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Successive responses of three coral holobiont components (coral hosts, symbiotic algae, and bacteria) to daily temperature fluctuations

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Ecological Indicators 2024年 158卷

作者： Hsieh, Yunli Eric Lu, Chih-Ying Liu, Po-Yu Kao, Jia-Min Yang, Sung-Yin Wu, Chien-Yi Wong, Jing-Wen Michelle Shikina, Shinya Fan, Tung-Yung Yang, Shan-Hua Systems Biology and Mathematical Modelling group Max Planck Institute of Molecular Plant Physiology Potsdam Germany Institute of Biochemistry and Biology Bioinformatics Department University of Potsdam Potsdam Germany School of BioSciences The University of Melbourne ParkvilleVIC Australia Molecular and Biological Agricultural Sciences Program Taiwan International Graduate Program National Chung Hsing University and Academia Sinica Taipei Taiwan Graduate Institute of Biotechnology National Chung Hsing University Taichung Taiwan Biodiversity Research Center Academia Sinica Taipei Taiwan School of Medicine College of Medicine National Sun Yat-sen University Kaohsiung Taiwan Institute of Fisheries Science National Taiwan University Taipei Taiwan Department of Aquatic Bioscience National Chiayi University Chiayi Taiwan Institute of Marine Environment and Ecology National Taiwan Ocean University Keelung Taiwan National Museum of Marine Biology and Aquarium Pingtung Taiwan

Corals and their associated microbiota form a "holobiont," which includes symbiotic algae and other associated microbiota dominated by bacteria. The composition of holobiont is influenced by various environmental factors, such as increasing sea water temperatures. Previous studies of the effects of temperature changes on coral physiology and associated bacterial communities have been conducted based on stable water temperatures set by mean temperatures, or by slowly increasing/decreasing temperatures. However, the daily temperature fluctuations that corals experience in nature are not stable. The current understanding of the effects of large daily temperature fluctuations on coral and associated bacterial community dynamics is limited. Hence, we conducted a four-week tank experiment using different large daily temperature fluctuations (±5 °C and ±7 °C) accompanied by continuous warming conditions (26 °C to 29 °C) to investigate the effects on two common reef-building corals, Stylophora pistillata and Pocillopora acuta. During the experiment, the activity of coral host catalase and superoxide dismutase were measured, the photosynthetic ability of symbiotic algae was recorded, and the variation in bacterial communities was analyzed using the V6-V8 region of 16S rDNA. According to the results, different parts of the holobionts of two coral species exhibited varying response rates to the continuous warming conditions and diurnal temperature fluctuations. Additionally, it was found that diurnal temperature fluctuations may mitigate the heat stress on the host and reduce the changes in bacterial response to warming. Therefore, it is suggested that the holobionts of different coral species may adopt different adaptation and survival strategies in response to diurnal temperature fluctuations and warming. Finally, based on the response of these two coral species under the conditions of diurnal temperature fluctuations and continuous warming, Acinetobacter and Rhodobacteracea

关键词： Temperature distribution

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Parameter Optimization of Support Vector Regression Using Harris Hawks Optimization

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Procedia Computer Science 2021年 179卷 17-24页

作者： I Nyoman Setiawan Robert Kurniawan Budi Yuniarto Rezzy Eko Caraka Bens Pardamean Computational Statistics Department Polytechnic of Statistics - STIS Jakarta 13330 Indonesia Department of Information Management College of Informatics Chaoyang University of Technology Taiwan (ROC) Bioinformatics and Data Science Research Center Bina Nusantara University Indonesia 11530 Computer Science Department BINUS Graduate Program - Master of Computer Science Program Bina Nusantara University Jakarta Indonesia. 11530.

Support Vector Regression (SVR) is often used in forecasting. Adjustment of parameters in the SVR affects the results of forecasting. This study aims to analyze the SVR method that is optimized using Harris Hawks Optimization (HHO), hereinafter referred to as HHO-SVR. The HHO-SVR was evaluated using five benchmark datasets to determine the performance of this method. The HHO process is also compared based on the type of kernel and other metaheuristic algorithms. The results showed that the HHO-SVR has almost the same performance as other methods but is less efficient in terms of time. In addition, the type of kernel also affects the process and results.

关键词： SVR harris hawks optimization parameter optimization kernel forecasting

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Count time series modelling of Twitter data topic modelling: A case of Indonesia flood events

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AIP Conference Proceedings 2023年第1期2594卷

作者： A. A. Hidayat B Pardamean Bioinformatics & 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

Twitter data provide rich and powerful information to leverage the dynamics of public perception to establish situational awareness and disaster mitigation strategies during critical times. In this paper, we perform topic modeling via Latent Dirichlet Allocation to extract topics from a collection of tweets related to Indonesia flood events in February 2021 with the query: “banjir”. The extracted topics are used as one of the features to build a generalized linear count time series model with Negative Binomial distribution. We find seven major topics from the model in which tweets containing a topic about the government’s role in handling the situation dominate the conversation. Taking into account a simple intervention analysis, we demonstrate a statistically significant change in the users’ behavior before and after the severe Jakarta flood on 20 February 2021. Moreover, a metric evaluation demonstrates that a covariate that describes the turning point of the Jakarta flood event is convenient to build a more accurate count time series model of the tweets.

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Single-cell epigenome analysis reveals age-associated decay of heterochromatin domains in excitatory neurons in the mouse brain

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细胞研究（英文版） 2022年第11期32卷 1008-1021页

作者： Yanxiao Zhang Maria Luisa Amaral Chenxu Zhu Steven Francis Grieco Xiaomeng Hou Lin Lin Justin Buchanan Liqi Tong Sebastian Preissl Xiangmin Xu Bing Ren Ludwig Institute for Cancer Research La JollaCAUSA School of Life Sciences Westlake UniversityHangzhouChina Bioinformatics and Systems Biology Graduate Program University of California San DiegoLa JollaCAUSA Ludwig Institute for Cancer Research La JollaCAUSA Department of Anatomy and Neurobiology School of MedicineUniversity of CaliforniaIrvineCAUSA Center for Epigenomics University of California San DiegoLa JollaCAUSA.6Institute of Experimental and Clinical Pharmacology and ToxicologyFaculty of MedicineUniversity of FreiburgFreiburgGermany Center for Epigenomics University of California San DiegoLa JollaCAUSA.6Institute of Experimental and Clinical Pharmacology and ToxicologyFaculty of MedicineUniversity of FreiburgFreiburgGermany The Center for Neural Circuit Mapping University of CaliforniaIrvineCAUSA Department of Anatomy and Neurobiology School of MedicineUniversity of CaliforniaIrvineCAUSA Department of Cellular and Molecular Medicine University of California San Diego School of MedicineLa JollaCAUSA Ludwig Institute for Cancer Research La JollaCAUSA Center for Epigenomics University of California San DiegoLa JollaCAUSA.6Institute of Experimental and Clinical Pharmacology and ToxicologyFaculty of MedicineUniversity of FreiburgFreiburgGermany institute for Genomic Medicine University of California San DiegoLa JollaCAUSA

Loss of heterochromatin has been implicated as a cause of pre-mature aging and age-associated decline in organ functions in mammals;however,the specific cell types and gene loci affected by this type of epigenetic change have remained *** address this knowledge gap,we probed chromatin accessibility at single-cell resolution in the brains,hearts,skeletal muscles,and bone marrows from young,middle-aged,and old mice,and assessed age-associated changes at 353,126 candidate cis-regulatory elements(cCREs)across 32 major cell ***,we detected increased chromatin accessibility within specific heterochromatin domains in old mouse excitatory *** gain of chromatin accessibility at these genomic loci was accompanied by the cell-type-specific loss of heterochromatin and activation of LINE1 *** further confirmed the loss of the heterochromatin mark H3K9me3 in the excitatory neurons but not in inhibitory neurons or glial *** results reveal the cell-type-specific changes in chromatin landscapes in old mice and shed light on the scope of heterochromatin loss in mammalian aging.

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Dynamic Hierarchical Skeleton-Based Network for Human Action Recognition in Video Content

SSRN

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SSRN 2024年

作者： Yang, Hualin Li, Xiying Chen, Calvin Yu-Chian Artificial Intelligence Medical Research Center School of Intelligent Systems Engineering Shenzhen Campus of Sun Yat-sen University Guangdong Shenzhen518107 China - Preferred Program Peking University Shenzhen Graduate School Guangdong Shenzhen518055 China School of Electronic and Computer Engineering Peking University Shenzhen Graduate School Guangdong Shenzhen518055 China Department of Medical Research China Medical University Hospital Taichung40447 Taiwan Department of Bioinformatics and Medical Engineering Asia University Taichung41354 Taiwan Guangdong Provincial Key Laboratory of Intelligent Transportation System Sun Yat-sen University Guangzhou China School of Intelligent Systems Engineering Sun Yat-sen University Guangdong Shenzhen518107 China

Human skeleton-based action recognition represents a pivotal field of study, capturing the intricate interplay between physical dynamics and intentional actions. Current research primarily focuses on extracting structural and temporal information from static skeleton-based graphs, but they grapple with a myriad of challenges. These include 1) an absence of hierarchical structure in encoding the skeleton-based graphs;2) A requirement for substantial prior knowledge to interpret the diverse spatial dynamics within singular action labels;3) An intricate task of representing the multifaceted temporal dynamics of individual actions. To counter this issue, we propose DHS-Net, an innovative dynamic hierarchical skeleton-based network in video content. The proposed DHS-Net incorporates the DHS Block as a central element, effectively facilitating information exchange through node concentration and diffusion across both structural and temporal dimensions. Through this architectural design, DHS-Net extracts hierarchical representations, enhancing the comprehensive understanding of spatio-temporal dynamics and marking a significant advancement in human action recognition. Our rigorous experimental evaluations further substantiate DHS-Net's supremacy, outperforming several state-of-the-art benchmarks in skeleton-based action recognition and achieving remarkable prediction accuracy. © 2024, The Authors. All rights reserved.

关键词： Dynamics

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Maintaining the Quality and Aroma of Coffee with Fuzzy Logic Coffee Roasting Machine 3

Maintaining the Quality and Aroma of Coffee with Fuzzy Logic...

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3rd International Conference on Eco Engineering Development, ICEED 2019

作者： Harsawardana Samodro, Bayu Mahesworo, Bharuno Suparyanto, Teddy Surya Atmaja, Don Bosco Pardamean, Bens Institut Pertanian STIPER Yogyakarta55281 Indonesia Mechatronics and AI Research and Development Center Biotechnic Innovation Yogyakarta55281 Indonesia Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta11480 Indonesia Computer Science Department BINUS Graduate Program - Master of Computer Science Bina Nusantara University Jakarta11480 Indonesia

With the increasing global demands of coffee, Indonesia need to increase their coffee beans supply and improve the quality to maintain its position in the international coffee industry. One of the most important coffeepre-processing, coffee bean roasting, is under developed in Indonesia. Indonesia coffee farmers prefer to use the traditional cauldron to roast their coffee beans. Roasting coffee beans using traditional cauldron is inefficient and resulting unequal roasted level for the coffee beans. In this study, we proposed atemperature control system based on fuzzy logic for coffee roaster machine. The system controls the temperature in accordance with the demanded roasting level. A thermal camera is attached inside the roasting chamber to monitor the heaton the roasted coffee beans. The thermal camera is integrated with a stirring mechanism to equalise the heat among the beans. © 2020 Published under licence by IOP Publishing Ltd.

关键词： Fuzzy logic

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Evaluation of GPT and BERT-based models on identifying protein-protein interactions in biomedical text

arXiv

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arXiv 2023年

作者： Rehana, Hasin Çam, Nur Bengisu Basmaci, Mert Zheng, Jie Jemiyo, Christianah He, Yongqun Özgür, Arzucan Hur, Junguk Computer Science Graduate Program University of North Dakota Grand ForksND58202 United States Department of Computer Engineering Bogazici University Istanbul34342 Turkey Unit for Laboratory Animal Medicine Department of Microbiology and Immunology University of Michigan Ann ArborMI48109 United States Department of Biomedical Sciences University of North Dakota School of Medicine and Health Sciences Grand ForksND58202 United States Center for Computational Medicine and Bioinformatics University of Michigan Ann ArborMI48109 United States

Detecting protein-protein interactions (PPIs) is crucial for understanding genetic mechanisms, disease pathogenesis, and drug design. However, with the fast-paced growth of biomedical literature, there is a growing need for automated and accurate extraction of PPIs to facilitate scientific knowledge discovery. Pre-trained language models, such as generative pre-trained transformers (GPT) and bidirectional encoder representations from transformers (BERT), have shown promising results in natural language processing (NLP) tasks. We evaluated the performance of PPI identification of multiple GPT and BERT models using three manually curated gold-standard corpora: Learning Language in Logic (LLL) with 164 PPIs in 77 sentences, Human Protein Reference Database with 163 PPIs in 145 sentences, and Interaction Extraction Performance Assessment with 335 PPIs in 486 sentences. BERT-based models achieved the best overall performance, with BioBERT achieving the highest recall (91.95%) and F1-score (86.84%) and PubMedBERT achieving the highest precision (85.25%). Interestingly, despite not being explicitly trained for biomedical texts, GPT-4 achieved commendable performance, comparable to the top-performing BERT models. It achieved a precision of 88.37%, a recall of 85.14%, and an F1-score of 86.49% on the LLL dataset. These results suggest that GPT models can effectively detect PPIs from text data, offering promising avenues for application in biomedical literature mining. Further research could explore how these models might be fine-tuned for even more specialized tasks within the biomedical domain. © 2023, CC BY.

关键词： Extraction

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RHC: A Dataset for In-Room and Out-Room Human Counting

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Procedia Computer Science 2021年 179卷 33-39页

作者： Bens Pardamean Hery Harjono Muljo Faizal Abid Herman Albert Susanto Tjeng Wawan Cenggoro Computer Science Department BINUS Graduate Program - Master of Computer Science Program Bina Nusantara University Jakarta Indonesia 11480 Bioinformatics and Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 Accounting Information Systems Program Information Systems Department School of Information Systems Bina Nusantara University Jakarta Indonesia 11480 Computer Science Department School of Computer Science Bina Nusantara University Jakarta Indonesia 11480

In recent years, research in human counting from CCTV (Closed Circuit Television) images have found an increasing demand to be deployed in real-world applications. The applications have been implemented in various settings, both indoor and outdoor. In the case of indoor setting, we found a type of room setting that conveys a problem to human counting model if we need to count only humans inside a room. With this respect, we present RHC (Room Human Counting) dataset, which images are captured in the aforementioned setting. The dataset can be used to develop a robust model that can differentiate between humans inside and outside a room. The dataset is publicly available at https://***/datasets/vt5c8h6kmh/1.

关键词： dataset human counting crowd counting in-room out-room

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Mrf-Former: A Multi-Scale Resolution Fusion Approach for Addressing Scale Discrepancies in Remote Sensing Image Change Detection

SSRN

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SSRN 2024年

作者： Yang, Hualin Ouyang, Jiarui Cheng, Junhao Zhang, Wen Li, Hui Li, Xiying Chen, Calvin Yu-Chian Artificial Intelligence Medical Research Center School of Intelligent Systems Engineering Shenzhen Campus of Sun Yat-sen University Guangdong Shenzhen518107 China - Preferred Program Peking University Shenzhen Graduate School Guangdong Shenzhen518055 China School of Electronic and Computer Engineering Peking University Shenzhen Graduate School Guangdong Shenzhen518055 China Department of Medical Research China Medical University Hospital Taichung40447 Taiwan Department of Bioinformatics and Medical Engineering Asia University Taichung41354 Taiwan Guangdong Provincial Key Laboratory of Intelligent Transportation System Sun Yat-sen University Guangzhou China School of Intelligent Systems Engineering Sun Yat-sen University Guangdong Shenzhen518107 China Institute of Artificial Intelligence Guangzhou University Guangzhou China

Dealing with resolution variations in dual-temporal remote sensing images is challenging due to differences in sensor capabilities, altitudes, footprints, resampling, and data fusion. Conventional methods for different-resolution change detection struggle to effectively address these challenges, primarily due to insufficient consideration of global and local feature interactions. In this paper, we propose a novel change detection model that leverages the power of multi-scale resolution fusion(MRF). By incorporating the MRF-Block, our approach extracts hierarchical multi-scale features from the input data, enabling effective capture of contextual information at various granularities. This facilitates improved handling of resolution disparities and promotes interactions between global and local features. Experimental evaluations conducted on diverse datasets, demonstrate the effectiveness of our proposed model in achieving accurate change detection in dual-temporal remote sensing imagery, even in scenarios characterized by varying resolutions. Code is available on-line at https://***/yanghl1914/MRF-Former. © 2024, The Authors. All rights reserved.

关键词： Remote sensing

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Meteorological parameters for PV installations in Indonesia

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AIP Conference Proceedings 2024年第1期3026卷

作者： Joko Pebrianto Trinugroho Alam Ahmad Hidayat Reza Rahutomo Bens Pardamean Bioinformatics & Data Science Research Center Bina Nusantara University Jakarta Indonesia 11480 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

Many countries are still dependent on fossil fuels as their primary energy supply. However, there is a growing concern about the sustainability and the environmental issue of fossil fuels. Therefore, it is important to utilize renewable resources as the energy supply, such as solar energy. As a country with a tropical climate, Indonesia has a great potential to use solar energy, due to the abundance of sunlight exposure. The present study aims to analyze several meteorological parameters for the installation of photovoltaic (PV) technology in Jakarta, Indonesia. The meteorological data provided by the Ministry of Environment and Forestry, Indonesia from 2008-2021 were used at three different locations in Jakarta. Data visualizations were used to show the difference between each variable in different locations. In addition, the statistical difference between the variables in the three locations was also examined using the Mann-Whitney U test. The test shows that all parameters are evenly distributed in the three locations except for a moderate difference in air temperature in the two locations. Furthermore, the monthly analysis of the parameters also indicates that the dry season, especially from August to September, would be the optimal time to utilize PV technology. Hence, this study would be useful to give preliminary insight regarding a site-specified assessment of PV plants in Jakarta based on local meteorological data.

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