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

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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Mapping Emergency Medicine data to the Observational Medical Outcomes Partnership Common data Model: A Gap Analysis of the American College of Emergency Physicians Clinical Emergency data Registry

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JACEP Open 2025年第1期6卷 100016-100016页

作者： Cohen, Inessa Diao, Zihan Goyal, Pawan Gupta, Aarti Hawk, Kathryn Malcom, Bill Malicki, Caitlin Sharma, Dhruv Sweeney, Brian Weiner, Scott G. Venkatesh, Arjun Taylor, R. Andrew Department of Emergency Medicine Yale School of Medicine New Haven CT United States Section for Biomedical Informatics and Data Science Yale University School of Medicine New Haven CT United States Program of Computational Biology and Bioinformatics Yale University New Haven CT United States American College of Emergency Physicians Washington DC United States Department of Emergency Medicine Brigham and Women's Hospital Boston MA United States Center for Outcomes Research and Evaluation (CORE) Section of Cardiovascular Medicine Yale School of Medicine New Haven CT United States

Objectives: This study aims to conduct a gap analysis to determine the feasibility of mapping electronic health record data from the Clinical Emergency data Registry (CEDR) to the Observational Medical Outcomes Partnership Common data Model (OMOP-CDM). Methods: We employed a structured approach using a custom-built comparison matrix. This matrix facilitated the alignment of CEDR data fields with the corresponding elements in the OMOP-CDM schema. Each field was evaluated for compatibility, with categorization into 3 distinct types: direct matches, fields requiring transformation, and fields with no OMOP-CDM equivalent. The mapping process was informed by consultations with the Observational Health data sciences and Informatics community forums and was guided by existing documentation and best practices in data harmonization. We performed descriptive analyses, quantifying the extent of direct matches and identifying the specific transformations needed for each CEDR-CDM field to ensure compliance with the OMOP-CDM model. Results: Our analysis indicates a high degree of compatibility between CEDR and OMOP, with over 90% (244/269) of CEDR fields being successfully mapped. Specifically, 173 fields had direct matches, whereas 71 required transformations. Challenges identified include addressing fields unique to CEDR with no OMOP-CDM equivalent and managing the transformations required for proper alignment. Conclusion: The OMOP-CDM presents a promising framework for standardizing emergency medicine data, thereby enhancing future query automation, analytics, and cross-institutional collaboration. Despite the potential challenges in capturing unique CEDR fields and addressing necessary transformations, most emergency department data can be standardized within the OMOP-CDM, fostering broader insights and applications in research and public health. © 2024 The Author(s)

关键词： databases electronic health records emergency service informatics opioid/adverse effects quality of health care registries

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Exploring the regulatory function of the N-terminal domain of SARS-CoV-2 spike protein through molecular dynamics simulation

arXiv

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arXiv 2021年

作者： Li, Yao Wang, Tong Zhang, Juanrong Shao, Bin Gong, Haipeng Wang, Yusong Liu, Siyuan Liu, Tie-Yan MOE Key Laboratory of Bioinformatics School of Life Sciences Tsinghua University Beijing100084 China Beijing Advanced Innovation Center for Structural Biology Tsinghua University Beijing100084 China Microsoft Research Asia Beijing China School of Data and Computer Science Sun Yat-sen University Guangzhou China Guangdong Key Laboratory of Big Data Analysis and Processing Guangzhou China

SARS-CoV-2 is what has caused the COVID-19 pandemic. Early viral infection is mediated by the SARS-CoV-2 homo-trimeric Spike (S) protein with its receptor binding domains (RBDs) in the receptor-accessible state. We performed molecular dynamics simulation on the S protein with a focus on the function of its N-terminal domains (NTDs). Our study reveals that the NTD acts as a "wedge" and plays a crucial regulatory role in the conformational changes of the S protein. The complete RBD structural transition is allowed only when the neighboring NTD that typically prohibits the RBD’s movements as a wedge detaches and swings away. Based on this NTD "wedge" model, we propose that the NTD-RBD interface should be a potential drug target. Copyright © 2021, The Authors. All rights reserved.

关键词： SARS

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Application of Predictive Analytics at Financial Institutions: A Systematic Literature Review 8

Application of Predictive Analytics at Financial Institution...

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8th IIAI International Congress on Advanced Applied Informatics, IIAI-AAI 2019

作者： Indriasari, Elisa Soeparno, Haryono Gaol, Ford Lumban Matsuo, Tokuro Doctor of Computer Science Bina Nusantara University Jakarta Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia Advanced Institute of Industrial Technology Japan

ISBN: (纸本)9781728126272

The issues that relate with the automatics and intelligent tracing of the transaction and banking customer become the main issues nowadays. Whereas most of transaction that already moved to digital and online transaction that needed more intelligent features on the Predictive Analyst. The rise of predictive analytics (PA) is one of the biggest disruptions in financial services. In the last years, PA methods grew sharply to give the baseline of data driven decision-making process for forecasting future business situation. PA uses various algorithms to discover different patterns in the big data environment that might create more value for businesses including in financial institutions. The potential implementation of data science in financial industry is still to be explored. In this paper, we summarize work done on PA at financial industry. We also explore the potential application of PA and investigating how data science and big data is going to be used in financial institutions in the future. © 2019 IEEE.

关键词： Predictive analytics

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XMAP: Cross-population fine-mapping by leveraging genetic diversity and accounting for confounding bias

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Nature Communications 2023年第1期14卷 6870页

作者： Cai, Mingxuan Wang, Zhiwei Xiao, Jiashun Hu, Xianghong Chen, Gang Yang, Can Department of Biostatistics City University of Hong Kong Hong Kong Guangzhou HKUST Fok Ying Tung Research Institute Guangzhou 511458 China Department of Mathematics The Hong Kong University of Science and Technology Hong Kong Shenzhen Research Institute of Big Data Shenzhen 518172 China Hunan Provincial Key Lab on Bioinformatics School of Computer Science and Engineering Central South University Changsha 410083 China WeGene Shenzhen Zaozhidao Technology Co. Ltd Shenzhen 518040 China Graduate Affairs Faculty of Medicine Chulalongkorn University Bangkok 10330 Thailand

Fine-mapping prioritizes risk variants identified by genome-wide association studies (GWASs), serving as a critical step to uncover biological mechanisms underlying complex traits. However, several major challenges still remain for existing fine-mapping methods. First, the strong linkage disequilibrium among variants can limit the statistical power and resolution of fine-mapping. Second, it is computationally expensive to simultaneously search for multiple causal variants. Third, the confounding bias hidden in GWAS summary statistics can produce spurious signals. To address these challenges, we develop a statistical method for cross-population fine-mapping (XMAP) by leveraging genetic diversity and accounting for confounding bias. By using cross-population GWAS summary statistics from global biobanks and genomic consortia, we show that XMAP can achieve greater statistical power, better control of false positive rate, and substantially higher computational efficiency for identifying multiple causal signals, compared to existing methods. Importantly, we show that the output of XMAP can be integrated with single-cell datasets, which greatly improves the interpretation of putative causal variants in their cellular context at single-cell resolution. © 2023, The Author(s).

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Prediction of Diblock Copolymer Morphology via Machine Learning

arXiv

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arXiv 2023年

作者： Park, Hyun Yu, Boyuan Park, Juhae Sun, Ge Tajkhorshid, Emad de Pablo, Juan J. Schneider, Ludwig Theoretical and Computational Biophysics Group NIH Resource Center for Macromolecular Modeling and Bioinformatics Beckman Institute for Advanced Science and Technology University of Illinois at Urbana-Champaign UrbanaIL61801 United States Center for Biophysics and Quantitative Biology University of Illinois at Urbana-Champaign UrbanaIL61801 United States Data Science and Learning Division Argonne National Laboratory LemontIL60439 United States Pritzker School of Molecular Engineering University of Chicago 5640 Ellis Ave ChicagoIL60637 United States Theoretical and Computational Biophysics Group Beckman Institute for Advanced Science and Technology University of Illinois at Urbana-Champaign UrbanaIL61801 United States Department of Biochemistry University of Illinois at Urbana-Champaign UrbanaIL61801 United States

A machine learning approach is presented to accelerate the computation of block polymer morphology evolution for large domains over long timescales. The strategy exploits the separation of characteristic times between coarse-grained particle evolution on the monomer scale and slow morphological evolution over mesoscopic scales. In contrast to empirical continuum models, the proposed approach learns stochastically driven defect annihilation processes directly from particle-based simulations. A UNet architecture that respects different boundary conditions is adopted, thereby allowing periodic and fixed substrate boundary conditions of arbitrary shape. Physical concepts are also introduced via the loss function and symmetries are incorporated via data augmentation. The model is validated using three different use cases. Explainable artificial intelligence methods are applied to visualize the morphology evolution over time. This approach enables the generation of large system sizes and long trajectories to investigate defect densities and their evolution under different types of confinement. As an application, we demonstrate the importance of accessing late-stage morphologies for understanding particle diffusion inside a single block. This work has implications for directed self-assembly and materials design in micro-electronics, battery materials, and membranes. Copyright © 2023, The Authors. All rights reserved.

关键词： Block copolymers

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Financial transaction database design for jamu small-medium enterprises

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AIP Conference Proceedings 2023年第1期2594卷

作者： R. Rahutomo A. Permatasari Y. Lie B. Pardamean Information Systems Department School of Information Systems Bina Nusantara University Jakarta Indonesia 11480 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

As jamu small-medium enterprises (SMEs) concentrate on establishing online sales and computerized systems, Point of Sales (PoS) becomes a strategic solution to maintain financial ...

As jamu small-medium enterprises (SMEs) concentrate on establishing online sales and computerized systems, Point of Sales (PoS) becomes a strategic solution to maintain financial stability with its capabilities in recording electronic transactions accurately. As the initial step in technology empowerment for jamu SMEs, the research proposes a concept in facilitating jamu SMEs to adapt in online business. A combination of Connolly and Begg's database design principles and McCarthy's Marketing Mix 4P generates a conceptual design of PoS database targeted specifically for jamu SMEs. The database design manages online purchasing transactions for jamu products by involving not only jamu SMEs and consumers but also a system administrator who manages data verification and extraction.

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#4451 MONOCYTE MIGRATION AND ACTIVATION IN ANCA-ASSOCIATED GLOMERULONEPHRITIS

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Nephrology Dialysis Transplantation 2023年第SUPPLEMENT_1期38卷

作者： Vegting, Yosta Hanford, Katie Jongejan, Aldo Moerland, Perry Gajadin, Gayle van der Bom-Baylon, Nelly Dekker, Tamara Vogt, Liffert Bemelman, Frederike Kroon, Jeffrey Hilhorst, Marc Amsterdam UMC University of Amsterdam Nephrology Amsterdam Netherlands Amsterdam UMC University of Amsterdam Experimental Vascular Medicine Amsterdam Netherlands Amsterdam UMC University of Amsterdam Epidemiology & Data Science (EDS) Bioinformatics Laboratory Amsterdam Netherlands

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A novel interpretable machine learning system to generate clinical risk scores: An application for predicting early mortality or unplanned readmission in a retrospective cohort study

arXiv

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arXiv 2022年

作者： Ning, Yilin Li, Siqi Ong, Marcus Eng Hock Xie, Feng Chakraborty, Bibhas Ting, Daniel Shu Wei Liu, Nan Centre for Quantitative Medicine Duke-NUS Medical School Singapore Singapore Programme in Health Services and Systems Research Duke-NUS Medical School Singapore Singapore Health Services Research Centre Singapore Health Services Singapore Singapore Department of Emergency Medicine Singapore General Hospital Singapore Singapore Department of Statistics and Data Science National University of Singapore Singapore Singapore Department of Biostatistics and Bioinformatics Duke University DurhamNC United States Singapore Eye Research Institute Singapore National Eye Centre Singapore Singapore SingHealth AI Health Program Singapore Health Services Singapore Singapore Institute of Data Science National University of Singapore Singapore Singapore

Risk scores are widely used for clinical decision making and commonly generated from logistic regression models. Machine-learning-based methods may work well for identifying important predictors, but such ‘black box’ variable selection limits interpretability, and variable importance evaluated from a single model can be biased. We propose a robust and interpretable variable selection approach using the recently developed Shapley variable importance cloud (ShapleyVIC) that accounts for variability across models. Our approach evaluates and visualizes overall variable contributions for in-depth inference and transparent variable selection, and filters out non-significant contributors to simplify model building steps. We derive an ensemble variable ranking from variable contributions, which is easily integrated with an automated and modularized risk score generator, AutoScore, for convenient implementation. In a study of early death or unplanned readmission, ShapleyVIC selected 6 of 41 candidate variables to create a well-performing model, which had similar performance to a 16-variable model from machine-learning-based ranking. © 2022, CC BY.

关键词： Machine learning

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SARS-CoV-2-identical protein regions found in mammalian coronaviruses have immunogenic potential and can imply cross-protection

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ImmunoInformatics 2024年 14卷

作者： Luciano Rodrigo Lopes Bio-Data Science and Bioinformatics Division Health Informatics Department Universidade Federal de São Paulo–UNIFESP Rua Botucatu 862 Prédio Leal Prado térreo Vila Clementino CEP 04023-062 SP São Paulo Brazil

Coronaviruses are known to infect a wide range of mammals. In humans, coronaviruses have been responsible for causing the common cold. The immune response against common cold coronaviruses appears to elicit a cross-protective response to SARS-CoV-2. This study identified protein regions in the mammalian coronaviruses' proteome that are identical to those of SARS-CoV-2. Using bioinformatics analysis, the study predicted the involvement of SARS-CoV-2-identical protein regions, identified in mammalian coronaviruses, in antigen-presenting processes and their ability to elicit immune responses. The SARS-CoV-2-identical protein regions were predominantly found in the proteomes of betacoronaviruses, with less prevalence in alphacoronaviruses. Alphacoronaviruses, such as FCoV in domestic felines and MCoV in minks, are known to infect species highly susceptible to SARS-CoV-2. In contrast, betacoronaviruses infect mammals with lower susceptibility to SARS-CoV-2, including dogs, mice, and farmed animals. Furthermore, betacoronaviruses exhibited a higher number of peptides with an increased potential for efficient presentation during the antigen-presenting process, indicating their greater immunogenicity. Conversely, the SW1 gammacoronavirus showed a lower count of SARS-CoV-2 protein regions and a reduced potential for efficient antigen presentation. The results suggested that the elevated number of SARS-CoV-2 identical stretches found in betacoronaviruses may provide potential cross-protection between SARS-CoV-2 and mammalian betacoronaviruses. This cross-protection could be similar to that observed between human coronaviruses causing the common cold and SARS-CoV-2. The limited numbers observed in the proteomes of FCoV, MCoV, and SW1-CoV may offer an explanation for the susceptibility of cats and minks to SARS-CoV-2, as well as a potential vulnerability in cetaceans.

关键词： Betacoronaviruses Zoonotic susceptibility Cross-protection Antigen presentation Immunogenicity

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