AI-Driven Spatial Data Analysis of Groundwater Level and Gravimetric Data in Roorkee Region, India by H. Sarkar, C. S. P. Ojha, S. K. Ghosh

“…However, traditional methods face challenges in predicting groundwater storage due to their inherent complexity. To address this gap and align with SDGs, this study aims to develop a regression-based machine learning model for spatially varying groundwater level prediction. …”
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A Conditional Simulation Method for Predicting Wind Pressure Fields of Large-Span Spatial Structures by Fangjin Sun, Tiantian Liu, Daming Zhang, Zhonghao Xu

“…However, due to the limited wind pressure data obtained from wind tunnel testing, it is quite meaningful to employ the limited measured data to predict the unknown wind pressure at target points. Considering the complexity of wind pressure fields of large-span spatial structures, a simplified nonparametric method based on conditional simulation is proposed to predict the unknown pressures using the existing data. …”
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Multimodal neural network for enhanced protein stability prediction by integration of contact scores and spatial maps by G Gladstone Sigamani, P.M. Durai Raj Vincent

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Mechanism of Influence of Spatial Perception on Residents’ Emotion in Child-Friendly Urban Streets of Fuzhou City by Shaofeng CHEN, Zhengyan CHEN, Yuhan XU, Zheng DING

“…Key practical implications include prioritizing traffic calming measures near schools and residential areas, balancing visual complexity through context-sensitive landscaping to avoid sensory overload or monotony, ensuring that safety infrastructure is supplemented by regular maintenance and caregiver-centered amenities, and employing adaptive fencing strategies that are consistent with spatial functions. …”
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Stability Analysis of Soil and Rock Mixed Slope Based on Random Heterogeneous Structure by Yafei Wang, Zhanrong Zhang, Xingpei Kang, Hao Xie, Chenchen Wang, Kun Liu

“…Due to the complexity in the heterogeneous internal structure and interactions between rocks and soil, the slide of soil–rock mixed slope is usually more complex than that of a homogeneous soil slope. …”
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Revealing the complex dynamics of monkeypox epidemics in heterogeneous networks by the evolutionary game theory by Mohammad Sharif Ullah, Jin Wang

“…Our work emphasizes the importance of multidisciplinary approaches in understanding the complex dynamics of infectious diseases and informing public health responses.…”
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A Two-State Random Walk Model of Sperm Search on Confined Domains by Martin Bier, Maciej Majka, Cameron Schmidt

“…Mammalian fertilization depends on sperm successfully navigating a spatially and chemically complex microenvironment in the female reproductive tract. …”
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Delineating Mixed Urban “Jobs-Housing” Patterns at a Fine Scale by Using High Spatial Resolution Remote-Sensing Imagery by Yao Yao, Chen Qian, Ye Hong, Qingfeng Guan, Jingmin Chen, Liangyang Dai, Zhangwei Jiang, Xun Liang

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Probabilistic analysis of ground settlement induced by soil and rock composite foundation excavation considering spatial variability by Yongjun Zhang, Zhenfu Zhang, Sijia Liu, Mingzhong Gao, Jintao Wang, Jinfeng Cao

“…Abstract The deposition processes of geotechnical materials are inherently complex, resulting in significant spatial variability in soil and rock properties. …”
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Method and experimental verification of spatial attitude prediction for an advanced hydraulic support system under mining influence by Zhuang Yin, Kun Zhang, ZengBao Zhang, Hongyue Chen, Lingyu Meng, Zhen Wang, Mingchao Du, Xiangpeng Hu, Defu Zhao, Dan Tian

“…Accurate prediction of the spatial attitude of the advanced hydraulic support group can provide a foundation for dynamically adjusting the spatial attitude to accommodate the deformation of the roadway’s surrounding rock. …”
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Spatial variation of intimate partner violence and its public health implication: a cross-sectional study by Abisola Esther Babatope, Demilade Olusola Ibirongbe, Idowu Peter Adewumi, Damola Olanipekun Ajisafe, Oluwafunbi Ajoke Fadipe, Gbenga Omotade Popoola, Kayode Olayiwola Adepoju, Oluyemi Adewole Okunlola

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Spatial heterogeneity determines the gastrointestinal microbiome signatures and ecological processes that govern bacterial community assembly in sheep by Yukun Zhang, Jiangbo Cheng, Changchun Lin, Fadi Li, Xiaoxue Zhang, Chong Li, Deyin Zhang, Xiaobin Yang, Dan Xu, Yuan Zhao, Liming Zhao, Xiaolong Li, Huibin Tian, Xiuxiu Weng, Weimin Wang

“…The composition and enterotypes of bacterial communities varied spatially along the gastrointestinal tract, primarily categorized into three distinct groups. …”
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Mendelian randomization analysis reveals potential association between allergic rhinitis and nasopharyngeal carcinoma by Qingfu Bao, Jianjun Zou, Changyang Wang, Haiying Wang

“…Abstract Background Nasopharyngeal carcinoma (NPC) is characterized by complex interactions within its tumor microenvironment. …”
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A dataset for surface defect detection on complex structured parts based on photometric stereo by Lin Wu, Yu Ran, Li Yan, Yixing Liu, You Song, Dongran Han

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A Quality Soft Sensing Method Designed for Complex Multi-process Manufacturing Procedures by Kaixiang PENG, Xin QIN, Jiahao WANG, Hui YANG

“…Both XGBoost and a residual network are used as prediction models to predict waviness.Conclusions The results indicate that, under the same number of selected features, the proposed multi-sensor process variable selection method outperforms the other four correlation-based feature selection methods (PCC, SCC, MI, MIC) in terms of predictive performance, achieving a balance between feature selection time complexity and prediction accuracy. Moreover, compared to the traditional two-dimensional (feature-time) sample construction method, the proposed three-dimensional (feature-time-procedure) sample space representation method, utilizing ResNet for temporal-spatial feature extraction and local-global feature fusion, further improves the model’s prediction accuracy. …”
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Lithological mapping and spectroscopic studies of carbonatite and clinopyroxenite from Hogenakkal carbonatite complex, India by Saraah Imran, Sourav Bhattacharjee, Ajanta Goswami, Aniket Chakrabarty

“…This study employs Landsat 8 multispectral data to map the spatial distribution and extent of the clinopyroxenite dykes. …”
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Using random forests to forecast daily extreme sea level occurrences at the Baltic Coast by K. Bellinghausen, B. Hünicke, E. Zorita

“…The method is based on a random forest classifier. It uses spatially resolved fields of daily sea level pressure, surface wind, precipitation, and the pre-filling state of the Baltic Sea as predictors for daily sea level above the 95 % quantile at each of seven tide gauge stations representative of the Baltic coast.…”
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Spatial heterogeneity patterns along the human footprint gradient and their ecological implications: A case study in South Korea by Kyoung-Ho Kim, Minkyu Park, Taeho Park, Donghae Baek, Gyobeom Kim, Namjoo Heo, Dong Jun Chun

“…Machine learning models incorporating multiple heterogeneity metrics significantly improved predictive performance compared to HF intensity alone, with Random Forest achieving the highest accuracy. These findings indicate that moderate levels of human activity create complex landscape mosaics that can sustain biodiversity, whereas intensive urbanization leads to homogenization. …”
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First passage time analysis of spatial mutation patterns reveals sub-clonal evolutionary dynamics in colorectal cancer. by Magnus J Haughey, Aleix Bassolas, Sandro Sousa, Ann-Marie Baker, Trevor A Graham, Vincenzo Nicosia, Weini Huang

“…Here, we propose a framework using first passage times of random walks to quantify the complex spatial patterns of tumour cell population mixing. …”
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Rapid Colonisation of Synanthropic Stone Martens in a Highly Urbanised Region: Insights From Temporal and Spatial Analysis by Karen Cox, Jan Gouwy, Joachim Mergeay, Sabrina Neyrinck, Koen Van Den Berge

“…Using genotypes from 5536 SNPs across 376 stone martens collected between 1995 and 2013, our findings indicate that stone martens successfully expanded through urban environments, yet dispersal was neither entirely random nor strictly distance‐dependent. The initial southeastern stronghold (E1) showed the lowest genetic diversity and limited spatial expansion, while other population sources contributed to recolonisation, highlighting a complex, multi‐source expansion. …”
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