Data-driven modeling and regression analysis on ship resistance of in-service performance by Daehyuk Kim, Shin Hyung Rhee

“…The analysis of added resistance due to waves shows significant, but sometimes inconsistent, transfer function coefficients, suggesting simpler model structures could be more effective. …”
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RELATIONSHIP BETWEEN PRIVATE DOMESTIC INVESTMENT AND ECONOMIC GROWTH IN NIGERIA (1986-2018): AUTO-REGRESSIVE DISTRIBUTED LAG APPROACH by Isiaka Kareem JIMBA, Rosemary Bukola AJALA

“…The study incorporated other investment measures like foreign direct investment and public investment into the model, while inflation and exchange rate were taken as control variables. Secondary data was sourced from CBN statistical bulletin of various editions and was estimated using autoregressive distributed lag bound test and its coefficients. …”
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Climate Change Risk, Performance, and Value Added in Agricultural Sector by Ramin Amani, Zanko Ghorbani, Zana Mozaffari

“…Results and Discussion The results of this research show that both climate change performance index variables and climate change risk have a positive and significant effect on the added value of the agricultural sector in all three functional groups and all deciles. …”
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THE PROPOSAL MODEL OF RATIONAL WORKFORCE ASSIGNMENT IN DOKUZ EYLUL UNIVERSITY BY ANALYTIC HIERARCHY PROCESS BASED 0-1 INTEGER PROGRAMMING by Yılmaz GÖKŞEN, Hakan AŞAN, Onur DOĞAN, Mustafa ÜNLÜ, Osman PALA

“…The Assignment model of the type of linear programming models is a mathematical method used to match the right person for the right job. The coefficients of the variables in the objective function of the assignment model constitute potential contributions of employees. …”
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Same data, different results? Machine learning approaches in bioacoustics by Kaja Wierucka, Derek Murphy, Stuart K. Watson, Nikola Falk, Claudia Fichtel, Julian León, Stephan T. Leu, Peter M. Kappeler, Elodie F. Briefer, Marta B. Manser, Nikhil Phaniraj, Marina Scheumann, Judith M. Burkart

“…We investigated the impact of using different feature extraction (spectro‐temporal measurements, linear and Mel‐frequency cepstral coefficients (MFCC), as well as highly comparative time‐series analysis) and classification methods (discriminant function analysis, neural networks, random forests (RF), and support vector machines) on the consistency of caller identity classification accuracy across 16 mammalian datasets. …”
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Study on a Quantitative Evaluation Method of Goaf Instability Risk of Phosphate Deposits in Layered Rock Mass by Dongfang CHEN, Mengke WANG, Dingping XU, Haiwang YE, Qizhou WANG, Jian LIU, Bin XIANG

“…The Hermite random polynomial coefficients between the input field of c and <italic>ϕ</italic>_j and the output field of the FAI are solved by the probability collocation method, establishing an explicit function expression between the probability collocation point and the FAI. …”
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Mild Cognitive Impairment and Cardiometabolic Risk Factors in Bosnian and Herzegovinian Patients with Heart Failure by Jasna Ibrahimović-Pašić, Orhan Lepara, Amela Dervišević, Nermina Babić, Nesina Avdagić, Amina Valjevac, Asija Začiragić

“…Associations between categorical variables and correlation coefficients were assessed by the Chi-square and Spearman test, respectively. …”
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Three-dimensional ultrasound for carotid vessel wall volume measurement by Ying-An Chen, Pei-Ya Chen, Shinn-Kuang Lin

“…Gray-scale 3D images from the distal common carotid artery (CCA) to internal carotid artery on both sides were acquired using a single-sweep 3D transducer and analyzed offline by using the vascular plaque quantification function of the Philips QLAB software. Then, the 3D IMT(QLAB intima–media thickness [QIMT]), total plaque volume (TPV), and VWV were measured by a neurologist and a technician, and the interobserver variability was assessed. …”
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The Relationship between Calcium-phosphorus Metabolism Disorder and Cognitive Impairment in Maintenance Hemodialysis Patients by Geng Ming-hui, Li Yu-yan, Tao Mi, Liao Wen-wen, He Yi-qing, Gao Ping

“…Montreal Cognitive Assessment （MoCA） scale was utilized for evaluating overall cognitive function. They were divided into two groups of cognitive impairment and non-cognitive impairment. …”
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Age-Related Differences in Bimanual Isometric Force Tracking by Elisa Galofaro, Nicola Vale, Giulia Ballardini, Nicola Smania, Maura Casadio

“…Notably, the percentage of total force exerted by the left hand was negatively correlated with the disparity between the left and right coefficients of variation. This study confirms previous findings on the effect of aging on bimanual force control and provides evidence suggesting that the contribution of each hand may depend on the variability in force exertion.…”
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A New Ground-Motion Prediction Model for Shallow Crustal Earthquakes in Türkiye by Ulubey Çeken, Fadime Sertçelik, Abdullah İçen

“…Additionally, a heteroscedastic model was created for aleatory variability as a function of <i>M_W</i>. The closest distance to the surface projection of the fault plane (<i>R_JB</i>) is between 0 and 350 km. …”
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A Fusion Strategy for High-Accuracy Multilayer Soil Moisture Downscaling and Mapping by Xu Zhang, Xin Liu, Xiang Zhang, Aminjon Gulakhmadov, Jiefeng Wu, Xihui Gu, Won-Ho Nam, Panda Rabindra Kumar, Veber Afonso Figueiredo Costa, Mahlatse Kganyago, Berhanu Keno Terfa, Wenying Du, Chao Wang, Peng Wang, Jing Yuan, Nengcheng Chen

“…Soil moisture (SM) is a critical factor influencing plant growth, agricultural yield, ecosystem functions, and water resource management. Existing SM products, such as SMAP, ERA5, and ESA-CCI, provide daily SM data. …”
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Assessment of heavy metal exposure risk to aquatic birds in the key wetland habitats of the Yellow River (China), using an integrated model by Jian Ding, Ni Wang, Yaqiao Lian, Qian Li, Xinran Li, Fei Yu

“…Heavy metal pollution poses a growing threat to wetland ecosystems, impacting their structure and function. Chenqiao Wetland and Qinglong Lake (Henan, China), key bird habitats in the middle and lower reaches of the Yellow River, were analyzed for heavy metal contamination. …”
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Effects of bedroom environment on average heart rate during sleep in temperate regions: Winter conditions in healthy males in their twenties with average BMI by Noriaki Oota, Yasuki Yamauchi, Gota Iwase, Masaru Abuku, Yasuhiro Hiraguri

“…Additionally, it has been suggested that as the average heart rate decreases, SDNN increases, indicating favorable autonomic function. This study aimed to identify the environmental factors that most significantly affect the day-to-day variability of average heart rate during sleep (SHR) in winter. …”
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Study on numerical simulation of rock breaking by PDC wear teeth cutting by Maosheng CAI, Hongbo WANG, Chunjiang ZHANG, Sai LI, Shuting CHENG

“…Considering the fluctuation of cutting efficiency and load, the front angle should be controlled at 15°−20° as far as possible, which is beneficial to prolong the service life of the cutting teeth. …”
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A Hybrid RBF-PSO Framework for Real-Time Temperature Field Prediction and Hydration Heat Parameter Inversion in Mass Concrete Structures by Shi Zheng, Lifen Lin, Wufeng Mao, Yanhong Wang, Jinsong Liu, Yili Yuan

“…Sensitivity analysis identified the ultimate adiabatic temperature rise as the dominant parameter (78% variance contribution), followed by synergistic interactions between hydration rate parameters, and indirect coupling effects of boundary correction coefficients. These findings guided a phased optimization strategy, as follows: prioritizing high-precision calibration of dominant parameters while relaxing constraints on low-sensitivity variables, thereby balancing accuracy and computational efficiency. …”
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Investigation of a chest radiograph-based deep learning model to identify an imaging biomarker for malnutrition in older adults by Ryo Sasaki, Yasuhiko Nakao, Fumihiro Mawatari, Takahito Nishihara, Masafumi Haraguchi, Masanori Fukushima, Ryu Sasaki, Satoshi Miuma, Hisamitsu Miyaaki, Kazuhiko Nakao

“…The predicted data were evaluated by computing the correlation coefficients and area under the curve (AUC). Results: As a numerical variables analysis, albumin and hemoglobin predictions were relatively accurate (R=0.71, 0.74). …”
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Gender-specific assessment of lipid profiles correlation with serum uric acid in non-dialysis chronic kidney disease patients: Prospective observational cross-sectional study by Yousuf Abdulkarim Waheed, Yousuf Abdulkarim Waheed, Huanhuan Yin, Jie Liu, Shifaa Almayahe, Maryam Bishdary, Karthick Kumaran Munisamy Selvam, Syed Muhammad Farrukh, Shulin Li, Shulin Li, Yanping Wang, Yanping Wang, Disheng Wang, Disheng Wang, Disheng Wang, Xinglei Zhou, Dong Sun, Dong Sun, Dong Sun

“…Using a multistage stratified sampling method based on age and SUA to examine the differences among groups, Spearman’s correlation and linear regression analysis were utilized to study the association between SUA and lipid profiles, and multivariate analysis to determine the effect of SUA quartiles on multiple dependent variables collectively.ResultsLDL-c was positively correlated with SUA levels, with Spearman’s correlation coefficients of R=0.3553 in males and 0.5137 in females (both with P&lt;0.0001). …”
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The Structural Model of Happiness Based on Mindfulness with Mediator Role of Emotional Intelligence, Self-Compassion and Resilience by Mohammad Reza Tamannai far, Faezeh Taraffo

“…Pearson's correlation coefficient method and structural equation modeling were used to analyze the data. …”
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TROLL 4.0: representing water and carbon fluxes, leaf phenology, and intraspecific trait variation in a mixed-species individual-based forest dynamics model – Part 2: Model evaluat... by S. Schmitt, S. Schmitt, S. Schmitt, F. J. Fischer, J. G. C. Ball, N. Barbier, M. Boisseaux, D. Bonal, B. Burban, X. Chen, G. Derroire, G. Derroire, G. Derroire, J. W. Lichstein, D. Nemetschek, N. Restrepo-Coupe, S. Saleska, G. Sellan, P. Verley, G. Vincent, C. Ziegler, J. Chave, I. Maréchaux

“…The simulated canopy height distribution showed a high correlation coefficient (CC) with observed aerial and satellite data (CC <span class="inline-formula">&gt;</span> 0.92), while the species and functional composition were well represented (CC <span class="inline-formula">&gt;</span> 0.75). …”
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