Search Results (3,953)

Modeling over-dispersed count data is a common challenge in applied statistics, especially in engineering applications where repeated events, system faults, and clustered observations often produce variability beyond that allowed by the classical Poisson model. In this paper, we introduce and study the Poisson–QGamma distribution, a new compound discrete model obtained by mixing the Poisson distribution with the QGamma distribution. The proposed distribution is analytically tractable and flexible enough to capture over-dispersion, skewness, and excess kurtosis, which are frequently observed in real count data. Several statistical properties of the distribution are derived, including the probability mass function, cumulative distribution function, survival and hazard rate functions, moments, dispersion index, skewness, kurtosis, entropy, and generating functions. Parameter estimation is considered using maximum likelihood, method of moments, least squares, and weighted least squares methods. The finite-sample behavior of these estimators is examined through Monte Carlo simulation. A regression model based on the Poisson–QGamma distribution is also developed for count responses with covariates. The proposed model is compared with classical and competing count models using simulation and real-data applications. Three engineering-related datasets, involving power grid failure counts, environmental sensor event counts, and packet loss counts in communication networks, are analyzed to illustrate the practical value of the model. The results show that the Poisson–QGamma model provides a better fit than several standard alternatives, including the Poisson, negative binomial, Poisson–Lindley, generalized Poisson, and COM–Poisson models, particularly in the presence of over-dispersion and heavy-tailed behavior. Overall, the proposed distribution offers a parsimonious and effective tool for modeling over-dispersed count data, while also contributing to the broader class of compound discrete distributions. Full article

In both experimental and theoretical analyses of data, we often look to select a set of simple components that can be combined to create an appropriate model for the data. A convenient way to do this is to use quantile functions that can be added or transformed to obtain new distributions. In this work, we connect quantile statistics and mean absolute deviations (MADs) by deriving a general class of MAD-based shape metrics expressed as integrals of the quantile function, with a direct geometric interpretation. Our approach is applicable to distributions with finite mean that include many of the commonly used distributions, including those without a variance, such as the Pareto. When simple midpoint quadrature is used, the proposed metrics recover widely used quantile-shape metrics, including the interquartile range, Galton skewness, and Moore’s octile kurtosis as special cases. We further propose a C-Trapezoid quadrature approximation that combines cubic polynomial endpoint extrapolation with trapezoidal integration, achieving approximation errors that are significantly lower than those of the midpoint approximation for many common distributions. The proposed approximation provides simple-to-compute formulas for shape analysis and yields closed-form, non-iterative parameter-estimation formulas. These formulas are easy to compute and interpret, and they are applicable to a wide class of distributions, including those without an explicit cumulative distribution function or some with heavy tails. Unlike maximum likelihood estimation, the proposed method is more robust and has simple geometric interpretation. We illustrate the methodology with two detailed case studies. The proposed approach gives a simple way to quickly assess distributional shape without any specialized tools. Full article

Index-modulated orthogonal frequency division multiplexing (OFDM-IM) has been recognized as a promising multicarrier transmission scheme due to its flexibility and favorable bit error rate (BER) performance. However, for future wireless communication systems requiring high reliability, high spectral efficiency, and low complexity, existing OFDM-IM schemes still face challenges in simultaneously improving spectral efficiency, maintaining diversity gain, and controlling detection complexity at the receiver. To address these issues, this paper proposes a joint-mode and repeated-index modulation-based coordinate interleaved OFDM scheme (MRIM-CI-OFDM). Building upon the shared subcarrier activation pattern (SAP) and coordinate interleaving structure, the proposed scheme introduces cross-cluster mode-pair indexing, enabling information bits to be jointly carried by the SAP domain, mode domain, and constellation symbol domain. This design enhances spectral efficiency while preserving the diversity advantages of coordinate interleaving. Furthermore, a rotated multi-mode constellation construction method based on inter-constellation minimum product distance is developed to improve mode separability. By exploiting the equivalent real-valued orthogonal structure introduced by coordinate interleaving, low-complexity maximum likelihood (ML) and three-stage Max-Log detectors are constructed. Simulation results demonstrate that the proposed low-complexity detectors achieve near-ML detection performance. Additionally, at a spectral efficiency of 1.25 bps/Hz, MRIM-CI-OFDM achieves approximately 3 dB SNR gain over the coordinate-interleaved/repeated-index benchmarks and more than 5 dB gain over conventional OFDM-IM. Full article

In modern reliability engineering, modeling bounded lifetime data under realistic experimental conditions is still challenging, especially when censoring schemes and unit removals are random. This study proposes a new and unified reliability framework by combining the flexible powering new power (PNP) distribution with a grouping-based progressive first-failure mechanism using a beta-binomial random design. The proposed approach explicitly accounts for the randomness in group removals, providing a more realistic description of practical life-testing experiments. Classical estimation is carried out using maximum likelihood methods with the Newton-Raphson algorithm, along with confidence intervals constructed under both standard and log-transformed parameterizations. To increase flexibility in inference, a Bayesian approach is developed based on a joint gamma and shifted log-normal prior, which respects parameter constraints and incorporates prior uncertainty. Since the posterior distributions cannot be obtained in closed form, a Metropolis-Hastings Markov chain Monte Carlo algorithm is used to generate reliable posterior estimates and credible intervals. Additionally, beyond sensitivity analysis, multiple prior robustness diagnostics are incorporated to ensure reliable hyperparameter calibration and to safeguard against prior misspecification. The performance of the proposed estimators is carefully examined through extensive Monte Carlo simulations under different censoring schemes and parameter settings. The simulation results indicate that the proposed Bayesian procedures often provide more stable estimation and shorter interval estimates with competitive coverage probabilities compared with the corresponding classical methods, particularly under moderate-to-heavy censoring settings. To demonstrate its practical usefulness, the proposed model is applied to two real datasets on tensile strength of carbon and polyester fibers, where it provides a good fit and useful insights into material reliability and failure behavior. In the same applications, the practical relevance and superior performance of the proposed distribution are demonstrated, where it outperforms existing bounded versions of several well-known models, including the gamma, Weibull, and Birnbaum-Saunders distributions. Overall, this work contributes to reliability analysis by offering a flexible and computationally efficient framework that accounts for both random censoring and complex lifetime patterns, with potential applications in engineering, materials science, and applied reliability studies. Full article

This paper introduces the Touchard process, a flexible two-parameter stochastic framework for modeling count data that depart from the classical Poisson assumptions. In contrast to standard Poisson processes, the proposed model allows for both nonstationary and dependent increments, enabling the representation of overdispersion, underdispersion, and temporal dependence within a unified structure. The main contribution lies in extending weighted Poisson models to a stochastic-process setting through recursively defined transition probabilities associated with Touchard marginal distributions. We derive key theoretical properties, including admissibility conditions and a recursive formulation for the transition probabilities, and propose an efficient simulation algorithm. Maximum likelihood estimation is developed for parameter inference, and a likelihood ratio framework is used for model comparison. An empirical application to motor vehicle crash data illustrates the ability of the model to capture dynamic patterns that are not adequately described by classical Poisson-based approaches. Full article

In this paper, we introduce a new extension of the Topp–Leone-G family, called the generalized Marshall–Olkin Topp–Leone-G (GMOTL-G) family of distributions. The proposed family is obtained by combining the generalized Marshall–Olkin and Topp–Leone-G generators, leading to a more flexible class of models for lifetime data. We study several of its mathematical and statistical properties and focus in particular on the generalized Marshall–Olkin Topp–Leone exponential (GMOTL-E) distribution as an important special case. For this model, we derive and discuss a number of useful characteristics, including the moment generating function, moments, order statistics, residual and reversed residual life functions, mean deviations, asymptotic behavior, and stochastic ordering. We also develop maximum likelihood estimation for the model parameters under both complete and right-censored samples. In addition, we construct a goodness-of-fit test for the proposed model under independent right censoring using a chi-square type approach. The performance of the estimation and testing procedures is investigated through simulation, and the results show good behavior of the estimators and satisfactory agreement between empirical and theoretical significance levels. Finally, two real data applications, one with complete data and one with right-censored data, are presented to illustrate the flexibility and practical usefulness of the proposed model. These results show that the new family provides an effective tool for modeling lifetime data and for assessing model adequacy in the presence of right censoring. Full article

In this paper, a distributed quasi-generalized Reed–Solomon (Q-GRS)-coded cooperative split labeling diversity (DQ-GRSCC-SLD) scheme is proposed to support reliable cooperative transmission of small-volume information in typical scenarios such as device-to-device (D2D) communication, vehicular ad hoc networks (VANETs) and wireless sensor networks. The system employs distinct labeling mappers at the source and the relay, enabling single-antenna transmission while constructing equivalently a dual-antenna labeling diversity model at the destination, which enhances interference resistance and reduces transmission costs. In addition, an ingenious design is proposed to ensure that the destination obtains the joint Q-GRS code. To optimize the weight distribution of the joint code, a traversal search (TS) algorithm is developed. Furthermore, a low-complexity joint decoding algorithm for Q-GRS codes, namely bracketing decoding, is presented by leveraging the efficient decoding algorithm of generalized Reed–Solomon (GRS) codes. Compared to the conventional maximum likelihood (ML) decoding, its complexity has been reduced from comparing $q^k$ codewords to evaluating q or $q+1$ promising codewords. A theoretical performance analysis of the DQ-GRSCC-SLD scheme is provided. Simulation results reveal that the proposed DQ-GRSCC-SLD scheme demonstrates its superior performance under practical scenarios. Full article

Background and Aims: Type 2 diabetes mellitus is a recognized risk factor for hepatocellular carcinoma (HCC), particularly in the setting of metabolic dysfunction-associated steatotic liver disease (MASLD), chronic viral hepatitis, advanced fibrosis, and cirrhosis. Beyond hyperglycemia and insulin resistance, diabetic hepatocarcinogenesis is shaped by metabolic inflammation, lipotoxicity, oxidative stress, fibrogenic remodeling, and the cirrhosis-dysplasia-HCC continuum. Sodium-glucose cotransporter-2 inhibitors (SGLT2i) may influence several hepatometabolic pathways, but the epidemiologic evidence linking SGLT2i use to HCC risk remains heterogeneous. Methods: We conducted a systematic review and meta-analysis of observational studies evaluating SGLT2i exposure and incident HCC in adults with type 2 diabetes. PubMed, Embase, and the Cochrane Library were searched up to 15 March 2026. Adjusted time-to-event estimates were pooled using a restricted maximum likelihood (REML) random-effects model. The certainty of evidence was assessed using the GRADE framework and judged to be very low. Results: Six observational studies including 526,446 participants were included. SGLT2i exposure was associated with a lower observed risk of incident HCC (pooled HR 0.59, 95% CI 0.45–0.77), but between-study heterogeneity was substantial (I² = 75.2%, τ² = 0.074). The association remained directionally similar after exclusion of Huynh et al. (HR 0.61, 95% CI 0.45–0.81) and in a DPP-4 inhibitor-restricted active-comparator analysis (HR 0.60, 95% CI 0.39–0.92). However, the 95% prediction interval crossed the null (0.25–1.37), indicating that future comparable studies may plausibly show no protective association. Conclusions: SGLT2i exposure was associated with a lower observed risk of incident HCC across available observational studies. However, the certainty of evidence was judged to be very low, and substantial heterogeneity, comparator variation, mixed time-to-event estimands, residual confounding, and a prediction interval crossing the null preclude causal interpretation. These findings should be considered hypothesis-generating rather than practice-changing evidence and support further hepatology-oriented validation. Full article

This study evaluates the wind energy potential of Polokwane, South Africa, using statistical distribution models to estimate wind power density (WPD) and assess turbine performance under low-wind inland conditions. Hourly wind speed and direction data (2015–2024) measured at a 10 m height above ground level (AGL) were analysed to characterise wind behaviour and assess energy availability. Four probability distributions, namely generalised logistic (GLD), generalised extreme value (GEVD), Gumbel (GD), and Weibull (WD), were fitted using the maximum likelihood (ML) method. Model performance was evaluated using Kolmogorov–Smirnov (KS), Anderson–Darling (AD), and Chi-square $\left({\chi }^2\right)$ tests, while wind power density accuracy was assessed using wind power density error (WPDE). The results showed that Polokwane is characterised by low wind speeds, with an overall mean wind speed of 2.72 m/s at 10 m AGL, reaching a low of 3.88 m/s at a hub height of 125 m. The GEVD model produced the most accurate wind power density estimate of 32.37 W/m², classifying the site within the poor wind resource category. Wind direction analysis revealed a dominant northeast sector with seasonal shifts toward the south. Wind turbine performance analysis showed improved energy generation at higher hub heights, with the Gamesa G136-4.5 MW turbine identified as the most suitable option for the site, achieving the highest net annual energy production (AEP) of 10.82 GWh/yr and the highest net capacity factor (CF) of 27.44%. These results indicate that the Polokwane site is suitable for low-to-moderate wind energy applications and small-scale distributed wind generation rather than large-scale commercial wind farm development. Full article

Online reviews are increasingly pivotal in consumer decision-making, with platforms employing mechanisms such as badges to denote reviewer credibility. Although prior research has examined the influence of expert reviewers, it has typically treated badge holders as a homogeneous group, overlooking how variation in tenure within expert tiers shapes the way readers process review content. This article examines how Yelp Elite badge tenure, operationalized as Red (1–4 years), Gold (5–9 years), and Black (10+ years) tiers and treated as a proxy for accumulated platform-recognized expertise, moderates the effects of peripheral cues (Extremity, Length) and central cues (Readability, Subjectivity, and Plutchik’s eight emotions) on perceived helpfulness within an Elaboration Likelihood Model (ELM) framework. The analysis draws on the full population of 324,426 restaurant reviews authored by Yelp Elite badge holders between 2019 and 2021, using a pooled count-model specification with badge tier as a categorical moderator. The primary specification is estimated using Poisson quasi-maximum likelihood with HC1-robust standard errors, and full negative binomial estimation is reported as a robustness check. Wald tests indicate that badge tenure significantly moderates eight of twelve cue–helpfulness relationships (${\chi }^2\left(24\right)=4938$, $p<0.001$). The effect of readability is monotonically positive and increases sharply with tenure, while the effect of joy varies across tenure groups. These findings suggest that reviewer expertise signals are not monolithic, refining theoretical insights on how tenure-based credibility cues moderate cue processing and offering practical implications for review platform management. The findings also indicate that platforms applying uniform ranking or surfacing rules across all Elite reviewers risk misallocating visibility, and that tenure-conditional weighting of textual cues warrants consideration. Full article

Allium kazim-kosei sp. nov. (Amaryllidaceae, sect. Codonoprasum) is described as a new species from Central Anatolia, Türkiye. The new species is morphologically similar to A. pseudoflavum but differs in several diagnostic characters, including bulb structure, scape height, leaf morphology, spathe venation, inflorescence and pedicel dimensions, tepal shape, presence of interstaminal teeth, capsule shape, and seed size. SEM observations reveal distinct micromorphological differences in seed testa ornamentation and pollen exine structure between the two species. Molecular phylogenetic analyses based on nuclear ITS and chloroplast trnL intron sequences support the recognition of A. kazim-kosei as a distinct species. The Kimura 2-parameter (K2P) genetic distance between A. kazim-kosei and A. pseudoflavum (8.54% for ITS) is considerably higher than typical interspecific divergences within sect. Codonoprasum. In the Maximum Likelihood phylogenetic tree, the two species form well-separated sister branches with high bootstrap support. The species is known only from gypseous soils around Kavuncu village (Eskişehir province, Türkiye), with an estimated Area of Occupancy (AOO) of 8 km² and Extent of Occurrence (EOO) of 45 km². Based on IUCN criteria, A. kazim-kosei is assessed as Endangered (EN) [B1ab(iii) + B2ab(iii)]. This discovery increases the total number of Allium species in Türkiye to 239 and the number of sect. Codonoprasum taxa to 74. The molecular results are fully congruent with the macro- and micromorphological characters, providing robust multi-evidence support for the recognition of the new species. Full article

Introduction: Effective perioperative management in cesarean section remains essential to optimize maternal outcomes. Melatonin (M) has been proposed as a potential adjunct due to its analgesic, anxiolytic, and antiemetic properties; however, evidence from randomized controlled trials (RCTs) remains inconsistent. This meta-analysis aimed to evaluate the efficacy and safety of preoperative melatonin compared with placebo in women undergoing cesarean section. Methods: A systematic search was conducted in PubMed, Scopus, and Cochrane from inception to 15 March 2026 for studies evaluating pregnant women undergoing elective cesarean section receiving preoperative melatonin versus placebo (P) (PROSPERO “CRD420261355468”). Heterogeneity was assessed using the I² statistic and Cochrane Q test. Risk ratios (RRs) and standardized mean differences (SMDs) were computed using a restricted maximum-likelihood estimator random-effects method. Trial Sequential Analysis (TSA) was performed to assess the robustness and sufficiency of the evidence. Results: Seven RCTs were included with 552 patients (melatonin: 278; placebo: 274). Preoperative melatonin significantly reduced opioid consumption in the overall pooled analysis (RR 0.31, 95% CI 0.12 to 0.80; p = 0.030; I² = 50%), and TSA supported the robustness of this opioid-sparing finding under the selected assumptions. Postoperative pain scores were also significantly lower in the melatonin group (SMD −2.10, 95% CI −2.43 to −1.78; p < 0.01; I² = 22%). The incidence of postoperative nausea showed a trend toward reduction in the conventional meta-analysis (RR 0.49, 95% CI 0.23–1.04; p = 0.057; I² = 34%); although TSA suggested a possible benefit, this finding should be considered exploratory. No significant difference was observed in intraoperative blood loss (SMD −0.33, 95% CI −1.53 to 0.88; p = 0.60; I² = 94%). Conclusions: Preoperative melatonin may be a promising adjunct in cesarean section, particularly for reducing postoperative pain and overall opioid consumption. TSA findings support the opioid-sparing result under selected assumptions, while the possible effect on postoperative nausea remains exploratory. Further high-quality trials are warranted before routine clinical implementation can be recommended. Full article

Opuntia miquihuanensis (Cactaceae: Opuntioideae), a new species endemic to the locality Peña-Aserradero, part of the Sierra Madre Oriental, Tamaulipas, Mexico, is formally described and illustrated. Phylogenetic analyses used maximum parsimony, maximum likelihood and Bayesian inference, based on sequences of trnL-trnF, psbJ-petA, matK, ycf1, ppc and ITS. The micromorphology of spines, epidermis, stoma, and pollen was characterized with scanning electron microscopy. Opuntia miquihuanensis is recovered as a supported species within Opuntia s.str. Full article

Angola is one of the countries with the highest HIV-1 genetic diversity, yet the implications of this diversity for antiretroviral therapy remain insufficiently characterised. Following the introduction of dolutegravir (DTG) in Angola in 2021, evaluating transmitted drug resistance prior to its widespread implementation is essential to inform treatment strategies and establish a baseline for future surveillance. In this study, 243 blood samples were collected from treatment-naïve people living with HIV attending the General Hospital of Benguela, Angola. The integrase coding region of proviral DNA was amplified and sequenced using the Sanger method. Phylogenetic relationships were inferred using a maximum likelihood approach, recombinant forms were characterised by bootscanning analysis, and resistance-associated mutations to integrase strand transfer inhibitors were identified using Stanford HIVdb, ANRS-MIE, and IAS-USA algorithms. A total of 92 integrase sequences were successfully obtained, revealing 16 distinct genetic forms, with unique recombinant forms accounting for 50.0%, followed by subtype C (10.9%) and sub-subtype F1 (8.7%). Five accessory mutations (L74I, L74M, Q95K, T97A, and E157Q) and one major mutation (E92G) were detected, corresponding to an overall prevalence of 28.8% (23/80). These findings highlight the extensive HIV-1 genetic complexity in Angola and support the continued use of DTG-based regimens, while underscoring the importance of sustained surveillance of integrase inhibitor resistance. Full article

The Neoproterozoic Wadi Mahasin metavolcanics (WMVs) in the Central Eastern Desert, Egypt, were remapped using Landsat-8 and Sentinel-2 imagery and verified by field observations, and their petrogenesis was evaluated using petrography, whole-rock geochemistry, and Pb isotopes. The image processing techniques of decorrelation stretch (DS), band ratios (BR), principal component analysis (PCA), and Minimum Noise Fraction (MNF) were applied to three remotely sensed datasets from Landsat-8, Sentinel-2B, and Planet to produce an updated geologic map of the study area. Moreover, two robust supervised classification techniques, maximum likelihood (MLC) and the support vector machine (SVM), enhanced geological contacts, structural elements, and produced classified images by 95.68% and 96%, respectively. The WMV suite comprises metadacite and metarhyolite with SiO₂ contents of 61.8–66.5 and 77.8–79.8 wt.%, respectively, and belongs to a subalkaline calc–alkaline series with a transitional medium- to high-K character at the felsic end. Primitive mantle-normalized patterns show enrichment in LILEs (Rb, U, K, and Pb) and depletion in Nb, Ta, Ti, and P, consistent with subduction-related felsic magmatism. Chondrite-normalized REE patterns are characterized by enriched LREEs, flat to weakly fractionated HREEs ((Gd/Yb)_N ≈ 1.5), and negative Eu anomalies (Eu/Eu* = 0.30–0.81). The flat HREE segment suggests melting of a garnet-free source, most plausibly a plagioclase–amphibole-bearing crustal assemblage. Eu/Eu* correlates positively with Sr for the suite as a whole, indicating plagioclase control during differentiation. Metarhyolite samples form a tightly clustered evolved group, whereas metadacites show broader scatter that mainly reflects differentiation. Pb isotopes and crust-like trace-element ratios (high Y/Nb, low Ce/Pb, and low Nb/U) indicate strong crustal involvement. Although assimilation–fractional crystallization from a mantle-derived parent magma cannot be excluded completely, the available isotopic data do not define a simple mantle-to-crust differentiation trend, and the uniformly evolved major- and trace-element signatures favor direct partial melting of felsic continental crust, followed by limited fractional crystallization. The WMV suite is, therefore, interpreted as a mature continental-arc felsic assemblage within the Arabian–Nubian Shield. Full article