The egg-cowries comprise a family of specialised carnivorous caenogastropods (Ovulidae Fleming, 1828) that feed by browsing on octocorals, hexacorals and stylasterid hydrozoans. A recent phylogenetic study, employing a Sanger-based multilocus nucleotide dataset, revealed numerous instances of morphological-molecular incongruence and raised the need for a revision of the current classification. To test alternative hypotheses of ovulid classifications, we applied a phylogenomic approach relying on an Exon-capture methodology to 41 samples from 26 genera and 41 species, representative of the subfamily- and genus-level diversity. Tree reconstructions were performed using both Maximum Likelihood and Bayesian inference methods, resulting in a total of five well-supported subfamily-level clades. The genera Jenneria and Pseudocypraea formed a monophyletic clade, sister to Pedicularia, altogether here considered as forming the subfamily Pediculariinae. The monophyly of Ovulinae was upheld, incorporating Quasisimnia. Prionovolvinae as traditionally recognised proved to be a melting pot of diverse genera and species, including Ovula isibasii, challenging conventional morphology-based classifications. To further investigate morphological variation within Ovulidae, we conducted 2D geometric morphometric analyses to assess shape differences. Groups emerging from Principal Component Analysis (PCA) aligned with the traditional, morphology-based classification. The weak phylogenetic signal associated with the morphometric patterns suggested that phylogeny had only a marginal influence on the morphological evolution of this clade, in contrast to the much stronger role played by host adaptation. This phylogenetic reassessment based on robust genomic data, not only helped to refine our taxonomic framework but also underscores the power of molecular insights in investigating complex evolutionary relationships within families such as the Ovulidae. Furthermore, the morphometric multivariate analysis proved efficient in revealing patterns and addressing eco-evolutionary links.

Associations between plant-based dietary patterns and risks of cognitive impairment and dementia: A systematic review and dose-response meta-analysis.

Hierarchical maximum likelihood estimation for time-resolved NMR data.

Bidirectional causal relationships between epilepsy subtypes and psychiatric disorders: A two-sample mendelian randomization study.

This study aimed to evaluate the psychometric properties and acceptability of the Vancouver Index of Acculturation (VIA) in a sample of UK-based East-Asian adults. Although widely used in cross-cultural research, relatively few studies have assessed the factor structure, validity, and user acceptability of the VIA in non-North American samples. A total of 236 East-Asian participants (mean age = 26.8, 47.06% female) completed the 20-item VIA and demographic questions. Confirmatory factor analysis (CFA) was conducted using AMOS with maximum likelihood estimation and robust standard errors. Exploratory factor analysis (EFA) using principal axis factoring and varimax rotation was also performed. Internal consistency, convergent and discriminant validity, and acceptability were evaluated. CFA showed poor model fit for the original two-factor VIA structure: χ2(169) = 367.12, p < 0.001; CFI = 0.84; RMSEA = 0.089. The Mainstream factor showed weak and mostly nonsignificant loadings, while the Heritage factor demonstrated strong loadings. Internal consistency was high for Heritage (α = 0.91) and acceptable for Mainstream (α = 0.81). EFA supported a refined 17-item two-factor model, excluding three low-loading Mainstream items. Discriminant validity was supported, but convergent validity was only partially established. Acceptability data indicated that while most items were well received, several were perceived as culturally ambiguous. Findings support the VIA's bidimensional structure but suggest that cross-cultural adaptation may be needed to improve measurement accuracy in UK-based East Asian populations. The study highlights the importance of further validation in culturally diverse samples.

Maximum likelihood neural additive models

Fast and efficient implementation of the maximum likelihood estimation for the linear regression with Gaussian model uncertainty

A compartmental mathematical model was developed to examine the transmission dynamics of chikungunya, integrating media awareness and optimal control strategies. Both asymptomatic and symptomatic infectious categories, along with a media-induced awareness component, were incorporated to more precisely represent epidemiological dynamics. The model's positivity, boundedness, and stability characteristics were confirmed, and the basic reproduction number was calculated using the next-generation matrix method. Model calibration was conducted utilizing cumulative case data from India and high-burden states (Gujarat, Karnataka, and Maharashtra) through maximum likelihood estimation. Sensitivity analysis was performed, and transmission-related parameters, specifically the mosquito biting rate and infection probabilities were identified, as the most significant determinants of epidemic persistence. The system's threshold behavior was demonstrated through contour plots of [Formula: see text] with respect to different pairs of parameters and variations of parameters. A comprehensive control framework incorporating two time-dependent variables-minimization of human-mosquito interaction and augmentation of treatment-was formulated and examined utilizing Pontryagin's Maximum Principle. The optimal control result indicated that the simultaneous application of both controls was associated with the most significant decrease in symptomatic infections, while individual interventions also were found to provide quantifiable advantages. The findings emphasized the necessity of incorporating preventive measures, awareness enhancement, and improved treatment into region-specific chikungunya management strategies.

Effect of resin type, cleaning solution, and aging on the mechanical properties and reliability of additively manufactured occlusal devices.

Copulas, generalized estimating equations, and generalized linear mixed models promote the analysis of grouped data where non-normal responses are correlated. Unfortunately, parameter estimation remains challenging in these three frameworks. Based on prior work of Tonda, we derive a new class of probability density functions that allow explicit calculation of moments, marginal and conditional distributions, and the score and observed information needed in maximum likelihood estimation. We also illustrate how the new distribution flexibly models longitudinal data following a non-Gaussian distribution. Finally, we conduct a tri-variate genome-wide association analysis on dichotomized systolic and diastolic blood pressure and body mass index data from the UK-Biobank, showcasing the modeling potential and computational scalability of the new distributional family.

African freshwaters are inhabited by many endemic fishes. However, little is known about the associated myxozoan diversity. The present paper describes a new parasite species of Henneguya Thélohan, 1892 infecting Distichodus mossambicus Peters, 1852, an endemic freshwater fish species commonly found in the Congo Basin. Fish were collected from the Kadey River at Mindourou, a village in the East Region of Cameroon. To study the new Henneguya species, morphological analysis using light microscopy was combined with a phylogenetic analysis of small subunit ribosomal DNA (SSU rDNA) using maximum likelihood and Bayesian inference methods. White and elongated plasmodia were found in the gill lamellae. The myxospore body was 11.5 ± 0.2 (mean ± SD) (range: 10.4-12.7) µm long, 3.3 ± 0.1 (2.7-3.9) µm wide, and 2.3 ± 0.1 (1.9-2.9) µm thick. The caudal appendages were 22.1 ± 0.4 (20.1-25.9) µm long and the total length of the new species was 29.7 ± 0.3 (27.5-32.3) µm. The 2 pyriform polar capsules were of the same size, 3.7 ± 0.1 (3.2-4.2) µm long and 1.0 ± 0.03 (0.9-1.2) µm wide. Phylogeny of the SSU rDNA showed the new Henneguya species within a subclade composed exclusively of unidentified Myxobolidae infecting African Citharinoidei fish. Further work characterizing myxozoan species using both morphological, molecular, and phylogenetic data is required to better understand myxozoan diversity in Africa.

Comparative Effect of Two Enhanced Prenatal Care Models on Care Experiences: A Randomized Controlled Trial.

This paper presents a contactless method for the simultaneous monitoring of heart rate (HR) and respiratory rate (RR) using a Frequency Modulated Continuous Wave (FMCW) radar operating at 122.5GHz. To address the challenges posed by spectral overlap and interference between cardiac and respiratory components, we introduce a signal separation and estimation framework based on Maximum Likelihood Estimation (MLE) combined with an orthogonal projection technique. The approach models the thoracic displacement captured by the radar as the superposition of periodic sources and applies spectral projection to isolate the fundamental frequencies and their harmonics. Theoretical performance is assessed through the derivation of the Cramér-Rao Lower Bound (CRLB) and extensive Monte Carlo simulations under varying SNR and sample size conditions. Experimental validation was conducted on 23 healthy volunteers, each providing two 20second recordings, using a clinical-grade reference monitor. The method achieves high estimation accuracy, with a mean absolute error of 0.69bpm for HR and 0.33bpm for RR. The algorithm is capable of reconstructing the cardiac pulse waveform while preserving key morphological features such as the systolic peak and dicrotic notch. Furthermore, the use of the projection technique further enhanced estimation accuracy under nonphysiological conditions, including both elevated and reduced rates. These findings demonstrate the potential of the proposed method as a reliable tool for contactless monitoring of vital signs and support its future integration into biomedical applications.

This paper presents an approximate Maximum Likelihood (ML) estimation framework for estimating the damping factor in exponentially decaying complex sinusoidal signals. We derive a closed-form approximate ML estimator, explicitly noting its validity for small damping factors. Its efficiency is assessed through the derivation of the Cramer-Rao Lower Bound (CRLB), which serves as the theoretical benchmark for estimator performance. Analytical proof demonstrates that the proposed approximate ML estimator achieves the CRLB under small-damping conditions, confirming its statistical efficiency and optimality. The performance of the estimator is evaluated by analyzing its behavior with respect to critical system parameters such as signal-to-noise ratio (SNR), sample size, signal amplitude, and damping intensity. Our analysis reveals several fundamental relationships: estimation accuracy improves with increasing SNR and a larger sample size, confirming that the approximate ML estimator effectively utilizes additional information. Furthermore, the empirical variance of the approximate ML estimator converges to the CRLB, validating its efficiency. These findings yield practical guidelines for system designers. We establish that weakly damped signals can achieve satisfactory accuracy with moderate resources, whereas strongly damped scenarios necessitate substantially enhanced signal conditions. The proposed framework provides optimal estimation performance while also achieving significantly reduced computational complexity. This combination makes it particularly suitable for applications requiring rapid damping parameter extraction, such as structural health monitoring, radar systems, and vibration analysis.

An offshore oil spill near Karawang, West Java, in July 2019 caused a considerable impact on the Pulau Rambut Wildlife Sanctuary, a protected area known for its mangrove ecosystems, which provide crucial habitat for waterbirds in Jakarta Bay. The purpose of this study was to map and quantify land cover types on Rambut Island, as well as examine land cover changes three years after the spill, with a focus on mangrove dynamics. Land cover categorization was performed using the Maximum Likelihood (ML) method applied to remote sensing data from SPOT-6 and SPOT-7 satellite photos for 2019, 2020, and 2021. Ground truthing and drone imagery were used to validate categorization results, and accuracy was determined using the Kappa statistics. All classes had strong levels of agreement, with Kappa values of 85.66%, 81.40%, and 82% in 2019, 2020, and 2021, respectively. Four types of land cover were identified: mangroves, non-mangrove forests, water bodies, and open spaces. Rambut Island has an expected mangrove covering of 18.80 ha in 2019, which increased to 21.15 ha in 2020 before significantly declining to 18.84 ha in 2021. These findings are consistent with field data, in which 12 of 13 MHI (Mangrove Health Index) plots were classed as moderate. This data implies that the 2019 oil spill did not result in a significant or long-term loss in mangrove area on Rambut Island.Keywords: mangrove, maximum likelihood, oil spill, Rambut Island, SPOT-6/7

This paper introduces a four-parameter extended odd log-logistic-Lindley distribution from which moments, hazard, and quantile functions are then obtained. The statistical properties of this distribution show the high flexibility of the proposed distribution. The maximum likelihood and least-squares estimators of the extended odd log-logistic-Lindley parameters are studied. Moreover, a simulation study is carried out for evaluating the performance of the estimation methods, and the usefulness of the new distribution is illustrated using two real data sets. Finally, Bayesian analysis and efficiency of Gibbs sampling are provided on the basis of two real data sets.

BackgroundChronic subdural hematoma (cSDH) remains a prevalent neurosurgical condition in elderly patients, traditionally managed via surgical evacuation when symptomatic. Middle meningeal artery embolization (MMAE) has recently emerged as a minimally invasive alternative. However, the comparative efficacy and safety of standalone MMAE versus standalone surgical evacuation remain inadequately defined.MethodsA comprehensive search of PubMed, Scopus, Embase, and Web of Science, was performed on March 20, 2025. Studies comparing standalone MMAE and standalone surgical evacuation in patients with cSDH were included. The primary outcome was recurrence; secondary outcomes included complication and mortality rates. A random-effects pairwise meta-analysis model using restricted maximum likelihood (REML) was applied to account for between-study variability.ResultsTen studies encompassing 50,138 patients were included. Recurrence was significantly lower with MMAE (RR = 0.51, 95% CI: 0.33-0.80, p = .00), with no statistically detected heterogeneity (I2 = 0%), although clinical variability across studies cannot be excluded. Mortality (RR = 0.70, 95% CI: 0.44-1.12, p = .14) and complications (RR = 1.04, 95% CI: 0.67-1.64, p = .85) did not differ significantly between both groups. The GRADE assessment rated the certainty of evidence for recurrence as moderate, while the certainty for both mortality and complications were rated as very low, underscoring the need for further high-quality studies.ConclusionStandalone MMAE significantly reduces recurrence risk compared to surgical evacuation in cSDH patients, while showing no significant difference in mortality or complication rates. These findings highlight MMAE as a promising first-line treatment option, particularly for patients at high surgical risk. Prospective randomized trials are warranted to further validate these outcomes.

Organic falls play an important role in the evolutionary transition of chemosymbiotic mollusks from shallow to deep seas. Exploring their genetic characteristics is essential to elucidating adaptive mechanisms. Here, we report the first complete mitochondrial genome of Glabracollonia laevigata (Family Colloniidae), collected from sunken wood at 200 m depth in the East China Sea. The circular genome is 18,056 bp in length with an average sequencing depth of 6847×, and contains 13 protein-coding genes (PCGs), two rRNA genes, and 23 tRNA genes, including a duplicated trnY. The nucleotide composition is biased toward A + T (69.0%). Most PCGs use ATG as the start codon, except nad6 (GTG) and nad4L (ATA), and all terminate with TAA or TAG. Codon usage analysis revealed a preference for A and U at the third codon position. Phylogenetic analyses based on concatenated PCGs, using Bayesian inference and maximum likelihood approaches, strongly support a close relationship between Colloniidae and Phasianellidae, consistent with recent studies. These findings offer new insights into the phylogenetic placement of Colloniidae within Trochoidea, while contributing to a broader understanding of biodiversity and evolutionary adaptation in organic-fall ecosystems.

Financial time series forecasting poses significant challenges due to the diverse risk profiles and dynamic behaviors of assets such as the S&amp;amp;P 500, NASDAQ, and Bitcoin, especially across different market periods. This study introduces a novel framework, waveletstochastic-chaos informed machine learning, that integrates wavelet transforms, stochastic processes, and chaos theory to improve machine learning prediction accuracy over a decade (2015–2025). The analysis is divided into four distinct periods: All Time, PreCOVID, COVID, and Post-COVID. The aim is to capture the multi-scale patterns, volatility, and complexity inherent in financial data, which will be assessed across various market conditions. The framework outperforms the baseline maximum likelihood models in most scenarios, achieving significant root mean squared errors for the scaled price predictions of S&amp;amp;P 500 (e.g., from 0.0348 to 0.0122 in All Time), NASDAQ (e.g., from 0.0284 to 0.0180 in All Time) and Bitcoin (e.g., from 0.0838 to 0.0288 in All Time) based on 1000 experimental trials. It excels in volatile periods like COVID and for high-risk Bitcoin, though it slightly underperforms in the stable Post-COVID recovery for S&amp;amp;P 500. Wavelet features are found to be critical for accuracy. Additionally, stochastic and chaos-based elements enhance performance in volatile and complex contexts, respectively, as confirmed by ablation studies. This study provides empirical evidence of predictive utility for financial time-series forecasting in assets with different dynamics and market regimes. The results indicate that multi-scale, stochastic, and complexity-based feature representations can improve forecasting performance within the examined datasets, suggesting that the framework may apply to other non-stationary time-series settings, although such extensions remain for future investigation.

Hemorrhage remains the leading preventable cause of trauma-related death. The effectiveness of whole-blood vs component therapy remains uncertain, particularly given heterogeneous patient populations and resuscitation protocols. To determine whether whole-blood transfusion is associated with reduced mortality compared with component therapy in adult trauma patients, with prespecified analysis by civilian vs military settings. In this updated systematic review and meta-analysis, MEDLINE, Embase, Cochrane Central Register of Controlled Trials, Web of Science, and CINAHL were searched from January 1, 2006, through June 30, 2025. Two reviewers independently screened 6888 records and extracted data. Randomized clinical trials and observational studies comparing whole-blood vs component therapy in adults (aged ≥16 years) with traumatic hemorrhage were included. The Risk of Bias in Nonrandomized Studies of Interventions (ROBINS-I) tool was used to assess the risk of bias in observational studies, while the Cochrane Risk of Bias 2 (RoB 2) tool was applied for randomized clinical trials. Random-effects meta-analysis used restricted maximum likelihood with Hartung-Knapp adjustment. Forty studies (2 randomized clinical trials, 38 cohort studies; n = 49 776) were included. Whole-blood transfusion, compared with component therapy, was associated with reduced 24-hour mortality (odds ratio [OR], 0.76; 95% CI, 0.60-0.95; τ2 = 0.27; I2 = 87%; 95% prediction interval [PI], 0.30-1.89). In civilians (24 studies; n = 39 028), mortality reduction was significant (OR, 0.73; 95% CI, 0.57-0.93; τ2 = 0.27; I2 = 89%; 95% PI, 0.28-1.91), corresponding to an absolute risk reduction of 4.6 percentage points (95% CI, 1.4-8.6 percentage points) based on median control mortality of 20% (range, 15%-25%). No benefit was observed in military settings (5 studies; n = 2171; OR, 0.99; 95% CI, 0.58-1.70). Civilians also showed reduced 30-day mortality (OR, 0.76; 95% CI, 0.60-0.98) and transfusion requirements (mean difference, -2.66 units; 95% CI, -3.96 to -1.35 units). In this updated systematic review and meta-analysis, whole-blood transfusion was associated with reduced mortality in civilian but not military adult trauma patients, although the wide 95% PIs suggest substantial heterogeneity, indicating that benefits may vary considerably across settings. These findings support selective whole-blood transfusion protocol implementation in civilian centers while highlighting the need for refined patient selection criteria.