A multi-year analysis of acoustic occurrence and habitat use of blue and fin whales in eastern and central Fram Strait. by Marlene Meister, Elena Schall, Robert Dziak, Stefanie Spiesecke, Karolin Thomisch

“…Climate change-induced habitat alterations in the Arctic Ocean are expected to affect spatial and temporal occurrence patterns of seasonally migrating baleen whale species, leading to poleward range shifts and prolonged stays in Arctic waters. …”
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Multi-Sensor Fusion for Land Subsidence Monitoring: Integrating MT-InSAR and GNSS with Kalman Filtering and Feature Importance to Northern Attica, Greece by Vishnuvardhan Reddy Yaragunda, Emmanouil Oikonomou

“…Additionally, the PS and SBAS vertical displacement data were fused using Kalman filtering to enhance spatial coverage and refine displacement estimates. …”
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Hybrid CNN-LSTM Model with Custom Activation and Loss Functions for Predicting Fan Actuator States in Smart Greenhouses by Gregorius Airlangga, Julius Bata, Oskar Ika Adi Nugroho, Boby Hartanto Pramudita Lim

“…The hybrid model integrates CNNs for spatial feature extraction and LSTMs for temporal dependency modeling, enhanced by a custom activation function and loss function tailored for the problem’s characteristics. …”
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From the Past to the Future: Unveiling the Impact of Extreme Climate on Vegetation Dynamics in Northern China Through Historical Trends and Future Projections by Yuxuan Zhang, Xiaojun Yao, Juan Zhang, Qin Ma

“…Over the past few decades, occurrences of extreme climatic events have escalated significantly, with severe repercussions for global ecosystems and socio-economics. northern China (NC), characterized by its complex topography and diverse climatic conditions, represents a typical ecologically vulnerable region where vegetation is highly sensitive to climate change. …”
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Behavioural user segmentation of app users based on functionality interaction patterns by Li-Yoong Ooi, Choo-Yee Ting, Helmi Zakariah, Eashvaren Chandar

“…User segmentation categorises a large and complex user base into manageable similar groups of users. …”
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A two-stage computational approach for stochastic Darcy-forchheimer non-newtonian flows by Muhammad Shoaib Arif, Muhammad Shoaib Arif, Kamaleldin Abodayeh, Yasir Nawaz

“…The Euler-Maruyama approach handles Wiener processes for stochastic models, providing robust performance under random fluctuations. A compact sixth-order spatial discretization scheme enhances solution accuracy while maintaining computational efficiency. …”
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A deep neural network framework for estimating coastal salinity from SMAP brightness temperature data by Yidi Wei, Qing Xu, Qing Xu, Xiaobin Yin, Xiaobin Yin, Yan Li, Yan Li, Kaiguo Fan

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Rest‐site selection by fishers (Martes pennanti) in the eastern deciduous forest by Sean W. Gess, E. Hance Ellington, Matthew R. Dzialak, Joseph E. Duchamp, Matthew Lovallo, Jeffrey L. Larkin

“…We quantified selection by comparing used and randomly selected available sites at 2 spatial scales: the rest structure and at the rest site (area surrounding rest structures). …”
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Numerical Study of Non-Schell Model Pulses in Nonlinear Dispersive Media with the Monte Carlo-Based Pseudo-Mode Superposition Method by Pujuan Ma, Yi Zhang, Yanlin Bai, Yangjian Cai, Jingsong Liu

“…Recently, we introduced random complex and phase screen methods as powerful tools for numerically investigating the evolution of partially coherent pulses (PCPs) in nonlinear dispersive media. …”
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Analysis of Synergistic Changes in PM_2.5 and O₃ Concentrations Based on Structural Equation Model Study by Zhangwen Su, Liming Yang, Yimin Chen, Rongyu Ni, Wenlong Wang, Honghao Hu, Bin Xiao, Sisheng Luo

“…Given the increasing importance of effectively identifying synergistic changes between PM_2.5 and O₃ and comprehensively analyzing their impact on air quality management in China, we employ the Sen+Mann–Kendall (Sen+M-K) trend test in this study to examine the temporal and spatial variation trends of PM_2.5 and O₃ in the Yangtze River Delta (YRD), from 2003 to 2020. …”
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Optimizing the Location of 5G Network Base Stations Taking into Account Intra-System Interference by Serhii Siden, Roman Tsarоv, Mohammed Jamal Salim, Kateryna Shulakova, Saad Malik Talha, Liliia Bodnar

“…A method is proposed for determining the number and optimal spatial coordinates of BSs in indoor environments, such as shopping malls or telemedicine centers, under random user distribution to ensure maximum coverage and network throughput while explicitly accounting for intra-system interference. …”
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On the movement of the honeybee queen in the hive by Jan Blaha, Martin Stefanec, Jiří Janota, Daniel Nicolas Hofstadler, Tomáš Rouček, Jiří Ulrich, Laurenz Alexander Fedotoff, George Broughton, Tomáš Vintr, Farshad Arvin, Thomas Schmickl, Tomáš Krajník

“…Inter-stop distances followed a power-law distribution, and queens repeatedly revisited specific spatial zones over multi-day timescales. These results indicate a dual-scale movement strategy that is not captured by standard random walk models, highlighting internal state or memory-based navigation. …”
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A Generalized Spatiotemporally Weighted Boosted Regression to Predict the Occurrence of Grassland Fires in the Mongolian Plateau by Ritu Wu, Zhimin Hong, Wala Du, Yu Shan, Hong Ying, Rihan Wu, Byambakhuu Gantumur

“…In order to achieve a better prediction, this paper proposes a generalized geographically weighted boosted regression (GGWBR) method that combines spatial heterogeneity and complex nonlinear relationships, and further attempts the generalized spatiotemporally weighted boosting regression (GSTWBR) method that reflects spatiotemporal heterogeneity. …”
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Tree Roots Reconstruction Framework for Accurate Positioning in Heterogeneous Soil by Wenhao Luo, Yee Hui Lee, Hai-Han Sun, Genevieve Ow, Mohamed Lokman Mohd Yusof, Abdulkadir C. Yucel

“…However, ignoring the random and complex nature of the heterogeneous soil and assuming the soil's relative permittivity constant throughout the survey region may yield an inaccurate tree root positioning. …”
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Measurement-guided therapeutic-dose prediction using multi-level gated modality-fusion model for volumetric-modulated arc radiotherapy by Changfei Gong, Changfei Gong, Changfei Gong, Yuling Huang, Yuling Huang, Yuling Huang, Junming Jian, Junming Jian, Junming Jian, Wenheng Zheng, Wenheng Zheng, Wenheng Zheng, Xiaoping Wang, Xiaoping Wang, Xiaoping Wang, Shenggou Ding, Shenggou Ding, Shenggou Ding, Yun Zhang, Yun Zhang, Yun Zhang

“…Furthermore, the existing models simply take advantage of low-dimensional dosimetry information, meaning that the spatial features about the complex dose distribution may be lost and limiting the predictive power of the models. …”
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A Web-Based Application for Smart City Data Analysis and Visualization by Panagiotis Karampakakis, Despoina Ioakeimidou, Periklis Chatzimisios, Konstantinos A. Tsintotas

“…Concerning the user’s dashboard, it supports interactive exploration via dynamic charts and spatial maps. This way, we demonstrate how future internet technologies permit the accessibility of complex urban sensor data for research, planning, and public engagement. …”
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Discretization-independent surrogate modeling of physical fields around variable geometries using coordinate-based networks by James Duvall, Karthik Duraisamy

“…The incorporation of random Fourier features greatly enhanced prediction and generalization accuracy for both approaches. …”
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Integration of Sentinel-1 and Sentinel-2 for temporal identification of aquacultural ponds by Vaishnavi Joshi, Dipanwita Haldar, Subhadip Dey

“…The Random Forest classifier obtained a maximum overall accuracy of 94% by combining optical and SAR data, significantly outperforming other classifiers. …”
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Advances in machine learning for the detection and characterization of microplastics in the environment by M. Maksuda Khanam, M. Khabir Uddin, Julhash U. Kazi

“…Extending these capabilities further, hyperspectral imaging combines spatial and spectral data to generate comprehensive chemical maps, enabling the simultaneous assessment of polymer composition and distribution. …”
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Dynamic Patch-Based Sample Generation for Pulmonary Nodule Segmentation in Low-Dose CT Scans Using 3D Residual Networks for Lung Cancer Screening by Ioannis D. Marinakis, Konstantinos Karampidis, Giorgos Papadourakis, Mostefa Kara

“…HighRes3DNet is a specialized 3D convolutional neural network (CNN) architecture based on ResNet principles which uses residual connections to efficiently learn complex spatial features from 3D volumetric data. …”
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