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Lockdown strategy worth lives: The SEIRD modelling in COVID-19 outbreak in Indonesia

IOP Conference Series: Earth and Environmental science 2021年第1期729卷

作者： I Nurlaila A A Hidayat B Pardamean Information Systems Department BINUS Online Learning 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

Lockdowns, despite their conflicting restrictions and consequences they might offer when enforced as a national strategy, are deemed to be suggestive for a prompt conquer to the Coronavirus Disease-19 (COVID-19) outbreak. There have been some success stories such as in China, South Korea and our ASEAN member fellow, Vietnam, which exhibited extremely fallen numbers of COVID-19 cases post the enforcement of lockdown. Indonesia, however, remains in the crux of dispute whether or not the lockdown is opted to force COVID-19 transmission down under control. We, in this respect, employ the most popular model which has been broadly applied in the field of epidemiology, referred to as SEIRD (Susceptible, Exposed, Infectious, Recovered, and Death), the extension form of an age-structured SEIR, where the Death (D) is included to provide more factual situation. We modify the I (Infectious) fraction as symp-tomatic (Is) and asymptomatic (Ia) infectives. There are three lockdown scenarios simulated in our modified SEIRD with the starting date are 26 April 2020 when the immediate lockdown was enacted-and a-week and two-week-gaps, respectively. We figured out that by stipulating the lockdown without delay (26 April 2020), the new cases could be kept below 10,000. A week delay escalates case number to 5,000 and delay for one more week results in beyond 20,000 new cases. Furthermore, when the intervention is delayed following the delayed lockdown, normalization would demand a longer period within which dealing with more critical and dying patients is unavoidable and should be more anticipated.

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Sustainable improvement of food SMEs through halal certification: A meta-analysis

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AIP Conference Proceedings 2024年第1期2957卷

作者： Rizal Bahara Muhammad N. Aidi Khaswar Syamsu Euis Sunarti Anuraga Jayanegara Natural Resources and Environmental Management Science Study Program Graduate School IPB University Jl Pajajaran No 1 Kampus IPB Baranangsiang Bogor West Java 1614 Indonesia Statistics and Data Science Department Mathematics and Natural Science Faculty IPB University Jl. Lingkar Kampus IPB Dramaga Bogor West Java 16680 Indonesia Halal Science Center LPPM IPB. Gedung Pascasarjana Gedung Kimia IPB University Jl Pajajaran No 1 Kampus IPB Baranangsiang Bogor West Java 1644 Indonesia Department of Family and Consumer Sciences Faculty of Human Ecology IPB University Jl. Lingkar Kampus IPB Dramaga Bogor West Java 16610 Indonesia Department of Nutrition and Feed Technology Faculty of Animal Science IPB University Jl. Lingkar Kampus IPB Dramaga Bogor West Java 16680 Indonesia

Small and medium enterprises (SMEs) are one of the important economic drivers in Indonesia, including during the Covid-19 pandemic. Indonesia as the country with the largest Muslim population requires halal certificates for all food products sold in Indonesia. Obstacles to the implementation and certification of halal in the food SME sector are still encountered due to, among others, the cost of certification, knowledge from human resources, ease of access and information. The purpose of this study was to evaluate the role of halal certification on financial performance in Food SMEs by employing the meta-analysis method. A number of six articles out of 55 articles were selected and integrated into a database. The data were analyzed based on the Hedges’ d (standardized mean difference/SMD) effect size values and confidence interval (CI) values by using the Open MEE software. The results showed that halal-certified food SMEs significantly increased sales (SMD: 3.182; 95% CI:1.228 to 5.136; p<0.001) as compared to those of food SMEs that were not halal-certified. In the location in the Indonesia subgroup, halal certification at Food SMEs in Bogor city had a higher sale (SMD: 12.105; 95% CI: 10.289 to 13.922; p<0.001) compared to other cities. The conclusion of this study is that halal certification enhances sales and thus contributes to the sustainability of food SMEs.

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Metrics for benchmarking and uncertainty quantification: Quality, applicability, and a path to best practices for machine learning in chemistry

arXiv

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arXiv 2020年

作者： Vishwakarma, Gaurav Sonpal, Aditya Hachmann, Johannes Department of Chemical and Biological Engineering University at Buffalo State University of New York BuffaloNY14260 United States Computational and Data-Enabled Science and Engineering Graduate Program University at Buffalo State University of New York BuffaloNY14260 United States New York State Center of Excellence in Materials Informatics BuffaloNY14203 United States

This review aims to draw attention to two issues of concern when we set out to make machine learning work in the chemical and materials domain, i.e., statistical loss function metrics for the validation and benchmarking of data-derived models, and the uncertainty quantification of predictions made by them. They are often overlooked or underappreciated topics as chemists typically only have limited training in statistics. Aside from helping to assess the quality, reliability, and applicability of a given model, these metrics are also key to comparing the performance of different models and thus for developing guidelines and best practices for the successful application of machine learning in chemistry. Copyright © 2020, The Authors. All rights reserved.

关键词： Benchmarking

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Robot Hand Interaction Using Plastic Deformation Control with Inner Position Loop

Robot Hand Interaction Using Plastic Deformation Control wit...

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IEEE/ASME (AIM) International Conference on Advanced Intelligent Mechatronics

作者： Kenichi Murakami Koki Ishimoto Taku Senoo Masatoshi Ishikawa Data Science Research Division Information Technology Center The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo Japan Department of Information Physics and Computing The University of Tokyo 7-3-1 Hongo Bunkyo-ku Tokyo Japan Electrical Systems and Control Engineering Program Graduate School of Advanced Science and Engineering Hiroshima University 1-4-1 Kagamiyama Higashi-Hiroshima City Hiroshima Japan

ISBN: (数字)9781728167947

ISBN: (纸本)9781728167954

In this study, the inner position loop addition for plastic deformation control of the error robustness of the model and actual parameters is proposed. The inner position loop is a type of position feedback control based on the estimation of model parameters and dynamics of robots. This position control system with proportional and derivative gains modifies the trajectory of the end effector close to the desired trajectory. The robustness of the proposed control scheme is evaluated by comparing it with plastic deformation control without an inner position loop in both simulation and actual environments. Finally, the stable reaction with the proposed control is demonstrated for the case where a human pushes the robot finger.

关键词： Strain Plastics Force Deformable models Robots Friction Trajectory

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Integrating spatially-resolved transcriptomics data across tissues and individuals: challenges and opportunities

arXiv

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arXiv 2024年

作者： Guo, Boyi Ling, Wodan Kwon, Sang Ho Panwar, Pratibha Ghazanfar, Shila Martinowich, Keri Hicks, Stephanie C. Department of Biostatistics Johns Hopkins Bloomberg School of Public Health BaltimoreMD United States Division of Biostatistics Department of Population Health Sciences Weill Cornell Medicine NY United States Lieber Institute for Brain Development Johns Hopkins Medical Campus BaltimoreMD United States Solomon H. Snyder Department of Neuroscience Johns Hopkins School of Medicine BaltimoreMD United States Biochemistry Cellular and Molecular Biology Graduate Program Johns Hopkins School of Medicine BaltimoreMD United States School of Mathematics and Statistics The University of Sydney NSW2006 Australia Sydney Precision Data Science Centre University of Sydney NSW2006 Australia Charles Perkins Centre The University of Sydney NSW2006 Australia Department of Psychiatry and Behavioral Sciences Johns Hopkins School of Medicine BaltimoreMD United States Johns Hopkins Kavli Neuroscience Discovery Institute BaltimoreMD United States Department of Biomedical Engineering Johns Hopkins University BaltimoreMD United States Center for Computational Biology Johns Hopkins University BaltimoreMD United States Malone Center for Engineering in Healthcare Johns Hopkins University BaltimoreMD United States

Advances in spatially-resolved transcriptomics (SRT) technologies have propelled the development of new computational analysis methods to unlock biological insights. As the cost of generating these data decreases, these technologies provide an exciting opportunity to create large-scale atlases that integrate SRT data across multiple tissues, individuals, species, or phenotypes to perform population-level analyses. Here, we describe unique challenges of varying spatial resolutions in SRT data, as well as highlight the opportunities for standardized preprocessing methods along with computational algorithms amenable to atlas-scale datasets leading to improved sensitivity and reproducibility in the future. © 2024, CC BY-NC-ND.

关键词： Biotic

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COVID-19 Testing Pipeline: Lesson Learned

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

作者： Dian Amirulloh Digdo Sudigyo Arif Budiarto Ika Nurlaila Erlin Listiyaningsih Andrew 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 Information System Department BINUS Online Learning Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program - Master of Computer Science Program Bina Nusantara University Jakarta Indonesia 11480

The transmission of severe acute respiratory syndrome coronavirus 2 (SARS CoV-2) in Indonesia is seen to be uncontrollably increasing that urges the government to leverage the capacity for the disease detections. Real-time polymerase chain reaction (RT-PCR), rapid test and computed tomography (CT) scan are the most common methods to determine if one has been infected regardless of whether or not the common symptoms of such Corona Virus Disease 2019 (COVID-19) surface. Among these three, RT-PCR is considered the gold standard for qualitative and quantitative assessment of SARS CoV-2 detection. The present paper aims at elaborating the framework of Roche's RT-PCR machine employed specifically for SARS CoV-2 detection performed by Genetics Indonesia which is deemed to be efficient and relatively quicker than other detection kits. RT-PCR machine detected SARS Cov-2 with RNA amplification curve equals to 10 copies RNA below the cut off value of Crossing point (Cp) positive control. Also elucidated in the paper is the implementations of EAV RNA and LightCycler® 96 RT-PCR System through which analysis time, amounts of individual required sample, as well as the reagents, can be accordingly reduced.

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Dynamic analysis and multi-objective optimization of an integrated solar energy system for Zero-Energy residential complexes

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Energy Conversion and Management 2025年 341卷

作者： Saleh Mobayen Ehsanolah Assareh Ali Dezhdar Siamak Hoseinzadeh Davide Astiaso Garcia Graduate School of Intelligent Data Science National Yunlin University of Science and Technology Douliu Yunlin 640301 Taiwan Built Environment and Engineering Program College of Sport Health and Engineering (CoSHE) Victoria University Melbourne Australia Strategic Research Institute (SRI) Asia Pacific University of Technology and Innovation (APU) Technology Park Malaysia Kuala Lumpur Malaysia Department of Renewable Energy Technology Materials and Energy Research Center Dezful Branch Islamic Azad University Dezful Iran Department of Planning Design Technology of Architecture Sapienza University of Rome Via Flaminia 72 00196 Rome Italy Department of Astronautical Electrical and Energy Engineering Sapienza University of Rome Via Eudossiana 18 Rome Italy

This study introduces and evaluates a novel, integrated solar energy system for achieving sustainable and zero-energy residential buildings. The proposed system integrates photovoltaic-thermal (PVT) solar panels, heat pumps, electrolyzers, fuel cells, reverse osmosis desalination units, and thermal storage tanks to simultaneously supply electricity, heating, cooling, and potable water. A primary challenge in solar energy systems—the intermittency of energy production—is addressed using energy storage solutions, including hydrogen-based electrolysis and fuel cell systems, which stabilize the supply across day-night cycles. The energy system is designed to meet the energy demands of a 160-unit residential complex in San Diego, each unit covering 110 m 2 . A dynamic simulation over an entire year is performed using TRNSYS software. System optimization is conducted via Response Surface Methodology (RSM), targeting three objective functions: total power capacity, life cycle cost (LCC), and thermal comfort represented by the predicted percentage dissatisfied (PPD) index. Optimization system is based on five key decision variables: solar PVT area, fuel cell capacity, electrolyzer capacity, heat pump capacity, and hydrogen tank size. Results demonstrate that, under optimized configurations, the system achieves an annual electricity output of 29,145.8 kWh/year, an LCC of $894,228, and a PPD index of 6.8 %, fully meeting the residential complex’s electricity demand of 200 MWh/year. The results validate the effectiveness of the hybrid system in enhancing efficiency, ensuring system reliability, and mitigating environmental impacts, thus offering a scalable solution for zero-energy building applications.

关键词： Building Energy Solar PVT Panels Fuel Cell Heat Pump Multi-Objective Optimization

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Improvement of Jakarta's air quality during large scale social restriction

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IOP Conference Series: Earth and Environmental science 2021年第1期729卷

作者： R Rahutomo K Purwandari J W C Sigalingging B Pardamean Information System Department School of Information Systems Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department BINUS Graduate Program - Master of Computer Science Program Bina Nusantara University Jakarta Indonesia 11480 Database Center Division of BMKG Meteorological Climatological and Geophysical Agency Jakarta Indonesia 10720 Bioinformatics & Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480

After Large-Scale Social Restriction (PSBB) established in Jakarta, a change of air quality was indicated by the citizens. Representatives of Indonesia's Agency for Meteorology, Climatology, and Geophysics (BMKG) supported as the fact that mobility of Jakarta's citizen and commuters were reduced. With utilizing Weather data Acquisition System managed by BMKG, this research compared fluctuations of Jakarta's air quality during two periods of time: Pre-PSBB and During-PSBB. This study proved that Jakarta's air quality has positively improved compared to the previous year, although in the lower range of unhealthy level.

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An Evaluation of Deep Neural Network Performance on Limited Protein Phosphorylation Site Prediction data

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Procedia Computer science 2019年 157卷 25-30页

作者： Favorisen Rosyking Lumbanraja Bharuno Mahesworo Tjeng Wawan Cenggoro Arif Budiarto Bens Pardamean Department of Computer Science Faculty of Mathematics and Natural Science University of Lampung Jalan Prof. Dr. Sumantri Brojonegoro No.17 35145 Bandar Lampung Indonesia Bioinformatics and 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

One of the common and important post-translational modification (PTM) types is phosphorylation. Protein phosphorylation is used to regulate various enzyme and receptor activations which include signal pathways. There have been many significant studies conducted to predict phosphorylation sites using various machine learning methods. Recently, several researchers claimed deep learning based methods as the best methods for phosphorylation sited prediction. However, the performance of these methods were backed up with the massive training data used in the researches. In this paper, we study the performance of simple deep neural network on the limited data generally used prior to deep learning employment. The result shows that a deep neural network can still achieve comparable performance in the limited data settings.

关键词： Phosphorylation Site Prediction Protein Phosphorylation Deep Learning Deep Neural Network

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Bioinformatics Pathway Analysis Pipeline for NGS Transcriptome Profile data on Nasopharyngeal Carcinoma

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

作者： Digdo Sudigyo Gisti Rahmawati Dicka W. Setiasari Risky H. Poluan Tjeng Wawan Cenggoro Arif Budiarto Alam Ahmad Hidayat Sri R. Indrasari Afiahayati Sofia M. Haryana Bens Pardamean Bioinformatics & Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 Study Program of Biotechnology Gadjah Mada University Yogyakarta Indonesia 55281 Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia 11480 Faculty of Medicine Public Health and Nursing Gadjah Mada University Yogyakarta Indonesia 55281 Department of Computer Science and Electronics Faculty of Mathematics and Natural Science Gadjah Mada University Yogyakarta Indonesia 55281 Computer Science Department BINUS Graduate Program - Master of Computer Science Program Bina Nusantara University Jakarta Indonesia 11480

Next-Generation Sequencing (NGS)-based genomics data have a huge potential to be used in transcriptomic profiling of Nasopharyngeal Carcinoma (NPC) to study the biosynthesis mechanism behind it. The high dimensionality of NGS data is the main challenge in performing the data analysis to extract useful information. In this workflow pipeline, memory-efficient Linux-based software such as HISAT2 and HTSeq are utilized to process the raw NGS data. Furthermore, Differential Expression Gene (DEG) list can be obtained by performing advanced analysis to the aligned Ribonucleic Acid (RNA) sequence using the edgeR protocol. This DEG list is one of the main inputs of biological pathway analysis that can be done in DAVID and PANTHER web-based software. Both tools generate a different pathway result related to inflammation.

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