Evaluation of Multiparameter Likelihoods through Iteration of Two-dimensional Slices by Joel S. Jayson

“…Markov Chain Monte Carlo (MCMC) computation has been the dominant instrument for evaluating multiparameter functions. For applications with a quasi-linear variable such as, A _s , the 2D iterative method is orders of magnitude more efficient than MCMC.…”
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Cardio-Ankle Vascular Index and Indices of Diabetic Polyneuropathy in Patients with Type 2 Diabetes by Akihiko Ando, Michiaki Miyamoto, Kazuhiko Kotani, Kenta Okada, Shoichiro Nagasaka, Shun Ishibashi

“…The cardio-ankle vascular index (CAVI) is used to test vascular function and is an arterial stiffness marker and potential predictor of cardiovascular events. …”
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Soil moisture and precipitation intensity jointly control the transit time distribution of quick flow in a flashy headwater catchment by H. Türk, C. Stumpp, M. Hrachowitz, K. Schulz, P. Strauss, G. Blöschl, M. Stockinger

“…The results showed that accounting for both soil moisture and precipitation intensity to define the shape of SAS functions for preferential flow improved the tracer simulation in streamflow (increasing the Nash–Sutcliffe efficiency from 0.31 to 0.51). …”
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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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Research on Ship Heave Motion Compensation Control Under Complex Sea State Environment Based on Improved Reinforcement Learning by ZHANG Qin, ZHOU Jingyi, WANG Xingyue, HU Xiong

“…The TD3 algorithm approximates the value function and policy by harnessing deep neural networks, equipping it to tackle complex and nonlinear sea condition challenges. …”
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Three-Dimensional Modified Cross-Section Hydrofoil Design and Performance Study by Hongpeng Cao, Yudong Xie, Zilei Ji

“…To improve the hydrodynamic performance of hydrofoils, this study combines the shape characteristics of flat and elliptical wings, uses parabolic function to fit the leading and trailing edges of hydrofoils, introduces the cross-section coefficient <i>λ</i> to characterize the cross-sectional size of hydrofoils along the spreading direction, and designs five hydrofoils with different cross-sections. …”
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Effects of shading on photosynthetic characteristics and shade-tolerance evaluation of three Ranunculaceae plants by HAN Ruiting, ZHAO Dandan, WANG Weiyi, ZHANG Gexiang*

“…The light saturation point(LSP), light compensation point(LCP)and dark respiration rate(Rd)of the three plants decreased gradually.(3)The original fluorescence(Fo)decreased first and then increased, while the maximum fluorescence(Fm), variable fluorescence(Fv), maximum photochemical efficiency of PS Ⅱ(Fv/Fm)and potential activity of PS Ⅱ(Fv/Fo)values increased first and then decreased; the quantum ratio of heat dissipation(φDo)and the energy dissipated per unit reaction center(DIo/RC)decreased first and then increased, while electron transport quantum yield(φEo), light energy absorbed per unit reaction center(ABS/RC), light energy captured per unit reaction center(TRo/RC), energy used to transfer electrons per unit reaction center(ETo/RC), photosynthetic performance index(PIabs)and comprehensive performance index(PItotal)increased first and then decreased.(4)Comprehensive analysis on 20 single indicators by using analysis methods such as principal component analysis and membership function method showed that the shade-tolerance of the three plants ranked as Thalictrum fortunei > Delphinium anthriscifolium var. savatieri > R. japonicus. …”
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A non-dominated sorting based multi-objective neural network algorithm of ethylene glycol hydrogenation reactor in energy reduction by Fakhrony Sholahudin Rohman, Sharifah Rafidah Wan Alwi, Dinie Muhammad, Muhamad Nazri Murat, Ashraf Azmi

“…Artificial intelligence (AI) can be applied to various ethylene glycol (EG) production aspects to improve efficiency, quality, and overall process optimization. …”
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Transfer Robustness Optimization for Urban Rail Transit Timetables by Liqiao Ning, Peng Zhao, Wenkai Xu, Ke Qiao

“…Next, to improve the computational efficiency, we propose an approximate linearization approach for the EETC function and introduce two types of binary variables and auxiliary substitution variables to convert the nonlinear model to a mixed-integer linear model. …”
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Implications of thermal stratification and radiative heat flux in blood-based ternary and dihybrid nanomaterial flow through a stretchable cylinder by Muzher Saleem, Ghada A. Khouqeer, Fazal Haq, Naglaa AbdelAll, Arshad Hussain, Mohammed Sallah

“…Non-dimensional mathematical model representing the physical phenomenon is solved through NDSolve function of Mathematica. Behavior of micropolar THNF and HNF velocity and thermal field versus influential variables are investigated. …”
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An inclusive solution based on grey water footprint for performance evaluation of industrial wastewater treatment systems by Keivan Arastou, Ali Dehnavi, Shervin Jamshidi

“…These advantages are critical for assessing an industrial WWTP treating complex wastewater, with hazardous pollutants and variable inflow. Moreover, we introduced four innovative criteria based on GWF and improved it as a multi-functional index. …”
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Modeling the position of tracked chassis in motion in the event of mechanical characteristics of separate drive electric motors of track contours by Goncharov K.A.

“…The use of electric motors in the structure of a separate drive of the tracked chassis circuits with a random combination of deviations of their sliding can both enhance the factors contributing to the relative run-up of the circuits and compensate for them depending on the function of the change in the motion resistance coefficient over time. …”
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Revolutionizing proton exchange membrane fuel cell modeling through hybrid aquila optimizer and arithmetic algorithm optimization by Manish Kumar Singla, S. A. Muhammed Ali, Ramesh Kumar, Pradeep Jangir, Mohammad Khishe, G. Gulothungan, Haitham A. Mahmoud

“…These parameters function as decision variables, and the objective function aimed for minimization is the sum square error (SSE) between the predicted and actual measured cell voltages. …”
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Investigation of Effective Factors to Reduce Natural Disaster Risks through Public Participation

“…Results from Pearson Correlation Coefficient indicated that independent variables, i.e., Social Sympathy, Feelings of Inability, Intellectual Function, Level of Awareness (from a given event) and Socio - economic Status, were significantly related to the dependent variable, namely, cooperation in decreasing risks from natural disasters. …”
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Performance of Machine Learning Classifiers for Diabetes Prediction by Mijala Manandhar, Shaikat Baidya, Babalpreet Kaur, Katia Atoji

“…The dataset included 768 instances with nine attributes, where the target variable indicated whether a patient tested positive for diabetes. …”
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SYNTHESIS OF QUASI BAND LADDER TRANSFORMING HIGH ORDER FILTERS by A. E. Kurochkin

“…To achieve this goal, all the synthesis tasks were solved, including the choice of the prototype, frequency transposition, calculation of the poles of the transfer function of the prototype, calculation of the poles of the transfer function of the filter, calculation of the reflection coefficient of the filter, the calculation of the input resistance of the filter, the implementation of the ladder chain by the Cauer method and denormalization of the values of the elements of the ladder chain. …”
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Modelling and optimisation of solar photovoltaic power using response surface methodology by Abdulrahman Mohammad, Mudhar Al-Obaidi, Hassan Dakkama, Haitham Bahlol

“…The response surface methodology model has indicated a linear relationship between the independent variables and power generated with a coefficient of determination of 98.45%. …”
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Prediction of Expected Fouling Time During Transmembrane Transition in Reverse Osmosis Systems by Jozsef Lakner, Gabor Lakner

“…However, due to the porous structure of membranes, they are prone to fouling, which reduces their efficiency and can eventually render the membranes incapable of functioning. …”
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Autonomous obstacle avoidance of underground coal mine transport robots based on intrinsic motivation reinforcement learning algorithm by ZHAO Kebao, LI Lingfeng, CHEN Zhuo, HAN Jun, YIN Rui

“…Existing robot obstacle avoidance methods mostly rely on preset rules or external reward signals, making it difficult to adapt to the complex and variable underground environment in coal mines. To achieve autonomous and efficient obstacle avoidance for underground coal mine transport robots, an autonomous obstacle avoidance method for underground coal mine transport robot based on Intrinsic Motivation Reinforcement Learning (IM-RL) algorithm was proposed. …”
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Multivariate predictive modeling of compressive strength in ground granulated blast furnace slag/fly ash-based alkali-activated concrete by Dina A. Emarah

“…Using a comprehensive dataset of 1590 samples with 14 input variables, it captures the complex, multi-variable dependencies affecting AAC's mechanical behavior. …”
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