Pemodelan dan simulasi kinematika robot swerve 4 roda by Indrazno Siradjuddin, Sapto Wibowo, Arta Ainur Rofiq

“…Movement of the robot not only determines the start and end coordinates, but also determines the speed of each motor needed to reach the desired position. In this research, the development kinematic control algorithm to control movement of 4-wheel swerve robot. …”
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Application of Concentration-Area fractal modeling and artificial neural network to identify Cu, Zn±Pb geochemical anomalies in Hashtjin area, NW of Iran by Ali Imamalipour, Hamed Ebrahimi, Amir reza Abdollahpur

“…Identification of geochemical anomalies plays an essential role in mineral exploration. Recent research investigations have shown that Machine Learning (ML) algorithms can identify geochemical anomalies associated with mineralization that represent targets for mineral exploration. …”
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Rice seed integrity evaluation: Developing a rapid onsite system to check seed fraud using a portable NIR spectroscopic device coupled with smartphone technology by Ernest Teye, Charles Lloyd Yeboah Amuah, Vida Gyimah Boadu, Kwadwo Anokye Dompreh, Maxwell Darko Asante, Francis Padi Lamptey, Stephen Narh, Daniel Dzorkpe Gamenyah, George Oduro Nkansah, Selorm Akaba

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Selection of suitable reference lncRNAs for gene expression analysis in Osmanthus fragrans under abiotic stresses, hormone treatments, and metal ion treatments by Yingting Zhang, Yingting Zhang, Qingyu Yan, Hui Xia, Xiangling Zeng, Xiangling Zeng, Xiangling Zeng, Jie Yang, Jie Yang, Jie Yang, Xuan Cai, Xuan Cai, Xuan Cai, Zeqing Li, Zeqing Li, Hongguo Chen, Hongguo Chen, Hongguo Chen, Jingjing Zou, Jingjing Zou, Jingjing Zou

“…Despite its importance, research on long non-coding RNAs (lncRNAs) in O. fragrans has been constrained by the absence of reliable reference genes (RGs).MethodsWe employed five distinct algorithms, i.e., delta-Ct, NormFinder, geNorm, BestKeeper, and RefFinder, to evaluate the expression stability of 17 candidate RGs across various experimental conditions.Results and discussionThe results indicated the most stable RG combinations under different conditions as follows: cold stress: lnc00249739 and lnc00042194; drought stress: lnc00042194 and lnc00174850; salt stress: lnc00239991 and lnc00042194; abiotic stress: lnc00239991, lnc00042194, lnc00067193, and lnc00265419; ABA treatment: lnc00239991 and 18S; MeJA treatment: lnc00265419 and lnc00249739; ethephon treatment: lnc00229717 and lnc00044331; hormone treatments: lnc00265419 and lnc00239991; Al3+ treatment: lnc00087780 and lnc00265419; Cu2+ treatment: lnc00067193 and 18S; Fe2+ treatment: lnc00229717 and ACT7; metal ion treatment: lnc00239991 and lnc00067193; flowering stage: lnc00229717 and RAN1; different tissues: lnc00239991, lnc00042194, lnc00067193, TUA5, UBQ4, and RAN1; and across all samples: lnc00239991, lnc00042194, lnc00265419 and UBQ4. …”
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Leveraging AI for early cholera detection and response: transforming public health surveillance in Nigeria by Adamu Muhammad Ibrahim, Mohamed Mustaf Ahmed, Shuaibu Saidu Musa, Usman Abubakar Haruna, Mohammed Raihanatu Hamid, Olalekan John Okesanya, Aishat Muhammad Saleh, Don Eliso Lucero-Prisno III

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Identification of Nicotinic Acetylcholine Receptor for N‐Acetylcysteine to Rescue Nicotine‐induced Injury Using Beating Cilia in Primary Tissue Derived Airway Organoids by Yichao Zheng, Qinyong Tian, Haowei Yang, Yongde Cai, Jiaxin Zhang, Yifen Wu, Shuo Zhu, Zuocheng Qiu, Yimin Lin, Jiangquan Hong, Yi Zhang, David Dockrell, Shaohua Ma

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A deep learning model for predicting systemic lupus erythematosus-associated epitopes by Jiale He, Zixia Liu, Xiaopo Tang

“…Traditional bioinformatics methods often struggle to capture the intricate sequence patterns and high-dimensional signals characteristic of epitope data. …”
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PREDICTION INTERVALS IN MACHINE LEARNING: RESIDUAL BOOTSTRAP AND QUANTILE REGRESSION FOR CASH FLOW ANALYSIS by Wa Ode Rahmalia Safitri, Farit Mochamad Afendi, Budi Susetyo

“…This study implements multivariate time series forecasting using gradient boosting algorithms (XGBoost, CatBoost, and LightGBM) to predict cash flow patterns in banking transactions, focusing on constructing reliable prediction intervals. …”
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Innovative approach for gauge-based QPE in arid climates: comparing neural networks and traditional methods by Bayan Banimfreg, Ernesto Damiani, Vesta Afzali Gorooh, Duncan Axisa, Luca Delle Monache, Youssef Wehbe

“…Abstract Background In the hyper-arid environment of the United Arab Emirates (UAE), understanding rainfall patterns is essential for effective water resource management, agricultural planning, and ecological conservation. …”
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iMESc – an interactive machine learning app for environmental sciences by Danilo Cândido Vieira, Danilo Cândido Vieira, Fabiana S. Paula, Luciana Erika Yaginuma, Gustavo Fonseca

“…IMESc permits the customization of plots and saving the workflows into “savepoints” guarantying reproducibility. iMESc bridges the gap between the complexity of machine learning algorithms and the need for user-friendly interfaces in environmental research. …”
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Artificial Intelligence in cancer epigenomics: a review on advances in pan-cancer detection and precision medicine by Karishma Sahoo, Prakash Lingasamy, Masuma Khatun, Sajitha Lulu Sudhakaran, Andres Salumets, Vino Sundararajan, Vijayachitra Modhukur

“…Aberrant methylation patterns enable early cancer detection and therapeutic stratification; however, their complex patterns necessitates advanced analytical tools. …”
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Enhancing Transpiration Estimates: A Novel Approach Using SIF Partitioning and the TL-LUE Model by Tewekel Melese Gemechu, Baozhang Chen, Huifang Zhang, Junjun Fang, Adil Dilawar

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Distributed Acoustic Sensing of Sounds in Audible Spectrum in Realistic Optical Cable Infrastructure by Petr Dejdar, Ondrej Mokry, Petr Munster, Tomas Horvath, Jiri Schimmel

“…This study presents a dataset comprising acoustic vibration patterns recorded by a commercial DAS system, providing valuable insights into the acoustic sensitivity of optical fibers. …”
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Recent developments of artificial intelligence methods for sea ice concentration monitoring using high-resolution imaging datasets by Marzuraikah Mohd Stofa, Siti Raihanah Abdani, Asraf Mohamed Moubark, Muhammad Ammirrul Atiqi Mohd Zainuri, Ahmad Asrul Ibrahim, Nor Azwan Mohamed Kamari, Mohd Asyraf Zulkifley

“…Comprehensive discussions of the aforementioned topics, including the main findings and patterns, are provided to stimulate future research.…”
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A novel smart surveillance approach to strengthen health facility-based disease surveillance in Tanzania by Ms Happy Mkali, MD Alix Miauton, Dr. Alexandra Kulinkina, Ms. Magreth Joram, MD Caroline Enos, Mr. Lazar Pavicevic, Mr. Vincent Faivre, Dr. MD Rainer Tan, Dr. Sabine Renggli, Ms. Theopista Lotto, Mr. Sinamgoda Ngailla, MD Godfrey Kavishe, Mr. Ibrahim Mtebene, Mr. Peter Agrea, MD Lameck Luwanda, Mr Geofrey Ashery, MD Chacha Mangu, Dr. MD Nyanda Ntinginya, Prof. Dr. Honorati Masanja, Prof. Dr. MD Isabella Eckerle, Prof. Dr. MD Valerie D'Acremont

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Gait-Based AI Models for Detecting Sarcopenia and Cognitive Decline Using Sensor Fusion by Rocío Aznar-Gimeno, Jose Luis Perez-Lasierra, Pablo Pérez-Lázaro, Irene Bosque-López, Marina Azpíroz-Puente, Pilar Salvo-Ibáñez, Martin Morita-Hernandez, Ana Caren Hernández-Ruiz, Antonio Gómez-Bernal, María de la Vega Rodrigalvarez-Chamarro, José-Víctor Alfaro-Santafé, Rafael del Hoyo-Alonso, Javier Alfaro-Santafé

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Developing a molecular diagnostic model for heatstroke-induced coagulopathy: a proteomics and metabolomics approach by Qingbo Zeng, Qingwei Lin, Longping He, Lincui Zhong, Ye Zhou, Xingping Deng, Nianqing Zhang, Qing Song, Qing Song, Jingchun Song, Jingchun Song

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Exploring the Global and Regional Factors Influencing the Density of <i>Trachurus japonicus</i> in the South China Sea by Mingshuai Sun, Yaquan Li, Zuozhi Chen, Youwei Xu, Yutao Yang, Yan Zhang, Yalan Peng, Haoda Zhou

“…In this cross-disciplinary investigation, we uncover a suite of previously unexamined factors and their intricate interplay that hold causal relationships with the distribution of <i>Trachurus japonicus</i> in the northern reaches of the South China Sea, thereby extending the existing research paradigms. Leveraging advanced machine learning algorithms and causal inference, our robust experimental design uncovered nine key global and regional factors affecting the distribution of <i>T. japonicus</i> density. …”
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TOM40 as a prognostic oncogene for oral squamous cell carcinoma prognosis by Lifei Deng, Hong Ran, Dunhui Yang, Zhen Wang, Peng Zhao, Hengjie Huang, Yongjin Wu, Peng Zhang

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Understanding discrepancies in soil moisture from SMAP and AMSR2: insights into performance and dry-down behavior by Zhiqing Peng, Tianjie Zhao, Jiancheng Shi, Lu Hu, Thomas J. Jackson, Michael H. Cosh, Hui Lu, Xiaodong Gao, Jingyao Zheng, Panpan Yao, Qian Cui, Peng Guo, Peilin Song, Zushuai Wei, Mengjia Wang, Anmin Fu

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