Dataset of aerial photographs acquired with UAV using a multispectral (green, red and near-infrared) camera for cherry tomato (Solanum lycopersicum var. cerasiforme) monitoringDrya... by Osiris Chávez-Martínez, Sergio Alberto Monjardin-Armenta, Jesús Gabriel Rangel-Peraza, Zuriel Dathan Mora-Felix, Antonio Jesus Sanhouse-García

“…A dataset of aerial photographs acquired with an Unmanned Aerial Vehicle (UAV) DJI Phantom 4 Pro is presented for monitoring a cherry tomato (Solanum lycopersicum var. cerasiforme) crop in Navolato, Mexico. …”
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Management during and after Covid-19 Pandemic: A Descriptive Quantitative Study by Zafar Iqbal, Muhammad Hasnain

“… The present quantitative study based on the review of literature and present management of various sector of Pakistan including the education, health and economy. …”
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Trends in Indicators of Violence Among Adolescents in Europe and North America 1994–2022 by Michal Molcho, Sophie D. Walsh, Nathan King, William Pickett, William Pickett, Peter D. Donnelly, Peter D. Donnelly, Alina Cosma, Alina Cosma, Frank J. Elgar, Kwok Ng, Kwok Ng, Kwok Ng, Kwok Ng, Lilly Augustine, Marta Malinowska-Cieślik, Ylva Bjereld, Wendy Craig

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Stellar Variability toward the Galactic Open Cluster NGC 7209 by Dorothy M. Mwanzia, Sneh Lata, W. P. Chen, Soumen Mondal, Geoffrey Okeng’o, John Buers, Samrat Ghosh, Athul Dileep, Arjav Jain, Alisher S. Hojaev, Santosh Joshi

“…We present the analysis of stellar variability in an open cluster NGC 7209 using optical V -band CCD photometric observations. …”
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Optimized SVR model for predicting dissolved oxygen levels using wavelet denoising and variable reduction: Taking the Minjiang River estuary as an example by Peng Zhang, Xinyang Liu, Huiru Zhang, Chengchun Shi, Gangfu Song, Lei Tang, Ruihua Li

“…However, predicting DO levels in regions with complex hydrological variations remains challenging. This study presents a novel DO prediction model using the Minjiang River estuary as an example by integrating advanced machine learning techniques. …”
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Multivariate Screening and Automated Clustering of Macrophage Immunoreactome to Nanoparticles and Photothermal Therapy by Sonia Becharef, Léa Jabbour, Nassima Bekaddour, Giulio Avveduto, Nathalie Luciani, Gautier Laurent, Rana Bazzi, Edouard Alphandery, Stéphane Roux, Amanda K. A. Silva, Kelly Aubertin, Jean‐Philippe Herbeuval, Florence Gazeau

“…However, predicting immune responses using high‐throughput tests is challenging due to the immunoreactome's complexity and plasticity. This work presents a fast, machine learning‐assisted predictive assay to classify the multifactorial immune responses to any kind of treatments. …”
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Clinical and neurophysiological predictors of the functional outcome in right-hemisphere stroke by Francesco Di Gregorio, Giada Lullini, Silvia Orlandi, Valeria Petrone, Enrico Ferrucci, Emanuela Casanova, Vincenzo Romei, Fabio La Porta

“…Objective: The aim of the present study is to examine the relationship between EEG measures and functional recovery in right-hemisphere stroke patients. …”
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Thorax, Trachea, and Lung Ultrasonography in Emergency and Critical Care Medicine: Assessment of an Objective Structured Training Concept by Raoul Breitkreutz, Martina Dutiné, Patrick Scheiermann, Dorothea Hempel, Sandy Kujumdshiev, Hanns Ackermann, Florian Hartmut Seeger, Armin Seibel, Felix Walcher, Tim Oliver Hirche

“…Subgroup analysis revealed that learning success was independent from the trainees’ previous ultrasound experience. …”
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Weak-lensing Mass Reconstruction of Galaxy Clusters with a Convolutional Neural Network. II. Application to Next-generation Wide-field Surveys by Sangjun Cha, M. James Jee, Sungwook E. Hong, Sangnam Park, Dongsu Bak, Taehwan Kim

“…., we demonstrated that many of these pitfalls of traditional mass reconstruction can be mitigated using a deep learning approach based on a convolutional neural network (CNN). …”
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Automatic classification of Carbonatic thin sections by computer vision techniques and one-vs-all models by Elisangela L. Faria, Rayan Barbosa, Juliana M. Coelho, Thais F. Matos, Bernardo C.C. Santos, J.L. Gonzalez, Clécio R. Bom, Márcio P. de Albuquerque, P.J. Russano, Marcelo P. de Albuquerque

“…Within this context, this work presents an approach using one-class or specialist models to identify four classes of lithology present in reservoir rocks in the Brazilian pre-salt. …”
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Ecolodge Success Model: Antecedents and Consequences by Zohreh Dehdashti Shahrokh, Mohammadreza Karimi Alavijeh, Molood Esfahani

“…Finally, with a holistic view to ecolodge, 3 ecolodge success factors and 2 antecedents of ecolodge success and 3 consequences of ecolodge success were obtained and a comprehensive model including the antecedents and consequences of the success of ecolodge has been presented and success evaluation indicators will also be presented. …”
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Auto-resolving the atomic structure at van der Waals interfaces using a generative model by Wenqiang Huang, Yucheng Jin, Zhemin Li, Lin Yao, Yun Chen, Zheng Luo, Shen Zhou, Jinguo Lin, Feng Liu, Zhifeng Gao, Jun Cheng, Linfeng Zhang, Fangping Ouyang, Jin Zhang, Shanshan Wang

“…However, a rapid, accurate, and robust approach to automatically resolve complex patterns in atomic-resolution microscopy remains difficult to implement. Here, we present a Trident strategy-enhanced disentangled representation learning method (a generative model), which utilizes a few unlabelled experimental images with abundant low-cost simulated images to generate a large corpus of annotated simulation data that closely resembles experimental results, producing a high-quality large-volume training dataset. …”
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RT-ring: a small wearable device for tremulous Parkinson’s disease diagnosis in primary care by Jolanda Buonocore, Jolanda Buonocore, Basilio Vescio, Basilio Vescio, Marida De Maria, Marianna Crasà, Rita Nisticò, Pier P. Arcuri, Giuseppe L. Cascini, Giuseppe L. Cascini, Giuseppe L. Cascini, Anna Latorre, Aldo Quattrone, Andrea Quattrone, Andrea Quattrone

“…The RT-ring is a miniaturized mobile device that uses machine learning based on inertial tremor data to estimate the RT pattern. …”
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Operationalizing postmortem pathology-MRI association studies in Alzheimer’s disease and related disorders with MRI-guided histology sampling by Chinmayee Athalye, Alejandra Bahena, Pulkit Khandelwal, Sheina Emrani, Winifred Trotman, Lisa M. Levorse, Zahra Khodakarami, Daniel T. Ohm, Eric Teunissen-Bermeo, Noah Capp, Shokufeh Sadaghiani, Sanaz Arezoumandan, Sydney A. Lim, Karthik Prabhakaran, Ranjit Ittyerah, John L. Robinson, Theresa Schuck, Edward B. Lee, M. Dylan Tisdall, Sandhitsu R. Das, David A. Wolk, David J. Irwin, Paul A. Yushkevich

“…To facilitate pathology-MRI association studies, we created a semi-automated MRI to histology registration pipeline and developed a quantitative pathology scoring system using weakly supervised deep learning. We validated this protocol on a cohort of 29 brains with diagnosis on the AD spectrum that revealed correlations between cortical thickness and phosphorylated tau accumulation. …”
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Emerging Technologies for 6G Non-Terrestrial-Networks: From Academia to Industrial Applications by Cong T. Nguyen, Yuris Mulya Saputra, Nguyen Van Huynh, Tan N. Nguyen, Dinh Thai Hoang, Diep N. Nguyen, Van-Quan Pham, Miroslav Voznak, Symeon Chatzinotas, Dinh-Hieu Tran

“…This article aims to provide a comprehensive survey on the utilization of network slicing, Artificial Intelligence/Machine Learning (AI/ML), and Open Radio Access Network (ORAN) to address diverse challenges of NTNs from the perspectives of both academia and industry. …”
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PPARG/SPP1/CD44 signaling pathway in alveolar macrophages: Mechanisms of lipid dysregulation and therapeutic targets in idiopathic pulmonary fibrosis by Ganggang Li, Yuwei Zhang, Huanyu Jiang, Xuanyu Wu, Yanwei Hao, Yuchen Su, Yutong Zou, Wenjia Xian, Fei Wang, Quanyu Du

“…In conclusion, these findings highlight the critical role of lipid metabolism in IPF and present novel molecular targets for the development of future therapeutic strategies.…”
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LimbMATE: A Versatile Platform for Closed-Loop Research in Prosthetics by Erik Gasparini, Rodolfo Cerqueira, Carlo Preziuso, Lucia Angelini, Robinson Guachi, Marco Controzzi, Christian Cipriani, Enzo Mastinu

“…The rapid advancements in machine learning methodologies carry a wide potential to match the increasing control demands of modern robotic hands. …”
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Exploring high entropy alloys: A review on thermodynamic design and computational modeling strategies for advanced materials applications by Peter Ifeolu Odetola, Bukola Joseph Babalola, Ayodeji Ebenezer Afolabi, Ufoma Silas Anamu, Emmanuel Olorundaisi, Mutombo Christian Umba, Thabang Phahlane, Olusoji Oluremi Ayodele, Peter Apata Olubambi

“…By dissecting the foundational ''four core effects'' intrinsic to HEAs—high entropy, sluggish diffusion, severe lattice distortion, and cocktail effect—we illuminate the path towards predictable and tailored material properties. Central to the present discourse is the application of valence electron concentration (VEC) and cutting-edge strategies, including the CALculation of PHAse Diagrams (CALPHAD) method, first-principles approach, and machine-learning algorithms, which collectively empower the prediction and understanding of HEA behavior. …”
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Analysis of the effects of immunotherapy depending on cancer subtypes on survival - a single center experience by Anna Rudzińska, Pola Juchaniuk, Jakub Oberda, Kacper Ponikowski, Paulina Gumółka, Karol Jakubik, Mikołaj Jeżak, Agnieszka Kalicińska, Angelika Doroszewska, Mariola Janiszewska, Katarzyna Szklener

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Enhancing wheat flour origin traceability by using laser-induced breakdown spectroscopy and Raman spectroscopy by Minghui Gu, Chao Liu, Hansong Huang, Xin Zhang, Jiguo Li, Qingbin Jiao, Liang Xu, Mingyu Yang, Xin Tan

“…The transfer model achieved a prediction accuracy of 97% on the remaining data, demonstrating the effectiveness of transfer learning.…”
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