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2nd International Conference on Biospheric Harmony Advanced Research, ICOBAR 2020

作者： Rahutomo, R. Purwandari, K. Sigalingging, J.W.C. Pardamean, B. Information System Department School of Information Systems Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program Master of Computer Science Program Bina Nusantara University Jakarta11480 Indonesia Database Center Division of BMKG Meteorological Climatological and Geophysical Agency Jakarta10720 Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia

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. © Published under licence by IOP Publishing Ltd.

关键词： Air quality

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Mobile Application Implementation as Agriculture 4.0 Strategy for Sugarcane Yield Prediction

Mobile Application Implementation as Agriculture 4.0 Strateg...

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HCI and UX Conference in Indonesia (CHIuXiD), International

作者： Hangger Gahara Mawandha Reza Rahutomo Teddy Suparyanto Bens Pardamean Faculty of Agricultural Technology Institut Pertanian Stiper Yogyakarta Indonesia Information Systems Department School of Information Systems Bina Nusantara University Jakarta Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia

ISBN: (数字)9798350304084

ISBN: (纸本)9798350304091

Information engineering strategies play a significant and transformative role in shaping the landscape of digital agriculture. It drives innovation and efficiency in modern farming practices, with a specific focus on enhancing the value of agricultural commodities, such as sugarcane. The application of mobile technology plays a crucial part in achieving increased sugarcane productivity. Mobile applications, equipped with advanced developer features, offer rapid and user-friendly access to vital information. Traditional methods of estimating sugarcane production relied on manual data recording on paper, followed by data transfer to computer systems, typically managed by sugar factory junior plant officers. This conventional approach presents several inherent weaknesses, including time and effort intensiveness during data recording and entry. Additionally, the potential for errors in calculation and data input is a concern. The storage capacity for paper-based documents is finite, and farmers are often unable to autonomously assess their production potential. The objective of this research is to confront these obstacles by creating a sugarcane production application for Android. This application functions as an information engineering approach focused on forecasting sugarcane yields for plantation owners and their assistants. The development procedure adhered to the systematic waterfall method, following the principles of the Software Development Life Cycle (SDLC) model. Data collection was carried out through observations, while interviews with junior plant officers provided valuable insights into sugarcane estimation techniques. Analysis involved the synthesis of observational and interview data to inform the design of the application’s interface and algorithmic system. The resulting application significantly simplifies the process of estimating production potential for farmers, enabling them to access sugarcane productivity data during harvest. Consequently, sugar

关键词： Productivity Operating systems Estimation Production facilities Raw materials Mobile applications Recording

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New candidate genes potentially involved in Zika virus teratogenesis

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Computers in Biology and Medicine 2024年 173卷 108259-108259页

作者： Ferrão Maciel-Fiuza, Miriãn Rengel, Bruna Duarte Wachholz, Gabriela Elis do Amaral Gomes, Julia de Oliveira, Maikel Rosa Kowalski, Thayne Woycinck Roehe, Paulo Michel Luiz Vianna, Fernanda Sales Schüler-Faccini, Lavínia Mayer, Fabiana Quoos Varela, Ana Paula Muterle Fraga, Lucas Rosa Graduate Program in Genetics and Molecular Biology Universidade Federal do Rio Grande do Sul Porto Alegre Brazil Instituto Nacional de Genética Médica Populacional Porto Alegre Brazil Genomics Medicine Laboratory Center of Experimental Research Hospital de Clínicas de Porto Alegre Porto Alegre Brazil Department of Morphological Sciences Institute of Health Sciences Universidade Federal do Rio Grande do Sul Porto Alegre Brazil Graduate Program in Medicine: Medical Sciences Universidade Federal do Rio Grande do Sul Porto Alegre Brazil Teratogen Information System Medical Genetics Service Hospital de Clínicas de Porto Alegre Porto Alegre Brazil Bioinformatics Core Hospital de Clínicas de Porto Alegre Porto Alegre Brazil Centro Universitário CESUCA Cachoeirinha Brazil Department of Microbiology Immunology and Parasitology Institute of Health Sciences Universidade Federal do Rio Grande do Sul Porto Alegre Brazil Graduate Program in Molecular and Cellular Biology Biotechnology Center Universidade Federal do Rio Grande do Sul Porto Alegre Brazil Graduate Program in Biosciences Universidade Federal de Ciências da Saúde de Porto Alegre Porto Alegre Brazil

Despite efforts to elucidate Zika virus (ZIKV) teratogenesis, still several issues remain unresolved, particularly on the molecular mechanisms behind the pathogenesis of Congenital Zika Syndrome (CZS). To answer this question, we used bioinformatics tools, animal experiments and human gene expression analysis to investigate genes related to brain development potentially involved in CZS. Searches in databases for genes related to brain development and CZS were performed, and a protein interaction network was created. The expression of these genes was analyzed in a CZS animal model and secondary gene expression analysis (DGE) was performed in human cells exposed to ZIKV. A total of 2610 genes were identified in the databases, of which 1013 were connected. By applying centrality statistics of the global network, 36 candidate genes were identified, which, after selection resulted in nine genes. Gene expression analysis revealed distinctive expression patterns for PRKDC, PCNA, ATM, SMC3 as well as for FGF8 and SHH in the CZS model. Furthermore, DGE analysis altered expression of ATM, PRKDC, PCNA. In conclusion, systems biology are helpful tools to identify candidate genes to be validated in vitro and in vivo. PRKDC, PCNA, ATM, SMC3, FGF8 and SHH have altered expression in ZIKV-induced brain malformations. © Elsevier Ltd

关键词： Viruses

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Retraction Note: A proposal for Internet of Smart Home Things based on BCI system to aid patients with amyotrophic lateral sclerosis

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Neural Computing and Applications 2024年第28期36卷 17761-17761页

作者： de Oliveira Júnior, Wilson G. de Oliveira, Juliana M. Munoz, Roberto de Albuquerque, Victor Hugo C. Graduate Program in Applied Informatics Laboratory of Bioinformatics University of Fortaleza Fortaleza Brazil School of Informatics Engineering Universidad de Valparaíso Valparaíso Chile

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Implementation of Face Patterns and Smile Recognition for Intelligent Class Attendance Systems

Implementation of Face Patterns and Smile Recognition for In...

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International Conference of Computer and Informatics Engineering (IC2IE)

作者： Miftakhurrokhmat Teddy Suparyanto Gregorius Natanael Elwirehardja Shofiyati Nur Karimah Bens Pardamean Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia Department of Informatics Faculty of Computer Science Universitas Amikom Yogyakarta Yogyakarta Indonesia Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta Indonesia

Students “attendance in class is one important success parameter in face-to-face learning processes. Conventional attendance systems, such as paper-based attendance sheets or identity card systems, require a long time in the manual recapitulation process. Without additional verifications, even computer vision-based methods are prone to fraudulent practices by the students instead of gaining their excitement and attention in a class. To stimulate students” attention in a class, this work designs an intelligent class attendance system, in which facial pattern and smile recognition are implemented by using the latter as an additional task-based verification to reduce the risks of fake attendance. For the face recognition module, this pilot study used FaceNet as a feature extractor combined with SVM for classification, whereas the Haar cascade algorithm is used for recognizing smiles. This face recognition pipeline was implemented as a service installed on minicomputers or Internet of Things (IoT) devices in each classroom and connected to an IP camera. Every recorded attendance will be sent as a notification to a mobile application for students that requires their active participation to confirm it with a smiling self-photo. The proposed pipeline obtained 92.86% accuracy on the test data, and 66.67% accuracy when evaluated in a real-life simulation setting through the implemented system. The lower accuracy in the simulation indicated that further improvements are indispensable, especially since the model obtained 28.57% False Negative Rate. Future studies will need to acquire more data and experiment with more efficient methods of attendance verification.

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Characterizing the mechanical response of metallic glasses to uniaxial tension using a spring network model

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Physical Review Materials 2023年第7期7卷 073605-073605页

作者： Aya Nawano Weiwei Jin Jan Schroers Mark D. Shattuck Corey S. O'Hern Department of Mechanical Engineering and Materials Science Yale University New Haven Connecticut 06520 USA Benjamin Levich Institute and Physics Department The City College of New York New York New York 10031 USA Department of Physics Yale University New Haven Connecticut 06520 USA Department of Applied Physics Yale University New Haven Connecticut 06520 USA Graduate Program in Computational Biology and Bioinformatics Yale University New Haven Connecticut 06520 USA

A coarse-grained spring network model is proposed for the prediction of the mechanical response of metallic glasses as a function of the microstructure prior to loading. This model describes the mechanical response of metallic glasses using a network of parallel springs that can break and reform, mimicking atomic rearrangements during deformation. We compare predictions of the spring network model for stress versus strain to results from numerical simulations of athermal quasistatic, uniaxial tensile deformation of Cu50Zr50 metallic glasses using Lennard-Jones (LJ) and embedded atom method (EAM) atomic interactions. We show that both the LJ and EAM models possess qualitatively similar stress σ versus strain γ curves. By specifying five parameters [ultimate strength, strain at ultimate strength, slopes of σ(γ) at γ=0 and at large strain, and strain at fracture where σ=0], we demonstrate that the spring network model can accurately describe the form of the stress-strain curves during uniaxial tension for the computational studies of Cu50Zr50, as well as recent experimental studies of several Zr-based metallic glasses.

关键词： Alloys Amorphous materials Glasses Packing & jamming problems Molecular dynamics

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Lateral transfer of mRNA and protein by migrasomes modifies the recipient cells

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细胞研究（英文版） 2021年第2期31卷 237-240页

作者： Mingli Zhu Qin Zou Rongyao Huang Ying Li Xudong Xing Jianhuo Fang Liang Ma Lifei Li Xuerui Yang Li Yu State Key Laboratory of Membrane Biology Tsinghua University-Peking University Joint Center for Life Sciences Beijing Frontier Research Center for Biological Structure School of Life ScienceTsinghua University Beijing 100084 China Joint Graduate Program of Peking-Tsinghua-National Institute of Biological Science Tsinghua University Beijing 100084 China Joint Graduate Program of Peking-Tsinghua-National Institute of Biological Science Tsinghua University Beijing 100084 China MOE Key Laboratory of Bioinformatics Tsinghua University Center for Synthetic & Systems Biology Tsinghua University School of Life Science Beijing 100084China State Key Laboratory of Membrane Biology Tsinghua University-Peking University Joint Center for Life Sciences Beijing Frontier Research Center for Biological Structure School of Life ScienceTsinghua University Beijing 100084 China MOE Key Laboratory of Bioinformatics Tsinghua University Center for Synthetic & Systems Biology Tsinghua University School of Life Science Beijing 100084China

Dear Editor,Migrasomes are recently discovered vesicular organelles which form on the retraction fibers(RFs)of migrating cells.1 Once detached from cells,migrasomes can rupture and release their luminal contents1 in a process named ***,migrasomes have been shown to play an important role in zebrafish organ morphogenesis by releasing chemokine signals to defined regions of the embryo.2 Thus,migracytosis is considered as a major mechanism for migrasomes to carry out their *** has been frequently observed that intact migrasomes can be engulfed by surrounding cells,1 and this has been proposed as a potential mechanism for lateral transfer of cellular contents between ***,it is not clear whether the lateral transfer of cellular contents by migrasomes has functional consequences for the recipient cells.

关键词： Extracellular signalling molecules Organelles

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ntEdit+Sealer: Efficient Targeted Error Resolution and Automated Finishing of Long-Read Genome Assemblies

Current Protocols

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Current Protocols 2022年第5期2卷 e442页

作者： Li, Janet X. Coombe, Lauren Wong, Johnathan Birol, Inanç Warren, René L. Canada's Michael Smith Genome Sciences Center Vancouver BC Canada Bioinformatics Graduate Program University of British Columbia Vancouver BC Canada Department of Medical Genetics University of British Columbia Vancouver BC Canada

High-quality genome assemblies are crucial to many biological studies, and utilizing long sequencing reads can help achieve higher assembly contiguity. While long reads can resolve complex and repetitive regions of a genome, their relatively high associated error rates are still a major limitation. Long reads generally produce draft genome assemblies with lower base quality, which must be corrected with a genome polishing step. Hybrid genome polishing solutions can greatly improve the quality of long-read genome assemblies by utilizing more accurate short reads to validate bases and correct errors. Currently available hybrid polishing methods rely on read alignments, and are therefore memory-intensive and do not scale well to large genomes. Here we describe ntEdit+Sealer, an alignment-free, k-mer-based genome finishing protocol that employs memory-efficient Bloom filters. The protocol includes ntEdit for correcting base errors and small indels, and for marking potentially problematic regions, then Sealer for filling both assembly gaps and problematic regions flagged by ntEdit. ntEdit+Sealer produces highly accurate, error-corrected genome assemblies, and is available as a Makefile pipeline from https://***/bcgsc/ntedit_sealer_protocol. © 2022 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol: Automated long-read genome finishing with short reads. Support Protocol: Selecting optimal values for k-mer lengths (k) and Bloom filter size (b). © 2022 The Authors. Current Protocols published by Wiley Periodicals LLC.

关键词： assembly finishing Bloom filter hybrid assembly polishing k-mer long-read genome assembly

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Impact of CLAHE-based image enhancement for diabetic retinopathy classification through deep learning

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Procedia Computer Science 2023年 216卷 57-66页

作者： Mira Hayati Kahlil Muchtar Roslidar Novi Maulina Irfan Syamsuddin Gregorius Natanael Elwirehardja Bens Pardamean Department of Electrical and Computer Engineering Universitas Syiah Kuala Banda Aceh 23111 Indonesia Telematics Research Center (TRC) Universitas Syiah Kuala Banda Aceh 23111 Indonesia Faculty of Medicine Universitas Syiah Kuala Banda Aceh 23111 Indonesia Department of Computer and Networking Engineering Politeknik Negeri Ujung Pandang Makassar 90245 Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta 11480 Indonesia Computer Science Department BINUS Graduate Program – Master of Computer Science Program Bina Nusantara University Jakarta 11480 Indonesia

Diabetic retinopathy (DR) is a type of diabetes mellitus that attacks the retina of the eye. DR will cause patients to experience blindness slowly. Generally, DR can be detected by using a special instrument called an ophthalmoscope to view the inside of the eyeball. However, in conditions where there is a very small difference between the normal image and the DR image, computer-based assistance is needed for maximizing image reading value. In this research, a method of image quality improvement will be carried out which will then be integrated with a classification algorithm based on deep learning. The results of image improvement using Contrast Limited Adaptive Histogram Equalization (CLAHE) shows that the average accuracy of the method on several models is very competitive, 91% for the VGG16 model, 95% for InceptionV3, and 97% for EfficientNet compared to the results original image which only has an accuracy of 87% for VGG16 model, 90% for InceptionV3 model, and 95% for EfficientNet. However, in ResNet34 better accuracy is obtained in the original image with an accuracy of 95% while in the CLAHE image the accuracy value is only 84%. The results of this comprehensive evaluation and recommendation of famous backbone networks can be useful in the computer-aided diagnosis of diabetic retinopathy.

关键词： Diabetic retinopathy Deep Learning CNN Image Enhancement CLAHE

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Single-cell pair-wise relationships untangled by composite embedding model

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iScience 2023年第2期26卷 106025页

作者： Subedi, Sishir Park, Yongjin P. Bioinformatics Graduate Program University of British Columbia Vancouver BC Canada BC Cancer Research Part of Provincial Health Care Authority Vancouver BC Canada Department of Pathology and Laboratory Medicine University of British Columbia Vancouver BC Canada Department of Statistics University of British Columbia Vancouver BC Canada

In multicellular organisms, cell identity and functions are primed and refined through interactions with other surrounding cells. Here, we propose a scalable machine learning method, termed SPRUCE, which is designed to systematically ascertain common cell-cell communication patterns embedded in single-cell RNA-seq data. We applied our approach to investigate tumor microenvironments consolidating multiple breast cancer datasets and found seven frequently observed interaction signatures and underlying gene-gene interaction networks. Our results implicate that a part of tumor heterogeneity, especially within the same subtype, is better understood by differential interaction patterns rather than the static expression of known marker genes. © 2023 The Author(s)

关键词： Cancer systems biology Machine learning Transcriptomics

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