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arXiv 2023年

作者： Zhang, Shiyun Jin, Weiwei Wang, Dong Xu, Ding Zhang, Jerry Shattuck, Mark D. O’Hern, Corey S. Department of Physics University of Science and Technology of China Anhui Hefei230026 China Department of Mechanical Engineering and Materials Science Yale University New HavenCT06520 United States Benjamin Levich Institute and Physics Department The City College of New York New YorkNY10031 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 and Bioinformatics Yale University New HavenCT06520 United States

Strain-controlled isotropic compression gives rise to jammed packings of repulsive, frictionless disks with either positive or negative global shear moduli. We carry out computational studies to understand the contributions of the negative shear moduli to the mechanical response of jammed disk packings. We first decompose the ensemble-averaged, global shear modulus as hGi = (1 − F−)hG+i + F−hG−i, where F− is the fraction of jammed packings with negative shear moduli and hG+i and hG−i are the average values from packings with positive and negative moduli, respectively. We show that hG+i and h|G−|i obey different power-law scaling relations above and below pN2 ∼ 1. For pN2 > 1, both hG+iN and h|G−|iN ∼ (pN2)β, where β ∼ 0.5 for repulsive linear spring interactions. Despite this, hGiN ∼ (pN2)β0 with β0 & 0.5 due to the contributions from packings with negative shear moduli. We show further that the probability distribution of global shear moduli P(G) collapses at fixed pN2 and different values of p and N. We calculate analytically that P(G) is a Gamma distribution in the pN2 1 limit. As pN2 increases, the skewness of P(G) decreases and P(G) becomes a skew-normal distribution with negative skewness in the pN2 1 limit. We also partition jammed disk packings into subsystems using Delanunay triangulation of the disk centers to calculate local shear moduli. We show that the local shear moduli defined from groups of adjacent triangles can be negative even when G > 0. The spatial correlation function of local shear moduli C(~r) displays weak correlations for pn2sub −2, where nsub is the number of particles within each subsystem. However, C(~r) begins to develop long-ranged spatial correlations with four-fold angular symmetry for pn2sub & 10−2 © 2023, CC BY-NC-ND.

关键词： Elastic moduli

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Antibodies from dengue patients with prior exposure to Japanese encephalitis virus are broadly neutralizing against Zika virus(vol 7, 15, 2024)

COMMUNICATIONS BIOLOGY

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COMMUNICATIONS BIOLOGY 2024年第1期7卷 15页

作者： Salem, Gielenny M. Galula, Jedhan Ucat Wu, Shang-Rung Liu, Jyung-Hurng Chen, Yen-Hsu Wang, Wen-Hung Wang, Sheng-Fan Song, Cheng-Sheng Chen, Fan-Chi Abarientos, Adrian B. Chen, Guan-Wen Wang, Cheng-, I Chao, Day-Yu Graduate Institute of Microbiology and Public Health College of Veterinary Medicine National Chung Hsing University Taichung City 402 Taiwan. Institute of Oral Medicine School of Dentistry College of Medicine National Cheng Kung University Tainan City 701 Taiwan. Graduate Institute of Genomics and Bioinformatics College of Life Sciences National Chung Hsing University Taichung City 40227 Taiwan. School of Medicine College of Medicine National Sun Yat-Sen University Kaohsiung City 80424 Taiwan. Center for Tropical Medicine and Infectious Disease Research Kaohsiung Medical University Kaohsiung City 80708 Taiwan. Doctoral Program in Microbial Genomics National Chung Hsing University and Academia Sinica Taichung City 402 Taiwan. Singapore Immunology Network Agency for Science Technology and Research (A*STAR) 8A Biomedical Grove Immunos Singapore 138648 Singapore. Graduate Institute of Microbiology and Public Health College of Veterinary Medicine National Chung Hsing University Taichung City 402 Taiwan. dychao@nchu.edu.tw.

Exposure to multiple mosquito-borne flaviviruses within a lifetime is not uncommon; however, how sequential exposures to different flaviviruses shape the cross-reactive humoral response against an antigen from a different serocomplex has yet to be explored. Here, we report that dengue-infected individuals initially primed with the Japanese encephalitis virus (JEV) showed broad, highly neutralizing potencies against Zika virus (ZIKV). We also identified a rare class of ZIKV-cross-reactive human monoclonal antibodies with increased somatic hypermutation and broad neutralization against multiple flaviviruses. One huMAb, K8b, binds quaternary epitopes with heavy and light chains separately interacting with overlapping envelope protein dimer units spanning domains I, II, and III through cryo-electron microscopy and structure-based mutagenesis. JEV virus-like particle immunization in mice further confirmed that such cross-reactive antibodies, mainly IgG3 isotype, can be induced and proliferate through heterologous dengue virus (DENV) serotype 2 virus-like particle stimulation. Our findings highlight the role of prior immunity in JEV and DENV in shaping the breadth of humoral response and provide insights for future vaccination strategies in flavivirus-endemic countries.

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Scalable Crystal Structure Relaxation Using an Iteration-Free Deep Generative Model with Uncertainty Quantification

arXiv

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arXiv 2024年

作者： Yang, Ziduo Zhao, Yi-Ming Wang, Xian Liu, Xiaoqing Zhang, Xiuying Li, Yifan Lv, Qiujie Chen, Calvin Yu-Chian Shen, Lei Department of Mechanical Engineering National University of Singapore Singapore117575 Singapore Artificial Intelligence Medical Research Center School of Intelligent Systems Engineering Shenzhen Campus of Sun Yat-sen University Shenzhen518107 China Department of Physics National University of Singapore Singapore117551 Singapore -Preferred Program School of Electronic and Computer Engineering Peking University Shenzhen Graduate School Shenzhen518055 China State Key Laboratory of Chemical Oncogenomics School of Chemical Biology and Biotechnology Peking University Shenzhen Graduate School Shenzhen518055 China Department of Medical Research China Medical University Hospital Taichung40447 Taiwan Department of Bioinformatics and Medical Engineering Asia University Taichung41354 Taiwan Guangdong L-Med Biotechnology Co. Ltd. Guangdong Meizhou514699 China Research Institute Chongqing401123 China

In computational molecular and materials science, determining equilibrium structures is the crucial first step for accurate subsequent property calculations. However, the recent discovery of millions of new crystals and complex twisted structures has challenged traditional computational methods, both ab initio and machine-learning-based, due to their computationally intensive iterative processes. To address these scalability issues, here we introduce DeepRelax, a deep generative model capable of performing geometric crystal structure relaxation rapidly and without iterations. DeepRelax learns the equilibrium structural distribution, enabling it to predict relaxed structures directly from their unrelaxed ones. The ability to perform structural relaxation at the millisecond level per structure, combined with the scalability of parallel processing, makes DeepRelax particularly useful for large-scale virtual screening. We demonstrate DeepRelax's reliability and robustness by applying it to five diverse databases, including oxides, Materials Project, two-dimensional materials, van der Waals crystals, and crystals with point defects. DeepRelax consistently shows high accuracy and efficiency, validated by density functional theory calculations. Finally, we enhance its trustworthiness by integrating uncertainty quantification. This work significantly accelerates computational workflows, offering a robust and trustworthy machine-learning method for material discovery and advancing the application of AI for science. Code for DeepRelax is available at https://***/Shen-Group/DeepRelax. Copyright © 2024, The Authors. All rights reserved.

关键词： Point defects

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Targeting the HTLV-I-Regulated BATF3/IRF4 Transcriptional Network in Adult T-Cell Leukemia/Lymphoma

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BLOOD 2017年 130卷 731-731页

作者： Nakagawa, Masao Shaffer, Arthur L. Ceribelli, Michele Zhang, Meili Wright, George Huang, Da Wei Xiao, Wenming Powell, John Petrus, Michael N. Yang, Yibin Phelan, James D. Kohlhammer, Holger Yoo, Hee Min Yang, Yandan Xu, Weihong Yu, Xin Zhao, Hong Bryant, Bonita R. Maeda, Michiyuki Waldmann, Thomas A. Staudt, Lou Department of Hematology Hokkaido University Graduate School of Medicine Sapporo Japan NIH NCI CCR Bethesda MD National Cancer Institute National Institutes of Health Bethesda NCATS NIH ROCKVILLE National Cancer Institute National Institutes of Health Center for Cancer Research Bethesda MD NCI NIH Bethesda Division of Bioinformatics and Biostatistics NCTR/FDA Jefferson Center for Information Technology National Institutes of Health Bethesda Blood Cell Development and Function Program Fox Chase Cancer Center Philadelphi Institute for Virus Research Kyoto University Kyoto Japan National Cancer Institute National Institutes of Health Bethesda MD

731

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DNAku Consumers Profile: One of The First Direct to Customer Genetics Testing in Indonesia

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IOP Conference Series: Earth and Environmental Science 2021年第1期794卷

作者： Deby Erina Parung Kians Azizatikarna Dian Amirulloh Erlin Listiyaningsih Bharuno Mahesworo Arif Budiarto Simon Bens Pardamean Genetics Indonesia Jakarta Indonesia 12940 Bioinformatics & Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program - Master of Computer Science Program Bina Nusantara University Jakarta Indonesia 11480

DNAku test is one of the first direct to customer genetics testing in Indonesia. DNAku test came with a different approach as it gave their customer reports of their genetic predisposition to corresponding traits. Four months after launch, we create consumer report of this genetics testing based on DNAku questionnaire results. We applied three statistical methods, including descriptive statistics, multivariate normality test, and t-test to the demographic data of the DNAku customers. The result shows population clusters which may represent population groups that are interested in genetics testing. The questionnaire also has questions about the customer's lifestyle. The results of these questions were processed to find the lifestyle of DNAku customers.

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Real-time Weed Identification Using Machine Learning and Image Processing in Oil Palm Plantations

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IOP Conference Series: Earth and Environmental Science 2022年第1期998卷

作者： Erick Firmansyah Teddy Suparyanto Alam Ahmad Hidayat Bens Pardamean Agricultural Engineering Department Institute of Agricultural STIPER Yogyakarta 55282 Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program – Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480

The effectiveness and efficiency of the operation of oil palm plantations are considered to be the most crucial factor to develop the productivity and profitability of the palm oil business. One of the major obstacles for the plants to optimally produce crops based on their capacity is caused by the presence of noxious weeds in the plantation area. However, weed control via chemical processes may potentially harm the surrounding environment if it is not properly managed. Therefore, an automatic system to assist the farmers to identify and control the weeds is required to minimize harmful impacts on the environment. Machine Learning (ML) and Artificial Intelligence (AI)-based systems provide powerful tools to perform such tasks. In this work, we aim for an ML-based system design to perform an automatic weed recognition task. The methodology can provide an effort for environmental sustainability in oil palm plantations. The weed identification involves the description, the local names, and tolerance class of the weeds as well as suggestions to control them. The flow of this work consists of weed and herbicide data acquisition, data labeling, model configurations, and data training. Further, the proposed system can be adopted as an android-based application in mobile devices that can deploy the trained model to predict weed category in both real-time and non-real-time tasks.

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Smart IoT CPO Storage Tank

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IOP Conference Series: Earth and Environmental Science 2022年第1期998卷

作者： Rengga Arnalis Renjani Hermantoro Prima Okta Adi Nugraha Kartika Purwandari Teddy Suparyanto Bens Pardamean Department of Agricultural Engineering Institute of Agriculture STIPER Yogyakarta Indonesia 55281 Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia 11480

Indonesia's crude palm oil (CPO) production from year to year continues to increase, at the end of 2020 it reached 17.35 million tons, up 3.6% from the previous year. Increasing production will result in more CPO stock and require good storage. The storage process that occurs is to maintain the temperature of the CPO so that the quality is not damaged. This temperature regulation is still done manually and raises the risk of work accidents. The purpose of this research is to create a temperature control system and automatic volume measurement that can be monitored from a smartphone. The manufacture of a control system used ESP8266 NodeMCu microcontroller, temperature sensor, proximity sensor, and 1000-Watt heater. programming used the Arduino IDE and C++. The result of this study was an IoT CPO Storage Tank design equipped with sensors and microcontrollers. The temperature was measured with the DS18B20 sensor had a data accuracy of 99.19% while the volume measured with the HC-SR04 sensor had an accuracy of 99.78%. Data obtained from the sensor could be seen through the Thingspeak application from a computer or smartphone.

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The by-product of oil palm dosage application on Turnera subulata growth supports water supply

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AIP Conference Proceedings 2024年第1期3026卷

作者： Pauliz Budi Hastuti Gilang Tri Anggara Wiwin Dyah Ully Parwati Teddy Suparyanto Digdo Sudigyo Bens Pardamean Faculty of Agriculture STIPER Institute of Agriculture Yogyakarta Indonesia 55281 Faculty of Agricultural Technology STIPER Institute of Agriculture Yogyakarta Indonesia 55281 Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program - Master of Computer Science Program Bina Nusantara University Jakarta Indonesia 11480

Plant growth with complex organic matter content can be enhanced by using oil palm by-products. These organic materials can maintain the water supply in the plant body. Therefore, in oil palm plantations with significant groundwater consumption, organic matter’s the ability to sustain water availability. Caterpillars that devour palm leaves are among the numerous pests that threaten oil palm plantations. Predators of leaf-eating caterpillars use the holly rose flower (Turnera subulata) in oil palm farms as a habitat. Therefore, the effect of the type and dose treatment of oil palm by-products on the growth of Turnera subulata was observed to support sustainable water management in oil palm plantations. The research was carried out using a factorial design arranged in a Completely Randomized Design (CRD) consisting of two components: the type of palm oil mill by-product (boiler ash, empty bunches, and solid) and the dose of a by-product (% volume) consisting of four dosages (0, 25, 33, and 50% volume). The research data were analyzed using variance at the 5% test level. A DMRT test at the 5% test level was conducted on the treatment that had a significant effect. The growth of Turnera subulata was most positively impacted by a solid application dose of 50% volume. Turnera subulata plants responded the least favorably to the application of empty bunches in any dose treatment.

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467P Examining the experience and preferences of patients with advanced cancer at a Tertiary Care Center

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Annals of Oncology 2024年 35卷 S1576-S1576页

作者： C.W. Kwak K. Herring J. Troy S. Wolf C. Malhotra T. Leblanc Duke-NUS Medical School Duke-NUS Graduate Medical School Singapore Duke Cancer Patient Experience Research Program (CPEP) Duke Cancer Institute Durham NC USA Department of Biostatistics & Bioinformatics Duke University School of Medicine Durham NC USA Lien Centre for Palliative Care and Program in Health Services and Systems Research Duke-NUS Graduate Medical School Singapore Duke Cancer Institute Duke University School of Medicine Durham NC USA

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Two-Step Activated Carbon Cloth Enhances Microbial Interactions and Methane Production During Anaerobic Digestion of Municipal Sludge

SSRN

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SSRN 2022年

作者： Kumar, Vikas Kieft, Brandon Devi, Parmila Hallam, Steven J. Eskicioglu, Cigdem UBC Bioreactor Technology Group School of Engineering University of British Columbia Okanagan Campus KelownaBCV1V 1V7 Canada Department of Microbiology and Immunology University of British Columbia VancouverBCV6T 1Z4 Canada Department of Microbiology and Immunology University of British Columbia VancouverBC Canada Graduate Program in Bioinformatics University of British Columbia VancouverBCV6T 1Z4 Canada Genome Science and Technology Program University of British Columbia 2329 West Mall VancouverBCV6T 1Z4 Canada Life Sciences Institute University of British Columbia VancouverBCV6T 1Z3 Canada ECOSCOPE Training Program University of British Columbia VancouverBCV6T 1Z3 Canada

This study investigated the effects of two-step activated carbon cloth (CC) on the syntrophic microbial association during anaerobic digestion (AD) of municipal sludge. A simple two-step activation, acid pretreatment (H2SO4/HNO3) followed by air calcination (550°C), was used to convert commercial untreated CC (U-CC) into high performance activated CC (A-CC). Biochemical methane potential (BMP) assays conducted at different CC dosages indicated that A-CC, at a dose of 0.80 g A-CC {1.48 g A-CC/g-VS (volatile solids)substrate}, enhanced methane yield from by 3.7 times and reduced the lag phase up to 15.6-fold, compared to non-CC control within 3 days. Characterization of CC surfaces and kinetic modeling indicated a 435-times increased A-CC pore size area (Barrett, Joyner, and Halenda, BJH) with the potential to promote electron transfer and accelerate kinetic rates of methane production. Consistent with these results, microbial community structure analysis of CC surfaces indicated rapid adherence of methanogenic archaea and bacterial syntrophs to A-CC within 3 days. Multi-variate statistical analyses indicated that these populations were highly enriched on 0.80 g A-CC dosage compared to controls. Based on these results it can be concluded that A-CC provides a robust selective environment for syntrophic energy metabolism driving enhanced methane production from municipal sludge. © 2022, The Authors. All rights reserved.

关键词： Anaerobic digestion

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