Multivariate Analyses with Two-Step Dimension Reduction for an Association Study Between ¹¹C-Pittsburgh Compound B and Magnetic Resonance Imaging in Alzheimer’s Disease... by Atsushi Kawaguchi, Fumio Yamashita

“…By applying this method to imaging data of 61 patients with AD (age: 55–85), the first component showed the strongest correlation with the composite score, owing to the supervised feature. The spatial pattern included the hippocampal and parahippocampal regions for MRI. …”
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On the robustness of the emergent spatiotemporal dynamics in biophysically realistic and phenomenological whole-brain models at multiple network resolutions by Cristiana Dimulescu, Cristiana Dimulescu, Ronja Strömsdörfer, Ronja Strömsdörfer, Agnes Flöel, Agnes Flöel, Klaus Obermayer, Klaus Obermayer, Klaus Obermayer

“…Whole-brain modelling allows us to explore candidate mechanisms causing the observed patterns. However, it is not fully established how the choice of model type and the networks’ spatial resolution influence the simulation results, hence, it remains unclear, to which extent conclusions drawn from these results are limited by modelling artefacts. …”
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Research on the Influence of SST in Different Regions on the Interannual Variability of Winter Fog Days over Eastern China by Qisheng CEN, Peng LIU

“…Based on observational data， it is evident that fog occurrence in Eastern China is notably higher during winter compared to other months.Spatial analysis of climatological statistics reveals a distinct heterogeneity， dividing Eastern China into northern and southern regions based on fog day patterns.Furthermore， winter can be subdivided into early （November and December） and late （January and February） periods， characterized by varying trends in fog occurrence and interregional correlations.Examining the relationship between sea surface temperature （SST） and fog days across both southern and northern China throughout winter， significant influences emerge.During early winter， fog days in both regions are markedly impacted by SST anomalies in the tropical Pacific.Conversely， in late winter， while the north Atlantic SST exerts a considerable influence on fog days in northern China， southern China continues to be strongly affected by tropical Pacific SST.Analyzing atmospheric circulation patterns reveals distinct mechanisms driving fog occurrences in different seasons.In early winter， warm SST anomalies in the tropical Pacific drive northward movement of the Western North Pacific Subtropical High， resulting in anticyclonic anomalies over northern Japan and weakened Siberian High， leading to increased fog days in both southern and northern areas of Eastern China.Conversely， in late winter， weakened influence from the tropical Pacific shifts the anomalous southerly winds only over southern China， while the north Atlantic SST anomalies induce anomalous southeasterly winds over northern areas， enhancing moisture transport from the north Pacific， with relatively stable atmospheric structure， thus significantly increasing fog days over northern China.…”
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Application of Multi-Scale Geological Modeling Technology in Sweet Spot Prediction of Shale Oil Reservoirs by HU Laidong, HUO Hanyong, GUAN Qianqian, TANG Caixia, TAO Ji, ZHANG Yuxuan

“…Considering fracture impacts on modeling, multi-scale observations (micron/millimeter/meter-scale) are employed to identify fractures, clarify their characteristics and development patterns. Under the spatial constraints of shale lithofacies models, stochastic simulations are conducted using discrete fracture network (DFN) models, structural fracture occurrence index models, and development intensity models to establish 3D fracture network models. …”
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Hydro-Climatic Variability and Peak Discharge Response in Zarrinehrud River Basin, Iran, Between 1986 and 2018 by Farnaz Mohammadi, Jaan H. Pu, Yakun Guo, Prashanth Reddy Hanmaiahgari, Ozra Mohammadi, Mirali Mohammadi, Ebrahim Al-Qadami, Mohd Adib Mohammad Razi

“…This confirms a synchronisation of rainfall trends, which are influenced by climate changes or regional hydrological patterns. This temporal offset between stations confirms the spatial and seasonal variation in rainfall distribution across the basin. …”
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GeoBM: A Python-based tool for integrated visualization of global bibliometric data by Chun Chong Fu, Jorge Fleta-Asín, Fernando Muñoz, Carlos Sáenz-Royo, Loo Keat Wei

“…Conventional geospatial visualization techniques—most notably choropleth maps—often introduce significant distortions due to their inability to adequately account for spatial heterogeneity and overdispersion in bibliometric distributions. …”
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Climate change impacts on the distribution and ecological niche overlap of Aromia bungii and its natural enemies: implications for biological control by Liang Zhang, Chaokun Yang, Ping Wang, Guanglin Xie, Wenkai Wang

“…Climate change is profoundly affecting the geographical distribution and ecological adaptability of species, posing new challenges to the spatial distribution patterns of pests and their natural enemies. …”
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Central nervous system infectious diseases mimicking multiple sclerosis: recognizing distinguishable features using MRI by Antonio Jose da Rocha, Ingrid Aguiar Littig, Renato Hoffmann Nunes, Charles Peter Tilbery

“…We discuss the most relevant imaging features in several infectious diseases that resemble MS and examine the primary spatial distributions of lesions and the gadolinium enhancement patterns related to MS. …”
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Conservation Law Analysis in Numerical Schema for a Tumor Angiogenesis PDE System by Pasquale De Luca, Livia Marcellino

“…The numerical schema demonstrates stable wave propagation patterns, in agreement with experimental observations. …”
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Assessment of Steady and Unsteady Full Annulus Simulations Predictivity for a Low-Speed Axial Fan at Load-Controlled Windmill by Aurélie Ortolan, Suk-Kee Courty-Audren, Nicolas Binder, Xavier Carbonneau, Yannick Bousquet, Florent Challas

“…A detailed analysis highlights that generic patterns of windmilling flows recorded on a steady approach are also reported on the unsteady case.…”
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Assessment of Urban Heat Island in an Agricultural Town (Oued Zenati-Algeria): Integrating Remote Sensing and GIS Analysis by Naidja Amina, Soltani Ines, Khammar Zedira

“…We calculated key indices (NDVI, NDBI, LST) to analyse UHI spatial patterns and their impact on different land cover types (urban, vegetation, agriculture). …”
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Health classification of pumps using transformer-based deep learning by Arunachalam Shivaa T V, Jayaprasanth Devakumar, Arunshankar Jayabalan

“…These DL models excel at understanding complex temporal and spatial patterns in sensor data, essential for accurate fault detection. …”
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Investigation and future projections of warm rain during the winter monsoon in the Western Java Sea, Indonesia by Wendi Harjupa, Wendi Harjupa, Wendi Harjupa, Eiichi Nakakita

“…Warm rain processes, driven by CLWC, are evident, as TRMM observations of shallow rainfall align with CLWC spatial distributions. AGCM simulations successfully replicate the observed CLWC patterns, showing strong agreement with TRMM data in the western region of Indonesia including WJS. …”
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Interpreting and evaluating digital soil mapping prediction uncertainty: A case study using texture from SoilGrids by Linda Lilburne, Anatol Helfenstein, Gerard B.M. Heuvelink, Andre Eger

“…The study objectives were to: 1) understand whether the provided uncertainty information is correct for both countries; 2) explore spatial patterns and relationships in the prediction error and uncertainty information using quantitative tools and new graphical analyses; 3) analyse whether these patterns and relations can be explained; and 4) explore how the uncertainty information and insights derived from graphical analyses might assist an end user to determine whether a map is suitable for their purpose. …”
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Spatiotemporal Dynamics of Emerging Foot-and-Mouth Disease, Bluetongue, and Peste Des Petits Ruminants in Algeria by Ilhem Zouyed, Sabrina Boussena, Nacira Ramdani, Houssem Eddine Damerdji, Julio A. Benavides, Hacène Medkour

“…These patterns may be influenced by species susceptibility, animal movement, trade, and climatic factors such as temperature and rainfall. …”
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An experimental study on seepage characteristics and grouting-induced permeability reduction of burnt rocks by Ziwei QIAN, Chunzhi TAN, Qiang SUN, Hai WANG, Gailing ZHANG

“…Through laboratory seepage and grouting experiments, this study revealed the seepage patterns and grouting-induced permeability mechanisms of typical burnt rock specimens. …”
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Time-lag effects of NEP and NPP to meteorological factors in the source regions of the Yangtze and Yellow Rivers by Hengshuo Zhang, Xizhi Lv, Yongxin Ni, Qiufen Zhang, Jianwei Wang, Li Ma

“…Vegetation productivity and ecosystem carbon sink capacity are significantly influenced by seasonal weather patterns. The time lags between changes in these patterns and ecosystem (including vegetation) responses is a critical aspect in vegetation-climate and ecosystem-climate interactions. …”
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Integrating the landscape scale supports SAR-based detection and assessment of the phenological development at the field level by Johannes Löw, Steven Hill, Insa Otte, Christoph Friedrich, Michael Thiel, Tobias Ullmann, Christopher Conrad

“…Applied to the DEMMIN site (Germany), the analysis revealed consistent TSM-GDD relationships for wheat, rape, and sugar beet, with descriptors such as soil fertility and water availability explaining spatial patterns (R2 ≈ 0.8). Key novelties include the identification of low tracking ranges in drought years, the demonstration of the impact of orbit-specific incidence angles on monitoring fidelity, and the highlighting of Sentinel-1’s ability to resolve phenological variance across fragmented landscapes. …”
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Early Breast Cancer Prediction Using Thermal Images and Hybrid Feature Extraction-Based System by Doaa Youssef, Hanan Atef, Shaimaa Gamal, Jala El-Azab, Tawfik Ismail

“…This valuable information is encoded in the spatial and local intensity variations of acquired breast images, revealing hidden patterns. …”
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Single-shot super-resolved fringe projection profilometry (SSSR-FPP): 100,000 frames-per-second 3D imaging with deep learning by Bowen Wang, Wenwu Chen, Jiaming Qian, Shijie Feng, Qian Chen, Chao Zuo

“…However, the imaging speed of current FPP methods is generally capped at several kHz, which is limited by the projector-camera hardware and the number of fringe patterns required for phase retrieval and unwrapping. …”
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