Nonlinear Creep Constitutive Model of Rock Considering Hardening Effect by Dipeng Zhu, Zhiyong Hu, Shuguang Zhang, Wei Qiu, Yijie Wang, Donglan Chen, Fan Mingzhuo, Shutian Zhao, Ye Sun, Wenbo Liu

“…To precisely capture the nonlinearity of rock creep and the law of accelerated deformation, a hardening function and a damage variable are introduced. Based on traditional rheological models, creep mechanisms, and damage laws, an accelerated creep constitutive model integrating hardening and damage effects is established. …”
Get full text

Structural network topologies are associated with deep brain stimulation outcomes in Meige syndrome by Bin Liu, Zhiqi Mao, Xinyuan Yan, Hang Yang, Junpeng Xu, Zhebin Feng, Yanyang Zhang, Xinguang Yu

“…The results indicated that HIG showed a higher clustering coefficient, longer characteristic path length, lower small-world index, and lower global efficiency compared with LIG. …”
Get full text

Engineering students' perceptions and actual use of AI-based math tools for solving mathematical problems by Kimberly F. Garcia, Ardvin Kester S. Ong, Ma. Janice J. Gumasing, Cesar Romeo V. Delos Reyes

“…The outcome indicated that students are more inclined to utilize AI tools when they find them engaging and are convinced that they can employ them efficiently and incorporate the tools in their academic routines. …”
Get full text

Versatile machine learning algorithms for FTIR spectroscopy: differentiating crosslinked and non-crosslinked gelatin samples by Juliana Rincón-López, Eliana Álvarez-Valdés, Daniela Velez-Arango, Estefanía Rojas Zuleta, Leidy Yuliana Vargas Soto, Liliana Lellesch, Victor Alonso García Londoño, Milton Rosero-Moreano, Gonzalo Taborda-Ocampo

“…The functional and mechanical properties of the gelatin depend on the chemical and structural characteristics. …”
Get full text

Maturity Classification and Quality Determination of Cherry Using VNIR Hyperspectral Images and Comprehensive Chemometrics by Yuzhen Wei, Siyi Yao, Feiyue Wu, Qiangguo Yu

“…Based on the spectral principal components, three classifiers were built to classify the maturity level: support vector machine, backpropagation neural network, and radial basis function neural network. Excellent results with a classification accuracy of 100% were obtained. …”
Get full text

Approximation by interpolation spectral subspaces of operators with discrete spectrum by M.I. Dmytryshyn

“…Applications to spectral approximations of the regular elliptic operators with variable smooth coefficients in the space $L_q(\Omega)$ over an open bounded set $\Omega\subset\mathbb{R}^n$ and some self-adjoint ordinary elliptic differential operators in a bounded interval $\Omega=(a,b)$ are shown.…”
Get full text

Using machine learning methods to determine a typology of patients with HIV-HCV infection to be treated with antivirals. by Antonio Rivero-Juárez, David Guijo-Rubio, Francisco Tellez, Rosario Palacios, Dolores Merino, Juan Macías, Juan Carlos Fernández, Pedro Antonio Gutiérrez, Antonio Rivero, César Hervás-Martínez

“…This study was based on the Spanish HERACLES cohort (NCT02511496) (April-September 2015, 2940 patients) and involved application of different neural network models with different basis functions (product-unit, sigmoid unit and radial basis function neural networks) for automatic classification of patients for treatment. …”
Get full text

Advancing geohazard risk assessment – A digital tool for steep slope management by Cherry Rose Godes, One-Bin Lim, Shanelle Aira Rodrigazo, Yongseong Kim, Yongjin Kim, Seungjoo Lee, Jaeheum Yeon

“…Growing climatic variability and rapid urbanization have increased landslide occurrences, posing significant challenges for risk assessment. …”
Get full text

Cardiometabolic risk factors in predicting obstructive coronary artery disease in patients with non-ST-segment elevation acute coronary syndrome by B. I. Geltser, M. M. Tsivanyuk, K. I. Shakhgeldyan, E. D. Emtseva, A. A. Vishnevskiy

“…The predictors of this model were 7 categorical (total cholesterol (CS) ≥5,9 mmol/L, low-density lipoprotein cholesterol >3,5 mmol/L, waist-to-hip ratio ≥0,9, waist-to-height ratio ≥0,69, atherogenic index ≥3,4, lipid accumulation product index ≥38,5 cm*mmol/L, uric acid ≥356 pmol/L) and 2 continuous (high density lipoprotein cholesterol and insulin resistance index) variables.Conclusion. The developed algorithm for selecting predictors made it possible to determine their significant predictive threshold values and weighting coefficients characterizing the degree of influence on endpoints. …”
Get full text

Family Resilience and Its Influencing Factors Among Patients With Lung Cancer Based on Double ABC‐X Theoretical Framework by Ziyi Shen, Yan Fang, Chengcheng Li, Xin Luo, Junling Cui, Yanchang Liu, Jingfang Hong

“…Relationships between variables and pathways were also explored based on the Double ABC‐X as the theoretical framework. …”
Get full text

Compositional and nutritional value of lupin cultivars: Identifying high-protein seeds for enhanced protein isolate production and phytochemical valorisation by Pau Taberner-Pibernat, Albert Ribas-Agustí, Gisela Quinteros, Gerard Sabeña, Miguel López-Gómez, Rubén Domínguez-Valencia, Ricard Bou

“…The wet extraction process yielded high-purity protein isolates with favourable extraction efficiency. These findings highlight the potential of lupin for diverse applications in the food and industrial sectors. …”
Get full text

Inversion and validation of soil water-holding capacity in a wild fruit forest, using hyperspectral technology combined with machine learning by Tingwei Song, Liang Guo, Qian Sun, Guizhen Gao, Jing Chen, Qikun Zhang

“…The results revealed a significant negative correlation between SWHC and the smoothed leaf spectral reflectance, with the best correlation coefficient was r = − 0.59. The use of third-order derivatives and logarithmic second-order derivatives further enhanced this correlation, yielding optimal coefficients of r = − 0.78 and r = − 0.72, respectively. …”
Get full text

Optimizing Load Frequency Control of Multi-Area Power Renewable and Thermal Systems Using Advanced Proportional–Integral–Derivative Controllers and Catch Fish Algorithm by Saleh A. Alnefaie, Abdulaziz Alkuhayli, Abdullah M. Al-Shaalan

“…Additionally, by contrasting the performance of the PID, PI, cascaded PI(PDN), and FOPID, PI(1+DD) controllers, the efficiency of the CFA is confirmed. Additionally, a sensitivity analysis that considers simultaneous modifications of the frequency bias coefficient (B) and speed regulation (R) within a range of ±25% validates the efficacy and dependability of the suggested CFA-tuned PI(1+DD). …”
Get full text

Maximising Achievable Rate Using Intelligent Reflecting Surface in 6G Wireless Communication Systems by Afrin Jahan Eva, Md. Sahal, Rabita Amin, Muhammad R. A. Khandaker, Risala Tasin Khan, Faisal Tariq, ASM Ashraf Mahmud

“…Intelligent reflecting surface (IRS) is a promising technique which aims to shift the paradigm of uncontrollable wireless environment to a controllable one by adding the function of reconfigurability using multiple passive reflecting elements. …”
Get full text

Improving Electrical Distance Accuracy for Cable Fault Location Based on the Prony Method by Xiang Ren, Zhiqiang Feng, Kai Zhou, Xueming Zhou, Jianjun Yuan, Yefei Xu, Li Zhang

“…By establishing a frequency-variable coupling model containing the transfer function of the cable with double joint structure, studying the mapping relationship between the cable attenuation constant and the electromagnetic wave velocity, and adopting the Prony estimation method combined with the singular value decomposition noise reduction algorithm to achieve the extraction of the attenuation constant and the decoupling of the segmented wave velocity, thus improving the electrical accuracy of fault location. …”
Get full text

On the added value of sequential deep learning for the upscaling of evapotranspiration by B. Kraft, B. Kraft, B. Kraft, J. A. Nelson, S. Walther, F. Gans, U. Weber, G. Duveiller, M. Reichstein, W. Zhang, M. Rußwurm, D. Tuia, M. Körner, Z. Hamdi, M. Jung

“…</p> <p>When using only meteorological covariates, we found that the sequential models (LSTM and TCN) performed better (each with a Nash–Sutcliffe efficiency (NSE) of 0.73) than the instantaneous models (FCN and XGBoost), both with an NSE of 0.70, in site-level cross-validation at the hourly scale. …”
Get full text

Factors affecting the design of the management dashboard framework with an emphasis on the components of human resources productivity by Hassan Barmaki, Farshad Faezy Razi, Ehtesham Rashidi

“…Using productivity as a standard is useful for calculating efficiency, and can guide efforts to allocate resources optimally. …”
Get full text

Mobile machine design through dynamic load simulation on their drive units by S. A. Partko, L. M. Groshev, A. N. Sirotenko

“…The work objective is to conduct a comparative analysis of the efficiency of existing calculation methods of statistical characteristics of uncorrelated external actions as applied to a mobile machine presented as a multidimensional dynamic system with actions having different correlations.Materials and Methods. …”
Get full text

Intelligent Field Sensor Station for Monitoring Agrophysical Parameters and Phenotyping in Precision Agriculture System by S. A. Vasilyev, S. Ye. Limonov, S. A. Mishin

“…(Results and discussion) The intelligent field sensor station successfully demonstrated its efficiency, confirming both its functionality and reliability in simultaneous data collection. …”
Get full text

Observational partitioning of water and CO₂ fluxes at National Ecological Observatory Network (NEON) sites: a 5-year dataset of soil and plant components for spatial... by E. Zahn, E. Bou-Zeid

“…<p>Long-term time series of transpiration, evaporation, plant net photosynthesis, and soil respiration are essential for addressing numerous research questions related to ecosystem functioning. However, quantifying these fluxes is challenging due to the lack of reliable and direct measurement techniques, which has left gaps in the understanding of their temporal cycles and spatial variability. …”
Get full text