Assessing Habitat Suitability for the Invasive Species Lantana camara on Bali Island: A Model Using the Biodiversity and Climate Change Virtual Laboratory (BCCVL) by Rajif Iryadi, Sutomo, Muhammad Hadi Saputra, Nida Humaida, Eko Pujiono, Jalma Giring Sukmawati, Aditya Hani, Komang Kartika Indi Swari, Dewa Ayu Intan Sari, Muhammad Bima Atmaja, Wieke Herningtyas, Reni Setyo Wahyuningtyas, Eddie van Etten

“…L. camara distribution prediction model in Bali used the Bioclim data input by identifying areas of low, medium, and high habitat suitability. …”
Get full text

THE DISTRIBUTION AND RELATIVE ABUNDANCE OF WILD TURKEYS IN FLORIDA by David S. Nicholson, Larry S. Perrin, Cory Morea, Roger Shields

“…This information will be used in conjunction with habitat suitability models, landownership, and other available data to prioritize future wild turkey management efforts in Florida.…”
Get full text

Generative autoencoder to prevent overregularization of variational autoencoder by YoungMin Ko, SunWoo Ko, YoungSoo Kim

“…The variational autoencoder is a generative model that performs variational inference to estimate a low-dimensional posterior dis-tribution given high-dimensional data. …”
Get full text

Impact of cold spells on hospitalizations of residents in Hengyang City from 2017 to 2023: A time series study based on different definitions of cold spells by Xiaoming DENG, Guanxiang ZOU, Weixiong PENG, Bin LI

“…A generalized linear model (GLM) combined with a distributed lag nonlinear model (DLNM) was used to assess the added effects of cold spells on non-accidental hospitalizations, as well as hospitalizations for circulatory system diseases and respiratory system diseases, after controlling the main effect of temperature. …”
Get full text

Time series analysis of the effect of diurnal temperature range on daily inpatients with chronic kidney disease in Urumqi by WU Ruikai, ZHANG Ying, YANG Haofeng, MA Long, SU Deqi

“…A distributed lag no-linear model (DLNM) was used to analyze the relationship between DTR and daily inpatients in CKD, controlling for day of the week effect, holiday effect, long-term trend and other factors, analyzing the relationship between DTR and CKD daily hospitalization.Results The expose-response curves of the number of patients admitted to CKD daily and DTR (with a lag of 0-21 days) showed an "N" shape, and the hospitalization risk of CKD patients increased first and then decreased with the increase of DTR. …”
Get full text

Potential Distribution of <i>Anoplophora horsfieldii Hope</i> in China Based on MaxEnt and Its Response to Climate Change by Dan Yong, Danping Xu, Xinqi Deng, Zhipeng He, Zhihang Zhuo

“…This study comprehensively analyzed the key environmental factors influencing the geographical distribution of <i>A. horsfieldii</i> and its spatiotemporal dynamics by integrating multi-source environmental data and employing ecological niche modeling. …”
Get full text

Impact of medical resources in residential area on unmet healthcare needs: Findings from a multi-level analysis of Korean nationwide data by Seo Yeong Choi, Il Yun, Jong Youn Moon

Get full text

Separation of benzene from cyclohexane by liquid-liquid extraction for a pseudo-ternary system with (sulfolane + 2-propanol) solvent: An experimental and modeling study by Seyed Mohammad Reza Seyedein Ghannad, Mohammad Reza Gharib, Ali Heydari

“…The low values of RMSD indicate that the ternary and pseudo-ternary systems could be well-fitted by the NRTL and UNIQUAC models. …”
Get full text

Distributed trust management scheme based on blockchain in Internet of vehicles by Haibo ZHANG, Yukun CAO, Kaijian LIU, Ruyan WANG

“…Aiming at the security problems caused by the low efficiency and accuracy of malicious vehicle identification in Internet of vehicles, a distributed trust management scheme based on blockchain in Internet of vehicles was proposed.A false information identification strategy was designed by aggregating the scoring information of vehicles, combined with Bayesian inference model.A reputation value updating algorithm was designed by combining the historical interaction information of vehicles and traffic information, malicious vehicles were identified by the reputation threshold.A blockchain was constructed roadside units to realize the distributed storage of traffic data and vehicle reputation values.The traditional proof of work consensus mechanism was improved to dynamically change the difficulty of miner node generating a block through the event level and the number of vehicles involved in scoring, and the waiting mechanism was used to temporarily stop the nodes that had recently blocked from participating in the election process of miner nodes, thus reducing the resource consumption caused by repeated calculations.The simulation results show that the proposed scheme can effectively identify false information, resist the deceptive behavior of malicious vehicles, improve the identification efficiency of malicious vehicles, reduce resource consumption, and is effective and feasible in distributed trust management for Internet of vehicles.…”
Get full text

Distributed trust management scheme based on blockchain in Internet of vehicles by Haibo ZHANG, Yukun CAO, Kaijian LIU, Ruyan WANG

“…Aiming at the security problems caused by the low efficiency and accuracy of malicious vehicle identification in Internet of vehicles, a distributed trust management scheme based on blockchain in Internet of vehicles was proposed.A false information identification strategy was designed by aggregating the scoring information of vehicles, combined with Bayesian inference model.A reputation value updating algorithm was designed by combining the historical interaction information of vehicles and traffic information, malicious vehicles were identified by the reputation threshold.A blockchain was constructed roadside units to realize the distributed storage of traffic data and vehicle reputation values.The traditional proof of work consensus mechanism was improved to dynamically change the difficulty of miner node generating a block through the event level and the number of vehicles involved in scoring, and the waiting mechanism was used to temporarily stop the nodes that had recently blocked from participating in the election process of miner nodes, thus reducing the resource consumption caused by repeated calculations.The simulation results show that the proposed scheme can effectively identify false information, resist the deceptive behavior of malicious vehicles, improve the identification efficiency of malicious vehicles, reduce resource consumption, and is effective and feasible in distributed trust management for Internet of vehicles.…”
Get full text

DiffViT-IBFD: A rolling bearing fault diagnosis approach based on diffusion model and vision transformer under data imbalance conditions by Zheru Dong, Wen Zhao, Di Zhu, Zixin Zhang, Yuheng Ren

“…Rolling Bearing fault data collected from industrial sites often exhibit class distribution imbalance, which significantly degrades the performance of deep learning-based intelligent bearing fault diagnosis models. …”
Get full text

Low-carbon transition and common prosperity: a quasi-natural experiment based on pilot policies of low-carbon cities by Jingyi Liang, Cuixia Qiao

“…Using panel data from 279 prefecture-level cities in China from 2010 to 2022, this study empirically examines the impact of low-carbon city pilot policies on common prosperity and their underlying mechanisms.MethodsCommon prosperity is measured using principal component analysis, and a staggered difference-in-differences model is applied for empirical analysis. …”
Get full text

Fusion of Geochemical Data and Remote Sensing Data Based on Convolutional Neural Network by Shi Bai, Jie Zhao, Tianhan Yu, Yunqing Shao

“…Ag and Cr are selected to verify the mobility and generalization of the model. Compared with the existing interpolation methods, the results show that the fusion method based on the model can better characterize the distribution law of geochemical data.…”
Get full text

Characterizing Offshore Freshened Groundwater Salinity Patterns Using Trans‐Dimensional Bayesian Inversion of Controlled Source Electromagnetic Data: A Case Study From the Canterbu... by Zahra Faghih, Amir Haroon, Marion Jegen, Romina Gehrmann, Katrin Schwalenberg, Aaron Micallef, Jan Dettmer, Christian Berndt, Joshu Mountjoy, Bradley A. Weymer

“…We integrate resistivity posterior probability distributions with borehole and seismic reflection data to estimate pore‐water salinity with corresponding uncertainty estimates. …”
Get full text

Modeling the health and economic implications of adopting a 1-dose 9-valent human papillomavirus vaccination program in adolescents in low/middle-income countries: An analysis of I... by Vincent Daniels, Kunal Saxena, Oscar Patterson-Lomba, Andres Gomez-Lievano, Jarir At Thobari, Nancy Durand, Evan Myers

“…<h4>Objective</h4>To evaluate the public health impact and cost-effectiveness of implementing a 1-dose or a 2-dose program of the 9-valent HPV vaccine in a low- and middle-income country (LMIC).<h4>Methods</h4>We adapted a dynamic transmission model to the Indonesia setting, and conducted a probabilistic sensitivity analysis using distributions reflecting the uncertainty in levels and durability of protection of a 1-dose that were estimated under a Bayesian framework incorporating 3-year vaccine efficacy data from the KEN SHE trial (base-case) and 10 year effectiveness data from the India IARC study (alternative analysis). …”
Get full text

Bayesian feedback in the framework of ecological sciences by Mario Figueira, Xavier Barber, David Conesa, Antonio López-Quílez, Joaquín Martínez-Minaya, Iosu Paradinas, Maria Grazia Pennino

“…This paper focuses on a sequential Bayesian procedure for linking two models by updating prior distributions. The Bayesian paradigm is implemented together with the integrated nested Laplace approximation (INLA) methodology, which is an effective approach for making inference and predictions in spatial models with high performance and low computational cost. …”
Get full text

Spatial Change of Dominant Baltic Sea Demersal Fish Across Two Decades by Liam MacNeil, Frane Madiraca, Saskia Otto, Marco Scotti

“…For cod, we conclude that biomass was less reliably predicted in comparison to the other major Baltic demersals studied here, warranting dynamic fishing covariates as a formerly major commercial fishing target. These models approach more dynamic species distribution models and are increasingly valuable to constrain uncertainties in biogeographic forecasting which often rely on annually‐averaged response curves, occurrence data, and suitability maps which rarely discriminate between areas of high and low biomass areas in space and time.…”
Get full text

Improving Classification Performance by Addressing Dataset Imbalance: A Case Study for Pest Management by Antonello Longo, Maria Rizzi, Cataldo Guaragnella

“…In this way, the model can learn from balanced data distribution in which some classes have a high correlation factor. …”
Get full text

Reflective Distributed Denial of Service Detection: A Novel Model Utilizing Binary Particle Swarm Optimization—Simulated Annealing for Feature Selection and Gray Wolf Optimization-... by Daoqi Han, Honghui Li, Xueliang Fu

“…IDSs guarantee the normal operation of the network by tracking network traffic and spotting possible assaults, thereby safeguarding data security. However, traditional intrusion detection methods encounter several issues such as low detection efficiency and prolonged detection time when dealing with massive and high-dimensional data. …”
Get full text

Floating Neutral Detection Using Actual Generation of Form 2S Meters by I. Vicente, A. Arrinda, J. E. Rodriguez-Seco, L. Piyasinghe

Get full text