COMPARING GAUSSIAN AND EPANECHNIKOV KERNEL OF NONPARAMETRIC REGRESSION IN FORECASTING ISSI (INDONESIA SHARIA STOCK INDEX) by Yuniar Farida, Ida Purwanti, Nurissaidah Ulinnuha

“…The analysis results obtained the best method in predicting ISSI values, namely nonparametric kernel regression using Nadaraya-Watson estimator and Gaussian kernel function with the MAPE value of 15% and the coefficient of determination of 85%. …”
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Assessing the effect of dynamics of unpredictable locust invasive behavior and its effect on food security and community livelihood by Mfano Charles Petro

“…Additionally, it was observed that the deterrent coefficient in the invaded and source zones (ηi and ηs) has a significant impact on controlling the dynamic behavior of locusts.…”
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Prediction of Pile Bearing Capacity Using Opposition-Based Differential Flower Pollination-Optimized Least Squares Support Vector Regression (ODFP-LSSVR) by Nhat-Duc Hoang, Xuan-Linh Tran, Thanh-Canh Huynh

“…Based on such datasets, LSSVR is capable of generalizing a multivariate function that estimates values of pile bearing capacity based on a set of variables describing pile characteristics and ground conditions. …”
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Mediating Effects of Stakeholders and Supervision on Corporate Social Responsibility by Fenghua Wang, Janice Lo, Monica Lam

“…All the standardized path coefficients (β) of direct effects from institutional pressures, market/societal pressures, and structural support to corporate social responsibility benefits are less than 0.1. …”
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Quality of Life in Patients with Multiple Sclerosis by Grażyna Franek, Marzena Bieniak, Aleksandra Cieślik

“…In order to calculate the variables, the following measures were used: arithmetic mean, standard deviation, coefficient of variation, asymmetry coefficient, kurtosis coefficient, Person linear correlation coefficient, Spearman rank correlation coefficient. …”
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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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Simultaneous single-sample determination of NMNAT isozyme activities in mouse tissues. by Giuseppe Orsomando, Lucia Cialabrini, Adolfo Amici, Francesca Mazzola, Silverio Ruggieri, Laura Conforti, Lucie Janeckova, Michael P Coleman, Giulio Magni

“…Final assay validation was achieved in a tissue extract by comparing the activity and expression levels of individual isozymes, considering their distinctive catalytic efficiencies. Furthermore, considering the key role played by NMNAT activity in preserving axon integrity and physiological function, this assay procedure was applied to both liver and brain extracts from wild-type and Wallerian degeneration slow (Wld(S)) mouse. …”
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Comparing machine learning approaches for estimating soil saturated hydraulic conductivity. by Ali Akbar Moosavi, Mohammad Amin Nematollahi, Mohammad Omidifard

“…Results revealed that all NN models particularly PSO-NNs were efficient in prediction of Kfs. However, further evaluations may be recommended for other soil conditions and input variables to quantify their potential uncertainties and wider potential and versatility before they are used in other geographical locations/soil conditions.…”
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Contribution of entropy analysis on three-dimensional Prandtl model under Hall and ion slip effects with generalized mass and heat fluxes via OHAM by Sana Akbar, Muhammad Sohail, Syed Tehseen Abbas, Abha Singh

“…This article also examined the combined impacts of thermal conductivity change together with variable mass diffusion co-efficient within the heat and mass transport in the occurrence of Prandtl fluid. …”
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Non-destructive textural quality assessment of peaches and nectarines using near-infrared spectroscopy integration time by Eva Cristina Correa, Paola Baltazar, Pilar Barreiro, Natalia Hernández-Sánchez, Lourdes Lleó, Ángela Melado-Herreros, Belén Diezma

“…A principal component analysis (PCA) was used to analyze textural variability, and discriminant function analysis (DFA) and artificial neural networks (ANNs) were applied to classify fruit firmness levels.PCA effectively defined a new variable, PC1, that captured the variance in fruit texture, correlating positively with juiciness and negatively with firmness. …”
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Introducing the MESMER-M-TPv0.1.0 module: spatially explicit Earth system model emulation for monthly precipitation and temperature by S. Schöngart, S. Schöngart, L. Gudmundsson, M. Hauser, P. Pfleiderer, Q. Lejeune, S. Nath, S. I. Seneviratne, C.-F. Schleussner, C.-F. Schleussner, C.-F. Schleussner

“…Owing to their runtime efficiency, emulators are especially useful when large amounts of data are required, for example, for in-depth exploration of the emission space, for investigating high-impact low-probability events, or for estimating uncertainties and variability. …”
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A New Four‐Component L*‐Dependent Model for Radial Diffusion Based on Solar Wind and Magnetospheric Drivers of ULF Waves by Kyle R. Murphy, Jasmine Sandhu, I. Jonathan Rae, Thomas Daggitt, Sarah Glauert, Richard B. Horne, Clare E. J. Watt, Sarah Bentley, Adam Kellerman, Louis Ozeke, Alexa J. Halford, Sheng Tian, Aaron Breneman, Leonid Olifer, Ian R. Mann, Vassilis Angelopoulos, John Wygant

“…The new models use L∗ as it accounts for adiabatic changes due to the dynamic magnetic field coupled with an optimized set of four components of solar wind and geomagnetic activity, Bz, V, Pdyn, and Sym−H, as independent variables (inputs). These independent variables are known drivers of ULF waves and offer the ability to calculate diffusion coefficients at a higher cadence then existing models based on Kp. …”
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Long-term evolution of the calibration constant on a mobile water vapour Raman lidar by P. Chazette, J. Totems, F. Laly

“…We note that the use of ground-based measurements does not introduce any more uncertainty in the lidar calibration coefficient than vertical profiles obtained by radiosondes or airborne means. …”
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Convergence analysis of option drift rate inverse problem based on degenerate parabolic equation by Miao-miao Song, Zui-cha Deng, Xiang Li, Qiu Cui

“…In this paper, we study the convergence of the inverse drift rate problem of option pricing based on degenerate parabolic equations, aiming to recover the stock price drift rate function by known option market prices. Unlike the classical inverse parabolic equation problem, the article transforms the original problem into an inverse problem with principal coefficients of the degenerate parabolic equation over a bounded region by variable substitution, thus avoiding the error introduced by artificial truncation. …”
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Sparse Learning of the Disease Severity Score for High-Dimensional Data by Ivan Stojkovic, Zoran Obradovic

“…This problem is solved by addressing a dual formulation which is smooth and allows an efficient optimization. The proposed approach might be used as an effective and reliable tool for both scoring function learning and biomarker discovery, as demonstrated by identifying a stable set of genes related to influenza symptoms’ severity, which are enriched in immune-related processes.…”
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Investigating wave solutions in coupled nonlinear Schrödinger equation: insights into bifurcation, chaos, and sensitivity by Adil Jhangeer, Abdallah M. Talafha, Ariana Abdul Rahimzai, Lubomír Říha

“…The transformation of the coupled partial differential equation into ordinary differential equation is achieved by utilizing a complex wave variable. Exponential function combinations are applied to construct the wave solutions. …”
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An Intelligent Inspection and Scheduling Algorithm for Integrated Pipe Gallery Based on Cloud Robot by ZHOU Xiwei, SHANG Xiao, SHANG Xinjuan, YAN Maode, WANG Fafa

“…The algorithm has very strong exploring precision and variable function, which makes this algorithm of fewer iterations, and can effectively improve the real-time detection of pipeline leakage source in pipeline corridor. …”
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Magnetic Field Effects on Convective Heat Transfer of Ferrofluid from a Heated Sphere in Porous Media by Ayesha Aktar, Sharaban Thohura, Md. Mamun Molla

“…Numerical outcomes are then represented in terms of local Nusselt number, velocity, temperature profile, and skin friction coefficient, respectively for a range of porosity parameters, ϵ = 0.4, 0.6, 0.8, magnetic effect parameter or Hartmann number, Ha = 0.0, 1.0, 3.0, 5.0 and the ferroparticle volume fraction coefficients, ϕ = 0%, 2%, 4%, 6%. …”
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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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