Impact of Multiscale Heterogeneous Sediments and Boundary Conditions on Dispersivity Spatial Variations by Ziqi Ma, Linlin Qi, Zhenxue Dai, Zhijie Yang, Yue Ma, Dayong Wang, Kenneth C. Carroll, Mohamad Reza Soltanian

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Evaluation of CMIP Earth System Models on Root Biomass Simulation by Ke ZHOU, Youqi SU, Yu ZHANG, Minhong SONG, Tongwen WU, Linfeng YANG, Xizhao WANG, Tianya LI

“…Roots play an important role in the carbon cycle of ecosystems.The Earth System Models （ESMs） of the Coupled Model Intercomparison Project （CMIP） have been widely used to simulate and predict root biomass.In this paper， the spatial distribution， dynamic change， and comparison with observed values of root biomass of 14 ESMs simulated historical experiments were analyzed.The results showed that： （1） The global distribution of multi-year average from 1850 to 2005 of root biomass indicated that 7 ESMs had maximum or minimum values， while the rest ESMs showed that root biomass was higher in the middle and high latitudes of the equator and the northern hemisphere.The root biomass distribution at different latitudes showed that 40°S is also one of the high value areas； （2） The simulation results from 1995 to 2005 are compared with the site observation data （1990 -2010） in different climatic zones by using SS index， the result showed deviations are relatively large but the simulation effect of temperate zone is slightly better than frigid zone and tropical zone.On the global scale， BCC-CSM2-MR is the best simulated ESM； （3） In the Qinghai-Xizang Plateau， ESMs can reasonably simulate the seasonal variation over the years 1850 to 2005 of root biomass， but the relationship between interannual variation of the simulated root biomass and the meteorological factors （temperature， precipitation） by different ESMs is different.In order to conduct more precise and in-depth research and analysis， in addition to improving the model， it is also necessary to improve the collection of observational data.…”
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Movement Patterns and Habitat Suitability of Translocated Sumatran Tigers (Panthera tigris sumatrae) by Farhan Reza Pahlevi, Lilik Budi Prasetyo, Dolly Priatna

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Spatial and Temporal Changes in Nutrient Source Contribution in a Lowland Catchment Within the Baltic Sea Region Under Climate Change Scenarios by Damian Bojanowski, Paulina Orlińska‐Woźniak, Paweł Wilk, Ewa Jakusik, Ewa Szalińska

“…To track spatial and seasonal changes of total nitrogen and phosphorus for the Wełna River (central Poland), we used climate change data and the SWAT model. …”
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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

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IMPROVE OF UNCERTAIN MICROSATELLITE MAGNETIC CLEANLINESS BASED ON MAGNETIC FIELD SPATIAL HARMONICS COMPENSATION by Б.І. Кузнецов, Т.Б. Нікітіна, І.В. Бовдуй, К.В. Чуніхін, В.В. Коломієць, Б.Б. Кобилянський

“…Both vector game solution calculated based on particles multi-swarm optimization (PMSO) algorithms from Pareto optimal solutions taking into account binary preference relations. Prediction model and location of compensating units in spherical coordinates as well as multipole harmonic coefficients of dipoles, quadrupoles and octupoles are calculated during prediction and control of uncertain microsatellite MC. …”
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Evaluation of Statistical Models of NDVI and Agronomic Variables in a Protected Agriculture System by Edgar Vladimir Gutiérrez-Castorena, Joseph Alejandro Silva-Núñez, Francia Deyanira Gaytán-Martínez, Vicente Vidal Encinia-Uribe, Gustavo Andrés Ramírez-Gómez, Emilio Olivares-Sáenz

“…This has created a database to generate predictive models of development and yield as a function of nutrient status. …”
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Evolution and Predictive Analysis of Spatiotemporal Patterns of Habitat Quality in the Turpan–Hami Basin by Yaqian Li, Yongqiang Liu, Yan Qin, Kun Zhang, Reifat Enwer, Weiping Wang, Shuai Yuan

“…Additionally, the InVEST-PLUS coupling model was employed to forecast habitat conditions under three different scenarios in 2050. …”
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Quantifying 3D coral reef structural complexity from 2D drone imagery using artificial intelligence by Aviv Suan, Simone Franceschini, Joushua Madin, Elizabeth Madin

“…The validation of our model resulted in R2 values of 0.71, 0.65, and 0.56 for each metric, respectively, indicating a robust predictive capability. …”
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Prediction of Surface Water Temperature and Its Spatial-Temporal Variation Characteristics of 11 Main Lakes in Yunnan–Guizhou Plateau by Shanshan Xu, Kun Yang, Xiaolu Zhou, Jie Zhang, Chenghao Yang, Yi Luo

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Establishment of agricultural drought monitoring at different spatial scales in southeastern Europe by Andreja SUŠNIK, Tjaša POGAČAR, Gregor GREGORIČ, Jožef ROŠKAR, Andrej CEGLAR

“…In the study two specific products designed for regional scale are described: preliminary maps of the SPI (Standardized Precipitation Index) and products generated by implementation of numerical weather prediction model. It seems to be a lot of potential in both products for a first overview of key meteorological parameters in the region. …”
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Current and future climate suitability for the hazel dormouse in the UK and the impact on reintroduced populations by Emma L. Cartledge, Joe Bellis, Ian White, Jane L. Hurst, Paula Stockley, Sarah Dalrymple

“…Here, we use species distribution models (SDMs) to map climate suitability for dormice in the UK. …”
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A dynamic prediction method for surface mining subsidence based on dynamic probability integral model and Logistic model by Lei HAN, Xinxin QI, Tianjun WANG, Chunmin PEI, Xudong WANG

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Ultra-short-term Multi-region Power Load Forecasting Based on Spearman-GCN-GRU Model by Junying WU, Xin LU, Hong LIU, Bin ZHANG, Shouliang CHAI, Yunchun LIU, Jianan WANG

“…To improve the prediction accuracy of multi-region power load, an ultra-short-term multi-region power load forecasting model based on Spearman-GCN-GRU is proposed with focus on the spatial-temporal correlation analysis of multi-region power data. …”
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Enhanced streamflow prediction with SWAT using support vector regression for spatial calibration: A case study in the Illinois River watershed, U.S. by Lifeng Yuan, Kenneth J Forshay

“…However, the highly non-linear relationship between rainfall and runoff makes prediction difficult with desirable accuracy. To improve the accuracy of monthly streamflow prediction, a seasonal Support Vector Regression (SVR) model coupled to the Soil and Water Assessment Tool (SWAT) model was developed for 13 subwatersheds in the Illinois River watershed (IRW), U.S. …”
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Golden eagle optimized CONV-LSTM and non-negativity-constrained autoencoder to support spatial and temporal features in cancer drug response prediction by Wesam Ibrahim Hajim, Suhaila Zainudin, Kauthar Mohd Daud, Khattab Alheeti

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Precise Spatial Prediction of Rice Seedlings From Large-Scale Airborne Remote Sensing Data Using Optimized Li-YOLOv9 by Jayakrishnan Anandakrishnan, Arun Kumar Sangaiah, Hendri Darmawan, Nguyen Khanh Son, Yi-Bing Lin, Mohammed J. F. Alenazi

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Analyzing the determinant factors of spatial groundwater availability in the Akaki catchment, Central Ethiopia by Getamesay Nigussie, Mekuria Argaw, Dessie Nedaw, Tsegaye Tadesse, Andreas Hartmann

“…Hence, this study investigated the spatial availability of groundwater within the catchment by considering eight different factors. …”
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Predicting the spatial demand for public charging stations for EVs using multi-source big data: an example from jinan city, china by Qimeng Ren, Ming Sun

“…By using multi-source big data, this paper analyzes the population distribution, traffic organization, infrastructure, land use and regional economy of Jinan urban area, China, and constructs a comprehensive evaluation index system to predict the spatial demand of PCS for EVs. We analyse: (1) Distribution of population activities on weekday and rest days, the closeness and betweenness of road network, high-density area, commerce, public service facilities, parks, transportation facilities, residential area, building coverage, floor area ratio, economic development area and housing price level. (2) Correlation and influence weights of 14 evaluation indexes and PCS layout. (3) Prediction of spatial demand distribution of PCS. (4) Comparison of current PCS distribution and spatial demand prediction results. …”
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Spatial patterns and MRI-based radiomic prediction of high peritumoral tertiary lymphoid structure density in hepatocellular carcinoma: a multicenter study by Juan Chen, Xiong Chen, Kai Fu, Lan Zhou, Shichao Long, Mengsi Li, Linhui Zhong, Aerzuguli Abudulimu, Wenguang Liu, Deng Pan, Ganmian Dai, Yigang Pei, Wenzheng Li

“…This study aimed to elucidate biological differences related to pTLS density and develop a radiomic classifier for predicting pTLS density in HCC, offering new insights for clinical diagnosis and treatment.Methods Spatial transcriptomics (n=4) and RNA sequencing data (n=952) were used to identify critical regulators of pTLS density and evaluate their prognostic significance in HCC. …”
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