Search Results (224)

This paper proposes an enhanced hierarchical fuzzy Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) integrated with the Analytic Network Process (ANP) for solving multi-criteria decision-making (MCDM) problems under uncertainty. Conventional fuzzy TOPSIS models often face significant challenges, such as restrictions to specific fuzzy number formats, difficulties in normalization when zero or very small values appear, and limited capacity to capture hierarchical interdependencies among criteria. To address these limitations, we develop a generalized fuzzy geometric mean approach for deriving weights from pairwise comparisons that can accommodate multiple fuzzy number types. Moreover, a novel normalization function is introduced, which ensures mathematically valid outcomes within the [0, 1] interval while avoiding division-by-zero and inconsistency issues. The proposed method is validated through both a numerical building selection problem and a practical supplier selection case study. Comparative analyses against established fuzzy MCDM models demonstrate the improved robustness, flexibility, and accuracy of the approach. Additionally, a sensitivity analysis confirms the stability of results with respect to variations in criteria weights, fuzzy number formats, and normalization techniques. These findings highlight the potential of the proposed fuzzy hierarchical TOPSIS-ANP framework as a reliable and practical decision support tool for complex real-world applications, including supply chain management and resource allocation under uncertainty. Full article

The increase in the volume of construction work carried out with chemical anchors has led to a corresponding growth in the supply of these products on the market. Anchors possess numerous characteristics, including strength, anchorage displacement, temperature, curing time, and cost. Designers face the challenge of choosing the optimal solution for specific construction conditions. In practice, this often results in choosing anchors with maximum strength and minimum cost, which is not always the best option for long-term use. The authors of this study propose addressing this challenge through a multi-criteria optimization method based on the Harrington function. For implementation, 18 criteria were used. They were derived from reference sources and experimental results. Tests were conducted under short-term and long-term static loading. Based on these tests, strength characteristics were determined, and statistical analysis was carried out to calculate coefficients of variation and confidence intervals for the mean values. Nine types of chemical anchors with different bases were tested: epoxy-based, acrylate-based, methacrylate-based, polyester-based, and epoxy-acrylate-based (five samples in each series). In this study, the assumption that all criteria have equal weight coefficients is made as a limitation. The results of the study are valid only for static loading of anchors in uncracked concrete. The optimal adhesive compound was determined for the basic winter and summer sets of criteria. The practical significance lies in the implementation of a multi-criteria optimization method for selecting the adhesive compound. This approach allows users to choose the optimal adhesive compound for their needs. Full article

Background: Muscle strength asymmetries between limbs are common in physically active populations and may influence performance and injury risk. This study aimed to: (i) analyze the reliability of the seated unilateral cable row exercise using a functional electromechanical dynamometer (FEMD) and to examine differences in reliability between sides and contraction types; (ii) investigate the relationship between the dominant and non-dominant sides, as well as between the dynamic and static force production of the back muscles; and (iii) quantify force output and assess interlimb asymmetries. Methods: Twenty-nine young physically active athletes completed two sets of four repetitions of a seated unilateral cable row at 0.30 m·s⁻¹ using the FEMD, followed by a 6-s isometric contraction. Two testing sessions were conducted seven days apart. Reliability was assessed using paired t-tests, the effect size, the coefficient of variation (CV), the standard error of measurement, and the intraclass correlation coefficient (ICC), with 95% confidence intervals. Results: Peak and average force values showed very high to extremely high relative reliability (ICC = 0.86–0.96) and acceptable absolute reliability (CV ≈ 10%). Differences between dominant and non-dominant sides varied depending on contraction type. While group-level asymmetries did not exceed 10%, individual analysis revealed that 14%, 32%, and 7% of participants had asymmetries greater than 15% in isometric, concentric, and eccentric force, respectively. Conclusions: This test demonstrates strong reliability and provides a practical method for assessing upper limb asymmetries in physically active individuals, with potential applications in performance monitoring and injury prevention. Full article

Background/Objectives: Electrical threshold testing (ETT) offers a promising method for assessing somatosensory function. Despite its growing use, fundamental aspects such as the physiological recovery time required between repeated threshold measurements remain poorly understood. This gap is critical when evaluating sensory, motor, or pain thresholds (EST, EMT, EPT) in pre–post designs or rapid intra-session protocols. The aim is to investigate the short-term recovery dynamics of electrical thresholds following electrical threshold testing, and to determine the minimum interval required for values to return to a stable baseline. Methods: In this pilot, repeated-measures study, 10 healthy adults (20 upper limbs) underwent three progressive stimulation trials (sensory, motor, and pain). Electrical thresholds were assessed at fixed recovery intervals (0–120 s), with duplicate measurements at each time point. Stability was defined as the absence of significant differences between repeated measures. Results: EST stabilized rapidly after sensory or motor stimulation, showing no significant differences beyond 0 and 15 s, respectively. Within pain stimulation, EST recovered at 60 s. EMT showed immediate recovery with motor stimulation and required longer recovery with pain stimulation, with stabilization observed at 90 s. EPT exhibited the highest variability, with the smallest time-dependent differences observed immediately after the first assessment. Conclusion: Recovery time after electrical stimulation varies by threshold type and intensity of the stimuli. EST and EMT can be reliably reassessed immediately after sensory and motor stimulation, respectively. However, when stimulation reaches EPT level, EST requires 60 s to recover and EMT needs 90 s. EPT demonstrates higher variability, indicating the need for further investigation. These findings support the implementation of standardized recovery intervals in ETT and underscore the importance of interpreting EPT results with caution during rapid assessments. Full article

This paper presents a comprehensive reliability analysis framework for the Chris–Jerry (CJ) lifetime distribution under an improved adaptive progressive Type-II censoring plan. The CJ model, recently introduced to capture skewed lifetime behaviors, is studied under a modified censoring structure designed to provide greater flexibility in terminating life-testing experiments. We derive maximum likelihood estimators for the CJ parameters and key reliability measures, including the reliability and hazard rate functions, and construct approximate confidence intervals using the observed Fisher information matrix and the delta method. To address the intractability of the likelihood function, Bayesian estimators are obtained under independent gamma priors and a squared-error loss function. Because the posterior distributions are not available in closed form, we apply the Metropolis–Hastings algorithm to generate Bayesian estimates and two types of credible intervals. A comprehensive simulation study evaluates the performance of the proposed estimation techniques under various censoring scenarios. The framework is further validated through two real-world datasets: one involving rainfall measurements and another concerning mechanical failure times. In both cases, the CJ model combined with the proposed censoring strategy demonstrates superior fit and reliability inference compared to competing models. These findings highlight the value of the CJ distribution, together with advanced censoring methods, for modeling lifetime data in physics and engineering applications. Full article

The development of technology has influenced changes in agricultural production. Farmers are increasingly using modern devices and machinery that provide valuable information, and to manage this information effectively, it is necessary to use specialized applications. This research aims to evaluate various applications and determine which one is most suitable for small- and medium-sized farmers to adopt in precision agriculture. This research employed expert decision-making to determine the importance of criteria and evaluate applications using linguistic values. Due to the presence of uncertainty in decision-making, an interval type-2 fuzzy (IT2F) set was used, which addresses this problem through the support of a membership function. This approach allows for the display of uncertainty and imprecision using an interval rather than a single exact value. This enables a more flexible and realistic representation of ratings, leading to more confident decision-making. These membership functions are formed in such a way that there is symmetry around the central linguistic value. To use this approach, the SiWeC (simple weight calculation) and CORASO (compromise ranking from alternative solutions) methods were adapted. The results of the IT2F SiWeC method revealed that the most important criteria for experts are data accuracy, efficiency, and simplicity. The results of the IT2F CORASO method displayed that the A3 application delivers the best results, confirmed by additional analyses. This research has indicated that digital tools, in the form of applications, can be effectively used in small- and medium-scale precision agriculture production. Full article

In this study, we develop new Hermite–Hadamard and Hermite–Hadamard–Fejér type inequalities for fuzzy interval-valued functions (FIVFs) that exhibit h-Godunova–Levin convexity, using the framework of the Riemann–Liouville fractional (RLF) q-integral. We introduce novel fuzzy extensions of classical inequalities and establish corresponding inclusion relations by utilizing the properties of fuzzy RLF q-integrals. Furthermore, we validate the theoretical results through illustrative numerical examples and graphical representations, demonstrating the applicability and effectiveness of the derived inequalities in the context of fuzzy and interval analysis. Full article

Determining the Jensen–Mercer inequality for interval-valued coordinated convex functions has been a challenging task for researchers in the fields of inequalities and interval analysis. We use ${\ominus }_g$ to establish the Jensen–Mercer inequality for interval-valued coordinated convex functions. In this paper, we make significant strides in establishing new results by introducing a novel approach. We present a Hermite–Hadamard (H.H.) Mercer-type inequality for interval-valued coordinated convex functions and show how it generalizes the traditional H.H. inequality. Specifically, the H.H. inequality for interval-valued coordinated convex functions can be derived as a special case by considering the endpoints of the H.H. Mercer-type inequality. Furthermore, we provide computational results that verify the accuracy of recent findings in the literature. Our results indicate that the proposed new results impose highly effective constraints on integrals of the specified functions and are valid for a broader class of functions. These new findings have significant implications for applications in fields such as economics, engineering, and physics, where they can improve the precision of system modeling and optimization. Full article

The Kolmogorov–Arnold network (KAN) is a regression model that is based on a representation of an arbitrary continuous multivariate function by a composition of functions of a single variable. Experimentally obtained datasets for regression models typically include uncertainties, which in some cases, cannot be neglected. The conventional way to account for the latter is to model confidence intervals of the systems’ outputs in addition to the expected values of the outputs. However, such information may be insufficient, and in some cases, researchers aim to obtain probability distributions of the outputs. The present paper proposes a method for estimating probability distributions of the outputs by constructing an ensemble of models. The suggested approach covers input-dependent probability distributions of the outputs and is capable of capturing the multi-modality, as well as the variation of the distribution type with the inputs. Although the method is applicable to any regression model, the present paper combines it with KANs, since their specific structure leads to the construction of computationally efficient models. The source codes are available online. Full article

The novelty herein pertains to a class of fractional differential equations involving the Hadamard fractional derivative of higher order. Our investigation encompasses the fractional integral operator of a logarithmic function. The mathematical tools utilized in this study are derived from an important function, wherein its behavior in terms of maximum value facilitates the establishment of bounds necessary for proving the existence of solutions, specifically through Green’s function. Based on this, we endeavor to estimate the bounds of Green’s function as well as analyze its properties within the considered interval. This approach enables us to establish the Hartman–Wintner- and Lyapunov-type inequalities for a class of fractional Hadamard problems. Furthermore, we introduce a novel technique to determine the maximum value of Green’s function. Finally, we illustrate these findings through two applications. Full article

Clarifying the spatiotemporal relationship between urban ecosystem services and changes in landscape patterns is essential, as it has significant implications for balancing ecological protection with socio-economic development. However, existing studies have largely focused on the one-sided impact of landscape patterns on either the supply or demand of ESs, with limited investigation into how changes in these patterns affect the growth rates of both supply and demand. The central urban area, characterized by complex urban functions, intricate land use structures, and diverse environmental challenges, further complicates this relationship; yet, the spatiotemporal differentiation patterns of ecosystem services’ supply–demand dynamics in such regions, along with the underlying influencing mechanisms, remain insufficiently explored. To address this gap, the present study uses Shenyang’s central urban area, China as a case study, integrating multiple data sources to quantify the spatiotemporal variations in landscape pattern indices and five ecosystem services: water retention, flood regulation, air purification, carbon sequestration, and habitat quality. The XGBoost model is employed to construct non-linear relationships between landscape pattern indices and the supply–demand ratios of these services. Using SHAP values and LOWESS analysis, this study evaluates both the magnitude and direction of each landscape pattern index’s influence on the ecological supply–demand ratio. The findings outlined above indicate that: there are distinct disparities in the spatiotemporal distribution of landscape pattern indices at the patch type level. Additionally, the changing trends in the supply, demand, and supply–demand ratios of ecosystem services show spatiotemporal differentiation. Overall, the ecosystem services in the study area are developing negatively. Further, the impact of landscape pattern characteristics on ecosystem services is non-linear. Each index has a unique effect, and there are notable threshold intervals. This study provides a novel analytical approach for understanding the intricate relationship between landscape patterns and ESs, offering a scientific foundation and practical guidance for urban ecological protection, restoration initiatives, and territorial spatial planning. Full article

Adverse cardiovascular events and increased mortality are associated with cardiac autonomic nervous system dysfunction in the early stages of the systemic sclerosis (SSc), even prior to the development of cardiac fibrosis. The objective of the study was to evaluate the impact of a three-month exercise training regimen and a subsequent comparable period of detraining on the activity of the cardiac autonomic nervous system in patients with SSc. A total of forty patients with SSc were randomized to either the control group (Group COΝ) or the exercise training group (Group ET). Cardiopulmonary exercise testing was performed at baseline, three months later, and six months later to assess peak oxygen uptake (VO₂peak). They also had 24 h electrocardiogram monitoring for heart rate variability (HRV) and heart rate turbulence analysis. The following time-domain indices were evaluated in the context of HRV analysis: the standard deviation of NN intervals (SDNN), the root mean square of successive RR interval differences (rMSSD), and the percentage of successive RR intervals that differ by more than 50 ms (pNN50). Additionally, regarding the frequency-domain indicators, the low-frequency (LF) and high-frequency (HF) components, as well as the LF/HF ratio, were evaluated. Independent t-tests and Chi-square tests were used for baseline comparisons, while two-way repeated measures ANOVA with Bonferroni post hoc tests assessed changes over time and between groups. Linear and multiple regression analyses were conducted to explore relationships among variables and identify predictors of HRV indices and VO₂peak. Group ET implemented a three-month mixed-type exercise training program, while Group COΝ received standard care. Group ET improved indices of vagal activity [rMSSD by 32.6% (p = 0.017), pNN50 by 57.1% (p = 0.01) and HF by 20.1% (p = 0.01)] and sympathovagal activity [SDNN by 15.5% (p = 0.002) and LF/HF by 12.03% (p = 0.004)] after three months. Exercising patients also increased their VO₂peak by 20.8% (p = 0.001). A robust positive correlation was observed between ΔVO₂peak and ΔSDNN (r = 0.754, p < 0.001). After three months, there was no statistically significant difference in the VO₂peak or any HRV index in the group COΝ. Compared to the baseline values, there was no statistically significant difference in group ET at 6 months, whereas the control group exhibited a decline. In summary, a three-month mixed-type exercise training program can enhance the cardiorespiratory efficiency and cardiac autonomic nervous system function of patients with SSc, as well as alleviate the deterioration that arises following the detraining period. Full article

A methodology for the statistical modeling of boundary value problems of mathematical physics for parabolic equations used to describe transport processes in a layer with incomplete data at the boundary of a body has been developed and presented. The boundary value problem is formulated for the case of a non-zero initial condition, the presence of a stable source at one boundary of the body (classical boundary condition), and a sample of experimental data for the desired function at the other boundary (statistical boundary condition). A linear regression model obtained from experimental data by the least squares method is used as a boundary condition. The article defines two-sided statistical estimates of the solution of the boundary value problem through linear regression coefficients, analyzes the mathematical model taking into account the influence of the sample size and covariance, determines the reliable intervals for linear regression and the desired function depending on the given level of reliability. The influence of the experimental data statistical characteristics on the desired function at the lower layer’s boundary for different types of samples in the case of large or small-time intervals is studied. The two-sided critical domain is obtained and analyzed on the basis of Fisher’s criterion. The influence of the reliability level on the reliable intervals, the solution to the parabolic boundary value problem, and the width of the bilateral critical domain constructed for the solution is analyzed. Full article

Life testing of products often requires extended observation periods. To shorten the duration of these tests, products can be subjected to more extreme conditions than those encountered in normal use; an approach known as accelerated life testing (ALT) is considered. This study investigates the estimation of unknown parameters and the acceleration factor for the modified Fréchet-Lomax exponential distribution (MFLED), utilizing Type II progressively first-failure censored (PFFC) samples obtained under the framework of constant-stress partially accelerated life testing (CSPALT). Maximum likelihood (ML) estimation is employed to obtain point estimates for the model parameters and the acceleration factor, while the Fisher information matrix is used to construct asymptotic confidence intervals (ACIs) for these estimates. To improve the precision of inference, two parametric bootstrap methods are also implemented. In the Bayesian context, a method for eliciting prior hyperparameters is proposed, and Bayesian estimates are obtained using the Markov Chain Monte Carlo (MCMC) method. These estimates are evaluated under both symmetric and asymmetric loss functions, and the corresponding credible intervals (CRIs) are computed. A comprehensive simulation study is conducted to compare the performance of ML, bootstrap, and Bayesian estimators in terms of mean squared error and coverage probabilities of confidence intervals. Finally, real-world failure time data of light-emitting diodes (LEDs) are analyzed to demonstrate the applicability and efficiency of the proposed methods in practical reliability studies, highlighting their value in modeling the lifetime behavior of electronic components. Full article

Hemp (Cannabis sativa L.) products have gained attention in poultry nutrition for their rich content of polyunsaturated fatty acids (PUFAs), bioactive compounds, and potential functional benefits. However, findings on their impact on laying-hen performance, egg quality, and yolk fatty acid profiles have been inconsistent. This meta-analysis aimed to evaluate the effects of dietary hemp products on laying-hen performance, egg quality traits, and yolk fatty acid composition, while exploring potential sources of heterogeneity across studies. A comprehensive literature search identified 21 studies that met the inclusion criteria. A random-effects model was used to calculate standardized mean differences (SMDs) with 95% confidence intervals (CIs) for various outcomes, including production performance, egg quality, and yolk fatty acid profiles. Subgroup and meta-regression analyses assessed the influence of factors such as inclusion level, hen age, and hemp product type. The results showed that hemp supplementation had no significant effect on hen-day production, egg mass, feed conversion ratio, or feed intake. However, yolk redness (SMD = 4.40; 95% CI: 2.46, 6.33; p < 0.001) and yellowness (SMD = 4.45; 95% CI: 2.75, 6.16; p < 0.001) were significantly enhanced. Hemp feeding also increased n-3 PUFA levels in egg yolk, including C18:3n3, C20:5n3, and C22:6n3, while reducing saturated and monounsaturated fatty acids. Subgroup analysis indicated that inclusion levels > 10% and hen age ≤ 25 weeks were associated with slight reductions in hen-day production, whereas older hens (>25 weeks) showed increased egg weight. In conclusion, hemp products can enrich yolk pigmentation and n-3 PUFA content in eggs, supporting the production of functional, value-added eggs without compromising the laying-hen performance. Full article