An Objective and Subjective Evaluation of Masticatory Efficiency in Periodontal Patients Before and After Basic Periodontal Therapy: A Case Series Study by María José Moya-Villaescusa, Claudia López-Lisón, José María Montoya-Carralero, Alfonso Jornet-García, Arturo Sánchez-Pérez

“…Methods: A prospective, longitudinal, case series study was carried out in 42 periodontal patients treated at the University Odontology Clinic. Masticatory efficiency before and after basic periodontal treatment was assessed using both objective (HueCheck Gum test) and subjective (Quality of Masticatory Function Questionnaire: QMFQ) methods. …”
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Correlation and path analysis of interaction between snap beans yield and its components with crop management by N. Shaban

“…Results showed that fresh weight of pod/studied variant (+++0.99), fresh weight of one pod (+++0.77), fresh weight of pods/ plant (+++0.67), calcium content in bean pods (++0.57), pods number /plant (++0.51), pollen fertility (++0.44) had positive impact on yield. The partial function of the studied parameters on variability of bean yield is 98.9%. …”
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On a geometric approach to the estimation of interpolation projectors by Mikhail V. Nevskii, Alexey Y. Ukhalov

“…Here $\sigma S$ is the result of homothety of $S$ with respect to the center of gravity with coefficient $\sigma$. Let $d\geqslant n+1,$ $\varphi_1(x),\ldots,\varphi_d(x)$ be linearly independent monomials in $n$ variables, and $\varphi_1(x)\equiv 1,$ $\varphi_2(x)=x_1,\ \ldots, \varphi_{n+1}(x)=x_n.$ Put $\Pi:=$lin$(\varphi_1,\ldots,\varphi_d).$ The interpolation projector $P: C(\Omega)\to \Pi$ with a set of nodes $x^{(1)},\ldots, x^{(d)} \in \Omega$ is defined by equalities $Pf\left(x^{(j)}\right)=f\left(x^{(j)}\right).$ Denote by $\|P\|_{\Omega}$ the norm of $P$ as an operator from $C(\Omega)$ to $C(\Omega)$ . …”
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Non-parametric calibration estimation of distribution function under stratified random sampling by Abdullah Mohammed Alomair, Weineng Zhu, Usman Shahzad, Fawaz Khaled Alarfaj

“…By leveraging auxiliary information under a stratified random sampling (StRS) framework, the proposed methodology employs multiple calibration constraints with a chi-square distance measure to derive calibrated weights, enhancing estimation efficiency. The estimators incorporate key descriptive measures of auxiliary variable, including the CDF and coefficient of variation, and tackle the challenge of bandwidth selection using advanced techniques such as plug-in selectors and cross-validation approaches. …”
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VBP-YOLO-prune: Robust apple detection under variable weather via feature-adaptive fusion and efficient YOLO pruning by Haohai You, Hao Wang, Zhanchen Wei, Chunguang Bi, Lijuan Zhang, Xuefang Li, Yingying Yin

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Characterizing the effects of age, puberty, and sex on variability in resting-state functional connectivity in late childhood and early adolescence by Kelly A. Duffy, Andrea Wiglesworth, Donovan J. Roediger, Ellery Island, Bryon A. Mueller, Monica Luciana, Bonnie Klimes-Dougan, Kathryn R. Cullen, Mark B. Fiecas

“…We found decreased variability in global efficiency across the age range, and increased variability within the frontolimbic network driven primarily by those assigned female at birth (AFAB). …”
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Two-Dimensional Probability Models for the Weighted Discretized Fréchet–Weibull Random Variable with Min–Max Operators: Mathematical Theory and Statistical Goodness-of-Fit Analysis... by Sofian T. Obeidat, Diksha Das, Mohamed S. Eliwa, Bhanita Das, Partha Jyoti Hazarika, Wael W. Mohammed

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The constrained-disorder principle defines the functions of systems in nature by Yaron Ilan

“…The Constrained Disorder Principle (CDP) defines all systems in nature by their degree of inherent variability. Per the CDP, the intrinsic variability is mandatory for their proper function and is dynamically changed based on pressures. …”
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Morpho-functional groups as an efficient tool for monitoring and management of the Billings reservoir (São Paulo, Brazil) by Ana Carolina Peixoto Chamizo, Cacilda Thais Janson Mercante, Munique de Almeida Bispo Moraes, Clóvis Ferreira do Carmo, Matheus Barbosa Herbst de Oliveira, João Alexandre Saviolo Osti

“…This research applied the Morphology-Based Functional Groups (MBFGs) combined with classical approaches, such as community descriptor species and phytoplankton classes in the Billings reservoir. …”
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Efficiency of structural brain networks mediates age-associated differences in executive functioning in older adults by Geraldine Rodríguez-Nieto, Geraldine Rodríguez-Nieto, Caroline Seer, Caroline Seer, Hamed Zivari Adab, Hamed Zivari Adab, Antonio Jimenez-Marin, Sima Chalavi, Sima Chalavi, Amirhossein Rasooli, Amirhossein Rasooli, Jesús M. Cortés, Jesús M. Cortés, Jesús M. Cortés, Stefan Sunaert, Stephan P. Swinnen, Stephan P. Swinnen

“…Further regional efficiency analyses identified the nodes that contributed to the mediation effect of local efficiency.DiscussionThese results shed light on the shared variability among the integrity of structural brain networks and EF at older age. …”
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Research on Variable Circulation Design Method and Internal Flow Characteristic of the Axial Flow Pump by Xuewei Yu, Qili Gan, Zifan Ling, Jiahui Gong, Jiajia Tang, Lijian Shi

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Performance and variability analysis of ALD-grown wafer scale HfO2/Ta2O5-based memristive devices for neuromorphic computing by Sanjay Kumar, Sanjay Kumar, Deepika Yadav, Spyros Stathopoulos, Themis Prodromakis

“…Furthermore, the least values of coefficient of variability (CV) in the device switching voltages are 6.09% (VSET) and 3.22% (VRESET) in the case of device-to-device (D2D) while 1.76% (VSET) and 2.14% (VRESET) in the case of cycle-to-cycle (C2C). …”
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The Zhegalkin Polynomial of Multiseat Sole Sufficient Operator by Leonid Y. Bystrov, Egor V. Kuzmin

“…The value of it allows one to determine the self-duality of a Boolean function. It is proved that the preserving 0 and 1 or preserving neither 0 nor 1 Boolean function is self-dual if and only if the dual remainder of its corresponding Zhegalkin polynomial is equal to 0 for any sets of function variable values. …”
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Neural Network Method of Controllers’ Parametric Optimization with Variable Structure and Semi-Permanent Integration Based on the Computation of Second-Order Sensitivity Functions... by Serhii Vladov, Lukasz Scislo, Nina Szczepanik-Ścisło, Anatoliy Sachenko, Victoria Vysotska

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Deformation Characteristic Analysis and Engineering Application of a Variable Cross-sectional Flexible Pin by Chen Hengjian, Xiao Shuhong

“…The deflection equation and slope-deflection equation of the variable cross-sectional flexible pin are obtained by using the Green's function method. …”
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Effects of Pretreatments in Convective Dehydration of Rosehip (Rosa eglanteria) by Alejandra Mabellini, Elizabeth Ohaco, Carlos Alberto Márquez, Antonio De Michelis, Jorge Enrique Lozano

“…The aim of this work was to experimentally determine drying curves for thin layer and bed drying of rosehip fruits, with and without pretreatments, to reduce processing times as a function of drying air operating variables, to propose dehydration kinetics of fruits and to determine its kinetic parameters for further use within drying simulation software. …”
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Addressing Challenges in Simulating Inter–Annual Variability of Gross Primary Production by Ranit De, Shanning Bao, Sujan Koirala, Alexander Brenning, Markus Reichstein, Torbern Tagesson, Michael Liddell, Andreas Ibrom, Sebastian Wolf, Ladislav Šigut, Lukas Hörtnagl, William Woodgate, Mika Korkiakoski, Lutz Merbold, T. Andrew Black, Marilyn Roland, Anne Klosterhalfen, Peter D. Blanken, Sara Knox, Simone Sabbatini, Bert Gielen, Leonardo Montagnani, Rasmus Fensholt, Georg Wohlfahrt, Ankur R. Desai, Eugénie Paul‐Limoges, Marta Galvagno, Albin Hammerle, Georg Jocher, Borja Ruiz Reverter, David Holl, Jiquan Chen, Luca Vitale, M. Altaf Arain, Nuno Carvalhais

“…Both models simulated hourly GPP and were parameterized for (a) each site–year, (b) each site with an additional constraint on IAV (CostIAV), (c) each site, (d) each plant–functional type, and (e) globally. This was followed by forward runs using calibrated parameters, and model evaluations using Nash–Sutcliffe efficiency (NSE) as a model‐fitness measure at different temporal scales across 198 eddy‐covariance sites representing diverse climate–vegetation types. …”
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Evaluation of the Variability of Micro and Macro Spray Parameters as a Function of Sampling Time Using a Laser Doppler Analyzer by Dariusz Lodwik, Mariusz Koprowski

“…In the first stage of the research, the variability of the coefficients characterizing the spray spectrum as a function of variable measurement time was analyzed. …”
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Comparison of the efficiency of zero and first order minimization methods in neural networks by E. A. Gubareva, S. I. Khashin, E. S. Shemyakova

“…Numerous experiments show that the analytical calculation time of an N variable function’s gradient is approximately N/5 times longer than the calculation time of the function itself. …”
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A Hierarchical Archimedean Copula (HAC) model for climatic variables: an application to Kenyan data by Kevin Otieno, Linda Chaba, Linda Chaba, Evans Omondi, Evans Omondi, Collins Odhiambo, Collins Odhiambo, Bernard Omolo, Bernard Omolo

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