Characterization and treatment monitoring of ureagenesis disorders using stable isotopes by Gabriella Allegri, Martin Poms, Nadia Zürcher, Véronique Rüfenacht, Nicole Rimann, Déborah Mathis, Beat Thöny, Matthias Gautschi, Ralf A. Husain, Daniela Karall, Karolina Orchel-Szastak, Francesco Porta, Dominique Roland, Barbara Siri, Carlo Dionisi-Vici, René Santer, Johannes Häberle

“…Thus, the method proved to be safe and efficient to monitor UCD patients of variable severity pre- and post-therapy, being suitable as physiological endpoint for development of therapies.…”
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LNT-YOLO: A Lightweight Nighttime Traffic Light Detection Model by Syahrul Munir, Huei-Yung Lin

“…A novel SEAM attention module is proposed to refine the features that represent both the spatial and channel information by leveraging the features from the Simple Attention Module (SimAM) and Efficient Channel Attention (ECA) mechanism. The HSM-EIoU loss function is also proposed to accurately detect a small traffic light by amplifying the loss for hard-sample objects. …”
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On Mixed Problems for Quasilinear Second-Order Systems by Rita Cavazzoni

“…The proof of the main theorem relies on two preliminary results: existence of the solution to mixed problems for linear second-order systems with smooth coefficients, and existence of the solution to initial-boundary value problems for linear second-order operators whose coefficients depend on the variables 𝑥 and 𝑡 through a function 𝑣∈𝐻𝑠(ℜ𝑑+1). …”
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Some Iterative Methods Free from Derivatives and Their Basins of Attraction for Nonlinear Equations by Farahnaz Soleimani, Fazlollah Soleymani, Stanford Shateyi

“…First, we make the Jain's derivative-free method optimal and subsequently increase its efficiency index from 1.442 to 1.587. Then, a novel three-step computational family of iterative schemes for solving single variable nonlinear equations is given. …”
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Bifurcations of Spatially Inhomogeneous Solutions of a Boundary Value Problem for the Generalized Kuramoto–Syvashinsky Equation by Alina V. Sekatskaya

“…In this paper, a differential partial equation with an unknown function of three variables time and two spatial variables – is considered. …”
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Modeling of Ozone Interactions with Various Air Pollutants and Meteorological Factors Using Jaya and Teaching-Learning Based Optimization (TLBO) Algorithms by Nurcan Öztürk

“…In conclusion, it is shown that Jaya and TLBO algorithms can be used in the optimization of the regression function coefficients in modelling some air pollutants interactions and the best-fit equation for each parameter is obtained from the quadratic function.…”
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Correlation of magnetic resonance imaging parameters with montreal cognitive assessment-Indonesian (MOCA-INA) score in dementia patients at Prof. Dr. IGNG Ngoerah General Hospital,... by Made Widhi Asih, Elysanti Dwi Martadiani, I Wayan Gede Artawan Eka Putra, Felicia Nike, Putri Ayu Ratnasari, Nugra Arenz Raturandang, Jessieca Liusen, Anak Agung Parama Swari Khrisna, Luh Dindi Ayu Surya Kanti, Adsel Kartadinata

“…Correlation between variables was evaluated based on the correlation coefficient, which indicates the direction and strength of the correlation. …”
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Exploring restoration efforts from a social lens: statistical models reveal relationships between salmon habitat restoration efforts and ecological and social characteristics of th... by Brittany D King, Robert Fonner

“…Among the social explanatory variables, the percentage of non-Hispanic white residents in a subwatershed was the most prominent predictor of the number of restoration worksites across models, producing positive and statistically significant estimated coefficients in the instream, riparian, and total worksite models. …”
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Association between Oral Health Status and Diabetic Nephropathy-Related Indices in Japanese Middle-Aged Men by Masami Yoshioka, Yoshifumi Okamoto, Masahiro Murata, Makoto Fukui, Shizuko Yanagisawa, Yasuhiko Shirayama, Kojiro Nagai, Daisuke Hinode

“…A positive correlation between the CPI score and serum creatinine and a negative correlation between CPI score and eGFR (Spearman’s rank correlation coefficient, r=0.459, p<0.01, and r=−0.460, p<0.01, respectively) were observed. …”
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Fuzzy volume fraction model representation of blood-based sisko tri-hybrid nanofluid flow via a stretching cylinder by N. Deepa, P. Kavya, N. Thamaraikannan, S. Madhanraj, P. Asaigeethan, K. Loganathan

“…The triangular membership function (TMF) is utilized to analyze the variability of uncertainty, while the α− cut is responsible for controlling the TFNs. …”
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Association between weight-bearing ankle dorsiflexion range of motion during deep squat sitting and quality of life after ankle fracture surgery: a cross-sectional study by Hayato Miyasaka, Hayato Miyasaka, Bungo Ebihara, Takashi Fukaya, Koichi Iwai, Shigeki Kubota, Hirotaka Mutsuzaki, Hirotaka Mutsuzaki

“…Multivariate analysis was performed using the four subscales of the SAFE-Q (pain and pain-related, physical functioning and daily living, social functioning, and general health and well-being) as dependent variables.ResultsThe multivariate analysis revealed that weight-bearing ankle dorsiflexion ROM during deep squat sitting was an independent variable for pain and pain-related [standardized partial regression coefficient (β) = 0.584, P &lt; 0.001], physical functioning and daily living (β = 0.376; P = 0.006), social functioning (β = 0.317; P = 0.045), and general health and well-being (β = 0.483; P = 0.005). …”
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Data-driven diabetes mellitus prediction and management: a comparative evaluation of decision tree classifier and artificial neural network models along with statistical analysis by Idris Zubairu Sadiq, Babangida Sanusi Katsayal, Bashiru Ibrahim, Maryam Ibrahim, Hassan Aliyu Hassan, Umar Muhammad Ghali, Abdullahi Garba Usman, Abubakar Usman, Sani Isah Abba

“…Principal Component analysis further highlighted five clusters of health-related variables, identifying age-related metabolic indicators (AGE, HbA1c, BMI), kidney function markers (creatinine (Cr), Urea), cardiovascular lipid profiles (Cholesterol, LDL), lipid transport (VLDL), and protective cardiovascular indicator (HDL). …”
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Predictor Importance for Hydrological Fluxes of Global Hydrological and Land Surface Models by João Paulo L. F. Brêda, Lieke A. Melsen, Ioannis Athanasiadis, Albert VanDijk, Vinícius A. Siqueira, Anne Verhoef, Yijian Zeng, Martine van derPloeg

“…We analyzed the JULES, ORCHIDEE, HTESSEL, SURFEX, and PCR‐GLOBWB models for the relative importance of precipitation, climate, soil, land cover and topographic slope as predictors of simulated average evaporation, runoff, and surface and subsurface runoff. RF models functioned as a metamodel and could reproduce GHM/LSMs outputs with a coefficient of determination (R2) over 0.85 in all cases and often considerably better. …”
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The reproducibility of 31-phosphorus MRS measures of muscle energetics at 3 Tesla in trained men. by Lindsay M Edwards, Damian J Tyler, Graham J Kemp, Renee M Dwyer, Andrew Johnson, Cameron J Holloway, Alan M Nevill, Kieran Clarke

“…Estimates of mitochondrial function were variable, but experimentally useful. …”
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A robust deep learning approach for photovoltaic power forecasting based on feature selection and variational mode decomposition by Mokhtar Ali, Abdelkerim Souahlia, Abdelhalim Rabehi, Mawloud Guermoui, Ali Teta, Imad Eddine Tibermacine, Abdelaziz Rabehi, Mohamed Benghanem

“…To further enhance model inputs, Variational Mode Decomposition (VMD) is applied to extract informative Intrinsic Mode Functions (IMFs) from the selected features. A comparative evaluation of the models indicates that recurrent neural networks, particularly GRU and LSTM, deliver superior performance across various metrics, including RMSE, MAE, nRMSE, nMAE, R², and the correlation coefficient. …”
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Dual-Stream Enhanced Deep Network for Transmission Near-Infrared Dorsal Hand Vein Age Estimation with Attention Mechanisms by Zhenghua Shu, Zhihua Xie, Xiaowei Zou

“…Simultaneously, another deep residual network is leveraged to strengthen the representation ability on subtle dorsal vein textures. Moreover, variable activation functions and pooling layers are integrated into the respective streams to enhance the nonlinearity modeling of the dual-stream model. …”
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GDP per capita vs foreign direct investment: key drivers of a country's technological leadership by Aleksy Kwilinski

“…A true fixed-effects stochastic frontier model was applied to panel data, based on the Cobb-Doug- las production function and the translogarithmic function, to evaluate the determinants of technological development and identify technical efficiency. …”
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Promoting Social Participation in the Primary Care Field: An Ecological Study on the Potential Reduction of Multimorbidity Prevalence by Ryota Takahashi, Tadao Okada, Kazushige Ide, Taishi Tsuji, Katsunori Kondo

“…Multiple regression analysis was performed with MP as objective variable; social participation or household income were explanatory variables, and education, population density, and health check-ups were adjustment variables. …”
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Inference of Impulse Responses via Bayesian Graphical Structural VAR Models by Daniel Felix Ahelegbey

“…Impulse response functions (IRFs) are crucial for analyzing the dynamic interactions of macroeconomic variables in vector autoregressive (VAR) models. …”
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Impact of Low-dose Imaging on PET Quantitative Accuracy and Image Quality by SU Xuesong, GENG Jianhua, ZHENG Rong, WANG Xuejuan

“…Subsequently, the recovery coefficient (RC), contrast recovery coefficient (CRC), contrast-to-noise ratio (CNR), percent background variability (PBV), background coefficient of variation (BCV), and residual error (RE) of the lung insert at different image planes were calculated within the phantom. …”