The estimation of correlation between milk and reproductive traits in holstein by canonical correlation analysis by İsmet Doğan

“…The process ot maximizing the correlation between two linear function ot two sets of random variables is known as Canonical Correlation Analysis, Canonical Correlation Analysis is a statistical method which has been used to describe the re latıonshıp between a set o! …”
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An improved statistical bias correction method for Global Climate Model (GCM) precipitation projection: A case study on the CMCC-CM2-SR5 model projection in China’s Huaihe River Ba... by Yuning Luo, Ke Zhang, Wen Wang, Xinyu Chen, Jin Feng, Haijun Wang, Wei Liu, Cheng Guo, Cuiying Chen, Xiaozhong Wang

“…We applied this and three other methods—EquiDistant Cumulative Distribution Function matching method (EDCDF), combined Linear Scaling and Cumulative Distribution Function matching method (LS-CDF) and Quantile-quantile mapping method (QUANT)—to correct biases in the CMCC-CM2-SR5 model. …”
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Decarbonisation pathways for industrial clusters through multi-energy systems by Ugochukwu Ngwaka, Yousaf Khalid, Janie Ling-Chin, John Counsell, Ruben Pinedo-Cuenca, Huda Dawood, Andrew J. Smallbone, Nashwan Dawood, Anthony P. Roskilly

“…Given the complex and nonlinear interconnections among systems within a multi-energy cluster, this study extends the dynamic multi-vector methodology to multi-energy system clusters, representing variables as nodes and converting them into transfer functions for system integration. …”
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Eco-engineered remediation: Microbial and rhizosphere-based strategies for heavy metal detoxification by Arun Karnwal, Gaurav Kumar, Alaa El Din Mahmoud, Joydeep Dutta, Rattandeep Singh, Abdel Rahman Mohammad Said Al-Tawaha, Tabarak Malik

“…Moreover, a detailed understanding of plant–microbe interactions and the role of secondary metabolite signalling in the rhizosphere is essential to improve remediation efficiency. Future strategies should prioritize the application of functional genomics, developing bioinoculants tailored to specific environmental conditions, and implementing robust ecological risk assessments for GEMs. …”
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Analysis of Hydrological and Meteorological Conditions in the Southern Baltic Sea for the Purpose of Using LNG as Bunkering Fuel by Ewelina Orysiak, Jakub Figas, Maciej Prygiel, Maksymilian Ziółek, Bartosz Ryłko

“…The southern Baltic Sea is characterized by highly variable weather conditions, particularly in autumn and winter, when storms, strong westerly winds, and temporary sea ice formation disrupt maritime operations. …”
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Smart technique for calculating fault current model parameters using short circuit current measurements by R. A. Mahmoud, O. P. Malik, W. M. Fayek

“…The difference concept can be utilized to obtain precise mathematical formulas for evaluating the parameters of the fault current model. This is for efficient implementation of multiple functions that include digital protective relay, fault locator, digital filter, CT saturation detector and compensator. …”
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Machine learning projection of climate and technology impacts on crops key to food security by Dan Li, Vassili Kitsios, David Newth, Terence John O’Kane

“…Our model is designed to capture the relationships between technology, climate variables and the annual growth rate in crop yield across the world’s producing regions. …”
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Determinants of growth differentiation factor 15 plasma levels in outpatients with peripheral arterial disease by Emma Skau, Philippe Wagner, Jerzy Leppert, Johan Ärnlöv, Pär Hedberg

“…Results: The multivariable analysis identified independent relations of GDF-15 with several of the included variables (adjusted R2 = 0.48). Diabetes (beta coefficient [β] of 0.37, 95% confidence interval [95% CI] 0.25 to 0.50), low-density lipoprotein (LDL) cholesterol (β = −0.22, 95% confidence interval [CI]: −0.34 to −0.09), and physical activity (β = −0.16, 95% CI: −0.25 to −0.06) had the strongest associations. …”
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Estimation of Fuzzy Measures Using Covariance Matrices in Gaussian Mixtures by Nishchal K. Verma

“…The mixture components of GMM provide the membership functions for the input-output fuzzy sets. By treating consequent part as a function of fuzzy measures, we derived its coefficients from the covariance matrices found directly from GMM and the defuzzified output constructed from both the premise and consequent parts of the nonadditive fuzzy rules that takes the form of Choquet integral. …”
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Building electrical consumption patterns forecasting based on a novel hybrid deep learning model by Nasser Shahsavari-Pour, Azim Heydari, Farshid Keynia, Afef Fekih, Aylar Shahsavari-Pour

“…Specifically, the proposed model comprises three key components: (i) a mutual information-based feature selection method to identify the most significant input variables influencing energy consumption; (ii) a variational mode decomposition (VMD) approach to decompose the original energy consumption signal into intrinsic mode functions (IMFs), capturing relevant trends and eliminating noise; and (iii) a long short-term memory (LSTM) neural network to perform time-series forecasting of the target energy consumption values. …”
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Production of Cyanobacterial Microscale Adsorbent by Hydrothermal Method for Pre-concentration of Cadmium from Water by T. Mohammadi Arian, G. Rahimi, R. Khavari Farid

“…The absorbent surface was rich in oxygen and nitrogen functional groups, such as hydroxyl, isothiocyanate, and carbonyl. …”
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The Relationship between the Reorganization of Higher Education Institutions' Operations in Poland During the COVID-19 Pandemic and Student Loyalty by Sojkin Bogdan, Bartkowiak Paweł, Michalak Szymon

“…Using exploratory factor analysis (EFA), the main components were identified for various variables pertaining to the functioning, organization, and delivery of online classes, as well as for aspects associated with university operations during the COVID-19 pandemic. …”
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RL-Cervix.Net: A Hybrid Lightweight Model Integrating Reinforcement Learning for Cervical Cell Classification by Shakhnoza Muksimova, Sabina Umirzakova, Jushkin Baltayev, Young-Im Cho

“…A novel application of RL for dynamic feature refinement and adjustment based on reward functions was employed to optimize the detection capabilities of the model. …”
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Development of a High-Cell-Density Production Process for a Biotherapeutic Yeast, <i>Saccharomyces cerevisiae</i> var. <i>boulardii</i>, for Use as a Human Probiotic by Ghaneshree Moonsamy, Sarisha Singh, Yrielle Roets-Dlamini, Koketso Kenneth Baikgaki, Santosh Omrajah Ramchuran

“…Once the optimised batch was validated in the replicate batches, the statistical analysis indicated a high level of reproducibility, with low variability across key performance indicators such as biomass concentration (unit), CFU production (CFU.mL⁻¹), and substrate utilization efficiency (g.g⁻¹). …”
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Stability analysis of the inner dump with inclined base considering anti-slip pillar by Li MA, Xinyu JIN, Qifeng ZHANG, Kaisheng JIANG, Mengbo LI, Yan HU

“…Taking the angle of inclination of the basement stratum and the discharge height of the soil disposal site as the variables for research, it was obtained that the angle of inclination of the basement stratum α or the height of the soil disposal H and the slope stability coefficient Fs were negatively correlated with the inverse proportionality function, the angle of inclination of the basement stratum had a greater influence on the slope stability, and the height of the discharge height of the soil disposal site had a second greater influence on the stability of the slope. …”
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Optimization of the encapsulation of arazá pulp by spray drying: Physicochemical, morphological and in vitro digestion studies by Greilis Quintero-Gamero, Francis S. Sánchez-Garzón, Aureliano Rodríguez-Cortina, María Hernández-Carrión, Luz Stella Nerio

“…Yield (Y), moisture (M), water activity (aw), water solubility index (WSI), hygroscopicity, ascorbic acid and phenolics encapsulation efficiency (EEAA, EEP), and the retention efficiency of DPPH and radical scavenging capacity (DPPH, ABTS) were studied as response variables; being Y, M, aw, WSI and EAA the ones considered for optimization purposes. …”
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Comparative evaluation of machine learning models for enhancing diagnostic accuracy of otitis media with effusion in children with adenoid hypertrophy by Xiaote Zhang, Qiaoyi Xie, Ganggang Wu

“…Confusion matrix analysis further confirmed RF as the optimal model, achieving 0.875 accuracy and robust inter-rater agreement (Cohen's kappa coefficient = 0.696) in the testing cohort. SHAP analysis identified the adenoid-to-nasopharyngeal ratio as the predominant diagnostic indicator, followed by tympanometric type and history of recurrent respiratory infections.ConclusionAn RF-based diagnostic model effectively identifies OME in AH children by integrating anatomical, functional, and inflammatory parameters, providing a clinically applicable tool for enhanced diagnostic accuracy and evidence-based management decisions.…”
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Structural Integrity and Life Assessment of Ti-6Al-4V Orthopaedic Implants by Katarina Čolić, Svetlana M. Kostić, Simon Sedmak, Nenad Gubeljak, Aleksandar Grbović

“…In X-FEM, the finite element space is enriched with discontinuity functions and asymptotic functions at the crack tip, which are integrated into the standard finite element approximation using the unity division property. …”
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DC Performance Variations of SOI FinFETs with Different Silicide Thickness by Jun-Sik Yoon

“…DC parameters including threshold voltage, low-field-mobility-related coefficient, and parasitic resistance are extracted from Y-function method for the comparison of DC performance and variability, and the correlation analysis. …”
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Integrating UAV-Based RGB Imagery with Semi-Supervised Learning for Tree Species Identification in Heterogeneous Forests by Bingru Hou, Chenfeng Lin, Mengyuan Chen, Mostafa M. Gouda, Yunpeng Zhao, Yuefeng Chen, Fei Liu, Xuping Feng

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