent hard spheres near a solute using three-dimensional Ornstein–Zernike (OZ) equations coupled with closures in which Percus–Yevick (PY) and hypernetted–chain (HNC) approximations were used or in which the bridge functions (BFs)proposed by Verlet, Duh and Henderson, and Kinoshita were incorporated. The solute was formed by two solvent hard spheres in contact with each other, with the result that the system was not radial-symmetric, necessitating the extension of the Verlet, Duh–Henderson, and Kinoshita BFs to three-variable functions considered in the Cartesian coordinate system. The results were compared with those from grand canonical Monte Carlo (MC) simulations. In terms of the PDF, HNC was superior to PY in the sense that the results from the former are closer to those from MC. Incorporation of the three BFs made the results even closer to those from MC. The three BFs shared almost the sameperformance for a solute immersed in a one-component solvent at the infinite-dilution limit. Analyses on the triplet distribution function (TDF) were also performed. It was found that in terms of the TDF, the incorporation of the BFs does not necessarily lead to improvement. © 2023, The Authors. All rights reserved.

关键词： Distribution functions

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Extremity in Opposition Supported by Illusion of Explanatory Depth: Study of Support Against Use of Quick Count on Presidential Election

Extremity in Opposition Supported by Illusion of Explanatory...

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International Conference on ICT For Smart Society (ICISS)

作者： Haykal Hafizul Arifin Mirra Noor Milla Hamdi Muluk Aly Lamuri Syazka Kirani Narindra Roosalina Wulandari Lilik Teguh Pambudi Sukma Nurmala Faculty of Psychology Universitas Indonesia Depok Indonesia Depok Indonesia Graduate School of Science and Engineering Rijksuniversiteit Groningen Groningen Netherlands International Business BINUS Business School International Undergraduate Program Bina Nusantara University Jakarta Indonesia Globanostra Think Tank Jakarta Indonesia Jakarta Indonesia Department of Psychology Universitas Brawijaya Malang Indonesia

ISBN: (数字)9798350389654

ISBN: (纸本)9798350389661

This study investigates the phenomenon of knowledge overestimation in the opposition's attitude towards quick counts in general elections in Indonesia. Involving 533 respondents in two studies, the findings of the first study indicate a significant correlation between subjective knowledge, objective knowledge, and the level of extremity in attitudes towards quick counts. These results reveal that individuals with extreme opposition attitudes tend to experience a discrepancy between the knowledge they claim to possess (subjective) and their actual knowledge (objective), depicting the Illusion of Explanatory Depth (IOED) phenomenon. The second study replicates and strengthens these findings, affirming those individuals with extreme opposition and belief in conspiracy theories about quick counts (“paid survey institutions”) have lower subjective knowledge and higher objective knowledge. These findings support the hypothesis that extreme opposition attitudes towards quick counts are fueled by a gap between subjective and objective knowledge. The implications of these findings for public opinion on quick count results in the Indonesian political context are briefly discussed, on how extremity in political views and conspiracy beliefs can skew individuals' perception and assessment of their knowledge.

关键词： Surveys Correlation Voting Extremities

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First-Principles Study of the Optical Dipole Trap for Two-Dimensional Excitons in Graphane

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Physical Review Letters 2022年第4期129卷 047401-047401页

作者： Hiroki Katow Ryosuke Akashi Yoshiyuki Miyamoto Shinji Tsuneyuki Photon Science Center Graduate School of Engineering The University of Tokyo Bunkyo-ku Tokyo 113-8656 Japan Department of Physics The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo 113-0033 Japan Research Center for Computational Design of Advanced Functional Materials National Institute of Advanced Industrial Science and Technology (AIST) Central 2 Tsukuba Ibaraki 305-8568 Japan

Recent studies on excitons in two-dimensional materials have been widely conducted for their potential usages for novel electronic and optical devices. Especially, sophisticated manipulation techniques of quantum degrees of freedom of excitons are in demand. In this Letter we propose a technique of forming an optical dipole trap for excitons in graphane, a two-dimensional wide gap semiconductor, based on first-principles calculations. We develop a first-principles method to evaluate the transition dipole matrix between excitonic states and combine it with the density functional theory and GW+BSE calculations. We reveal that in graphane the huge exciton binding energy and the large dipole moments of Wannier-like excitons enable us to induce the dipole trap of the order of meV depth and μm width. This Letter opens a new way to control light-exciton interacting systems based on newly developed numerically robust ab initio calculations.

关键词： Electric polarization Excitons 2-dimensional systems Semiconductors Density functional theory

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Enhancing wound healing and adhesion through dopamine-assisted gelatin-silica hybrid dressings

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International Journal of Biological Macromolecules 2024年第PT 2期258卷 128845页

作者： Lin, Yu-Chien Wang, Huey-Yuan Tang, Yao-Chun Lin, Wan-Rong Tseng, Ching-Li Hu, Chih-Chien Chung, Ren-Jei Department of Chemical Engineering and Biotechnology National Taipei University of Technology Taipei10608 Taiwan School of Materials Science and Engineering Nanyang Technological University 50 Nanyang Avenue Singapore639798 Singapore Department of Stomatology MacKay Memorial Hospital Taipei104217 Taiwan Graduate Institute of Biomedical Materials and Tissue Engineering College of Biomedical Engineering Taipei Medical University Taipei11031 Taiwan International Ph. D. Program in Biomedical Engineering College of Biomedical Engineering Taipei Medical University Taipei11031 Taiwan Research Center of Biomedical Device College of Biomedical Engineering Taipei Medical University Taipei11031 Taiwan International Ph. D. Program in Cell Therapy and Regenerative Medicine College of Medicine Taipei Medical University Taipei11031 Taiwan Bone and Joint Research Center Chang Gung Memorial Hospital Linkou33305 Taiwan Taipei10608 Taiwan

Gelatin, widely employed in hydrogel dressings, faces limitations when used in high fluid environments, hindering effective material adhesion to wound sites and subsequently reducing treatment efficacy. The rapid degradation of conventional hydrogels often results in breakdown before complete wound healing. Thus, there is a pressing need for the development of durable adhesive wound dressings. In this study, 3-glycidoxypropyltrimethoxysilane (GPTMS) was utilized as a coupling agent to create gelatin-silica hybrid (G-H) dressings through the sol-gel method. The coupling reaction established covalent bonds between gelatin and silica networks, enhancing structural stability. Dopamine (DP) was introduced to this hybrid (G-H-D) dressing to further boost adhesiveness. The efficacy of the dressings for wound management was assessed through in-vitro and in-vivo tests, along with ex-vivo bioadhesion testing on pig skin. Tensile bioadhesion tests demonstrated that the G-H-D material exhibited approximately 2.5 times greater adhesion to soft tissue in wet conditions compared to pure gelatin. Moreover, in-vitro and in-vivo wound healing experiments revealed a significant increase in wound healing rates. Consequently, this material shows promise as a viable option for use as a moist wound dressing. © 2023

关键词： Adhesion

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Reconfigurable Intelligent Surface-Aided Joint Radar and Covert Communications: Fundamentals, Optimization, and Challenges

arXiv

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arXiv 2022年

作者： Du, Hongyang Kang, Jiawen Niyato, Dusit Zhang, Jiayi Kim, Dong In The School of Computer Science and Engineering The Energy Research Institute @ NTU Interdisciplinary Graduate Program Nanyang Technological University Singapore The School of Computer Science and Engineering Nanyang Technological University Singapore The School of Electronic and Information Engineering Beijing Jiaotong University Beijing100044 China The Department of Electrical and Computer Engineering Sungkyunkwan University Suwon16419 Korea Republic of

Future wireless communication systems will evolve toward multi-functional integrated systems to improve spectrum utilization and reduce equipment sizes. A joint radar and communication (JRC) system, which can support simultaneous information transmission and target detection, has been regarded as a promising solution for emerging applications such as autonomous vehicles. In JRC, data security and privacy protection are critical issues. Thus, we first apply covert communication into JRC and propose a joint radar and covert communication (JRCC) system to achieve high spectrum utilization and secure data transmission simultaneously. In the JRCC system, an existence of sensitive data transmission is hidden from a maliciously observant warden. However, the performance of JRCC is restricted by severe signal propagation environment and hardware devices. Fortunately, reconfigurable intelligent surfaces (RISs) can change the signal propagation smartly to improve the networks performance with low cost. We first overview fundamental concepts of JRCC and RIS and then propose the RIS-aided JRCC system design. Furthermore, both covert communication and radar performance metrics are investigated and a game theory-based covert rate optimization scheme is designed to achieve secure communication. Finally, we present several promising applications and future directions of RIS-aided JRCC systems. © 2022, CC BY.

关键词： Data transfer

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Tuning the Size and Stiffness of Inflatable Particles

arXiv

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arXiv 2025年

作者： Pashine, Nidhi Wang, Dong Baines, Robert Goyal, Medha Shattuck, Mark D. O’Hern, Corey S. Kramer-Bottiglio, Rebecca Department of Mechanical Engineering Yale University New HavenCT06520 United States Department of Physics BioInspired Institute Syracuse University SyracuseNY13244 United States Department of Physics Benjamin Levich Institute City College of New York New York CityNY10031 United States Department of Physics Yale University New HavenCT06520 United States Department of Applied Physics Yale University New HavenCT06520 United States Graduate Program in Computational Biology & Biomedical Informatics Yale University New HavenCT06520 United States

We describe size-varying cylindrical particles made from silicone elastomers that can serve as building blocks for robotic granular materials. The particle size variation, which is achieved by inflation, gives rise to changes in stiffness under compression. We design and fabricate inflatable particles that can become stiffer or softer during inflation, depending on key parameters of the particle geometry, such as the ratio of the fillet radius to the wall thickness, r/t. We also conduct numerical simulations of the inflatable particles and show that they only soften during inflation when localization of large strains occurs in the regime r/t → 0. This work introduces novel particle systems with tunable size and stiffness that can be implemented in numerous soft robotic applications. © 2025, CC BY.

关键词： Stiffness

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Pressure-driven homogenization of lithium disilicate glasses

arXiv

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arXiv 2023年

作者： Bakhouch, Yasser Buchner, Silvio Silveira, Rafael Abel Resende, Leonardo Pereira, Altair Soria Hasnaoui, Abdellatif Atila, Achraf LS2ME Faculté Polydisciplinaire Khouribga Sultan Moulay Slimane University of Beni Mellal B.P 145 Khouribga25000 Morocco Graduate Program in Materials Science Federal University of Rio Grande do Sul Porto Alegre Brazil Department of Material Science and Engineering Saarland University Saarbrücken66123 Germany

Lithium disilicate glasses and glass-ceramics are good potential candidates for biomedical applications and solid-state batteries, and serve as models of nucleation and crystal growth. Moreover, these glasses exhibit a phase separation that influences their nucleation and crystallization behavior. The atomistic mechanisms of the phase separation and their pressure dependence are unclear so far. Here, we used molecular dynamics simulations supported by experiments to assess the spatial heterogeneity of lithium disilicate glasses prepared under pressure. We show that the glass heterogeneity decreases with increasing the cooling pressure and almost disappears at pressures around 30 GPa. The origin of the heterogeneity is due to the attraction between Li cations to form clustering channels, which decreases with pressure. Through our results, we hope to provide valuable insights and guidance for making glass-ceramics with controlled crystallization. Copyright © 2023, The Authors. All rights reserved.

关键词： Phase separation

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Classification of Hotel Customer Based on Support Vector Machine

Classification of Hotel Customer Based on Support Vector Mac...

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International Conference on Advanced Mechatronics, Intelligent Manufacture, and Industrial Automation (ICAMIMIA)

作者： Choirul Huda Yaya Heryadi Lukas Wayan Suparta Antoni Wibowo Computer Science Department Doctor of Computer Science Graduate Program Bina Nusantara University Jakarta Indonesia Computer Science Department Bina Nusantara University Jakarta Indonesia Computer Engineering Research Group (CERG) Atma Jaya University Jakarta Indonesia Computer Science Department Graduate Program Bina Nusantara University Jakarta Indonesia

ISBN: (纸本)9781665499705

The tourism industry has contributed positively for regional and global economic income in recent years. Although this sector faces a hard challenge in COVΓD-19 pandemic, it has been predicted that it will rebound and will continue in growing as in previous periods. Tourist experience should become important to be improved regarding the service level for visitors such as the improvement of hotel customer accommodation. The aim of this study is classifying the hotel customer based on Support Vector Machine (SVM). This classification conducted through classification of satisfaction level and the related factors. The result of the study presented a good accuracy and precision of SVM in conducting customer hotel classification at 93% accuracy level with error level of prediction result for about 0.27 based on Root Mean Squared Error (RSME) function. The features of customer satisfaction at this study are proposed to be important preferences for improvement of customer services in hospitality.

关键词： Support vector machines Economics Mechatronics Pandemics Tourism industry Europe Machine learning

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Impact of Image Enhancement for Osteoporosis Detection Based on Deep Learning Algorithm

Impact of Image Enhancement for Osteoporosis Detection Based...

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Computer System, Information Technology, and Electrical engineering (COSITE), International Conference on

作者： Riza Dianil Iman Roslidar Roslidar Kahlil Muchtar Amalia Amalia Mohammad Syaryadhi Alfatirta Mufti Novi Maulina Department of Electrical and Computer Engineering Universitas Syiah Kuala Banda Aceh Indonesia Department of Computer Science Universitas Sumatera Utara Medan Indonesia Graduate School of System Designs Tokyo Metropolitan University Tokyo Japan Doctorate Student of Doctoral Program in Medical Sciences Faculty of Medicine Universitas Syiah Kuala Banda Aceh Indonesia

Osteoporosis can be defined as a degenerative disease with reduced bone mass and changes in bone architecture that can lead to bone fragility and the risk of fractures. This abnormality can be indicated by the bone density which in visual can be determined using X-Ray images. However, X-Ray images are susceptible to noise, while in image analysis image contrast affects deep learning abilities. Hence, the CLAHE (Contrast Limited Adaptive Histogram Equalization) algorithm is used as a contrast enhancement technique in X-Ray images. This study aims to build a deep learning model using the CLAHE-enhanced image dataset with the ResNet-50 and ResNet-101 architectures. The model was built using two different datasets, namely the original image dataset and the CLAHE-enhanced image dataset. The result shows that the highest performance is given by the ResNet-101 model using the CLAHE-enhanced image dataset with an accuracy rate of 96%, precision of 95%, specificity of 95%, recall of 97% and an Fl-score of 96%, respectively. By using the CLAHE algorithm, the resulting image has high contrast and looks better at displaying features in the image so as to produce better model performance.

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AVTENet: Audio-Visual Transformer-based Ensemble Network Exploiting Multiple Experts for Video Deepfake Detection

arXiv

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arXiv 2023年

作者： Hashmi, Ammarah Shahzad, Sahibzada Adil Lin, Chia-Wen Tsao, Yu Wang, Hsin-Min The Social Networks and Human-Centered Computing Program Taiwan International Graduate Program Academia Sinica Taipei11529 Taiwan The Institute of Information Systems and Applications National Tsing Hua University Hsinchu30013 Taiwan The Department of Computer Science National Chengchi University Taipei11605 Taiwan The Department of Electrical Engineering The Institute of Communications Engineering National Tsing Hua University Hsinchu300044 Taiwan The Research Center for Information Technology Innovation Academia Sinica Taipei11529 Taiwan The Institute of Information Science Academia Sinica Taipei11529 Taiwan

Forged content shared widely on social media platforms is a major social problem that requires increased regulation and poses new challenges to the research community. The recent proliferation of hyper-realistic deepfake videos has drawn attention to the threat of audio and visual forgeries. Most previous work on detecting AI-generated fake videos only utilizes visual modality or audio modality. While there are some methods in the literature that exploit audio and visual modalities to detect forged videos, they have not been comprehensively evaluated on multi-modal datasets of deepfake videos involving acoustic and visual manipulations. Moreover, these existing methods are mostly based on CNN and suffer from low detection accuracy. Inspired by the recent success of Transformer in various fields, to address the challenges posed by deepfake technology, in this paper, we propose an Audio-Visual Transformer-based Ensemble Network (AVTENet) framework that considers both acoustic manipulation and visual manipulation to achieve effective video forgery detection. Specifically, the proposed model integrates several purely transformer-based variants that capture video, audio, and audio-visual salient cues to reach a consensus in prediction. For evaluation, we use the recently released benchmark multi-modal audio-video FakeAVCeleb dataset. For a detailed analysis, we evaluate AVTENet, its variants, and several existing methods on multiple test sets of the FakeAVCeleb dataset. Experimental results show that our best model outperforms all existing methods and achieves state-of-the-art performance on Testset-I and Testset-II of the FakeAVCeleb dataset. © 2023, CC BY.

关键词： Statistical tests

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