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Single-cell transcriptomics uncovers EGFR signaling-mediated gastric progenitor cell differentiation in stomach homeostasis (vol 14, 3750, 2023)

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NATURE COMMUNICATIONS 2023年第1期14卷 1-16页

作者： Takada, Hitomi Sasagawa, Yohei Yoshimura, Mika Tanaka, Kaori Iwayama, Yoshimi Hayashi, Tetsutaro Isomura-Matoba, Ayako Nikaido, Itoshi Kurisaki, Akira Laboratory of Stem Cell Technologies Graduate School of Science and Technology Nara Institute of Science and Technology Takayama-cho Ikoma Nara Japan Laboratory for Bioinformatics Research RIKEN Center for Biosystems Dynamics Research Wako Saitama Japan Department of Functional Genome Informatics Biological Data Science Medical Research Institute Tokyo Medical and Dental University Bunkyo Tokyo Japan Master’s/Doctoral Program in Life Science Innovation (Bioinformatics) Degree Programs in Systems and Information Engineering Graduate School of Science and Technology University of Tsukuba Tsukuba Ibaraki Japan

Defects in gastric progenitor cell differentiation are associated with various gastric disorders, including atrophic gastritis, intestinal metaplasia, and gastric cancer. However, the mechanisms underlying the multilineage differentiation of gastric progenitor cells during healthy homeostasis remain poorly understood. Here, using a single-cell RNA sequencing method, Quartz-Seq2, we analyzed the gene expression dynamics of progenitor cell differentiation toward pit cell, neck cell, and parietal cell lineages in healthy adult mouse corpus tissues. Enrichment analysis of pseudotime-dependent genes and a gastric organoid assay revealed that EGFR-ERK signaling promotes pit cell differentiation, whereas NF-κB signaling maintains gastric progenitor cells in an undifferentiated state. In addition, pharmacological inhibition of EGFR in vivo resulted in a decreased number of pit cells. Although activation of EGFR signaling in gastric progenitor cells has been suggested as one of the major inducers of gastric cancers, our findings unexpectedly identified that EGFR signaling exerts a differentiation-promoting function, not a mitogenic function, in normal gastric homeostasis.

关键词： Adult stem cells Stem-cell differentiation Stem-cell niche

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Quantitative Assessment of Gait in Spinocerebellar Ataxia Using Deep Learning

Quantitative Assessment of Gait in Spinocerebellar Ataxia Us...

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Electronic Communications, Internet of Things and Big Data (ICEIB), International Conference on

作者： Ming-Hui Lai Don-Gey Liu Ching-Hwa Cheng Chung-Yu Lai Master's Program of Biomedical Informatics and Biomedical Engineering Feng Chia University Taichung Taiwan Department of Electronic Engineering Feng Chia University Taichung Taiwan Department of Medical Equipment Development and Application Hungkuang University Taichung Taiwan

ISBN: (数字)9798350360721

ISBN: (纸本)9798350360738

Spinocerebellar ataxia is a neurological disorder characterized by impaired neural coordination, leading to unstable gait, coordination difficulties, and other motor abnormalities. This disease significantly impacts patients' daily lives, making it challenging for them to maintain balance, walk smoothly, and even perform fine motor skills. The causes of spinocerebellar ataxia are diverse, including genetic factors, brain injuries, or certain diseases. Many patients with spinocerebellar ataxia require specialized medical care and ongoing monitoring to manage its effects. This study aims to utilize Human Posture Estimation to detect the gait patterns of patients with spinocerebellar ataxia and integrate it with a deep learning model to distinguish between normal and affected individuals. The outcomes offer physicians an objective diagnostic tool and facilitate early detection and intervention for patients with impaired gait, thereby supporting the enhancement or preservation of their quality of life. The current prediction accuracy for the risk of ataxia gait is 80%, with an F1 score of 78.26%. It is necessary to conduct a detailed quantitative assessment by analyzing the gait of patients with spinocerebellar ataxia. Quantitative evaluation of the data allows for an objective assessment of the patient's gait, which helps healthcare professionals to more accurately understand and assess the gait status of patients with spinocerebellar ataxia.

关键词： Deep learning Neurological diseases Accuracy Medical services Motors Feature extraction Skeleton

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Analyzing Significance of Facial Features for Detection of Parkinson's Disease via Static Images

Analyzing Significance of Facial Features for Detection of P...

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Electronic Communications, Internet of Things and Big Data (ICEIB), International Conference on

作者： Chuang-Chien Chiu Shoou-Jeng Yeh Yen-Chi Sun Department of Automatic Control Engineering Feng Chia University Taichung Taiwan Section of Neurology and Neurophysiology Cheng-Ching General Hospital Taichung Taiwan Master's Program of Biomedical Informatics and Biomedical Engineering Feng Chia University Taichung Taiwan

ISBN: (数字)9798350360721

ISBN: (纸本)9798350360738

Parkinson's disease (PD) is a neurodegenerative disorder often characterized by motor symptoms such as hypomimia, and a reduction in facial expression. We explored the significance of facial features in identifying PD through static images, focusing on detecting hypomimia. A dataset comprised of PD patients and healthy controls' static facial images were collected and analyzed. Facial feature detection was conducted using OpenCV and Dlib libraries for the precise localization of key landmarks. In the subsequent feature extraction, parameters such as symmetry, eye aspect ratio, mouth corner distance, muscle tension, and mouth aperture ratio were used. Through the standardization of these features, meaningful comparisons across diverse images were made. By analyzing hypomimia-related features alongside traditional facial parameters, the results provide a comprehensive understanding of the role of facial expressions in PD diagnosis. The findings suggested that examining facial features in static images enhances the accuracy of PD detection and understanding of the nuanced motor symptoms associated with the disease.

关键词： Accuracy Parkinson's disease Sociology Mouth Standardization Muscles Motors

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Analysis of plant pattern using water balance and cimogram based on oldeman climate type 2

Analysis of plant pattern using water balance and cimogram b...

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2nd International Conference on Eco engineering Development 2018, ICEED 2018

作者： Caraka, R.E. Tahmid, M. Putra, R.M. Iskandar, A. Mauludin, M.A. Hermansah Goldameir, N.E. Rohayani, H. Pardamean, B. Bina Nusantara University Jakarta11480 Indonesia Indonesia Agency for Meteorology Climatology and Geophysics Indonesia Informatics Engineering STMIK AKBA Makassar Indonesia Laboratory of Sociology and Extension Universitas Padjadjaran Indonesia Universitas Riau Kepulauan Batam Indonesia Riau University Indonesia Universitas Adiwangsa Jambi Indonesia Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta11480 Indonesia

The transfer of land has an impact on the decreasing of the agricultural land area, so it is necessary to plan the right cropping pattern as an effort to increase the productivity of agricultural cultivation. Also, Climate is one of the factors influencing the determination of cropping pattern in a region. Analysis of climatic characteristics in the determination of cropping pattern not only based on oldeman climatic classification. At the same time, the study of groundwater availability for plants and climogram of climatic elements is needed in determining planting schedule which is suitable for planting and determination of irrigation water supply, either the right amount of time. This study aims to identify and build spatial of the oldeman climate classification. It also determines the cropping pattern for seasonal crops based on the calculation of water balance and climogram (rainfall and air temperature) in each type of climate oldeman district of Cirebon and surrounding areas. Data used monthly rainfall data period 1981-2010 from BMKG Jatiwangi station and air temperature data, plant coefficient and the base map of Cirebon region. The analysis method includes classification of Oldeman climate type, spatial data processing, water balance calculation by Thorntwaite & Matter method and making climogram (rainfall and temperature) with: k = p0 + p1/FC;p0 = 1.000412351;p1 = -1.073807306 and determination of planting pattern of each type of oldeman. © 2018 Institute of Physics Publishing. All rights reserved.

关键词： Groundwater

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Unitig-centered pan-genome machine learning approach for predicting antibiotic resistance and discovering novel resistance genes in bacterial strains

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Computational and Structural Biotechnology Journal 2024年 23卷 1864-1876页

作者： Do, Duyen Thi Yang, Ming-Ren Vo, Tran Nam Son Le, Nguyen Quoc Khanh Wu, Yu-Wei Graduate Institute of Biomedical Informatics College of Medical Science and Technology Taipei Medical University Taipei Taiwan Department of Electrical Engineering National Taiwan University of Science and Technology Taipei Taiwan Department of Business Administration College of Management Lunghwa University of Science and Technology Taoyuan City Taiwan Professional Master Program in Artificial Intelligence in Medicine College of Medicine Taipei Medical University Taipei Taiwan Clinical Big Data Research Center Taipei Medical University Hospital Taipei Taiwan TMU Research Center for Digestive Medicine Taipei Medical University Taipei Taiwan

In current genomic research, the widely used methods for predicting antimicrobial resistance (AMR) often rely on prior knowledge of known AMR genes or reference genomes. However, these methods have limitations, potentially resulting in imprecise predictions owing to incomplete coverage of AMR mechanisms and genetic variations. To overcome these limitations, we propose a pan-genome-based machine learning approach to advance our understanding of AMR gene repertoires and uncover possible feature sets for precise AMR classification. By building compacted de Brujin graphs (cDBGs) from thousands of genomes and collecting the presence/absence patterns of unique sequences (unitigs) for Pseudomonas aeruginosa, we determined that using machine learning models on unitig-centered pan-genomes showed significant promise for accurately predicting the antibiotic resistance or susceptibility of microbial strains. Applying a feature-selection-based machine learning algorithm led to satisfactory predictive performance for the training dataset (with an area under the receiver operating characteristic curve (AUC) of > 0.929) and an independent validation dataset (AUC, approximately 0.77). Furthermore, the selected unitigs revealed previously unidentified resistance genes, allowing for the expansion of the resistance gene repertoire to those that have not previously been described in the literature on antibiotic resistance. These results demonstrate that our proposed unitig-based pan-genome feature set was effective in constructing machine learning predictors that could accurately identify AMR pathogens. Gene sets extracted using this approach may offer valuable insights into expanding known AMR genes and forming new hypotheses to uncover the underlying mechanisms of bacterial AMR. © 2024 The Authors

关键词： Genes

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Methodology for the design of a nanosatellite telecommunication system in S-Band based on Software for Digital Mission engineering

Methodology for the design of a nanosatellite telecommunicat...

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International Conference on AeroSpace Science and Technology 2023, ICASST 2023

作者： García-Guillén, L.A. Sanchéz-Sanchéz, J.L. Ramírez-Aguilar, J.A. Ferrer-Pérez, J.A. Romo-Fuentes, J.C. Farah-Simón, A. Chávez-Moreno, R.G. Sánchez Hernández, D.C. Sánchez-Guzmán, J.A. Valdés-Galicia, J.F. Master's and Doctorate Programm in Engineering Engineering Faculty Universidad Nacional Autónoma de México CDMX Mexico Bachelor's in Aero Systems Electronics Engineering Universidad Aeronáutica en Querétaro Queretaro Mexico Advanced Technology Unit School of Engineering UNAM Queretaro Juriquilla Mexico Astronomy Institute Universidad Nacional Autónoma de México CDMX Mexico Faculty of Informatics Autonomous University of Queretaro Queretaro Juriquilla Mexico Space Program University Universidad Nacional Autónoma de México CDMX Mexico

A trend in the development of nanosatellite platforms for technology demonstration has increased in both private industry and academic projects. Communication link design plays a crucial role in the success of space missions, enabling efficient and reliable data transmission between satellites and ground stations. In this context, the use of advanced tools such as System Tool Kit (STK) has gained significant importance by enabling a comprehensive analysis of the technical and operational aspects of the communication link. In an effort to make the future design of the communications subsystem payload on a nanosatellite more efficient and accessible, this paper shows a methodology for the efficient use of STK to perform link analysis. © Published under licence by IOP Publishing Ltd.

关键词： Nanosatellites

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An Examination of the Possible Application of Artificial Intelligence Audit Process in Organizations

An Examination of the Possible Application of Artificial Int...

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International Conference on Cybernetics and Intelligent System (ICORIS)

作者： Wahyu Sardjono Dewi Sagita Pranata Muhammad Isamesal Information Systems Management Department BINUS Graduate Program – Master of Information Systems Management Bina Nusantara University Jakarta Indonesia Cyber Security Studi Program Department of Informatics Faculty of Natural Mathematical & Engineering Sciences King's College London Strands West Minster England Master of Management Department Faculty of Economics and Busines Universitas of Airlangga Surabaya Indonesia

ISBN: (数字)9798331539603

ISBN: (纸本)9798331539610

This study investigates how artificial intelligence (AI) can transform audit processes, including how AI can be used in businesses to execute non-technical audit tasks and what effect this will have on those tasks. A qualitative case study methodology is used in the research design to give detailed insights into how AI is being adopted by businesses. This study aims to analyze the aspects that impact AI implementation from the viewpoints of managers, auditors, and other stakeholders. The findings show that artificial intelligence (AI) has a great deal of promise for non-technical audit procedures in businesses. AI can automate tedious jobs, evaluate large data sets to identify hazards and enhance teamwork and communication. These developments may lead to increased productivity, maybe better audit quality, and more effective processes. But there are still difficulties. Data quality is essential to the success of AI integration, and auditors may exhibit bias in favor of human professionals. Careful thought must also be given to ethical issues about transparency and possible job displacement. All things considered, this study adds significant knowledge to both the academic literature and real-world auditing applications. It improves our comprehension of the function of AI in the industry and provides useful information for people involved in information technology development, audit, and legislation.

关键词： Productivity Ethics Data analysis Reviews Data integrity Transforms Natural language processing Teamwork Stakeholders Artificial intelligence

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The Banking Industry is Undergoing a Digital Transformation as Part of Industrial 4.0

The Banking Industry is Undergoing a Digital Transformation ...

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International Conference on Smart Computing & Communications (ICSCC)

作者： Wahyu Sardjono Dewi Sagita Pranata Aditya Agung Dwi Ramdhana Information Systems Management Department BINUS Graduate Program - Master of Information Systems Management Bina Nusantara University Jakarta Indonesia Department of Informatics Cyber Security Studi Program Faculty of Natural Mathematical & Engineering Sciences King's College London Strands West Minster England Master of Management Faculty of Economics and Business University of Airlangga Surabaya Indonesia

ISBN: (数字)9798350363104

ISBN: (纸本)9798350363111

In the current day, digital transformation is imperative; both customer demand and market competitiveness are mostly driving that trend. The fourth industrial revolution has also affected the financial sector. One difficulty that has to be addressed is the desire from customers for quick and useful services. Traditional procedures need to be replaced with digital ones. Furthermore, banking organizations will have a competitive edge in the current market if they are successful in this digital transformation process. Successful transformation, however, does not happen by accident; in fact, the likelihood of completing this change is seen to be very low, necessitating rigorous planning for a company that is ready for the future. There are several components to the preparation in question, both internal and external. In this situation, the company's ability to combine and rearrange its resources quickly is essential for adapting to the ever-changing business environment.

关键词： Industries Leadership Companies Banking Market research Fourth Industrial Revolution Planning Faces Accidents

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Power Line Interference Detection and Rejection in ECG

Power Line Interference Detection and Rejection in ECG

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Advances in Communication Technology——2011 3rd World Congress in Applied Computing, Computer Science, and Computer engineering (ACC 2011)

作者： Yue-Der Lin Ching-Che Tsai Hu-Ying Ho Shih-Fan Wang Kang-Ping Lin Hen-Hong Chang Master's Program in Biomedical Informatics & Biomedical Engineering Feng Chia University Department of Automatic Control Engineering Feng Chia University Holistic Medical Device Research and Development Center Chung Yuan Christian University Institute of Traditional Chinese Medicine Chang-Gung University

A novel power-line interference(PLI) reduction algorithm is proposed as a pre-processing step for electrocardiogram(ECG) signals. A distinct feature of this proposed algorithm is its ability to detect the presence of PLI in the ECG signal before applying the PLI removal algorithm. A constant-false alarm rate(CFAR) PLI detector using a band-pass IIR notch filter is developed for this purpose. Once the presence of PLI is detected, a recursive least-squares(RLS) adaptive IIR filter then will be applied to eliminate the PLI anomaly. On the other hand, if the PLI is not detected, no PLI reduction filtering will be applied. The proposed intelligent algorithm is able to perform PLI reduction operation without human operator supervision. The proposed RLS adaptive notch filtering algorithm also exhibits fast convergence and numerical stability.

关键词： Power-line interference(PLI),electrocardiogram(ECG),constant-false alarm rate(CFAR),recursive least-squares(RLS).

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Minimizing the Number of Stunting Prevalence Using the Euclid Algorithm Clustering Approach

Minimizing the Number of Stunting Prevalence Using the Eucli...

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International Conference of Computer Science and Information Technology

作者： Muhammad Zarlis Tanty Oktavia Relita Buaton Ferda Ernawan Kevin Andrian Department BINUS Graduate Program - Master of Information System Management Information System Management Bina Nusantara University Jakarta Indonesia Informatics Engineering STMIK Kaputama Binjai Indonesia Faculty of Computing Universiti Malaysia Pahang Al-Sultan Abdullah Pekan Malaysia Department of Information Systems Management BINUS Graduate Program-Master of Information Systems Management Bina Nusantara University Jakarta Indonesia

Superior and quality human resources are based on healthy human resources with indicators of adequate nutritional intake according to age development. However, the world still faces the problem of hunger and malnutrition today. According to a UNICEF report, the number of people suffering from malnutrition in the world will reach 767.9 million people in 2021. The World Health Organization (WHO) said that malnutrition is a dangerous threat to the health of the world's population. Stunting also has an impact in Indonesia, the prevalence of toddlers experiencing stunting in Indonesia is 24.4% in 2021. The solution created is to classify and cluster the prevalence of stunting to produce a pattern that can be used as best practice to be transmitted to other affected areas. The algorithm used is Euclid. The Euclid algorithm can cluster stunting prevalence data into 4 clusters with the very little category at 79%, the little category at 67%, the many categories at 51%, and the very much category at 21%. The results of the classification and clustering of the best stunting prevalence in cluster one with a very small number, can be used as a source of accurate and updated information that can be used by the government in its efforts to optimize stunting handling in each district/city based on artificial intelligence which can provide handling and optimization patterns. stunting in every district/city.

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