Fire Regime in a Peatland Restoration Area: Lesson from Central Kalimantan by Bekti Larasati, Mamoru Kanzaki, Ris Hadi Purwanto, Ronggo Sadono

“…Moreover, spatial analysis using Kernel Density Estimation (KDE) showed fire recur in degraded areas. …”
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Patterns of Location and Other Determinants of Retail Stores in Urban Commercial Districts in Changchun, China by Feilong Hao, Yuxin Yang, Shijun Wang

“…Using point of interest data and consumer survey data in three main commercial districts in Changchun, China, this study investigates the spatial structures of commercial districts and the patterns of distribution of retail stores to assess the determinants of the development of retail stores in commercial districts. Kernel density estimation, nearest neighbor index, and Pearson’s correlation analysis were used for this study. …”
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Temporal–Spatial Dynamics and Collaborative Effects of Cropland Resilience in China by Liang Luo, Yetong Li, Wenjie Ma, Jianbo Rong, Jie Wei, Yong Cui, Tingting Qu

“…Additionally, it employs quantitative analysis methods, including kernel density estimation, the standard deviation ellipse, the Theil Index, and the geographical detector, to systematically examine the spatiotemporal dynamics of cropland resilience and its driving factors in China. …”
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Level measurement, regional variations, and the dynamic evolution of active aging in China—analysis based on CHARLS tracking data by Jiru Guo, Xiaoli Zhang, Xiaoli Zhang, Longyin Chen, Hong Yang

“…Exploring the current state and evolutionary trends of active aging over the past decade is a fundamental prerequisite and the primary task for implementing this strategy.MethodsBased on data from the China Health and Retirement Longitudinal Study (2011-2018), this study primarily employs methods such as the entropy method, Gini coefficient, Moran index, and Kernel density estimation to analyze the development level, regional differences, and dynamic evolution of active aging in China.Results(1) From a general point of view, the overall level of active aging in China has not been high in the past decade, but has shown a rising trend year by year. …”
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Two-stage efficiency evaluation of industrial water resources and the role of digital inclusive finance: insight from Yangtze River Delta by Linjie Feng, Tingting Liu, Zhenjie Yang, Yi Shi, Hongxi Chen, Ka Leong Chan, Bin Chen

“…As shown by the Kernel density Estimation, the degree of efficiency dispersion within same metropolitan area is reducing; and (4) digital inclusive finance will boost overall efficiency and water treatment efficiency, with green innovation as a mediating factor. …”
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Multi-scenario analysis of green water resource efficiency under carbon emission constraints in the Chengdu-Chongqing urban agglomeration, China: A system dynamics approach by Keyao Yu, Zhigang Li

“…We analyze its dynamic trends using kernel density estimation and standard deviation ellipse methods. …”
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Gravity and Remote Sensing Methods as a Solution in Identifying Geothermal Reservoirs on Volcanoes by null Wiyono, Salman Hamja Siombone, Sukir Maryanto

“…The quantitative interpretation of the gravity data is based on the surface density estimation graph using the Parasnis method and 3D inversion modeling, using residual Bouguer anomaly data. …”
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Spatiotemporal differentiation and influencing factors of primary, secondary, and tertiary industries integration in China’s four major tea-producing regions by ZHENG Feifei, ZHAN Huilong, LEI Guoquan, CHEN Meiying

“…Using spatial analysis techniques such as kernel density estimation, convergence analysis, the diamond model, and Multi-scale Geographically Weighted Regression, the study explored the spatiotemporal change patterns of industrial integration and the spatial heterogeneity of influencing factors. …”
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Influence of human settlements factors on the spatial distribution patterns of traditional villages in Liaoning province by Guiqiao Tao, Xueming Li, Shenzhen Tian, Hang Li, Yishan Song

“…Employing the Gini coefficient, kernel density estimation, and the Geographically Weighted Regression (GWR) model, this study analyzes the impact of human settlements factors on the spatial distribution patterns of traditional villages in Liaoning province. …”
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Spatiotemporal evolution and driving factors of the synergistic effects of pollution control and carbon reduction in China by Qinggang Meng, Xiaolan Chen, Hui Wang, Wanfang Shen, Peixin Duan, Xinyue Liu

“…The distribution patterns, transition probabilities, and driving mechanisms of the CCD of PCCR are explored using kernel density estimation, Markov chains, and geographically and temporally weighted regression (GTWR). …”
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Spatial-temporal distribution and evolution of medical and health talents in China by Lei Zhang, Jie Tang, Qianqian Zhou, Yu Song, Dayong Zhang

“…Furthermore, the regional dynamic distribution of MHT was analyzed using kernel density estimation diagrams. The spatial autocorrelation of MHT was assessed through global and local Moran’s I, and the spatial gap and decomposition of MHT were analyzed using the Dagum Gini coefficient. …”
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Estimation the pH of CO2-saturated NaCl solutions using gene expression programming: Implications for CO2 sequestration by Mohammad Rasool Dehghani, Parirokh Ebrahimi, Moein Kafi, Hamed Nikravesh, Yousef Kazemzadeh

“…A cumulative frequency plot of absolute relative error showed all data points had errors below 0.102, with over 90 % below 0.0615. Kernel density estimation plots confirmed the model generally underestimated pH values. …”
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Validation of musculoskeletal segmentation model with uncertainty estimation for bone and muscle assessment in hip-to-knee clinical CT images by Mazen Soufi, Yoshito Otake, Makoto Iwasa, Keisuke Uemura, Tomoki Hakotani, Masahiro Hashimoto, Yoshitake Yamada, Minoru Yamada, Yoichi Yokoyama, Masahiro Jinzaki, Suzushi Kusano, Masaki Takao, Seiji Okada, Nobuhiko Sugano, Yoshinobu Sato

“…The high segmentation and muscle volume/density estimation accuracy and the high accuracy in failure detection based on the predictive uncertainty exhibited the model’s reliability for analyzing individual MSK structures in large-scale CT databases.…”
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Geo-behavioural predictors of diagnosed hypertension in Igbo Ora Area, Oyo State, Nigeria by Olalekan J. Taiwo, Joshua O. Akinyemi, Ayodeji Adebayo, Oluwafemi A. Popoola, Rufus O. Akinyemi, Onoja M. Akpa, Paul Olowoyo, Akinkunmi P. Okekunle, Ezinne O. Uvere, Omotolani Titilayo Ajala, Chukwuemeka Nwimo, Olayinka J. Adebajo, Adewale E. Ayodele, Ayodeji Salami, Oyedunni S. Arulogun, Olanrewaju Olaniyan, Richard W. Walker, Carolyn Jenkins, Bruce Ovbiagele, Mayowa Owolabi

“…Spatial patterns were analyzed using the Nearest Neighbour Statistic, Ripley K Function, and Kernel Density Estimation, while Binomial logistic regression identified predictors. …”
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Identification of the primary pollution sources and dominant influencing factors of soil heavy metals using a random forest model optimized by genetic algorithm coupled with geodet... by Tong Liu, Mingshi Wang, Mingya Wang, Qinqing Xiong, Luhao Jia, Wanqi Ma, Shaobo Sui, Wei Wu, Xiaoming Guo

“…Pollution sources were identified using Absolute Principal Component Score (APCS), with 8 anthropogenic factors, 9 natural factors, and 4 soil physicochemical properties mapped using Geographic Information System (GIS) kernel density estimation. Geodetector and a genetic algorithm optimized random forest model (GA-RF) were employed to quantify the dominant factors and precisely identify pollution sources. …”
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Estimation of blue carbon stock in the Liaohe Estuary wetland based on soil thickness and multi-scenario modeling by Lina Ke, Nan Lei, Shilin Zhang, Changkun Yin, Yao Lu, Lei Wang, Qin Tan, Yu Zhao, Quanming Wang

“…This paper took the Liaohe Estuary wetland as the study area, combined with the distributional difference characteristics of soil carbon density in wetlands, constructed a wetland carbon density estimation method that improved the SoLIM model, and coupled the PLUS and InVEST models to achieve the fine estimation of wetland blue carbon stock under different simulation scenarios. …”
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Status and annual change of vulnerability among middle-aged and elderly people with cardiometabolic multimorbidity in a division of Xinjiang Production and Construction Corps, 2017... by Ziqi WANG, Jieting CHEN, Mei ZHANG, Mingxia JING

“…The entropy weighting method was used to dynamically evaluate the vulnerability level of the CMM population from 2017 to 2021. Kernel density estimation was used to analyze the spatial and temporal evolution characteristics of the vulnerability level of the CMM population in different community types. …”
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Optimal timing of organs-at-risk-sparing adaptive radiation therapy for head-and-neck cancer under re-planning resource constraints by Fatemeh Nosrat, Cem Dede, Lucas B. McCullum, Raul Garcia, Abdallah S.R. Mohamed, Jacob G. Scott, James E. Bates, Brigid A. McDonald, Kareem A. Wahid, Mohamed A. Naser, Renjie He, Aysenur Karagoz, Amy C. Moreno, Lisanne V. van Dijk, Kristy K. Brock, Jolien Heukelom, Seyedmohammadhossein Hosseinian, Mehdi Hemmati, Andrew J. Schaefer, Clifton D. Fuller

“…The MDP parameters were derived from a dataset comprising 52 HNC patients treated between 2007 and 2013. Kernel density estimation was used to smooth the sample distributions. …”
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Dense Nursery Stock Detecting and Counting Based on UAV Aerial Images and Improved LSC-CNN by PENG Xiaodan, CHEN Fengjun, ZHU Xueyan, CAI Jiawei, GU Mengmeng

“…[Conclusions]The improved LSC-CNN model integrated the advantages of point supervision learning from density estimation methods and the generation of target bounding boxes from detection methods.These improvements demonstrate the enhanced performance of the improved LSC-CNN model in terms of accuracy, precision, and reliability in detecting and counting trees. …”
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A Framework to Estimate Local Atmospheric Densities With Reduced Drag‐Coefficient Biases by Vishal Ray, Daniel J. Scheeres, Suood Alnaqbi, W. Kent Tobiska, Siamak G. Hesar

“…We report an improvement of up to 70% in density estimates for the simulations. Finally, POD data from Spire satellites are used for validation. …”
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