Assessment of relationship between sea surface temperature (SST) changes and precipitation types in Nigeria from 2000 to 2022 by Tertsea Igbawua, Fanan Ujoh, Solomon Kwaghfan Mkighirga, Grace Adagba

“…The analysis of NIF values indicates a varied but generally stronger relationship between WAf SST anomalies and precipitation types compared to nino3.4 SST versus precipitation types. As a signal for prediction of seasonal and spatial distribution of precipitation across Nigeria’s different climatic zones, this outcome can support planning for food security, water and biodiversity conservation, and climate change adaptation and mitigation.…”
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Mesoscale Numerical Simulation and Cloud Microphysical Characteristics of the Warm Zone Blizzard in Northern Xinjiang by Anbei LI, Chenxiang JU, Yaman ZHOU, Man LI, Ruqi LI

“…The warm zone blizzard are both infrequent and highly destructive， making their accurate prediction a challenging and crucial focus.This study utilized four distinct cloud microphysics schemes （Lin， Thompson， WDM6， and WSM6） within the WRF mesoscale model to conduct a numerical simulation of a typical warm zone blizzard process in the northern Xinjiang in the middle of November 2016.The research objectives encompassed the evaluation of the model's capacity to simulate the warm zone blizzard， the selection of an optimal parameterization scheme， an analysis of the vertical distribution and evolution of hydrometeors during the snowstorm， and an exploration of the developmental patterns of related mesoscale systems contributing to the snowstorm.The analysis yielded the following key findings： （1） Among the diverse cloud microphysics parameterization schemes tested， the Lin scheme demonstrated the most favorable performance， effectively simulating snowfall magnitudes， spatial distributions， and trends.（2） In the cloud， all kinds of water condensate particles are active in the lower and middle troposphere， with graupel and snow being the most.Ice crystals， snow， cloud water and graupel particles are distributed from the upper layer to the lower layer.Near the windward slope of Altai Mountain is the center of the large concentration of each water condensate particle.The vertical alignment of the high value center of the four kinds of cloud water condensate particles in the strong snowfall area is conducive to the transformation of each particle.（3） High-humidity systems upstream moved westward， with the intensification of low-level southward jet streams resulting in pronounced moisture convergence.The western foothills of the Altai Mountains acted as a barrier， promoting moisture convergence by blocking the windward side； The low-level southerly jet also provides a continuous updraft and unstable condition for the generation of the blizzard.Strong snowfall is located in a wide updraft area between two groups of secondary circulations.The explosive growth of vertical movement is conducive to triggering the release of unstable energy， providing strong dynamic lifting conditions for the development and maintenance of the blizzard.…”
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On the Universality of the Split Monopole Black Hole Magnetosphere by S. Selvi, O. Porth, B. Ripperda, L. Sironi

“…Our results enable a quantitative prediction of the timescales and spatial structure of these evolving magnetospheres, essential for understanding electromagnetic counterparts to gravitational wave events and reconnection-powered flares from accreting BHs.…”
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Epigenetic-modification associated hnRNPA3 acts as a prognostic biomarker and promotes malignant progression of HCC by Xufan Cai, Weihui Guo, Fang Wu, Weilang Xu, Tao Ding, Yizhe Diao, Lei Wang, Zhenyuan Qian, Guangyuan Song

“…Logistic regression, receiver operating characteristic curve (ROC), Kaplan–Meier analysis, and nomogram modeling were used to evaluate prognostic values of hnRNPA3 in HCC. hnRNPA3 level in cell subtypes in HCC tumor microenvironment was analysed through spatial transcriptomic. …”
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Trends and research networks in greening business: A bibliometric analysis by Dana Kangalakova, Zaira Satpayeva, Makpal Nurkenova, Gulnara Nyussupova

“…The greening of businesses is becoming a priority area of strategic management for companies, considering the growing environmental challenges and the need to move toward sustainable business models. This study aims to identify the historical, evolutionary, spatial, and conceptually scientific landscape of greening businesses through bibliometric analysis. …”
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Infrared Monocular Depth Estimation Based on Radiation Field Detail Enhancement by Rihua Hao, Chao Xu, Chonghao Zhong

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Vision transformer embedded video anomaly detection using attention driven recurrence by Ummay Maria Muna, Shanta Biswas, Syed Abu Ammar Muhammad Zarif, Philip Jefferson Deori, Tauseef Tajwar, Swakkhar Shatabda

“…To further enhance the multiclass prediction performance, we develop a cluster-based weighting mechanism that assigns weights to classification scores based on feature similarity. …”
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Enhanced YOLOv10 Framework Featuring DPAM and DALSM for Real-Time Underwater Object Detection by Suthir Sriram, Aburvan P., Arun Kaarthic T. P., Nivethitha Vijayaraj, Thangavel Murugan

“…The marine fusion loss (MFL) provides an object detection prediction that combines both binary cross-entropy loss and complete intersection over union (CIoU) loss to enhance bounding box localization while also including spatial context to incorporate important underwater features. …”
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Progressive Guided Fusion Network With Multi-Modal and Multi-Scale Attention for RGB-D Salient Object Detection by Jiajia Wu, Guangliang Han, Haining Wang, Hang Yang, Qingqing Li, Dongxu Liu, Fangjian Ye, Peixun Liu

“…The depth map contains abundant spatial structure cues, which makes it extensively introduced into saliency detection tasks for improving the detection accuracy. …”
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Enhanced simulation of gross and net carbon fluxes in a managed Mediterranean forest by the use of multi-sensor data by Marta Chiesi, Nicola Arriga, Luca Fibbi, Lorenzo Bottai, Luigi D'Acqui, Alessandro Dell’Acqua, Sara Di Lonardo, Lorenzo Gardin, Maurizio Pieri, Fabio Maselli

“…The proposed advancements are aimed at improving the model performance in managed Mediterranean forests and concern: i) the calibration of C-Fix GPP sensitivity to water stress; ii) the quantification of the green, woody and soil C pools which regulate the prediction of NPP and NEP. …”
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Explainable AI for Spectral Analysis of Electromagnetic Fields by Dimitris Kalatzis, Agapi Ploussi, Ellas Spyratou, Theodor Panagiotakopoulos, Efstathios P. Efstathopoulos, Yiannis Kiouvrekis

“…A comparative evaluation of six machine learning algorithms was conducted: XGBoost, LightGBM, Random Forests, k-Nearest Neighbors, Neural Networks and Decision Trees to assess prediction performance across each frequency band. Furthermore, SHAP (SHapley Additive exPlanations) was employed to elucidate the contribution of spatial and demographic characteristics to the intensity of the EMF. …”
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Geographic Information Systems and Cartography for a Sustainable World by Andriani Skopeliti, Anastasia Stratigea, Vassilios Krassanakis, Apostolos Lagarias

“…At the heart of the discussion in this SI lies: (i) GIS, a valuable tool and a means for modeling, designing, and analyzing (spatial) data and processes related to the pursuance of sustainability objectives at both local and global scales; and (ii) Cartography as a discipline, which through maps and visualizations can convey the present state. …”
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Estimation and trend analysis of grassland aboveground biomass on the Qinghai-Xizang Plateau based on machine learning by Ruoqi Zhang, Qisheng Feng, Yonghui Zhang, Jingjing Mai, Tiangang Liang

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Synergistic Semantic Segmentation and Height Estimation for Monocular Remote Sensing Images via Cross-Task Interaction by Xuanang Peng, Shixin Wang, Futao Wang, Jinfeng Zhu, Suju Li, Longfei Liu, Zhenqing Wang

“…Recent studies have shown that multi-task learning methods can enhance the complementarity of task-related features, thus maximizing the prediction accuracy of multiple tasks at a low computational cost. …”
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Design of a Contact-Type Electrostatic Spray Boom System Based on Rod-Plate Electrode Structure and Field Experiments on Droplet Deposition Distribution by Hao Sun, Changxi Liu, Yufei Li, Hang Shi, Shengxue Zhao, Miao Wu, Jun Hu

“…The reliability of the device was verified through COMSOL numerical simulations, charge-to-mass ratio, droplet size, and droplet size spectrum measurements, and a droplet size prediction model was established. The deposition characteristics in soybean fields were analyzed using the Box–Behnken experimental design method. …”
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Spatiotemporal Analysis of Soil Moisture Variability and Precipitation Response Across Soil Texture Classes in East Kazakhstan by Dmitry Chernykh, Roman Biryukov, Andrey Bondarovich, Lilia Lubenets, Anatoly Pavlenko, Kamilla Rakhymbek, Denis Revenko, Zheniskul Zhantassova

“…The study of the hydrological regimes of rivers in different regions of the globe has revealed the need to include the soil moisture content in flood prediction models. This paper investigates the nature of the dependence of soil moisture content on soil texture in the East Kazakhstan region. …”
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Supply-Demand Matching Evaluation and Coupling Coordination of Cultural Ecosystem Services in Urban Park Green Spaces by Yang YU, Xian YANG, Xiang LI, Liyuan QIAN, Sixiang ZHOU

“…First, an evaluation indicator system and a supply-demand relationship model encompassing supply potential, supply opportunity, and resident demand dimensions are constructed to analyze the matching relationship and spatial distribution characteristics of CES. …”
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A novel multi-modal rehabilitation monitoring over human motion intention recognition by Saleha Kamal, Saleha Kamal, Mohammed Alshehri, Yahya AlQahtani, Abdulmonem Alshahrani, Nouf Abdullah Almujally, Ahmad Jalal, Ahmad Jalal, Hui Liu, Hui Liu, Hui Liu

“…Stochastic Gradient Descent (SGD) is employed to optimize the feature space, and a deep neuro-fuzzy classifier is proposed to balance interpretability and predictive accuracy. Evaluated on three benchmark datasets—NTU RGB + D 120, PKUMMD, and UWA3DII—our model achieves classification accuracies of 94.50%, 91.23%, and 88.60% respectively, significantly outperforming state-of-the-art methods. …”
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Vis-NIR soil spectral library of the Hungarian Soil Degradation Observation System by János Mészáros, Zsófia Kovács, Péter László, Szilvia Vass-Meyndt, Sándor Koós, Béla Pirkó, Nóra Szűcs-Vásárhelyi, Zsófia Bakacsi, Annamária Laborczi, Kitti Balog, László Pásztor

“…Therefore, development of national-level soil spectral libraries containing information about all soil types represented in a country is continuously increasing to serve as a basis for calibrated predictive models capable of assessing physical and chemical parameters of soils at multiple spatial scales. …”
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Ionospheric Response to the 24–27 February 2023 Solar Flare and Geomagnetic Storms Over the European Region Using a Machine Learning–Based Tomographic Technique by Ting Li, Dunyong Zheng, Changyong He, Fei Ye, Pengfei Yuan, Yibin Yao, Mengguang Liao, Jian Xie

“…Computerized ionospheric tomography based on machine learning (CIT‐ML) was used to predict the IEDs of unobserved voxels. The IEDs were examined using observation data from the Swarm satellite. …”
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