Gross Tonnage-Based Statistical Modeling and Calculation of Shipping Emissions for the Bosphorus Strait by Kaan Ünlügençoğlu

“…These EPA-estimated values served as dependent variables in the modeling process. The modeling framework followed a three-step strategy: (1) outlier detection using Rosner’s test to reduce the influence of outliers on model accuracy, (2) curve fitting with 12 regression models representing four curve types—polynomial (e.g., linear, quadratic), concave/convex (e.g., exponential, logarithmic), sigmoidal (e.g., logistic, Gompertz, Weibull), and spline-based (e.g., cubic spline, natural spline)—to capture diverse functional relationships between GT and emissions, and (3) model comparison using difference performance metrics to ensure a comprehensive assessment of predictive accuracy, consistency, and bias. …”
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Process engineering by Ahmed Mohamed Farid Shaaban, Azza Ibrahim Hafez, Mona Amin Abdel-Fatah, Nabil Mahmoud Abdel-Monem, Mohamed Hanafy Mahmoud

“…The solution diffusion model was used to develop power correlations to calculate the permeate side solute mass transfer coefficient as a function of effective cross-flow Reynolds number. …”
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Improved representation of soil moisture processes through incorporation of cosmic-ray neutron count measurements in a large-scale hydrologic model by E. Fatima, E. Fatima, R. Kumar, S. Attinger, S. Attinger, M. Kaluza, O. Rakovec, O. Rakovec, C. Rebmann, C. Rebmann, R. Rosolem, R. Rosolem, S. E. Oswald, L. Samaniego, L. Samaniego, S. Zacharias, M. Schrön

“…<p>Profound knowledge of soil moisture and its variability plays a crucial role in hydrological modelling to support agricultural management, flood and drought monitoring and forecasting, and groundwater recharge estimation. …”
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Assessing the stability of indoor farming systems using data outlier detection by Jean Pompeo, Ziwen Yu, Chi Zhang, Songzi Wu, Ying Zhang, Celina Gomez, Melanie Correll

“…Ensuring data quality in CEA systems is essential, as it affects system stability and operational efficiency. This research aims to assess system stability by analyzing the correlation between cumulative agricultural operations (Agr.Ops) and air temperature data variability.MethodsThe methodology involved collecting air temperature data from IoT sensors in the CEA system throughout lettuce cultivation trials. …”
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Fusion of Multimodal Audio Data for Enhanced Speaker Identification Using Kolmogorov-Arnold Networks by Aryaman Tamotia, Dhruv Shantu Karmokar, Rethi Komal, K. Khadar Nawas, A. Shahina, A. Nayeemulla Khan

“…One of the critical innovations within this design is a class of trainable activation functions that eliminate the need for traditional weight parameters, thereby providing scalable and computationally efficient solutions. …”
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Exercise, Training &amp; Health by Mentz L, Winkert K, Schlegel S, Rohlmann F, Steinacker JM, Treff G

“…The highest differences between individual CVs were found in step 1, ranging from 2.9% to 11.8%.Conclusion: Stroke-to-stroke variability during rowing ergometer testing amounts to 4.7%, which is probably higher than during testing on externally controllable bicycle ergometers, where resistance is controlled as a function of cadence. …”
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Optimisation of the performance and structure of soluble ball seat metal sealing rings based on response surface by CHEN Zhen, RAN Qingjie, CHEN Nengpeng, WANG Qiaomu

“…The increase of groove parameters (groove width and depth) can enhance the contact pressure, and at the same time, increase the equivalent stress, which may lead to local strength deficiency.Through the sensitivity analysis, the sensitivity coefficients of the radius of the metal seal ring to the equivalent force and contact pressure were found to reach 0.67 and 0.82, which were the dominant variables affecting the sealing performance; the width and depth of the grooves regulated the stress distribution through the geometric compensation mechanism. …”
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Three-dimensional dynamics of mesothelin-targeted CAR.CIK lymphocytes against ovarian cancer peritoneal carcinomatosis by Federica Galvagno, Valeria Leuci, Annamaria Massa, Chiara Donini, Ramona Rotolo, Sonia Capellero, Alessia Proment, Letizia Vitali, Andrea Maria Lombardi, Valentina Tuninetti, Lorenzo D’Ambrosio, Alessandra Merlini, Elisa Vigna, Giorgio Valabrega, Luca Primo, Alberto Puliafito, Dario Sangiolo

“…MSLN-CAR.CIK effectively killed and were functionally efficient against OC targets. In a “floating-like” 3D context with floating OC spheroids, both tumor localization and killing by MSLN-CAR.CIK were significantly boosted by fluid flow. …”
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Investigation into the monitoring and control of mechanical dynamics in inclined mining equipment utilizing digital twin technology by Panshi XIE, Hang YANG, Yongping WU, Baofa HUANG, Weidian LIN, Leilei YI

“…Ultimately, the feasibility and efficacy of this system are corroborated through a multi-functional, variable-angle large-scale "support-surrounding rock" system physical simulation platform. …”
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An updated non-intrusive, multi-scale, and flexible coupling interface in WRF 4.6.0 by S. Masson, S. Jullien, E. Maisonnave, D. Gill, G. Samson, M. Le Corre, L. Renault

“…The present paper details the development and the functionalities of the coupling interface we implemented in WRF. …”
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Enhanced prediction of heating value of municipal solid waste using hybrid neuro-fuzzy model and decision tree-based feature importance assessment by Oluwatobi Adeleke, Obafemi O. Olatunji, Tien-Chien Jen, Iretioluwa Olawuyi

“…To this end, the feature importance analysis of MSW input variables was carried out using the decision tree regressor with the Gini importance (GI) metrics to identify the most influential variable. …”
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RNAtango: Analysing and comparing RNA 3D structures via torsional angles. by Marta Mackowiak, Bartosz Adamczyk, Marta Szachniuk, Tomasz Zok

“…RNA molecules, essential for viruses and living organisms, derive their pivotal functions from intricate 3D structures. To understand these structures, one can analyze torsion and pseudo-torsion angles, which describe rotations around bonds, whether real or virtual, thus capturing the RNA conformational flexibility. …”
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Application of machine learning and neural network models based on experimental evaluation of dissimilar resistance spot-welded joints between grade 2 titanium alloy and AISI 304 s... by Marwan T. Mezher, Alejandro Pereira, Rusul Ahmed Shakir, Tomasz Trzepieciński

“…The best prediction model was found to be the ANN model when training the conjugate gradient with the Polak-Ribiere updates (Traincgp) training function with the hyperbolic tangent sigmoid transfer function (Tansig) with the mean squared error (MSE) and correlation coefficient (R2) values recorded as 0.01886 and 0.94973, respectively. …”
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Arterial hypertension and myocardial electric heterogeneity in patients with coronary heart disease by L. A. Leshchinsky, B. L. Multanovsky, A. G. Petrov, S. B. Ponomarev

“…Myocardial electric heterogeneity, especially in PS, correlated with left ventricular (LV) hypertrophy, LV diastolic function, and the overall functional status of cardiovascular system. …”
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Evaluating Machine Learning Models for Predicting Hardness of AlCoCrCuFeNi High-Entropy Alloys by Uma Maheshwera Reddy Paturi, Muhammad Ishtiaq, Pasupuleti Lakshmi Narayana, Anoop Kumar Maurya, Seong-Woo Choi, Nagireddy Gari Subba Reddy

“…This study evaluates the predictive capabilities of various machine learning (ML) algorithms for estimating the hardness of AlCoCrCuFeNi high-entropy alloys (HEAs) based on their compositional variables. Among the ML methods explored, a backpropagation neural network (BPNN) model with a sigmoid activation function exhibited superior predictive accuracy compared to other algorithms. …”
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Meristic and morphometric comparison of an undescribed sucker of the Río Culiacán (Catostomus sp.) and Yaqui sucker (Catostomus bernardini) (Catostomidae, Teleostei) from the Sierr... by Gorgonio Ruiz-Campos, Sergio Sánchez-Gonzáles, Richard L. Mayden, Alejandro Varela-Romero

“…Likewise, the discrimination was associated with the lowest values for predorsal distance, soft posterior ocular margin to occiput, and number of anal rays. The standardized coefficients for canonical variables 1 and 2 accounted 82.6% of the total variation. …”
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Treatment of Pediatric Colchicine Poisoning with Single-Pass Albumin Dialysis: A Case Report by Atessa Bahadori, Rishil Patel, Cal Robinson, Steve Balgobin, Michael Zappitelli, Nithiakishna Selvathesan

“…The rationale for CVVHDF with SPAD was based on the high protein binding, variably high volume of distribution, previous reports showing a sieving coefficient of 0.2 with CVVH, and the high mortality risk. …”
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A Data-Driven Approach Based on Deep Neural Network Regression for Predicting the Compressive Strength of Steel Fiber Reinforced Concrete by Nhat-Duc Hoang, Van-Duc Tran

“…Experimental results show that the L1 regularization helps achieve the most desired performance, with a coefficient of determination (R2) of roughly 0.96. Notably, an asymmetric loss function is used along with Nadam to decrease the percentage of overestimated cases from 50.83% to 27.08%. …”
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Estimativa das temperaturas máximas e mínimas do ar para a região do Circuito das Frutas, SP Estimation of maximum and minimum air temperatures for the "Circuito das Frutas" region... by Ludmila Bardin, Mário J. Pedro Júnior, Jener F. L. de Moraes

“…Also, maps with the spacial variability of the maximum and minimum mean monthly and annual temperatures are presented for the region.…”
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The Effect of Vocal Rehabilitation on Patients with Vocal Cord Paralysis by Mila Bunijevac, Andrijana Mikić, Maša Đurišić

“…Measures of central tendency, measures of variability, one-factor analysis of variance, t-test for independent samples, chi-square test and interclass correlation coefficient were applied in statistical data processing. …”
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