Study on the Evolution and Prediction of Land Use and Landscape Patterns in the Jianmen Shu Road Heritage Area by Chenmingyang Jiang, Xinyu Du, Jun Cai, Hao Li, Qibing Chen

Get full text

Monitoring vegetation dynamics in Qinling–Daba mountains during 2001–2023 using an improved two-leaf model and remote-sensing datasets by Enjun Gong, Jing Zhang, Jun Wang

Get full text

Instability and uncertainty of carbon storage in karst regions under land use change: a case study in Guiyang, China by Heng Zhou, Heng Zhou, Mingdong Tang, Jun Huang, Jinting Zhang, Jingnan Huang, Jingnan Huang, Haijuan Zhao, Haijuan Zhao, Yize Yu

“…Instability was primarily due to transitions of Cropland-Forest, Forest-Cropland, Cropland-Grassland, and Cropland-Impervious, while uncertainties mainly arise from Cropland-Forest, Cropland-Impervious, and Grassland-Impervious transitions. (3) DEM, AI, Distance from national highways, SHDI, and Mean annual precipitation affected instability significantly. (4) Encouraging Shrub-Forest, Shrub-Cropland and Cropland-Forest conversions, and controlling Forest-Cropland, Forest-Shrub, and Cropland-Impervious conversions within the stable intervals of factors, can enhance carbon storage and reduce uncertainty. …”
Get full text

Influential predictors of azithromycin pharmacokinetics: a systematic review of population pharmacokinetics by Janthima Methaneethorn, Zheng Jiao, Rowan AlEjielat, Totsapol Jirasomprasert

Get full text

Machine Learning‐Based High‐Throughput Screening, Molecular Modeling and Quantum Chemical Analysis to Investigate Mycobacterium tuberculosis MetRS Inhibitors by Rajesh Maharjan, Kalpana Gyawali, Arjun Acharya, Madan Khanal, Kamal Khanal, Mohan Bahadur Kshetri, Dr. Madhav Prasad Ghimire, Dr. Tika Ram Lamichhane

Get full text

Cationic substitution, dynamical stability, thermal stability, electronic and thermoelectric properties in 2D dialkali metal monoxides via DFT and ML approach by S. Chellaiya, Thomas Rueshwin, R. D. Eithiraj

“…A ML model was trained to predict the ZT of 1T-KXO using random forest regression and linear regression.…”
Get full text

CNN-Based Optimization for Fish Species Classification: Tackling Environmental Variability, Class Imbalance, and Real-Time Constraints by Amirhosein Mohammadisabet, Raza Hasan, Vishal Dattana, Salman Mahmood, Saqib Hussain

“…Advanced preprocessing techniques, such as data augmentation, turbidity simulation, and transfer learning, were employed to enhance dataset robustness and address class imbalance. …”
Get full text

Assessing carbon storage dynamics in an ecological civilization demonstration zone amid rapid urbanization: A multi-scenario study of Guizhou Province, China by Rui Chen, Xuehai Fei, Jingyu Zhu, Weiduo Chen, Haiqiang Du, Yingqian Huang, Yi Shen, Yong Zhang, Aping Niu, Peng Xu

“…The results show that Guizhou’s carbon storage increased from 3423.13 Tg to 3475.42 Tg, with forest restoration increasing it by 301.62 Tg and agricultural expansion reducing it by 218.63 Tg. …”
Get full text

Optimal life-cycle adaptation of coastal infrastructure under climate change by Ashmita Bhattacharya, Konstantinos G. Papakonstantinou, Gordon P. Warn, Lauren McPhillips, Melissa M. Bilec, Chris E. Forest, Rahaf Hasan, Digant Chavda

Get full text

Comparative Study on Soil Infiltration Characteristics of Different Land Use Types in Horqin Sandy Land by Yin Jiawang, Ala Musa, Su Yuhang, Jiang Shaoyan

“…The initial infiltration rates ranged from 1.595 mm/min to 12.020 mm/min, and followed the order of bare sandy land>Caragana korshinskii plantation>corn field > Pinus sylvestris plantation>Caragana microphylla plantation>meadow grassland>abandoned grassland>sparse forest grassland. The infiltration rate at 15 min varied from 0.617 mm/min to 3.690 mm/min, and followed the order of bare sandy land>Caragana korshinskii plantation>Pinus sylvestris plantation>Caragana microphylla plantation>corn field>abandoned grassland>meadow grassland>sparse forest grassland. …”
Get full text

Evaluation of Topographic Effect Parameterizations in Weather Research and Forecasting Model over Complex Mountainous Terrain in Wildfire-Prone Regions by Yong Han Jo, Seung Hee Kim, Yun Gon Lee, Chang Ki Kim, Jinkyu Hong, Junhong Lee, Keunchang Jang

“…The model performance was evaluated over the mountainous region in Gangwon-do, South Korea’s most significant forest area. The simulation results of the wildfire case in 2019 show that subgrid-scale orographic parameterization considerably improves model performance regarding wind speed, with a lower root mean square error (RMSE) and bias by 53% and 57%, respectively. …”
Get full text

Knowledge Model Based Intelligent Visual Identification of Catenary Defects by TANG Peng, JIN Weidong, ZHANG Xingbin, ZHANG Zhijun, XING Kaipeng, HUO Zhihao

“…In the proposed method, numerical unbiased simulation of hanger defects is performed based on expert experience and typical cases, abnormality recognition of hanger is achieved based on multi-scale visual attention, and rapid state screening is carried out based on forest parameters. …”
Get full text

Modeling of wave-induced drift based on stepwise parameter calibration by Kui Zhu, Xueyao Chen, Lin Mu, Lin Mu, Lin Mu, Dingfeng Yu, Dingfeng Yu, Runze Yu, Zhaolong Sun, Tong Zhou, Tong Zhou

“…A force analysis method and three ML methods, long short-term memory (LSTM), back-propagation (BP) neural network, and random forest (RF), were used to fit the wave-induced drift velocity by combining eight different parameter schemes. …”
Get full text

AI-enhanced automation of building energy optimization using a hybrid stacked model and genetic algorithms: Experiments with seven machine learning techniques and a deep neural net... by Mohammad H. Mehraban, Samad ME Sepasgozar, Alireza Ghomimoghadam, Behrouz Zafari

“…This model was trained and validated using simulation data from selected areas of London. It was further evaluated on unseen data from diverse UK cities without retraining, confirming its predictive power across varying climatic conditions. …”
Get full text

A distributed hybrid model for agricultural water-land resource matching by Shufang Wang, Mohamed Khaled Salahou, Liping Wang, Honghui Sang, Shiwei Li, Yuping Lv

“…This model integrates VIC-3L for water resource simulation, RF-CA-Markov for land use simulation, and GCMs for regional climate projection, employing a water-land matching coefficient to quantify their spatial matching status. …”
Get full text

Spatiotemporal Dynamics and Future Projections of Carbon Use Efficiency on the Mongolian Plateau: A Remote Sensing and Machine Learning Approach by Xinyu Yang, Qiang Yu, Buyanbaatar Avirmed, Yu Wang, Jikai Zhao, Weijie Sun, Huanjia Cui, Bowen Chi, Ji Long

“…The results indicate the following: (1) significant spatial variation exists, with high-value CUE areas (≥0.7) in the northwest due to favorable climatic conditions, while low-value areas (<0.6) in the east are affected by decreasing precipitation and overgrazing; (2) CUE increased at an annual rate of 1.03%, with a 43% acceleration after the 2005 climate shift, highlighting the synergistic effects of ecological engineering; (3) our findings reveal that the interaction of evapotranspiration and temperature dominates CUE spatial differentiation, with the random forest model accurately predicting CUE dynamics (root mean square error (RMSE) = 0.0819); (4) scenario simulations show the SSP3-7.0 pathway will peak CUE at 0.6103 by 2050, while the SSP5-8.5 scenario will significantly reduce spatial heterogeneity. …”
Get full text

Assessment of the Impacts of Different Carbon Sources and Sinks on Atmospheric CO₂ Concentrations Based on GEOS-Chem by Ge Qu, Jia Zhou, Yusheng Shi, Yongliang Yang, Mengqian Su, Wen Wu, Zhitao Zhou

“…Conversely, areas with strong carbon sinks, such as forests and oceans, exhibit lower net CO₂ accumulation.…”
Get full text

Integrative bioinformatics analysis to decipher common pathogenic processes in type 2 diabetes mellitus and pancreatic cancer by Faez Falah Alshehri

“…Machine learning classifiers, particularly Random Forest demonstrated the highest accuracy in classifying samples based on the expression of these hub genes. …”
Get full text

Damage Localization Using Fiber Bragg Grating Sensors in Self-referencing Conguration: A Numerical Study by Abhishek Patange, Farzam Omidi Moaf, Piotr Fiborek, Adityan Arumuganainar, Rohan Nandkishor Soman

“…The three techniques employed are decision tree, logistic model tree and random forest. Key findings highlight the effectiveness of random forest models in classifying damage states with a 98.67% accuracy. …”
Get full text

Evaluating Carbon Sink Responses to Multi-Scenario Land Use Changes in the Dianchi Lake Basin: An Integrated PLUS-InVEST Model Approach by Zhenheng Gao, Quanli Xu, Shu Wang, Qihong Ren, Youyou Li

“…Results indicate that from 2000 to 2020, the region experienced significant urbanization, with cropland decreasing and forest land expanding. Forests contributed the most to the total carbon storage, followed by cropland. …”
Get full text