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arXiv 2021年

作者： Piaggi, Pablo Miguel Panagiotopoulos, Athanassios Z. Debenedetti, Pablo G. Car, Roberto Department of Chemistry Princeton University PrincetonNJ08544 United States Department of Chemical and Biological Engineering Princeton University PrincetonNJ08544 United States Princeton Institute for the Science and Technology of Materials Princeton University PrincetonNJ08544 United States Department of Physics Princeton University PrincetonNJ08544 United States Program in Applied and Computational Mathematics Princeton University PrincetonNJ08544 United States

Machine learning models are rapidly becoming widely used to simulate complex physicochemical phenomena with ab initio accuracy. Here, we use one such model as well as direct density functional theory (DFT) calculations to investigate the phase equilibrium of water, hexagonal ice (Ih), and cubic ice (Ic), with an eye towards studying ice nucleation. The machine learning model is based on deep neural networks and has been trained on DFT data obtained using the SCAN exchange and correlation functional. We use this model to drive enhanced sampling simulations aimed at calculating a number of complex properties that are out of reach of DFT-driven simulations and then employ an appropriate reweighting procedure to compute the corresponding properties for the SCAN functional. This approach allows us to calculate the melting temperature of both ice polymorphs, the driving force for nucleation, the heat of fusion, the densities at the melting temperature, the relative stability of ice Ih and Ic, and other properties. We find a correct qualitative prediction of all properties of interest. In some cases, quantitative agreement with experiment is better than for state-of-the-art semiempirical potentials for water. Our results also show that SCAN correctly predicts that ice Ih is more stable than ice Ic. Copyright © 2021, The Authors. All rights reserved.

关键词： Ice

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DeePMD-kit v2: A software package for Deep Potential models

arXiv

引用

arXiv 2023年

作者： Zeng, Jinzhe Zhang, Duo Lu, Denghui Mo, Pinghui Li, Zeyu Chen, Yixiao Rynik, Marián Huang, Li'ang Li, Ziyao Shi, Shaochen Wang, Yingze Ye, Haotian Tuo, Ping Yang, Jiabin Ding, Ye Li, Yifan Tisi, Davide Zeng, Qiyu Bao, Han Xia, Yu Huang, Jiameng Muraoka, Koki Wang, Yibo Chang, Junhan Yuan, Fengbo Bore, Sigbjørn Løland Cai, Chun Lin, Yinnian Wang, Bo Xu, Jiayan Zhu, Jia-Xin Luo, Chenxing Zhang, Yuzhi Goodall, Rhys E.A. Liang, Wenshuo Singh, Anurag Kumar Yao, Sikai Zhang, Jingchao Wentzcovitch, Renata Han, Jiequn Liu, Jie Jia, Weile York, Darrin M. Weinan, E. Car, Roberto Zhang, Linfeng Wang, Han Laboratory for Biomolecular Simulation Research Institute for Quantitative Biomedicine Department of Chemistry and Chemical Biology Rutgers University PiscatawayNJ08854 United States AI for Science Institute Beijing100080 China DP Technology Beijing100080 China Academy for Advanced Interdisciplinary Studies Peking University Beijing100871 China HEDPS CAPT College of Engineering Peking University Beijing100871 China College of Electrical and Information Engineering Hunan University Changsha China Yuanpei College Peking University Beijing100871 China Program in Applied and Computational Mathematics Princeton University PrincetonNJ08540 United States Department of Experimental Physics Comenius University Mlynská Dolina F2 Bratislava842 48 Slovakia Center for Quantum Information Institute for Interdisciplinary Information Sciences Tsinghua University Beijing100084 China Center for Data Science Peking University Beijing100871 China ByteDance Research Zhonghang Plaza No. 43 North 3rd Ring West Road Haidian District Beijing China College of Chemistry and Molecular Engineering Peking University Beijing100871 China Baidu Inc. Beijing China Key Laboratory of Structural Biology of Zhejiang Province School of Life Sciences Westlake University Zhejiang Hangzhou China Westlake AI Therapeutics Lab Westlake Laboratory of Life Sciences and Biomedicine Zhejiang Hangzhou China Department of Chemistry Princeton University PrincetonNJ08544 United States SISSA Scuola Internazionale Superiore di Studi Avanzati Trieste34136 Italy Laboratory of Computational Science and Modeling Institute of Materials École Polytechnique Fédérale de Lausanne Lausanne1015 Switzerland Department of Physics National University of Defense Technology Hunan Changsha410073 China State Key Lab of Processors Institute of Computing Technology Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China School of Electronics Engineerin

DeePMD-kit is a powerful open-source software package that facilitates molecular dynamics simulations using machine learning potentials (MLP) known as Deep Potential (DP) models. This package, which was released in 2017, has been widely used in the fields of physics, chemistry, biology, and material science for studying atomistic systems. The current version of DeePMD-kit offers numerous advanced features such as DeepPot-SE, attention-based and hybrid descriptors, the ability to fit tensile properties, type embedding, model deviation, Deep Potential - Range Correction (DPRc), Deep Potential Long Range (DPLR), GPU support for customized operators, model compression, non-von Neumann molecular dynamics (NVNMD), and improved usability, including documentation, compiled binary packages, graphical user interfaces (GUI), and application programming interfaces (API). This article presents an overview of the current major version of the DeePMD-kit package, highlighting its features and technical details. Additionally, the article benchmarks the accuracy and efficiency of different models and discusses ongoing developments. © 2023, CC BY-NC-ND.

关键词： Molecular dynamics

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Towards realistic simulations of human cough: effect of droplet emission duration and spread angle

arXiv

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arXiv 2022年

作者： Li, Mogeng Chong, Kai Leong Ng, Chong Shen Bahl, Prateek de Silva, Charitha M. Verzicco, Roberto Doolan, Con MacIntyre, C. Raina Lohse, Detlef Physics of Fluids Group Max Planck Center for Complex Fluid Dynamics J. M. Burgers Center for Fluid Dynamics and MESA+ Research Institute Department of Science and Technology University of Twente Enschede7500AE Netherlands Max Planck Institute for Dynamics and Self-Organisation Göttingen37077 Germany Shanghai Key Laboratory of Mechanics in Energy Engineering Shanghai Institute of Applied Mathematics and Mechanics School of Mechanics and Engineering Science Shanghai University Shanghai200072 China School of Mechanical and Manufacturing Engineering UNSW Sydney KensingtonNSW2052 Australia Dipartimento di Ingegneria Industriale University of Rome 'Tor Vergata' Roma00133 Italy Gran Sasso Science Institute Viale F. Crispi L'Aquila7 67100 Italy Biosecurity Program The Kirby Institute UNSW Sydney KensingtonNSW2052 Australia College of Public Service & Community Solutions College of Health Solutions Arizona State University PhoenixAZ United States

Human respiratory events, such as coughing and sneezing, play an important role in the host-to-host airborne transmission of diseases. Thus, there has been a substantial effort in understanding these processes: various analytical or numerical models have been developed to describe them, but their validity has not been fully assessed due to the difficulty of a direct comparison with real human exhalations. In this study, we report a unique comparison between datasets that have both detailed measurements of a real human cough using spirometer and particle tracking velocimetry, and direct numerical simulation at similar conditions. By examining the experimental data, we find that the injection velocity at the mouth is not uni-directional. Instead, the droplets are injected into various directions, with their trajectories forming a cone shape in space. Furthermore, we find that the period of droplet emissions is much shorter than that of the cough: experimental results indicate that the droplets with an initial diameter 10µm are emitted within the first 0.05 s, whereas the cough duration is closer to 1 s. These two features (the spread in the direction of injection velocity and the short duration of droplet emission) are incorporated into our direct numerical simulation, leading to an improved agreement with the experimental measurements. Thus, to have accurate representations of human expulsions in respiratory models, it is imperative to include parametrisation of these two features. © 2022, CC BY.

关键词： COVID-19

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Application of fishing boat’s redrawing technique by using the tools pantograph on coastal purse seiner of North Sulawesi

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AIP Conference Proceedings 2023年第1期2694卷

作者： Kawilarang. W. A. Masengi B. Pinontoan H. Kolibu I. F. Mandagi S. A. Lawelle E. P. Sitanggang I. L. Labaro A. W. R. Masengi F. Wongkar J. Tumbal The Graduate Program of Marine Science Sam Ratulangi University Manado Indonesia Faculty of Fisheries and Marine Sciences Sam Ratulangi University Manado Indonesia Faculty of Mathematics and Natural Sciences Sam Ratulangi University Manado Indonesia Faculty of Fisheries and Marine Sciences Halo Uleo University Kendari Indonesia Faculty of Marine Engineering Minaesa Institute of Technology Tomohon Indonesia

North Sulawesi marine fisheries play a leading role in income after agriculture in this region. The dominant marine fisheries on sub-sector capture fisheries are pelagic fish species. The contributions of marine production North Sulawesi are supported by coastal purse seiner fisheries activities. On the other hand, so many problems faced by the fishery authority are Illegal, Unreported, Unregulated (IUU) fishing activities implementation on capture fisheries activities in eastern parts of Indonesia, especially around North Sulawesi marine areas. Nowadays, so many IUU fishing implementations in Indonesia, like markdown on the size and boat duplications on documents of the fishing boat. Moreover, the fisheries authorities in North Sulawesi have difficulties measuring the actual tonnage of the fishing boat due to any difficulties measuring the size of the boat when on the sea. To overcome these problems, a technique to minimize these difficulties could be answered by implementing the pantograph as a tool. In this study, the result of the pantograph data measured could be continued to analyze by using the shipbuilding software of the DelftShip. Furthermore, we can be predicted the boat’s displacement, tonnage, fineness coefficients, resistance and propulsion needs.

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Correction to: Efficient tunable plasmonic mode converters infiltrated with nematic liquid crystal layers

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Optical and Quantum Electronics 2021年第8期53卷 1-1页

作者： Kabeel, Randa H. Areed, Nihal F. F. Hameed, Mohamed Farhat O. Obayya, Salah S. A. Department of Electronics and Communications Engineering Faculty of Engineering University of Mansoura Mansoura Egypt Centre for Photonics and Smart Materials Zewail City of Science and Technology Giza Egypt Nanotechnology and Nanoelectronics Engineering Program Zewail City of Science and Technology Giza Egypt Mathematics and Engineering Physics Department Faculty of Engineering University of Mansoura Mansoura Egypt

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Fermentation of rice straw raw material to bioethanol using consortium enzyme

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AIP Conference Proceedings 2023年第1期2679卷

作者： Lailatul Fithri Luddy Febriyanto One Asmarani Rahmat Eko Sanjaya Ardiana Ilham Nurrohman Mirni Lamid Abdul Munir Abd Murad Ni Nyoman Tri Puspaningsih 1Proteomic Laboratory University-CoE-Research Center for Bio-Molecule Engineering Universitas Airlangga Surabaya 60115 Indonesia 2Departement of Chemistry Faculty of Science and Technology Universitas Airlangga Surabaya 60115 Indonesia 3Doctoral Program of Mathematics and Natural Sciences Faculty of Science and Technology Universitas Airlangga Surabaya 60115 Indonesia 4Animal Husbandry Faculty of Veterinery Medicine Universitas Airlangga Surabaya 60115 East Java Indonesia 5School of Biosciences and Biotechnology Faculty of Science and Technology Universiti Kebangsaan Malaysia Bangi 43600 Selangor Malaysia

Rice straw is one of the abundant lignocellulosic agricultural by-product in Indonesia. Rice straw has several characteristics that make it a potential raw material for bioenergy production such as ethanol. It contain high cellulose and hemicelluloses that can be hydrolyzed into fermentable sugars. This study aimed to hydrolyze rice straw cellulose and hemicellulose using xylanase, cellulose, and xylose isomerase enzymes. 2% H2SO4 was used in pretreatment before the rice straw hydrolyzed with consortium enzymes. Concentrations of rice straw substrate was made to 5%, 10%, 15%, and 20% (w/v) and also made 1:1, 1:2, and 1:3 volume ratio between substrate and enzymes. The results showed that the highest rate of bioethanol obtained from 10% (w/v) rice straw substrate and enzyme activity in consortium was 0.279 U/mL (xylanase), 0.329 U/mL (cellulase), and 0.024 U/mL (xylose isomerase). The hydrolyzate was fermented by Saccharomyces cerevisiae BJ1824 and produce 8.81x10−2 %(v/v) ethanol measured by Gas Chromatography (GC).

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SI-spreading-based network embedding in static and temporal networks

arXiv

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arXiv 2020年

作者： Zhan, Xiu-Xiu Li, Ziyu Masuda, Naoki Holme, Petter Wang, Huijuan Faculty of Electrical Engineering Mathematics and Computer Science Delft University of Technology Mekelweg 4 Delft2628 CD Netherlands Department of Mathematics University at Buffalo State University of New York Buffalo New YorkNY14260-2900 United States Computational and Data-Enabled Science and Engineering Program University at Buffalo State University of New York Buffalo New YorkNY14260-2900 United States Institute of Innovative Research Tokyo Institute of Technology Yokohama226-8503 Japan

Link prediction can be used to extract missing information, identify spurious interactions as well as forecast network evolution. Network embedding is a methodology to assign coordinates to nodes in a low-dimensional vector space. By embedding nodes into vectors, the link prediction problem can be converted into a similarity comparison task. Nodes with similar embedding vectors are more likely to be connected. Classic network embedding algorithms are random-walk-based. They sample trajectory paths via random walks and generate node pairs from the trajectory paths. The node pair set is further used as the input for a Skip-Gram model, a representative language model that embeds nodes (which are regarded as words) into vectors. In the present study, we propose to replace random walk processes by a spreading process, namely the susceptible-infected (SI) model, to sample paths. Specifically, we propose two SI-spreading-based algorithms, SINE and TSINE, to embed static and temporal networks, respectively. The performance of our algorithms is evaluated by the missing link prediction task in comparison with state-of-the-art static and temporal network embedding algorithms. Results show that SINE and TSINE outperform the baselines across all six empirical datasets. We further find that the performance of SINE is mostly better than TSINE, suggesting that temporal information does not necessarily improve the embedding for missing link prediction. Moreover, we study the effect of the sampling size, quantified as the total length of the trajectory paths, on the performance of the embedding algorithms. The better performance of SINE and TSINE requires a smaller sampling size in comparison with the baseline algorithms. Hence, SI-spreading-based embedding tends to be more applicable to large-scale networks. Copyright © 2020, The Authors. All rights reserved.

关键词： Network embeddings

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Prediction of the activity of carbohydrate moiety of bromelain as immunomodulator using an in silico approach

引用

AIP Conference Proceedings 2023年第1期2480卷

作者： Trina Ekawati Tallei Fatimawali Afriza Yelnetty Nurdjannah Jane Niode Diah Kusumawaty Billy Johnson Kepel Souvia Rahimah Yunus Effendi Rinaldi Idroes Sefren Geiner Tumilaar Shafi Mahmud Talha Bin Emran Department of Biology Faculty of Mathematics and Natural Sciences Sam Ratulangi University Manado 95115 North Sulawesi Indonesia Pharmacy Study Program Faculty of Mathematics and Natural Sciences Sam Ratulangi University Manado 95115 North Sulawesi Indonesia Animal Products Technology Study Program Faculty of Animal Husbandry Sam Ratulangi University Manado 95115 North Sulawesi Indonesia Department of Dermatology and Venereology Faculty of Medicine University of Sam Ratulangi RD Kandou Hospital Manado 95163 North Sulawesi Indonesia Department of Biology Education Faculty of Mathematics and Science Education Universitas Pendidikan Indonesia Bandung 40154 Jawa Barat Indonesia Department of Chemistry Faculty of Medicine Sam Ratulangi University Manado 95115 North Sulawesi Indonesia Food Technology Study Program Department of Food Industrial Technology Faculty of Agroindustrial Technology Universitas Padjadjaran Jatinangor 45363 West Java Indonesia Biology Study Program Faculty of Science and Technology Universitas Al Azhar Jakarta 12110 Indonesia Department of Pharmacy Faculty of Mathematics and Natural Sciences Universitas Syiah Kuala Kopelma Darussalam Banda Aceh 23111 Indonesia Microbiology Laboratory Department of Genetic Engineering and Biotechnology University of Rajshahi Rajshahi 6205 Bangladesh Department of Pharmacy BGC Trust University Bangladesh Chittagong 4381 Bangladesh

Bromelain is a glycoprotein that contains a single carbohydrate moiety group and displays proteolytic activity. Bromelain has long been known to act as an immunomodulator; however, the immunomodulatory activity of its carbohydrate moiety has been very rarely studied and is not well understood. This study aimed to predict the immunomodulatory activity of the carbohydrate moiety of bromelain (CMB) by evaluating it using the PASS server, and the binding affinities between CMB and various pro-inflammatory cytokines were analyzed using a molecular docking approach. This research was conducted by docking the CMB ligand to the following receptor proteins: interleukin-6 (IL-6), IκBβ/nuclear factor (NF)-κB p65 homodimer complex (IκBα/NF-κB p65), tumor necrosis factor-alpha (TNF-α), and IL-1β. The biological potential of CMB was predicted using the online PASS server. The results of the computational analysis indicated that the highest binding energy was identified between CMB and IκBβ/NF-κB p65 (−10.3 kcal/mol), followed by TNF-α (−9.7 kcal/mol), and IL-6 and IL-1β, with values of −8.2 kcal/mol for both. The CMB activity predicted by the Way2Drug PASS server indicated that this molecule is likely to display significant immunostimulant activity. These findings suggested that CMB can be considered a potential lead molecule for further drug development to identify agent that can prevent or cure inflammation and restore balance to the immune system. However, the predictions determined in this study remain to be validated in future in vitro and in vivo studies.

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A PARALLEL VARIATIONAL MESH QUALITY IMPROVEMENT METHOD FOR TETRAHEDRAL MESHES 28

A PARALLEL VARIATIONAL MESH QUALITY IMPROVEMENT METHOD FOR T...

引用

28th International Meshing Roundtable, IMR 2019

作者： Shontz, Suzanne M. Varilla, M.A.L. Huang, Weizhang Department of Electrical Engineering and Computer Science Bioengineering Program Information and Telecommunication Technology Center University of Kansas LawrenceKS United States Husky Injection Molding Systems Ltd. Luxembourg Luxembourg Department of Mathematics University of Kansas LawrenceKS United States

ISBN: (纸本)9781733489003

There are numerous large-scale applications requiring mesh adaptivity, e.g., computational uid dynamics and weather prediction. Parallel processing is needed for simulations involving large-scale adaptive meshes. In this paper, we propose a parallel variational mesh quality improvement algorithm for use with distributed memory machines. Our method parallelizes the serial variational mesh quality improvement method by Huang and Kamenski. Their approach is based on the use of the Moving Mesh PDE method to adapt the mesh based on the minimization of an energy functional for mesh equidistribution and alignment. This leads to a system of ordinary differential equations (ODEs) to be solved which determine where to move the interior mesh nodes. An efficient solution is obtained by solving the ODEs on subregions of the mesh with overlapped communication and computation. Strong and weak scaling experiments on up to 128 cores for meshes with up to 160M elements demonstrate excellent results. © 2019 Proceedings of the 28th International Meshing Roundtable, IMR 2019. All rights reserved.

关键词： Ordinary differential equations

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Biochemical mechanisms and molecular interactions of vitamins in cancer therapy

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Cancer Pathogenesis and Therapy 2025年第1期3卷 3-15页

作者： Abdullahi T.Aborode Isreal A.Onifade Mercy M.Olorunshola Gladys O.Adenikinju Ibude J.Aruorivwooghene Adeboboye C.Femi Osasere Jude-Kelly Osayawe Abraham Osinuga Ebenezer A.Omojowolo Adekunle F.Adeoye Segun Olapade Ibroadhfrimed O.Acdoelaku Ogundepo D.Moyinoluwa Oluwatosin M.Adeyemo Godfred Y.Scott Ruth A.Ogbonna Emmanuel A.Fajemisin Omama Ehtasham Soyemi Toluwalashe Adetolase A.Bakre Ridwan O.Adesola Seto C.Ogunleye Nnenna R.Anyanwu Terungwa H.lorkula Department of Chemistry Mississippi State UniversityStarkvilleMS 39759USA Department of Biology University at AlbanyAlbanyNY 12222USA Department of Biological Sciences State University of New York at BinghantonBinghamtonNY 13902USA Department of Biological and Environmental Sciences University of Rhode IslandKingstonRI 02881USA Department of Biological Sciences University of Kansas Medical CenterKansasKS 66103USA Department of Microbiology Federal University of TechnologyAkure 340110Nigeria Department of Chemistry and Biochemistry Brigham Young UniversityProvoUT 84602USA 8 Department of Chemical and Biomolecular Engineering University of Nbraska-LincolnLincolnNE 68588USA9 Department of Chemistry University of AlbanyState University of New YorkAlbanyNY 12222USA Department of Mathematics and Statistics Georgia State UniversityAtlantaGA 30302USA Department of Chemistry University of LouisvilleLouisvilleKY 40208USA Department of Biochemistry Federal University of TechnologyAkure 340110Nigeria Deparment of Medical Diagnostics Kwame Nkrumah University of Science and TechnologyKumasi AK385Ghana Department of Research and Development Nasarawa State AIDS and STI Control ProgramNasarawaLafia 96210Nigeria Department of Integrative Biomedical Science University of Cape TownCape'Town 7701South Africa Department of Medicine and Surgery Karachi Medical and Dental CollegeKarachi 74700Pakistan Department of Medicine Lagos State University College of MedicineLagos 10010Nigeria Department of Veterinary Medicine Faculty of Veterinary MedicineUniversity of lbadanlbadan 200005Nigeria Faculty of Pharmaceutical Sciences University of JosPlateauJos 930003Nigeria

Recently,the potential role of vitamins in cancer therapy has attracted considerable research ***,the reported findings are inconsistent,with limited information on the biochemical and molecular interactions of different vitamins in various cancer ***,the presence of vitamin receptors in tumor cells suggests that vitamins play a significant role in the molecular and biochemical interactions in ***,studies on the efficacy of vitamin supplementation and dosage levels on tumor progression and mortality risk have yielded inconsistent ***,molecular and biochemical investigations have reported the function of vitamins in the proliferation,growth,and invasiveness of tumor cells,as well as in cell cycle arrest and inflammatory ***,different vitamins may regulate the cancer microenvironment by activating various molecular *** significantly affect immunological function,antioxidant defense,inflammation,and epigenetic control,and can improve treatment outcomes by affecting cell behavior and combating stress and DNA ***,further research is necessary to confirm the efficacy of vitamins,establish ideal dosages,and develop effective cancer prevention and treatment *** supplementation plans guided by medical knowledge are crucial to achieving optimal results in clinical and preclinical *** this review,we critically evaluated the effects of different vitamins on the risk and development of ***,we examined the potential of vitamin supplements to enhance the efficacy of drug therapy and counteract resistance mechanisms that often arise during cancer treatment.

关键词： Vitamins Cancer Biochemical Molecular interactions Therapy

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