Search Results (537)

Decision-making theory has developed over many decades at the intersection of economics, mathematics, psychology, and engineering. Its classical foundations include Bernoulli’s expected utility theory, von Neumann and Morgenstern’s rational choice theory, and the criteria proposed by Savage, Wald, Hurwicz, and others. However, in real-world contexts, decisions are made under uncertainty, incompleteness, and unreliability of information, which classical approaches do not adequately address. To overcome these limitations, modern multi-criteria decision-making methods such as Analytic Hierarchy Process (AHP), Technique for Order Preference by Similarity to Ideal Solution (TOPSIS), VlseKriterijumska Optimizacija I Kompromisno Resenje (Compromise solution approach) (VIKOR), and ELimination Et Choix Traduisant la REalité (Elimination and Choice Expressing Reality) (ELECTRE), as well as their fuzzy and Z-number extensions, are widely applied to the modeling and evaluation of complex systems. These Z-number extensions are based on the concept of Z-numbers introduced by Lotfi Zadeh in 2011 to formalize higher-order uncertainty. This study introduces the Z-Regret principle, which extends Savage’s regret criterion through the use of Z-numbers. Supported by Rafik Aliev’s mathematical justifications concerning arithmetic operations on Z-numbers, the model evaluates regret not only as a loss relative to the best alternative but also by incorporating the degree of confidence and reliability of this evaluation. Calculations for the selection of digital advertising platforms in terms of performance assessment under various scenarios demonstrate that the Z-Regret principle enables more stable and well-founded decision-making under uncertainty. Full article

Variograms are a cornerstone of spatial analysis in geostatistics, traditionally applied to real-valued variables under the intrinsic hypothesis. Many soil properties, particularly when integrating magnetic and geochemical measurements, can be expressed as complex-valued variables that capture both magnitude and phase information. In the case of magnetic susceptibility, the imaginary component reflects energy losses associated with viscous magnetization, which in soils can indicate the presence of pedogenic ferrimagnetic minerals, while its relative increase may also reveal anthropogenic magnetite contamination. This study examines the formulation and application of variograms for such complex-valued variables in the context of soil research. Two complementary definitions are considered: an intrinsic-based approach, which directly estimates the variogram from increments and is applicable under the intrinsic hypothesis, and a covariance-based approach, which requires stronger second-order stationarity. Simulated complex-valued soil property data with controlled spatial structures were used to compare the behaviour of these formulations with their real-valued counterparts. The findings indicate that complex-valued variograms preserve additional spatial information, particularly related to local phase shifts, while maintaining compatibility with conventional variographic modelling. Full article

Schrödinger’s operator relations combined with Einstein’s special relativistic energy-momentum equation produce the linear Klein–Gordon partial differential equation. Here, we extend both the operator relations and the energy-momentum relation to determine new families of nonlinear partial differential relations. The Planck–de Broglie duality principle arises from Planck’s energy expression $e=h\nu$, de Broglie’s equation for momentum $p=h/\lambda$, and Einstein’s special relativity energy, where h is the Planck constant, $\nu$ and $\lambda$ are the frequency and wavelength, respectively, of an associated wave having a wave speed $w=\nu \lambda$. The author has extended these relations to a family that is characterised by a second fundamental constant $h^{\prime }$ and underpinned by Lorentz invariant power-law particle energy-momentum expressions. In this note, we apply generalized Schrödinger operator relations and the power-law relations to generate a new family of nonlinear partial differential equations that are characterised by the constant $\kappa =h^{\prime }/h$ such that $\kappa =0$ corresponds to the Klein–Gordon equation. The resulting partial differential equation is unusual in the sense that it admits a stretching symmetry giving rise to both similarity solutions and simple harmonic travelling waves. Three simple solutions of the partial differential equation are examined including a separable solution, a travelling wave solution, and a similarity solution. A special case of the similarity solution admits zeroth-order Bessel functions as solutions while generally, it reduces to solving a nonlinear first-order ordinary differential equation. Full article

Caleosins (CLOs) or peroxygenases (PXGs), a class of structural proteins of lipid droplets (LDs), comprise a small family of multifunctional proteins widely involved in oil accumulation, organ development, and stress responses. Despite the proposal of two clades termed H and L in Arabidopsis thaliana, their evolution in the order Brassicales has not been well established. In this study, the first genome-wide analysis of the caleosin family was conducted in papaya (Carica papaya), a Caricaceae plant without any recent whole-genome duplication (WGD). A high number of five members representing both H and L clades were identified from the papaya genome. Further identification and comparison of 68 caleosin genes from 14 representative plant species revealed seven orthogroups, i.e., H1–4 and L1–3, where H1 and L1 have already appeared in the basal angiosperm Amborella trichopoda, supporting their early divergence before angiosperm radiation. Five CpCLO genes belong to H1 (1) and L1 (4), and extensive expansion of the L1 group was shown to be contributed to by species-specific tandem and transposed duplications, which may contribute to environmental adaptation. Orthologous and syntenic analyses uncovered that lineage-specific expansion of the caleosin family in Brassicales relative to A. trichopoda was largely contributed to by tandem duplication and recent WGDs, as well as the ancient γ whole-genome triplication (WGT) shared by all core eudicots. Independent gain or loss of certain introns and apparent expression divergence of caleosin genes were also observed. Tissue-specific expression analysis showed that CpCLO2 and −5 are constitutively expressed, whereas others appear to be tissue-specific, implying function divergence. Interestingly, the H-forms CpCLO1 and RcCLO1 were shown to exhibit similar expression profiles to most oleosin genes that are preferentially expressed oil-rich tissues such as seeds/endosperms, shoots, and calluses, implying their putative involvement in oil accumulation, as observed in Arabidopsis. The results obtained from this study provide a global view of CpCLO genes and insights into lineage-specific family evolution in Brassicales, which facilitates further functional studies in papaya and other non-model species. Full article

Background/Objectives: Tubo-ovarian high-grade serous carcinoma (HGSC) is a highly lethal malignancy, usually diagnosed at an advanced stage due to the lack of early symptoms and biomarkers. Contraceptive hormone use is associated with a reduced risk of HGSC, but the relative contributions of natural versus synthetic progestins, and their interaction with estrogens, are poorly understood. Methods: We evaluated the chemo-preventive efficacy of a synthetic progestin medroxyprogesterone acetate (MPA), progesterone (P4), and combined 17β-estradiol-progesterone (E2 + P4) in a well-characterized genetically engineered mouse model (GEMM) of oviductal HGSC based on the conditional inactivation of one or both alleles of the Brca1, Trp53, Rb1, and Nf1 tumor suppressor genes (BPRN-het and BPRN-homo mice, respectively). Mice received hormones or placebo via slow-release pellets implanted subcutaneously. After induction of tumor formation, the mice were monitored for tumor development, progression, and survival. Tumor incidence was assessed histologically, and hormone effects were further explored via RNA-seq analysis of oviductal tissues. Results: MPA significantly reduced HGSC incidence and delayed tumor progression compared to the placebo, P4, and P4 + E2 in both BPRN-homo and BPRN-het mice, with up to 78% tumor-free survival in the MPA-treated BPRN-het cohort. P4 monotherapy did not provide significant protection vs. the placebo, but the effects of P4 could have been impacted by a failure to achieve sustained release of the hormone beyond 4–8 weeks. The E2 + P4 combination accelerated tumorigenesis and reduced survival (p < 0.0001 in BPRN-homo and p = 0.0004 in BPRN-het mice). MPA did not affect tumorigenesis in a colon cancer GEMM, or the growth of mouse HGSC-derived cells in vivo, suggesting the role of MPA in the early stages of HGSC development. Gene expression analyses showed that P4 and MPA downregulated cholesterol homeostasis, early and late estrogen response, and epithelial–mesenchymal transition pathways, though only MPA afforded tumor protection. Conclusions: These findings demonstrate that a synthetic progestin, specifically MPA, confers robust protection against HGSC development, while a combination including E2 (E2 + P4) increases risk. This work also illustrates how HGSC GEMMs can be used to compare the chemo-preventive effects of various synthetic progestins on HGSC development in order to prioritize the most effective ones for use in preventing HGSC in both general and high-risk populations. Full article

This study develops a tractable, closed-form expression for the asymptotic variance of the coefficient of variation (CV) estimator under a reparameterized Birnbaum–Saunders (BirSau) distribution. Using the method of moments, we derive analytical formulas for the mean, variance, and coefficient of variation of $X\sim \mathrm{BirSau}(\mu ,\lambda )$ and construct a plug-in estimator for the CV. By applying the delta method within this new nonlinear parametrization, we obtain an explicit and compact expression for the asymptotic variance of the CV estimator, thereby extending general asymptotic theory to a distribution-specific setting where higher-order moments lack closed forms under the classical parametrization. Extensive Monte Carlo simulations are conducted to examine the estimator’s finite-sample performance under various parameter configurations and sample sizes. The results demonstrate that the estimator exhibits decreasing bias and variance as the sample size increases, with strong convergence to its theoretical asymptotic behavior. A real-data application using rainfall measurements from northeastern Thailand further illustrates the practical utility of the proposed approach in quantifying relative variability across regions. These findings provide a concise analytical foundation for the coefficient of variation under the Birnbaum–Saunders framework, enhancing its theoretical development and facilitating practical implementation in environmental and reliability analyses. Full article

Catalytic upgrading of vacuum residue (VR) is critical for enhancing fuel yield and reducing waste in petroleum refining. This study explores VR cracking over a novel cerium-loaded acidified metakaolinite catalyst (MKA800–20%Ce) prepared via calcination at 800 °C, acid leaching, and wet impregnation with 20 wt.% Ce. The catalyst was characterized using FTIR, BET, XRD, TGA, and GC–MS to assess structural, textural, and thermal properties. Catalytic cracking was carried out in a fixed-bed batch reactor at 350 °C, 400 °C, and 450 °C. The MKA800@Ce20% catalyst showed excellent thermal stability and surface activity, especially at higher temperatures. At 450 °C, the catalyst yielded approximately 11.72 g of total liquid product per 20 g of VR (representing a ~61% yield), with ~3.81 g of coke (~19.1%) and the rest as gaseous products (~19.2%). GC-MS analysis revealed enhanced production of light naphtha (LN), heavy naphtha (HN), and kerosene in the 400–450 °C range, with a clear temperature-dependent shift in product distribution. Structural analysis confirmed that cerium incorporation enhanced surface acidity, redox activity, and thermal stability, promoting deeper cracking and better product selectivity. Kinetics were investigated using an eight-lump first-order model comprising 28 reactions, with kinetic parameters optimized through a genetic algorithm implemented in MATLAB. The model demonstrated strong predictive accuracy taking into account the mean relative error (MRE = 9.64%) and the mean absolute error (MAE = 0.015) [MAE: It is the absolute difference between experimental and predicted values; MAE is dimensionless (reported simply as a number, not %). MRE is relative to the experimental value; it is usually expressed as a percentage (%)] across multiple operating conditions. The above findings highlight the potential of Ce-modified kaolinite-based catalysts for efficient atmospheric pressure VR upgrading and provide validated kinetic parameters for process optimization. Full article

This study develops an improved family of estimators for estimating the finite population median within a two-phase sampling method. The proposed estimators, which use transformation techniques to reduce survey costs when full auxiliary information is unavailable, yield more accurate results than traditional methods. These transformations employ robust statistical measures such as Hodges–Lehmann location, Gini mean difference, and Bowley’s skewness, which strengthen resistance against outliers and heavy-tailed distributions. Through the use of these modern tools within the two-phase sampling framework, the proposed estimators achieve greater flexibility and robustness compared to conventional quantile-based approaches. A first-order approximation is employed to derive the bias and mean squared error expressions. The performance of the proposed estimators is examined through simulation experiments across multiple distributional scenarios and validated using real datasets against standard approaches. Findings based on percent relative efficiency confirm that the proposed estimators improve the accuracy and efficiency of median estimation in two-phase sampling, demonstrating superiority over conventional methods across various practical scenarios. Full article

Background/Objectives: Childbirth is a natural and joyfully anticipated life event for parents and relatives. Yet, in some cases, it can be a medical emergency requiring immediate intervention, i.e., neonatal resuscitation. The majority of newborns breathe spontaneously; a small number, though, may receive basic life support (assisted transition), and an even smaller but clinically significant number require advanced life support (resuscitation). Within the context of family-centered care, the presence of parents during resuscitation has emerged as a factor with potential implications for emotional adjustment, communication with healthcare providers, and early parent–infant bonding. However, the presence of family members during neonatal resuscitation remains a subject of ongoing debate among healthcare professionals (HCPs). Despite increasing recognition of its potential benefits, HCPs’ views on parental presence during such critical procedures have not been extensively investigated in Greece. This study aims at developing and validating a tool to assess healthcare professionals’ views on parental presence during neonatal resuscitation. Methods: A preliminary questionnaire was developed based on the principles of family-centered care and adapted to the Greek population. The first phase included expert assessment of validity, clarity, and relevance using a modified Delphi method. Item Content Validity Index (I-CVI) and Scale CVI (S-CVI) were calculated. Pilot testing was conducted to assess test–retest reliability. Reliability was assessed using the Intraclass Correlation Coefficient (ICC) and Bland–Altman analyses. The study followed the principles of the Declaration of Helsinki, ensuring anonymity, informed consent, and confidentiality. Results: The questionnaire includes 37–50 items allocated in four sections. It demonstrated excellent content validity (CVI = 1.00) and good test–retest reliability (ICC = 0.86). Qualitative feedback indicated that the tool is user-friendly and comprehensive. Interestingly, participants expressed genuine concerns regarding the implementation of parental presence in neonatal resuscitation. Conclusions: The questionnaire development process led to a comprehensive tool, ready for large-scale testing in order to further establish its validity and internal consistency. Full article

Grapevine cultivars (Vitis vinifera L.) generally exhibit relatively high tolerance to drought stress. In contrast, the drought tolerance of other Vitis species and their hybrids used as rootstocks differs considerably. In order to attain a better understanding of the molecular basis of drought tolerance in grapevine, we conducted a comparative transcriptomic analysis of roots of drought-stressed Cabernet Sauvignon (CS, Vitis vinifera L.) and rootstock of Kober 5BB (V. berlandieri × V. riparia) using the Affymetrix Vitis Genome Array Version 2.0. We identified 1279 (745 upregulated and 534 downregulated) and 1925 (807 upregulated and 118 downregulated) differentially expressed genes in 5BB and CS. Numerous genes that are putatively involved in aquaporins, proline-rich protein, reactive oxygen species, osmoprotection, and lipid transfer were differentially expressed in response to drought stress in both genotypes. When gene ontology analyses were examined, it was observed that CS and 5BB genotypes were associated with the highest number of similar genes in both the molecular function (protein binding, catalytic activity, and DNA binding) and the biological process (metabolic process and translation) categories. The identification of different regulated genes between 5BB and CS roots is expected to help advance our understanding of molecular mechanisms operating during drought stress in grapevine roots. Full article

In the general linear Lie algebra of continuous linear transformations in n dimensions, we show that unequal Abelian scaling transformations on the components of a vector can stabilize the system information in the presence of Markov component transformations on the vector, which, alone, would lead to increasing entropy. The more interesting results follow from seeking Diophantine (integer) solutions, with the result that the system can be stabilized with constant information for each of a set of entropy rates ($k=\mathrm{1,2},3,\dots$ ). The first of these—the simplest—where $k=1$, results in the Fibonacci sequence, with information determined by the olden mean, and Fibonacci interpolating functions. Other interesting results include the fact that a new set of higher order generalized Fibonacci sequences, functions, golden means, and geometric patterns emerges for $k=2, 3, \dots$ Specifically, we define the $k$^th order golden mean as ${\Phi }_k=k/2+\sqrt{{(k/2)}^2+1}$ for $k =1, 2, 3, \dots .$. One can easily observe that one can form a right triangle with sides of 1 and $k/2$ and that this will give a hypotenuse of $\sqrt{{(k/2)}^2+1}$. Thus, the sum of the $k/2$ side plus the hypotenuse of these triangles so proportioned will give geometrically the exact value of the golden means for any value of k relative to the third side with a value of unity. The sequential powers of the matrix $(k^2+1,k,k,1)$ for any integer value of $k$ provide a generalized Fibonacci sequence. Also, using the general equation expressed as ${\Phi }_k={\displaystyle \frac{k}{2}}+\sqrt{{(k/2)}^2+1}$ for $k =\mathrm{1,2},3, \dots ,$ one can easily prove that ${\Phi }_k=k+1/{\Phi }_k$ which is a generalization of the familiar equation expressed as $\Phi =1+1/\Phi$. We suggest that one could look for these new ratios and patterns in nature, with the possibility that all of these systems are connected with the retention of information in the presence of increasing entropy. Thus, we show that two components of the general linear Lie algebra ($GL(n,\mathbb{R})$), acting simultaneously with certain parameters, can stabilize the information content of a vector over time. Full article

Inclusive education continues to face significant challenges nowadays due to a lack of resources, specialized support, and teacher training. In the context of primary education in Europe, families of students with functional diversity express their concern about the lack of adequate responses to their needs. However, there are merely a few studies that delve into the reality of inclusion from the family perspective. Therefore, this study aims to analyze the perceptions of families of students with functional diversity in Extremadura (Spain), regarding the quality of the educational response offered by schools. For this purpose, the study sample consisted of 70 family members of students with functional diversity in this region. For data collection and analysis, a semi-structured interview was used, applying thematic analysis and chi-square statistical tests in order to explore significant differences in the perceptions gathered. The interviews were transcribed and the answers gathered were categorized. The results show that almost half of the families consider the information received about the disability and the progress of their relatives to be insufficient. Likewise, there is a low level of satisfaction with the support and resources provided by both associations and the public administration. Consequently, the need to strengthen effective communication between schools and families is highlighted as a fundamental pillar to advance toward true educational inclusion. Full article

In this work, we present the procedure to obtain exact spherical shape functions for finite element modeling applications, without resorting to any kind of approximation, for generic prismatic spherical elements and for the case of spherical six-node tri-rectangular and eight-node quadrangular spherical prisms. The proposed spherical shape functions, given in explicit analytical form, are expressed in geographic coordinates, namely colatitude, longitude and distance from the center of the sphere. We demonstrate that our analytical shape functions satisfy all the properties required by this class of functions, deriving at the same time the analytical expression of the Jacobian, which allows us changes in coordinate systems. Within the perspective of volume integration on Earth, entering a variety of geophysical and geodetic problems, as for mass change contribution to gravity, we consider our analytical expression of the shape functions and Jacobian for the six-node tri-rectangular and eight-node quadrangular right spherical prisms as reference volumes to evaluate the volume of generic spherical triangular and quadrangular prisms over the sphere; volume integration is carried out via Gauss–Legendre quadrature points. We show that for spherical quadrangular prisms, the percentage volume difference between the exact and the numerically evaluated volumes is independent from both the geographical position and the depth and ranges from 10⁻³ to lower than 10⁻⁴ for angular dimensions ranging from 1° × 1° to 0.25° × 0.25°. A satisfactory accuracy is attained for eight Gauss–Legendre quadrature points. We also solve the Poisson equation and compare the numerical solution with the analytical solution, obtained in the case of steady-state heat conduction with internal heat production. We show that, even with a relatively coarse grid, our elements are capable of providing a satisfactory fit between numerical and analytical solutions, with a maximum difference in the order of 0.2% of the exact value. Full article

This research focuses on estimating the population median within a stratified random sampling framework by using robust statistical measures with transformation-based methodologies. An efficient estimator aims to minimize both the bias and the variance, thereby reducing the overall mean squared error (MSE, leading to more reliable outcomes. We introduce an improved class of proposed estimators that utilizes transformation techniques to effectively address data variability and enhance estimation accuracy. To evaluate their performance, we derive expressions for bias and mean square error (MSE) up to the first-order approximation for both existing and newly developed estimators, establishing theoretical conditions for their effectiveness. Additionally, the proposed estimators are compared with traditional methods using simulated populations generated from different probability distributions and actual datasets. The results indicate that the newly introduced estimators improve precision and efficiency in median estimation, yielding more reliable outcomes. When assessed against conventional estimators, the findings demonstrate that the new estimators outperform in terms of the percent relative efficiency criterion. Full article

This study estimates the population median through stratified random sampling, which enhances accuracy by ensuring the proper representation of key population groups. The proposed class of estimators based on transformations effectively handles data variability and enhances estimation efficiency. We examine bias and mean square error expressions up to the first-order approximation for both existing and newly introduced estimators, establishing theoretical conditions for their applicability. Moreover, to assess the effectiveness of the suggested estimators, five simulated datasets derived from distinct asymmetric distributions (gamma, log-normal, Cauchy, uniform, and exponential), along with actual datasets, are used for numerical analysis. These estimators are designed to significantly enhance the precision and effectiveness of median estimation, resulting in more reliable and consistent outcomes. Comparative analysis using percent relative efficiency (PRE) reveals that the proposed estimators perform better than conventional approaches. Full article