Circulations migratoires des peuples de l’Ouest Cameroun : impacts culturels et cultuels by Gisèle PIEBOP

“…Résumé : Reconnus mondialement pour leur dynamisme économique qui leur vaut le sobriquet de « poumon de l’économie camerounaise », les peuples de la région de l’Ouest au Cameroun se démarquent également par leur extrême propension expansive aussi bien à l’intérieur qu’au-delà des frontières du triangle national camerounais. …”
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An investigation of machine learning methods applied to genomic prediction in yellow-feathered broilers by Bogong Liu, Huichao Liu, Junhao Tu, Jian Xiao, Jie Yang, Xi He, Haihan Zhang

“…In this study, seven different ML methods—support vector regression (SVR), random forest (RF), gradient boosting decision tree (GBDT), extreme gradient boosting (XGBoost), light gradient boosting machine (LightGBM), kernel ridge regression (KRR) and multilayer perceptron (MLP) were employed to predict the genomic breeding values of laying traits, growth and carcass traits in a yellow-feathered broiler breeding population. …”
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Leveraging advanced deep learning and machine learning approaches for snow depth prediction using remote sensing and ground data by Haytam Elyoussfi, Abdelghani Boudhar, Salwa Belaqziz, Mostafa Bousbaa, Karima Nifa, Bouchra Bargam, Abdelghani Chehbouni

“…Study focus: The research integrates remote sensing data, particularly the Normalized-Difference Snow Index (NDSI) from the MODIS Sensor, with machine learning (ML) and deep learning (DL) models to predict daily snow depth (DSD) at a local scale. The models evaluated include two ML approaches: Support Vector Regression (SVR) and eXtreme Gradient Boosting (XGBoost) and four DL models: 1-Dimensional Convolutional Neural Network (1D-CNN), Long Short-Term Memory Networks (LSTM), Gated Recurrent Unit (GRU), and Bi-directional Long Short-Term Memory Network (Bi-LSTM). …”
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Using remote sensing and machine learning to generate 100-cm soil moisture at 30-m resolution for the black soil region of China: Implication for agricultural water management by Liwen Chen, Boting Hu, Jingxuan Sun, Y. Jun Xu, Guangxin Zhang, Hongbo Ma, Jingquan Ren

“…To fill this gap, we propose a novel framework for estimation high spatial resolution multi-layer soil moisture data. …”
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Long-Term Statistical Analysis of Severe Weather and Climate Events in Greece by Vassiliki Kotroni, Antonis Bezes, Stavros Dafis, Dimitra Founda, Elisavet Galanaki, Christos Giannaros, Theodore Giannaros, Athanasios Karagiannidis, Ioannis Koletsis, George Kyros, Konstantinos Lagouvardos, Katerina Papagiannaki, Georgios Papavasileiou

“…Greece, with its complex topography, experiences severe and extreme weather events that have escalated in recent years and are projected to continue rising under future climate conditions. …”
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Machine Learning–Based Risk Factor Analysis and Prediction Model Construction for the Occurrence of Chronic Heart Failure: Health Ecologic Study by Qian Xu, Xue Cai, Ruicong Yu, Yueyue Zheng, Guanjie Chen, Hui Sun, Tianyun Gao, Cuirong Xu, Jing Sun

“… BackgroundChronic heart failure (CHF) is a serious threat to human health, with high morbidity and mortality rates, imposing a heavy burden on the health care system and society. …”
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Transgressive hybrids as hopeful holobionts by Benjamin Thomas Camper, Andrew Stephen Kanes, Zachary Tyler Laughlin, Riley Tate Manuel, Sharon Anne Bewick

“…Rather, the emerging paradigm in holobiont literature is that hybridization disrupts symbiosis between a host lineage and its microbiome, leaving hybrids at a fitness deficit. …”
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Wear Behavior Analysis and Gated Recurrent Unit Neural Network Prediction of Coefficient of Friction in Al10Cu-B₄C Composites by Mihail Kolev, Ludmil Drenchev, Veselin Petkov, Rositza Dimitrova, Krasimir Kolev, Boris Yanachkov

“…The addition of B₄C microparticles to Al10Cu composites significantly influenced their tribological properties with 2.5 wt.% B₄C achieving a 21.74% reduction in the coefficient of friction (COF) and 7.5 wt.% B₄C providing a remarkable 65.00% improvement in wear resistance. …”
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Analysis of geothermal impact on metabolite compounds of heat-tolerant plant species using clustering and similarity cliff by N.B. Maulydia, K. Khairan, T.E. Tallei, F. Mohd Fauzi, R. Idroes

“…These areas are also known to harbor a variety of medicinal plants, historically used for therapeutic properties. …”
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Prediction of Winter Wheat Parameters with Planet SuperDove Imagery and Explainable Artificial Intelligence by Gabriele De Carolis, Vincenzo Giannico, Leonardo Costanza, Francesca Ardito, Anna Maria Stellacci, Afwa Thameur, Sergio Ruggieri, Sabina Tangaro, Marcello Mastrorilli, Nicola Sanitate, Simone Pietro Garofalo

“…Model explainability was assessed with the SHAP method. A SHAP analysis highlighted that GNDVI, Cl1, and NDRE were the most important VIs for predicting RCC, while yellow and red bands were the most important for DM prediction, and yellow and nir bands for RWC prediction. …”
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Exploring cement Production's role in GDP using explainable AI and sustainability analysis in Nepal by Ramhari Poudyal, Biplov Paneru, Bishwash Paneru, Tilak Giri, Bibek Paneru, Tim Reynolds, Khem Narayan Poudyal, Mohan B. Dangi

“…Utilizing regression models like Extra Trees (Extremely Randomized Trees) Regressor, CatBoost (Categorial Boosting) Regressor, and XGBoost (eXtreme Gradient Boosting) Regressor, Random Forest and Ensemble of Sparse Embedded Trees (SET) machine learning is used to examine the demand, supply, and Gross Domestic Product (GDP) performance of cement manufacturing in India which shares a common cement related infrastructure to Nepal. …”
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Evaluating the Relationship between Factors Enhancing the Competitiveness of Customer Foreign Currency Services in the Banking Industry by Saeideh Rahimi, Alireza Rousta, Farzad Asayesh

“…Foreign currency services form a major part of banks' services and generate substantial income in both rials and foreign currencies. …”
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Mutual-information of meteorological-soil and spatial propagation: Agricultural drought assessment based on network science by Qingzhi Wen, Xinjun Tu, Lei Zhou, Vijay P Singh, Xiaohong Chen, Kairong Lin

“…Under high emission scenarios SSP2-45 and SSP5-85, the mutual-information between meteorological and hydrological elements progressively increased, and this increased information to extreme agricultural drought. The information transfer that occurred under a wide range of meteorological and hydrological elements can also be applied to the mutual-information network.…”
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Influence of climate factors on the formation of radial increment of walnut wood by Leonid Osadсhuk, Volodymyr Mahuran, Liubov Kondratiuk

“…This factor plays an essential role in ensuring a favorable soil moisture regime. In the second half of the growing season (July-August), on the contrary, a decrease in precipitation was observed, which has an ambiguous effect on the productive reserves of moisture in the soil. …”
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Functional Characterization of the <i>PoWHY1</i> Gene from <i>Platycladus orientalis</i> and Its Role in Abiotic Stress Tolerance in Transgenic <i>Arabidopsis thaliana</i> by Chun Ou, Zhiyu Dong, Xudong Zheng, Wenhui Cheng, Ermei Chang, Xiamei Yao

“…The expression levels of <i>JAZ1</i>, <i>LOX1</i>, <i>ABI1</i>, and <i>ABI2</i> were decreased, while the expression levels of <i>RAB18</i>, <i>APX1</i>, <i>GSTF6</i>, and <i>DREB2A</i> were increased, indicating that overexpression of <i>PoWHY1</i> enhanced the salt stress tolerance of <i>A. thaliana</i>. …”
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Exploring Proso Millet Resilience to Abiotic Stresses: High-Yield Potential in Desert Environments of the Middle East by Srinivasan Samineni, Sridhar Gummadi, Sumitha Thushar, Dil Nawaz Khan, Anestis Gkanogiannis, Luis Augusto Becerra Lopez-Lavalle, Rakesh Kumar Singh

“…The reproductive phase was highly vulnerable to heat stress, with 88% of this period experiencing daytime temperatures exceeding 40 °C, with a peak reaching up to 49 °C. These extreme conditions, coinciding with the crop’s critical growth stages, triggered a significant increase in chaffy grain production, substantially reducing overall grain yield. …”
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Machine learning prediction of anxiety symptoms in social anxiety disorder: utilizing multimodal data from virtual reality sessions by Jin-Hyun Park, Yu-Bin Shin, Dooyoung Jung, Ji-Won Hur, Seung Pil Pack, Heon-Jeong Lee, Hwamin Lee, Chul-Hyun Cho, Chul-Hyun Cho

“…IntroductionMachine learning (ML) is an effective tool for predicting mental states and is a key technology in digital psychiatry. This study aimed to develop ML algorithms to predict the upper tertile group of various anxiety symptoms based on multimodal data from virtual reality (VR) therapy sessions for social anxiety disorder (SAD) patients and to evaluate their predictive performance across each data type.MethodsThis study included 32 SAD-diagnosed individuals, and finalized a dataset of 132 samples from 25 participants. …”
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Dielectric Temperature Stability and Enhanced Energy-Storage Performance of Sr_0.4Ba_0.6(Zr_0.2Ti_0.2Sn_0.2Ta_0.2Nb<sub>... by Yingying Zhao, Ziao Li, Shiqiang Yang, Pu Mao, Ruirui Kang

“…By utilizing the high-entropy approach, the resulting SBN40-H ceramics demonstrated extremely fine grains, averaging 0.58 μm in size. Furthermore, these ceramics possessed a high bandgap of 3.35 eV, which, when combined with the small grain size, contributed to a remarkable breakdown strength of 570.01 kV/cm. …”
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Thymus ad astra, or spaceflight-induced thymic involution by Wataru Muramatsu, Wataru Muramatsu, Maria Maryanovich, Maria Maryanovich, Maria Maryanovich, Taishin Akiyama, Taishin Akiyama, George S. Karagiannis, George S. Karagiannis, George S. Karagiannis, George S. Karagiannis, George S. Karagiannis, George S. Karagiannis

“…Spaceflight imposes a constellation of physiological challenges—cosmic radiation, microgravity, disrupted circadian rhythms, and psychosocial stress—that critically compromise astronaut health. …”
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Tissue- and Cell Type-Specific Expression of the Long Noncoding RNA Klhl14-AS in Mouse by Sara Carmela Credendino, Nicole Lewin, Miriane de Oliveira, Swaraj Basu, Barbara D’Andrea, Elena Amendola, Luigi Di Guida, Antonio Nardone, Remo Sanges, Mario De Felice, Gabriella De Vita

“…lncRNAs are acquiring increasing relevance as regulators in a wide spectrum of biological processes. The extreme heterogeneity in the mechanisms of action of these molecules, however, makes them very difficult to study, especially regarding their molecular function. …”
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