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Molecular surveillance of bat flies (Diptera: Nycteribiidae and Streblidae) and other ectoparasites in Ratchaburi, Thailand: Unraveling host associations and coronavirus transmission dynamics in the context of zoonotic spillover risk

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Journal of Infection and Public Health 2025年第7期18卷 102792-102792页

作者： Phumee, Atchara Rattanatumhi, Khwankamon Putcharoen, Opass Chitcharoen, Suwalak Sutthanont, Nataya Suwanbamrung, Charuai Pataradool, Thanapat Boonserm, Rungfar Sunantaraporn, Sakone Savigamin, Chatuthanai Schmidt-Chanasit, Jonas Siriyasatien, Padet Department of Medical Technology School of Allied Health Sciences Walailak University Nakhon Si Thammarat Thailand Excellent Center for Public Health Research: EC for PHR Walailak University Nakhon Si Thammarat Thailand Thai Red Cross Emerging Infectious Diseases Clinical Centre King Chulalongkorn Memorial Hospital Faculty of Medicine Chulalongkorn University Bangkok Thailand Department of Medicine Faculty of Medicine Chulalongkorn University Bangkok Thailand Department of Microbiology Faculty of Medicine Khon Kaen University Khon Kaen Thailand Department of Medical Entomology Faculty of Tropical Medicine Mahidol University Bangkok Thailand Public Health Research Program School of Public Health Walailak University Nakhon Si Thammarat Thailand Center of Excellence in Vector Biology and Vector Borne Diseases Department of Parasitology Faculty of Medicine Chulalongkorn University Bangkok Thailand Johns Hopkins Bloomberg School of Public Health Baltimore United States Bernhard-Nocht-Institute for Tropical Medicine Hamburg Germany Faculty of Mathematics Informatics and Natural Sciences University of Hamburg Hamburg Germany

Background: Bats act as hosts for various ectoparasites, including bat flies, bugs, fleas, ticks, and mites, which play crucial roles in the transmission of bat-borne pathogens. As obligate blood-feeding parasites, these ectoparasites can serve as direct vectors or indirectly influence pathogen dynamics in bat populations. In Thailand, molecular studies on bat ectoparasites are limited, with scarce data on their diversity, distribution, and role in zoonotic pathogen transmission. This study aims to provide the first molecular characterization of bat flies and other ectoparasites in Ratchaburi, Thailand, focusing on their blood meals and potential involvement in coronavirus transmission. Methods: Ectoparasites were identified using the cytochrome oxidase I (COI) gene, while host blood meals were confirmed using the cytochrome b (CytB) gene. A total of 37 bat flies and additional ectoparasites (ticks and flea) were analyzed. Coronavirus screening was conducted through targeted amplification of the RNA-dependent RNA polymerase (RdRp) gene, followed by sequencing and phylogenetic analysis of positive samples. Results: Three bat fly genera were identified: Nycteribia sp. (20), Phthiridium sp. (15), and Raymondia sp. (2). Blood meal analysis indicated host associations with Rhinolophus coelophyllus for Nycteribia sp., R. pusillus and Chaerephon plicatus for Phthiridium sp., and R. pusillus for Raymondia sp. Additionally, two Ixodes sp. ticks and one Hystrichopsylla sp. flea were found, all associated with C. plicatus. Coronavirus screening identified positive samples, with sequencing revealing alphacoronaviruses and betacoronaviruses. Conclusions: This study highlights the importance of molecular tools in characterizing ectoparasites, their blood meal sources, and associated pathogens. It underscores the potential of ectoparasites as non-invasive tools for coronavirus detection in bats, addressing knowledge gaps and contributing to public health strategies for mitigating

关键词： Bat fly Blood meal Coronaviruses Ectoparasites Thailand

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Predicting Potential Fires in Indonesia by Analyzing VIIRS Night Data during 2018 – 2022

Predicting Potential Fires in Indonesia by Analyzing VIIRS N...

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International Symposium on Grids and Clouds 2023 in conjunction with HEPiX Spring Workshop, ISGC and HEPiX 2023

作者： Suhardiman, Basuki Hermanto, Benni Rio Directorate of Information Technology Institut Teknologi Bandung Jl Ganesha 10 Bandung Indonesia Master’s Program in Computational Science Faculty of Mathematics and Natural Sciences Institut Teknologi Bandung Jl Ganesha 10 Bandung Indonesia Biomedical Engineering Department School of Electrical Engineering and Informatics Institut Teknologi Bandung Indonesia

Forest fires have been detected to occur in Indonesia since 1998. The forest fires mostly resulted from human activities in order to expand their land, especially oil palm lands. Once a land clearing is carried out, it covers areas of tens to hundreds of thousands of hectares. The peak of the forest fires occurred in 2015 when almost half of the world was affected especially by smoke from the fire. In 2011, VIIRS (Visible Infrared Imaging Radiometer Suite) was launched by NOAA (National Oceanic and Atmospheric Administration). In their collected data, there is data on Indonesia issued daily for areas in the islands of Java, Sumatra, Kalimantan, Sulawesi, and the general areas of Indonesia. The VIIRS night data shows the possibility of some burning at night. We need to identify burnings that potentially become fires, which are potentially producing smoke. It is important to observe areas where large-scale forest fires frequently occur, so the authority could do some prevention beforehand. Using existing data released per day per area, we utilize an ANN (Artificial Neural Network) to identify a potential fire. The processes start with data cleaning and processing, Neural Network creation, and finally ANN training and testing. By using the ANN prediction model with the MinMax Scaler, we choose variables Temperature, Radiant Heat Intensity, and Source Footprint. Simulations are made to show the ranges of these variables that predict the possibility of’flame’ status occurring. We conclude that the ANN method can give more accurate results than the existing classification. © Copyright owned by the author(s) under the terms of the Creative Commons.

关键词： Fires

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An application program of fingerprint detection using wavelet transform for authentication 3

An application program of fingerprint detection using wavele...

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3rd Management and Innovation Technology International Conference, MITiCON 2016

作者： Kwaochai, Aunchisa Pongyupinpanich, Surapong Areekul, Pratya San-Um, Wimol Intelligent Electronic System Research Laboratory Faculty of Engineering Thai-Nichi Institute of Technology Pattanakarn 37 Saunlaung Bangkok10250 Thailand Master Program of Forensic Informatics Ramkhamhang University Bangkapi Bangkok10240 Thailand Department of Mathematics Computer Science Chulachomklao Royal Military Academy Province Nakornnayok26001 Thailand

ISBN: (纸本)9781509041053

This paper presents the application program of fingerprint detection using wavelet transform for authentication. Fingerprints are obtained from the site of crime, old documents and excavated things. This paper proposes a fingerprint recognition technique based on wavelet-based texture pattern recognition method. By collecting incomplete fingerprints of 2 people with 6 images each. The original seven of uncompleted fingerprint images were undetected and only one was detected. After enhancing image quality using wavelet transform method, it was found that those of seven images were completed. The comparison method was a matching technique. This work focuses on the ability of the program and knowledge of image processing by studying algorithms of image processing. In design algorithm process, different technique enhancements were employed as well as the study of different of filters and algorithms based on existing research results from literature. © 2016 IEEE.

关键词： Wavelet transforms

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Exploring the Impact of Age and Gender on Multi-Device Usage Patterns in Online Education

Exploring the Impact of Age and Gender on Multi-Device Usage...

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International Conference on informatics and Computational Sciences (ICICoS)

作者： Dewi Arianti Wulandari Tri Retnaningsih Soeprobowati Dinar Mutiara Kusumo Nugraheni Doctoral Program Of Information System Diponegoro University Semarang Indonesia Department of Biology Faculty of Science of Mathematics Diponegoro University Semarang Indonesia Department of Informatics Faculty of Science and Mathematics Diponegoro University Semarang Indonesia

ISBN: (数字)9798350375886

ISBN: (纸本)9798350375893

Using digital literacy in the educational environment can make students more responsible and wiser in using and accessing technology. To find out how prepared the educational environment is in facing this digital era a study that aimed to determine whether there is a correlation between age and gender factors with the number of devices used in the online learning process was conducted at one of the private universities in West Jakarta. The results of this study can contribute to the model developments in both online and offline learning processes to increase student motivation. The data collection method used is qualitative with primary data from survey results, using non-probability sampling, and descriptive analysis. The sample of this study was students at that university with a total of 310 students. Based on the test results using the two-way ANOVA test on the SPSS tool, the result is 0.055. This value is above the significance value requirement of 0.05. The age and gender do not significantly affect device usage, with a Sig value of $\gt0.05$, and the simultaneous relationship between age and gender does not affect device usage. It can be concluded that digital literacy has been applied in that university which can be proven from the test results that 225 students out of 310 or $\mathbf{72.5 \%}$ use more than one device in online learning activities.

关键词： Surveys Portable computers Data analysis Social networking (online) Education Data collection Mobile handsets

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Properties of the mixing layer height retrieved from ceilometer measurements in Slovakia and its relationship to the air pollutant concentrations

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Environmental Science and Pollution Research 2023年第54期30卷 115666-115682页

作者： Nguyen, Duy-Hieu Štefánik, Dušan Šedivá, Tereza Lin, Chitsan Ph.D. Program in Maritime Science and Technology College of Maritime National Kaohsiung University of Science and Technology Kaohsiung811213 Taiwan Slovak Hydrometeorological Institute Jeséniova 17 Bratislava833 15 Slovakia Faculty of Mathematics Physics and Informatics Comenius University in Bratislava Mlynská Dolina F1 Bratislava842 48 Slovakia Department of Marine Environmental Engineering National Kaohsiung University of Science and Technology Kaohsiung811213 Taiwan

Mixing layer height (MLH) is an important meteorological parameter for air quality since it significantly affects ground-level pollution in the atmosphere. This study examined the properties of the MLH on diurnal and seasonal timescales over a 3-year period (2020–2022) using high temporal resolution measurements from eight Vaisala CL31 ceilometers situated around Slovakia. Hourly averaged MLH data was retrieved from the BL-View software using merged method. The highest daily maxima for the MLH occurred mostly in summer and spring, while the lowest values occurred predominantly during winter and autumn. The average MLH daily maximum in summer was 2229 m, and just 859 m in winter. During summer, the spatial distribution of the MLH daily maxima was more uniform compared to winter, when the air masses within the individual valleys did not mix well. Correlations between ground-level pollutant concentrations and hourly mean/daily mean MLH were analyzed. The highest correlation, R≈0.6, was found for O3. For PM10, PM2.5, and NOx, the anticorrelations with MLH were found with maximum in winter (R ≈ − 0.3 for hourly data and R ≈ − 0.5 for daily mean data) but no relation in summer. Lastly, the ceilometer MLH was compared to the radiosonde retrieved MLH for various cloud covers. Our analysis is based on an extensive set of empirical data, which can improve the accuracy and effectiveness of meteorological and atmospheric chemistry models. The findings can support air pollution forecasting and warning systems, providing valuable insights for policymakers and researchers. © 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Air quality

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Structural Effects and Aggregation in a Social-Network Model of Natural Resource Consumption

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IFAC-PapersOnLine 2017年第1期50卷 7675-7680页

作者： Manzoor T. Rovenskaya E. Muhammad A. Department of Electrical Engineering Lahore University of Management Sciences (LUMS) Lahore Pakistan Center for Water Informatics & Technology (WIT) Lahore University of Management Sciences (LUMS) Pakistan Advanced Systems Analysis Program International Institute for Applied Systems Analysis (IIASA) Laxenburg Austria Faculty of Computational Mathematics and Cybernetics Lomonosov Moscow State University Moscow Russian Federation

In this paper we consider a networked system of natural-resource consumption, where the agents are governed by a recently reported model of consumer psychology Dynamics of the consumption for each agent are influenced by the state of the resource and consumption of her neighbors. The process is parameterized by the psychological characteristics of each agent. This study extends the original model to incorporate the underlying network topology and explores the effects of aggregation via densely-connected communities present in the network. The exercise yields new interpretations of the predictions made by the original model in context of the influence network. We present aggregation mechanisms first for certain canonical structures of the consuming population and later on for a class of non-canonically structured populations. In the end we present an approximate aggregation scheme for populations where only some inaccurate information of the consumer characteristics is available. © 2017

关键词： Control in economics identification of environmental systems Modeling Multi-agent systems Natural resources management Social Networks

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Amniotic fluid segmentation based on pixel classification using local window information and distance angle pixel

Amniotic fluid segmentation based on pixel classification us...

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作者： Ayu, Putu Desiana Wulaning Hartati, Sri Musdholifah, Aina Nurdiati, Detty S. Doctoral Program Department of Computer Science and Electronics Faculty of Mathematics and Natural Science Universitas Gadjah Mada Yogyakarta Indonesia Department of Computer Science and Electronics Faculty of Mathematics and Natural Sciences Universitas Gadjah Mada Yogyakarta Indonesia Department of Obstetrics and Gynecology Faculty of Medicine Universitas Gadjah Mada Yogyakarta Indonesia Department of Information Technology Faculty Computer and Informatics Institut Teknologi dan Bisnis STIKOM Bali Denpasar Indonesia

The amniotic fluid surrounds and protects the fetus from colliding with one another during the uterus development process. It also protects the umbilical cord from the uterine wall pressure, helps fetus movement, and develops muscles and bones. Selection of the most profound areas of improper and withdrawal points are not straight caliper is very likely that affect the outcome screening. Furthermore, there are similarities in texture and gray level between objects, especially in the boundary area between amniotic fluid and other objects, such as the placenta and uterus, which causes the border area to be less clear. Therefore, this research proposes a novel pixel classification model to separate amniotic fluid from other objects with a limit on the specified window size to solve this issue. In contrast to the most existing semantic segmentation methods or pixel-wise classification, we use the sampling window technique to construct train sets of data to produce pixel-level information more specifically in certain areas. Furthermore, each window extracts pixel information on gray level features and local variance (GLLV), using a novel Distance Angle Pixel (DAP). To evaluate the proposed model performance, we perform an extensive comparison with state-of-art methods by testing it on amniotic fluid ultrasound images. The results showed that the proposed model with a 3 × 3 window and random forest classifier could achieve the best value using an average Dice similarity coefficient (DSC) of 0.876, Jaccard/IoU of 0.768, and Pixel accuracy of 85.7%. The proposed model has 0.324 DSC improved from U-Net, 0.046 from gray-level pixel classification, 0.092 from thresholding, 0,252 from active contour, and 0.19 from rectangle window sampling. © 2021

关键词： Pixels

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Intelligent Traffic Management System using Internet of Things: A Systematic Literature Review

Intelligent Traffic Management System using Internet of Thin...

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International Conference on Computing, Engineering, and Design (ICCED)

作者： Hendra Marcos Rahmat Gernowo Isnaini Rosyida Oky Dwi Nurhayati Doctoral Program of Information System School of Postgraduate Studies Diponegoro University Semarang Indonesia Department of Informatics Universitas Amikom Purwokerto Department of Mathematics Faculty of Mathematics and Natural Sciences Universitas Negeri Semarang Semarang Indonesia

ISBN: (纸本)9781665453905

The number of vehicles on the road will continue to expand as cities worldwide grow in population. This increases transportation congestion, especially in major cities and especially during rush hour. This phenomenon continuously pushes academics, city authorities, and urban planners to enhance traffic control systems for safety and efficiency. The application of Internet of Things (IoT) in the field of intelligent transportation systems is getting the attention of many parties. A well-controlled transportation management system can reduce congestion, especially at intersections and roads. This study was conducted to observe and study the development of research in transportation management, especially the use of IoT technology. There are 743 documents according to the keywords given related to IMS and ITS, the period 2012 until September 2021. Mapping of these articles, both in terms of publishers, the relationship between authors, and the methods used from keywords, abstracts, and titles, is expected to help the author determine research gaps and future research directions.

关键词： Systematics Roads Bibliographies Urban areas Sociology Transportation Traffic control

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Discoffery: A Coffee Types Detection Apps using an EfficienNet-Lite Architecture 7

Discoffery: A Coffee Types Detection Apps using an EfficienN...

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7th International Conference on Sustainable Information Engineering and Technology, SIET 2022

作者： Budiman, Satrio Arif Pramono, Andi Priyambadha, Bayu Putri, Annisa Maharani Arya Purnomo, Agung Nugroho, Ilham Setyo Information System Computer Science Faculty University of Brawijaya Malang65145 Indonesia Interior Design Department School of Design Bina Nusantara University Jakarta11480 Indonesia Department of Informatics Computer Science Faculty Brawijaya University Malang65145 Indonesia Department of Mathematics Faculty of Mathematics and Natural Sciences Brawijaya University Malang65145 Indonesia Entrepreneurship Department BINUS Business School Undergraduate Program Bina Nusantara University Jakarta11480 Indonesia

ISBN: (纸本)9781450397117

According to data from the World Food and Agriculture Organization (FAO), Indonesia produced the fourth-most coffee in the world in 2017 and 2018. Gayo, Robusta Dampit, and Toraja coffees are only a few well-known coffee varieties Indonesian growers produce. This research aims to create an app that can identify the type of coffee and serve as a coffee-related educational tool. A single case study was the research methodology used. By employing the EfficienNet-Lite architecture for transfer learning, a model for categorizing coffee beans is created. Users can get information through the photographs they submit with the help of the type of application development that uses deep learning to do categorization based on image data of coffee bean types. The coffee bean classification feature was built using transfer learning with the EfficientNet architecture. A training accuracy of 87% and a validation accuracy of 81% were achieved using the EfficientNet-Lite 0 architecture. © 2022 ACM.

关键词： Deep learning

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Effect of feedback on learning motivation of primary teacher education students in primary school physics courses 10

Effect of feedback on learning motivation of primary teacher...

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10th National Physics Seminar, SNF 2021

作者： Sianipar, L.K. Sitompul, H. Sanjaya, L.A. Puspa, R.W.D. Pertiwi, W.A. Qoiriyah, W. Department of Physics Education Universitas Pelita Harapan Tangerang15811 Indonesia Department of Physics Faculty of Mathematics and Natural Science Universitas Negeri Jakarta Indonesia Kartika VIII-1 Senior High School Jakarta Indonesia Islamic Education Management Study Program Faculty Islamic of Education and Teacher Training Muhammad Azim Institute Jambi Indonesia Informatics Engineering Study Program Faculty of Engineering Sheikh Yusuf Islamic University Tangerang Indonesia

Based on the results of the questionnaire distributed to Primary Teacher Education Students, 96% of students said that Physics is difficult to understand because the material is very complex, many formulas, especially the learning process is done online. This study aims to describe the influence of providing feedback on the motivation of Primary Teacher Education Students in primary school physics courses. The method used in this research is descriptive qualitative. Meanwhile, the instrument used was a questionnaire which was distributed to 115 elementary school education students. The result of the research shows that giving feedback consistently is able to motivate students. This can be seen from the results of the questionnaires distributed, each indicator is of very good value. © 2021 Institute of Physics Publishing. All rights reserved.

关键词： Students

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