Multi-Temporal Remote Sensing Satellite Data Analysis for the 2023 Devastating Flood in Derna, Northern Libya by Roman Shults, Ashraf Farahat, Muhammad Usman, Md Masudur Rahman

“…Different supervised classification methods were examined, including random forest, support vector machine, naïve-Bayes, and classification and regression tree (CART). …”
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Comparative Community Ecology Reveals Conserved Ectoparasite Microbiomes Amidst Variable Host and Environment Microbiomes by Kelly A. Speer, Luis Víquez‐R, Winifred F. Frick, Ana Ibarra, Nancy B. Simmons, Katharina Dittmar, Ricardo Sánchez Calderón, Raisa Preciado, Rodrigo Medellín, Marco Tschapka, Simone Sommer, Susan L. Perkins

“…However, we know comparatively little about the processes that dictate the composition of non‐maternally inherited bacteria in insect microbiomes, despite the importance of these bacteria in insect health, fitness, and vector competence. …”
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Zika virus and the fetal-maternal interface: deciphering the mechanisms of placental infection and implications for pregnancy outcomes by Sam Chak Sum Wong, Joshua Fung, Pak-Ting Hau, Yanjie Guo, Philip C. N. Chiu, Hong Wa Yung, Gilman Kit Hang Siu, Franklin Wang-Ngai Chow, Cheuk-Lun Lee

“…Finally, we propose future directions for mitigating ZIKV’s impact on maternal-fetal health, emphasizing the need for comprehensive research into viral pathogenesis, advanced model systems, and vector control programmes to prevent this devastating infection.…”
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Metabolic Engineering of <i>Zymomonas mobilis</i> for Xylonic Acid Production from Lignocellulosic Hydrolysate by Banrui Ruan, Xiongying Yan, Zhaoqing He, Qiaoning He, Shihui Yang

“…Bio-based xylonic acid produced from inexpensive lignocellulosic biomass has enormous market potential and enhances the overall economic benefits of biorefinery processes. In this study, the introduction of genes encoding xylose dehydrogenase driven by the promoter P<i>pdc</i> into <i>Z. mobilis</i> using a plasmid vector resulted in the accumulation of xylonic acid at a titer of 16.8 ± 1.6 g/L. …”
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Motivation toward physical activity and nutrition in older cancer patients: the MONAGE protocol using ecological momentary assessment and accelerometers by Mathis Brusseau, Blandine Gallet-Suchet, Gérard Dray, Sophie Gendrault, Lobna Harguem, Julie Boiché

“…The data analysis strategy shall include Multilevel Vector Autoregressive Models with k-means clustering. …”
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Machine-Learning-Based Biomechanical Feature Analysis for Orthopedic Patient Classification with Disc Hernia and Spondylolisthesis by Daniel Nasef, Demarcus Nasef, Viola Sawiris, Peter Girgis, Milan Toma

“…The performance of various ML models, including decision trees, support vector machines, and neural networks, is evaluated using metrics such as accuracy, AUC, recall, precision, F1, Kappa, and MCC. …”
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Thirty-day mortality risk prediction for geriatric patients undergoing non-cardiac surgery in the surgical intensive care unit by Mengke Ma, Jiatong Liu, Caiyun Li, Yingxue Chen, Huishu Jia, Aijie Hou, Hongzeng Xu

“…Five predictive models were established: categorical boosting (CatBoost), logistic regression (LR), decision tree (DT), random forest (RF), and support vector machine (SVM). External validation was performed utilizing data from 153 patients in the MIMIC-III database. …”
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Insights into the Regulatory Roles of miRNAs in the Salivary Glands of the Soft Ticks <i>Ornithodoros moubata</i> and <i>Ornithodoros erraticus</i> by Ana Laura Cano-Argüelles, Ricardo Pérez-Sánchez, Cristian Gallardo-Escárate, Rocío Vizcaíno-Marín, María González-Sánchez, Ana Oleaga

“…In ticks, salivary miRNAs are proposed to play key roles in modulating host–vector interactions during blood feeding. Previously, we identified salivary miRNAs in <i>Ornithodoros moubata</i> and <i>Ornithodoros erraticus</i>, major vectors of African swine fever and tick-borne human relapsing fever. …”
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iTRAQ-base quantitative proteomic analysis of bulblets development in Lilium davidii var. unicolor and LdGASA plays important roles during plant development by Xueyan Li, Yiguang Bai, Xinying Hu, Weidong Wang, Lihong Zhou, Ruiqi Zhang, Weisheng Liu, Yingdong Yang

“…We cloned the full length of LdGASA, analyzed its expression profile during lily bulblet development, and constructed its overexpression vector and transformed into Arabidopsis thaliana. …”
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The Smart Product Backlog: A Classification Model of User Stories by Mauricio Gaona-Cuevas, Victor Bucheli Guerrero, Fredy H. Vera-Rivera

“…In agile software development processes, user stories (US) had been used to specify application functionalities from the users&#x2019; perspective. …”
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The Modern Trends of Financial Reporting Development by Olga V. Rozhnova

“…The complexity of the way to it is natural, as the identification of the trends, their interpretation and description is a continuous process, aimed not only at summarizing of the next stage of development of the financial statements, but also on the creation of a prototype of the future stage.…”
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Development and Evaluation of Solar Radiation Sensor Using Cost-Effective Light Sensors and Machine Learning Techniques by Jesús Antonio Nava-Pintor, Uriel E. Alcalá-Rodríguez, Héctor A. Guerrero-Osuna, Marcela E. Mata-Romero, Emmanuel Lopez-Neri, Fabián García-Vázquez, Luis Octavio Solís-Sánchez, Rocío Carrasco-Navarro, Luis F. Luque-Vega

“…This study explores the feasibility of using low-cost ambient light sensors combined with statistical and machine learning models based on linear, random forest, and support vector regressions to estimate solar irradiance. To achieve this, an Internet of Things-based system was developed, integrating the light sensors with cloud storage and processing capabilities. …”
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Analysis of Microbiome for AP and CRC Discrimination by Alessio Rotelli, Ali Salman, Leandro Di Gloria, Giulia Nannini, Elena Niccolai, Alessio Luschi, Amedeo Amedei, Ernesto Iadanza

“…Subsequently, the synthesised data quality was evaluated using a logistic regression model in parallel with an optimised support vector machine algorithm (polynomial kernel). The data quality is considered good when neither of the two algorithms can discriminate between real and synthetic data, showing low accuracy, F1 score, and precision values. …”
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A Convolutional Neural Network Model for Classifying Resting Tremor Amplitude in Parkinson&#x2019;s Disease by Augusto Ielo, Serena Dattola, Lilla Bonanno, Paolo De Pasquale, Alberto Cacciola, Angelo Quartarone, Maria Cristina De Cola

“…The proposed model outperformed traditional machine learning techniques as Random Forest, Support Vector Machine (SVM) and Decision Trees, demonstrating superior accuracy in tremor classification. …”
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Improving kinetic model fitting for total titratable acidity in bananas using genetic algorithms by Alejandro Kevin Méndez Castillo, Elizabeth Contreras López, Jesús Guadalupe Pérez Flores, Laura García Curiel, Emmanuel Pérez Escalante, Karla Soto Vega, Carlos Ángel-Jijón, Alicia Cervantes Elizarrarás

“…., neural networks, or support vector regression), to better capture the biochemical processes underlying acidity changes in bananas. …”
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An Optimized Method for Single Cell Cloning of Human CAR-T Cells Based on FBS-Coated Plates by Mahdie Jafari, Shahriyar Abdoli, Masoud Moghaddam Pour, Mohammad Ali Shokrgozar, Zahra Sharifzadeh

“…Despite significant improvements in CAR-T cell production processes, the isolation and expansion of CAR-engineered T cells continue to pose significant challenges. …”
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Bioaerosols in Agriculture: A Comprehensive Approach for Sustainable Crop Health and Environmental Balance by Njomza Gashi, Zsombor Szőke, Péter Fauszt, Péter Dávid, Maja Mikolás, Ferenc Gál, László Stündl, Judit Remenyik, Melinda Paholcsek

“…Closely intertwined with the agricultural domain, these particles exert a significant influence on crops through the dissemination of various microorganisms that modulate crop growth dynamics, adaptive responses to environmental stimuli, and the nutritional profile of agricultural products. As the main vector, airborne particles are at the forefront in the transmission of plant pathogens. …”
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Exploration of machine learning approaches for automated crop disease detection by Annu Singla, Ashima Nehra, Kamaldeep Joshi, Ajit Kumar, Narendra Tuteja, Rajeev K. Varshney, Sarvajeet Singh Gill, Ritu Gill

“…Recent advancements in machine learning (ML) offer promising alternatives by automating the disease detection processes with high precision and efficiency. We comprehensively analyze various ML techniques, including Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), Support Vector Machines (SVMs), Random Forest (RF), and Deep Learning Architectures like ResNet and Inception, among others, highlighting their methodologies, datasets, performance metrics, and real-world applications. …”
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Using ecological and life-history characteristics for projecting species' responses to climate change by Sven Pompe, Jan Hanspach, Franz W. Badeck, Stefan Klotz, Helge Bruelheide, Ingolf Kühn

“…First, we established relationships between modelled loss of occupied grid cells (‘range loss’, R²=0.29), or gain of currently unoccupied grid cells (‘range gain’, R²=0.30), for 195 plant species with distributional data under the A1FI climate change scenario up to 2080, and ecological and life history traits (life form, leaf persistence, ecological strategy, pollen vector, Ellenberg indicator values and characteristics derived from species’ ranges). …”
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Development and validation of machine learning classifiers for predicting treatment-needed retinopathy of prematurity by Nasser Shoeibi, Majid Abrishami, Seyedeh Maryam Hosseini, Mohammad-Reza Ansari-Astaneh, Razieh Farrahi, Bahareh Gharib, Fatemeh Neghabi, Mojtaba Abrishami, Mehdi Sakhaee, Mehrdad Motamed Shariati

“…We developed and assessed several classifiers: logistic regression (LR), decision tree (DT), support vector machine (SVM), naïve Bayes (NB), K-nearest neighbors (KNN), XGBoost, artificial neural networks (ANN), and random forest (RF). …”
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