Releasing the octoPus, an open-source digital tool to promote Integrated Pest Management by Simone Bregaglio, Eugenio Rossi, Lorenzo Ascari, Gabriele Mongiano, Eleonora Del Cavallo, Sofia Bajocco, Luisa Maria Manici, Antonio Gerardo Pepe, Chiara Bassi, Rocchina Tiso, Fabio Pietrangeli, Giovanna Cattaneo, Camilla Nigro, Marco Secondo Gerardi, Simone Bussotti, Angela Sanchioni, Danilo Tognetti, Mariangela Sandra, Irene De Lillo, Paolo Framarin, Sandra Di Ferdinando, Riccardo Bugiani

“…However, they consistently identified a moisture and thermal north-south suitability gradient in Italy, accurately detecting grapevine seasons with low or high downy mildew pressure. …”
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Hepatitis E virus genotypes and subgenotypes causing acute hepatitis, Bulgaria, 2013-2015. by Roberto Bruni, Umbertina Villano, Michele Equestre, Paola Chionne, Elisabetta Madonna, Dilyana Trandeva-Bankova, Maria Peleva-Pishmisheva, Tencho Tenev, Eleonora Cella, Massimo Ciccozzi, Giulio Pisani, Elitsa Golkocheva-Markova, Anna Rita Ciccaglione

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exoALMA. IX. Regularized Maximum Likelihood Imaging of Non-Keplerian Features by Brianna Zawadzki, Ian Czekala, Maria Galloway-Sprietsma, Jaehan Bae, Marcelo Barraza-Alfaro, Myriam Benisty, Gianni Cataldi, Pietro Curone, Stefano Facchini, Daniele Fasano, Mario Flock, Misato Fukagawa, Himanshi Garg, Cassandra Hall, Thomas Hilder, Jane Huang, John D. Ilee, Andrea Isella, Andrés F. Izquierdo, Kazuhiro Kanagawa, Geoffroy Lesur, Cristiano Longarini, Ryan A. Loomis, Ryuta Orihara, Christophe Pinte, Daniel J. Price, Giovanni Rosotti, Jochen Stadler, Richard Teague, Hsi-Wei Yen, Gaylor Wafflard-Fernandez, David J. Wilner, Andrew J. Winter, Lisa Wölfer, Tomohiro C. Yoshida

“…The exoALMA collaboration employed two different imaging procedures to ensure the consistent detection of NKFs: CLEAN, the standard iterative deconvolution algorithm, and regularized maximum likelihood (RML) imaging. …”
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Spatiotemporal variation of the association between climate dynamics and HFRS outbreaks in Eastern China during 2005-2016 and its geographic determinants. by Junyu He, George Christakos, Jiaping Wu, Bernard Cazelles, Quan Qian, Di Mu, Yong Wang, Wenwu Yin, Wenyi Zhang

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Evaluation of Time-Domain Acoustic Signature in TIG Welding of 5083 Aluminum Alloy: A Methodological Comparison of Feature Reduction Approaches by V M Gautham, A Sumesh, E V Jithin, K Rameshkumar, Dinu Thomas Thekkuden

“…In this scenario, condition monitoring of the weld using machine learning algorithms is a remedy to detect the defects instantly. …”
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An Efficient Analytical Method for Determining the Effects of Silver Nanoparticles on Vibrio parahaemolyticus in Estuarine Water by Xiangyi HOU, Xiaoyang WANG, Yuanyuan ZHANG, Ruohan LIANG, Feng LU, Qianqian YANG, Xiaodan PU, Yan ZHANG, Keming QU, Xuzhi ZHANG

“…Based on a 32-channel C4 detector and special algorithms, we developed a 32-channel electronic microbial growth analyzer (EMGA). …”
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Machine learning for improved size estimation of complex marine particles from noisy holographic images by Zonghua Liu, Zonghua Liu, Marika Takeuchi, Yéssica Contreras, Thangavel Thevar, Alex Nimmo-Smith, John Watson, Sarah L. C. Giering

“…However, most standard algorithms fail to accurately size objects in reconstructed holograms owing to the high background noise. …”
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Liquid biopsy-derived extracellular vesicle protein biomarkers for diagnosis and prognostic assessment of lung squamous cell carcinoma by Sheng Ma, Na Zhao, Xin Dong, Yaru Wang, Lei Song, Ruiqi Zheng, Xiaochen Zhi, Congcong Ma, Shujun Cheng, Jie Li, Yutao Liu, Ting Xiao

“…Additionally, a prognostic prediction model for LUSC was developed using a combination of 101 machine learning algorithms. Risk scoring of patients was performed to explore the underlying reasons for prognostic differences between high and low-risk groups. …”
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MISHTI study evaluating hepatic fibrosis in type 2 diabetes patients in India by Debasis Datta, Krishna G. Seshadri, Samit Ghosal

“…While FIB 4 is sensitive for detecting significant fibrosis, its low specificity limits its utility as a standalone diagnostic test, particularly in T2D patients. …”
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The Role of Radiological Imaging in the Diagnosis of Acute Appendicitis by E Albiston

“…Several strategies have been employed to improve the accuracy of the diagnosis of appendicitis and to reduce the associated perforation rate. Because clinical algorithms have been disappointing, many physicians resort to radiological modalities. …”
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Statistical Analysis of Haralick Texture Features to Discriminate Lung Abnormalities by Nourhan Zayed, Heba A. Elnemr

“…In spite of the presence of low contrast and high noise in images, the proposed algorithms introduce promising results in detecting the abnormality of lungs in most of the patients in comparison with the normal and suggest that some of the features are significantly recommended than others.…”
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Interpretable machine learning approach for electron antineutrino selection in a large liquid scintillator detector by A. Gavrikov, V. Cerrone, A. Serafini, R. Brugnera, A. Garfagnini, M. Grassi, B. Jelmini, L. Lastrucci, S. Aiello, G. Andronico, V. Antonelli, A. Barresi, D. Basilico, M. Beretta, A. Bergnoli, M. Borghesi, A. Brigatti, R. Bruno, A. Budano, B. Caccianiga, A. Cammi, R. Caruso, D. Chiesa, C. Clementi, S. Dusini, A. Fabbri, G. Felici, F. Ferraro, M.G. Giammarchi, N. Giudice, R.M. Guizzetti, N. Guardone, C. Landini, I. Lippi, S. Loffredo, L. Loi, P. Lombardi, C. Lombardo, F. Mantovani, S.M. Mari, A. Martini, L. Miramonti, M. Montuschi, M. Nastasi, D. Orestano, F. Ortica, A. Paoloni, E. Percalli, F. Petrucci, E. Previtali, G. Ranucci, A.C. Re, M. Redchuck, B. Ricci, A. Romani, P. Saggese, G. Sava, C. Sirignano, M. Sisti, L. Stanco, E. Stanescu Farilla, V. Strati, M.D.C. Torri, A. Triossi, C. Tuvè, C. Venettacci, G. Verde, L. Votano

“…However, given the low cross-section of antineutrino interactions, the development of a powerful event selection algorithm becomes imperative to achieve effective discrimination between signal and backgrounds. …”
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Video Pulses: User-Based Modeling of Interesting Video Segments by Markos Avlonitis, Konstantinos Chorianopoulos

“…Previous research in video retrieval has focused on content-based techniques, such as pattern recognition algorithms that attempt to understand the low-level features of a video. …”
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Using machine learning methods to investigate the role of volatile organic compounds in non-alcoholic fatty liver disease by Chih-Hao Shen, Ruei-Hao Huang, Yaw-Kuen Li, Ta-Wei Chu, Ta-Wei Chu, Dee Pei, Dee Pei

“…This study aimed to explore whether NAFLD could be effectively detected using 341 volatile organic compounds (VOCs) via 10 machine learning (Mach-L) algorithms in a cohort of 1,501 individuals.MethodsParticipants were selected from the Taiwan MJ cohort, which includes comprehensive demographic, biochemical, lifestyle, and VOCs data. …”
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Vibration-based gait analysis via instrumented buildings by Ellis Kessler, Vijaya VN Sriram Malladi, Pablo A Tarazaga

“…Signal-energy-based algorithms detect the heel strike of each step during trials. …”
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Mesangial cell-derived CircRNAs in chronic glomerulonephritis: RNA sequencing and bioinformatics analysis by Ji Hui Fan, Xiao Min Li

“…Pro-inflammatory cytokines and cell cycle stages were detected by Enzyme-linked immunosorbent assay (ELISA) and Flow Cytometry experiment, respectively. …”
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Research status and progress on key technologies of intelligent orchard by CUI Hongwei, LU Xiaoxuan, YANG Yaqing, LU Xinyi, MA Hao, JI Jiangtao, JIN Xin, LI Xiuzhen, ZHAO Zimeng, ZENG Ningning

“…Orchard production currently faces several challenges, including labor shortages, low mechanization levels, and inefficient resource utilization. …”
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Machine learning-based brain magnetic resonance imaging radiomics for identifying rapid eye movement sleep behavior disorder in Parkinson’s disease patients by Yandong lian, Yibin Xu, Linlin Hu, Yuguo Wei, Zhaoge Wang

“…This study aims to develop and validate an magnetic resonance imaging (MRI) radiomics-based machine learning classifier to accurately detect RBD patients with Parkinson’s disease (PD). …”
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Annotation of Text Corpora by Sentiment and Presence of Irony within a Project of Citizen Science by Ilya Vyacheslavovich Paramonov, Anatoliy Yurievich Poletaev

“…It was also shown that the results of automatic algorithms of detecting the sentiment of sentences improved by 12–13 % when using a corpus for which all the annotators (from 3 till 5) had the agreement, in comparison with a corpus annotated by only one volunteer.…”
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The Military Aleatory: Weaponizing Winds by Ryan Bishop

“…An example of this can be found in a current military system for soldiers to model and predict low-atmosphere turbulence in the field. This article undertakes a brief examination of the role of nuclear technologies in relation to military meteorology, an overview of how control is found within the aleatory, followed by a section on military meteorology’s fundamental role in window modelling that reveal the logics and technics that detect signal from noise when none seems possible, before closing with military prediction of wind turbulence and a short cumulative refrain on wind and radiation exposure, with further links to the various sections.…”
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