Machine-learning unravels spatial shifting in homogeneous rainfall subregions in Central Africa under global warming by Alain T Tamoffo, Fernand L Mouassom, Torsten Weber

“…Although the rainfall regimes characterizing Central Africa (CA) have just recently been described, it is equally urgent to investigate potential changes in their spatial extent under different global warming pathways, which motivates the present study. …”
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SPATIAL & TEMPORAL WATER BALANCE ANALYSIS CONSIDERING STRUCTURAL & NON-STRUCTURAL MEASURES IN THE CISANGKUY RIVER BASIN by IH Ko, W Putuhena, I. Sudono, YJ Kim, TW Kim

“…This paper deals with the spatial-temporal water balance analysis and shows the results of effect analysis with regard to structural measures and nonstructural measures. …”
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The Metaverse Is Geospatial: A System Model Architecture Integrating Spatial Computing, Digital Twins, and Virtual Worlds by Theofilos Papadopoulos, Konstantinos Evangelidis, Theodore H. Kaskalis, Georgios Evangelidis

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Forecasting dengue across Brazil with LSTM neural networks and SHAP-driven lagged climate and spatial effects by Xiang Chen, Paula Moraga

“…Conclusion This study presents a scalable and robust framework for dengue forecasting across Brazil, effectively integrating temporal, climatic, and spatial information into an LSTM-based model. …”
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A potential spatial working memory training task to improve both episodic memory and fluid intelligence. by Sarah R Rudebeck, Daniel Bor, Angharad Ormond, Jill X O'Reilly, Andy C H Lee

“…By giving careful consideration to the neural correlates underlying episodic and working memory, we devised a computerized working memory training task in which neurologically healthy participants were required to monitor and detect repetitions in two streams of spatial information (spatial location and scene identity) presented simultaneously (i.e. a dual n-back paradigm). …”
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Measurement and Spatial Transfer of Blue Water Footprint in Urumqi-Changji-Shihezi Megalopolis——Based on MRIO Model by LYU Zhengyin, SUN Jianguang

“…To find a way to alleviate the pressure on water resources during the coordinated development of the Urumqi-Changji-Shihezi megalopolis,this paper calculated the blue water footprint in the megalopolis from the perspectives of production and consumption with a city-scale multi-region input-output (MRIO) model.The pattern of spatial transfer among the sectors of the region and between the region and the rest of the country was also measured.The results lead to the following conclusions:① In 2012,the blue water footprint of production in the Urumqi-Changji-Shihezi megalopolis was 3.383 billion m³,mainly due to the large production scale of the agriculture,forestry,animal husbandry,and fishery in Changji.In contrast,the blue water footprint of consumption was as high as 6.403 billion m³ because Urumqi and Shihezi imported a lot of blue water footprint in the primary industry (mainly from inside Xinjiang) and the tertiary industry (mainly from outside Xinjiang).② The self-sufficiency of the Urumqi-Changji-Shihezi megalopolis is limited.Nevertheless,the various sectors of each city are closely related to each other,and those in Shihezi are especially prominent in pulling the region's water consumption up to a high level.③ The Urumqi-Changji-Shihezi megalopolis has a net import of blue water footprint from within Xinjiang that is higher than its net export to outside Xinjiang.Specifically,Urumqi achieves a net import from both inside and outside Xinjiang and has a net export only in the sectors of petroleum,coking products,and processed nuclear fuel products.In contrast,Changji,presenting itself with a net export,and Shihezi,with a net import,rely on the inflow from the primary and tertiary industries within Xinjiang on the one hand and are burdened with the demand of major agricultural provinces outside Xinjiang and the developed provinces and cities in Southeast China for agricultural and livestock products and primary industrial products on the other hand.This research can thus provide a reference for the rational allocation of water resources in the Urumqi-Changji-Shihezi megalopolis and the strategic arrangement for foreign trade.…”
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Super-resolution for electron microscope scanning images of shale via spatial-spectral domain attention network by Junqi Chen, Lijuan Jia, Jinchuan Zhang, Yilong Feng

“…This study introduced a novel neural network called the spatial-spectral domain attention network (SSDAN), which employed spatial and spectral domain attention mechanisms to extract features and restore information in parallel. …”
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Combining video and GPS-tracking to study the spatial foraging distribution of a single-prey loading seabird by Ruben C. Fijn, Wouter Courtens, Bas W.R. Engels, Emiel E. van Loon, Judy Shamoun-Baranes

“…Combining GPS-data and prey observations yielded detailed knowledge on the movements and chick diets of tracked birds as well as the spatial origin and lengths of captured prey items. …”
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Analyzing the Spatial-Temporal Patterns of Urban Heat Islands in Nanjing: The Role of Urbanization and Different Land Uses by Ji-Yu Deng, Hua Lao, Chenyang Mei, Yizhen Chen, Yueyang He, Kaihuai Liao

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Early visual processing for low spatial frequency fearful face is correlated with cortical volume in patients with schizophrenia by Lee JS, Park G, Song MJ, Choi K, Lee S

“…During electroencephalographic recordings, participants passively viewed neutral or fearful faces with broad, high, or low spatial frequency characteristics. Voxel-based morphometry was performed to investigate brain volume correlates of visual processing deficits. …”
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Assessing the spatial variability of soil properties in the semiarid areas of Hintalo Wejerat District, Tigray region, Ethiopia by Abeba Nigussie Retta, Fassil Kebede, Mitiku Haile, Girmay Gebresamuel, Amanuel Zenebe, Gebreyohannes Girmay

“…Abstract Knowledge of soil spatial variability and mapping is essential. It helps determine the effects of agricultural activities on soil properties, develop appropriate soil management techniques, and promote site-specific agricultural practices. …”
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PM2.5 in Sri Lanka: Trend Analysis, Low-cost Sensor Correlations and Spatial Distribution by Ranil Dhammapala, Ashani Basnayake, Sarath Premasiri, Lakmal Chathuranga, Karen Mera

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Symmetrical Modular Optical Phased Array With Combined Spatial and Amplitude Modulation for Scalable Indoor Wireless Networks by Kosala Herath, Malin Premaratne, Sharadhi Gunathilake, Ampalavanapillai Nirmalathas

“…Furthermore, we introduce a new symmetrical excitation mechanism combined with spatial modulation for data symbol encoding within the MOPA architecture. …”
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Spatial patterns of multidrug resistant tuberculosis and relationships to socio-economic, demographic and household factors in northwest Ethiopia. by Kefyalew Addis Alene, Kerri Viney, Emma S McBryde, Archie C A Clements

“…<h4>Background</h4>Understanding the geographical distribution of multidrug-resistant tuberculosis (MDR-TB) in high TB burden countries such as Ethiopia is crucial for effective control of TB epidemics in these countries, and thus globally. We present the first spatial analysis of multidrug resistant tuberculosis, and its relationship to socio-economic, demographic and household factors in northwest Ethiopia.…”
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Revealing multi-scale spatial synergy of mega-city region from a human mobility perspective by Bichen Fang, Mingxiao Li, Zhengdong Huang, Yang Yue, Wei Tu, Renzhong Guo

“…To this end, this study presents an alternative data-driven framework to reveal the multi-scale spatial synergy of mega-city regions from a human mobility perspective. …”
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Health-care distribution of patients with genitourinary birth defects in Colombia: a spatial analysis of registered cases by Jessica Santander, Andrés Gutiérrez, Marcela Pérez-Sosa, María P. Donoso, Nicolas Fernandez

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A method for quantifying uncertainty in spatially interpolated meteorological data with application to daily maximum air temperature by C. T. Doherty, C. T. Doherty, W. Wang, H. Hashimoto, H. Hashimoto, I. G. Brosnan

“…This paper describes, applies, and evaluates a method for quantifying prediction uncertainty in spatially interpolated estimates of meteorological variables. …”
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Modeling of spatial spread of COVID-19 pandemic waves in Russia using a kinetic-advection model by V. V. Aristov, A. V. Stroganov, A. D. Yastrebov

“…The investigated possibility of predicting the spatial spread of the virus according to the time lag of reaching the peak of infections in Russia as a whole as compared to Moscow is connected with geographical features: in Russia, as in some other countries, the main source of infection can be identified. …”
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Research on temporal-spatial distribution differences and formation mechanisms of NPP in the Lanzhou section of the yellow river mainstream by Jin Ma, Xuan Yang, Xiaodan Li, Lide Zhang, Jiaojiao Lei, Lina Wang, Xuelu Liu

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Patterns of West Nile virus vector co-occurrence and spatial overlap with human cases across Europe by Shirin Taheri, Mikel Alexander González, María José Ruiz-López, Ramón Soriguer, Jordi Figuerola

“…Our results also revealed a strong spatial overlap between hotspots of human WNV cases and vector co-occurrence, highlighting regions of elevated transmission risk.The high-risk hotspots identified in this large-scale study can guide local surveillance efforts and optimize resource allocation, ultimately enhancing the effectiveness of WNV surveillance.…”
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