Search Results (1,065)

Generally, following an omnibus (overall equality) test, multiple pairwise comparison (MPC) tests are typically conducted as the second step in a sequential testing procedure to identify which specific pairs (e.g., proportions) exhibit significant differences. In this manuscript, we develop maximum likelihood estimation (MLE) methods to construct three different types of confidence intervals (CIs) for multiple pairwise differences in proportions, specifically in contexts where both types of misclassifications (i.e., over-reporting and under-reporting) exist in multiple-sample binomial data. Our closed-form algorithm is straightforward to implement. Consequently, when dealing with multiple sample proportions, we can readily apply MPC adjustment procedures—such as Bonferroni, Šidák, and Dunn—to address the issue of multiplicity. This manuscript advances the existing literature by extending from scenarios with only one type of misclassification to those involving both. Furthermore, we demonstrate our methods using a real-world data example. Full article

Background/Objectives: Large-language modules facilitate accessing health information instantaneously. However, they do not provide the same level of accuracy or detail. In pediatric orthopedics, where parents have urgent concerns regarding knee deformities (bowlegs and knock knees), the accuracy and dependability of these chatbots can affect parent decisions to seek treatment. The goal of this study was to analyze how AI chatbots addressed parental concerns regarding pediatric knee deformities. Methods: A set of twenty standardized questions, consisting of ten questions each on bowlegs and knock knees, were designed through literature reviews and through analysis of parental discussion forums and expert consultations. Each of the three chatbots (ChatGPT, Gemini, and Copilot) was asked the same set of questions. Five pediatric orthopedic surgeons were then asked to rate each response for accuracy, clarity, and comprehensiveness, along with the degree of misleading information provided, on a scale of 1–5. The reliability among raters was calculated using intraclass correlation coefficients (ICCs), while differences among the chatbots were assessed using a Kruskal–Wallis test with post hoc pairwise comparisons. Results: All three chatbots displayed a moderate-to-good score for inter-rater reliability. ChatGPT and Gemini’s scores were higher for accuracy and comprehensiveness than Copilot’s (p < 0.05). However, no notable differences were found in clarity or in the likelihood of giving incorrect answers. Overall, more detailed and precise responses were given by ChatGPT and Gemini, while, with regard to clarity, Copilot performed comparably but was less thorough. Conclusions: There were notable discrepancies in performance across the AI chatbots in providing pediatric orthopedic information, which demonstrates indications of evolving potential. In comparison to Copilot, ChatGPT and Gemini were relatively more accurate and comprehensive. These results highlight the persistent requirement for real-time supervision and stringent validation when employing chatbots in the context of pediatric healthcare. Full article

The construction industry plays a key role in economic development but continues to face challenges in promoting employee well-being, particularly mental health and social sustainability. While existing decision-making tools emphasize environmental and economic factors, the social dimension remains largely overlooked, creating a significant gap in both research and practice. To address this, the study develops a decision support tool (DST) to help construction organizations prioritize strategic investments that enhance employee social sustainability. The tool is based on a hybrid multi-criteria decision-making framework, combining the Analytical Hierarchy Process (AHP) with Fuzzy MOORA to integrate both quantitative and qualitative assessments. A literature review, along with findings from a previous empirical study, identified 27 validated criteria, grouped into seven core sustainability alternatives. Additionally, five decision criteria (cost, risk, compatibility, return on investment, and difficulty) were refined through expert interviews. The DST was implemented as a modular Excel-based tool allowing users to input data, conduct pairwise comparisons, evaluate alternatives using linguistic scales, and generate a final ranking through defuzzification. A case study in a private construction company showed Training and Development and Work Environment as top priorities. An online expert focus group confirmed the DST’s clarity, usability, and strategic relevance. By addressing the often-neglected social pillar of sustainability, this tool offers a practical and transparent framework to support decision-making, ultimately enhancing employee well-being and organizational performance in the construction sector. Full article

Objective: This paper aimed to assess the effectiveness of the Rapid Maxillary Expander (RME) II System, compared to the Sander bite-jumping appliance (SBJ) and an untreated control group, in the treatment of Class II skeletal malocclusion in children. Methods: Thirty Class II patients treated with the RME II System (Group R) were compared to 30 patients treated with the SBJ (Group S) and 30 untreated Class II children (Group C). Cephalograms were analysed at the beginning of the study (T0) and at the end of the treatment (T1). Eight cephalometric parameters were evaluated: the divergence angle (SN-MP), ANB, lower face height (LFH), CO-GN, 1 + SN, IMPA, overjet, and overbite. The Shapiro–Wilk normality test was conducted to assess the distribution of the data. A t-test was then used for pairwise comparisons of the cephalometric measurements between T0 and T1. Differences among the groups were analysed using one-way ANOVA with Tukey’s post hoc correction. Results: ANOVA revealed a statistically significant difference for all analysed variables except 1 + SN. The post hoc Tukey’s test identified the following differences: SN-MP was 2.51° greater in Group S than in Group R, LFH was 5.46 mm greater in Group C than in Group R and 3.11 mm greater in Group S than in Group R, IMPA was 4.01° greater in Group S than in Group R, and overbite was 1.96 mm lower in Group S than in Group R. Conclusions: The RME II System provides better control of mandibular plane inclination and lower incisor proclination during the correction of Class II skeletal malocclusion. Both devices are effective in correcting Class II skeletal malocclusion. Full article

Manufacturing organisations face increasing pressure to assess and report their sustainability performance, particularly with the introduction of the European Sustainability Reporting Standards (ESRS). This paper presents a novel sustainability assessment framework that integrates ESRS guidelines with the Analytic Hierarchy Process (AHP) to provide a comprehensive evaluation methodology for manufacturing organisations. The framework addresses the limitations of existing approaches by systematically incorporating standardised sustainability indicators while enabling precise weighting of their relative importance. Through a structured approach, the framework evaluates environmental, social, and governance dimensions using both measurable and non-measurable indicators derived from ESRS guidelines. The methodology includes automated pairwise comparisons and weight calculations, significantly reducing the complexity traditionally associated with multi-criteria decision-making methods. The framework’s effectiveness is demonstrated through its implementation in a manufacturing organisation, where it successfully evaluated 38 sustainability indicators across 10 ESRS-defined subtopics. The case study highlighted areas requiring immediate attention, particularly in water and marine resources management, where performance fell below the established benchmark. This research contributes to both theory and practice by offering manufacturing organisations a structured approach to sustainability assessment that combines regulatory compliance with effective performance evaluation. The framework’s automated nature and integration of standardised reporting requirements make it particularly valuable for organisations transitioning to mandatory sustainability reporting under ESRS guidelines. Full article

Objectives: To examine the effects of surface treatments on the color stability, surface roughness, surface gloss, and wettability of monolithic polychromatic material jetting (MJT) 3D-printed denture material. Material and Methods: Twenty-one color variants of the same denture material (TrueDent; Stratasys, Eden, MN, USA) underwent two surface treatments (polishing only or polishing and glazing), creating 42 study groups with a total of 420 samples (n = 10 per group). The samples were manufactured using a PolyJet 3D printer (J5 DentaJet; Stratasys, Eden, MN, USA), a type of MJT 3D printer. Color measurements were taken with a digital spectrophotometer before and after the surface treatments, and quantitative color differences (ΔE₀₀ and ΔC*) were calculated using the CIE2000 system. Comparisons of ΔE₀₀ were made against the 50%:50% acceptability threshold (AT) of 1.8 and the 50%:50% perceptibility threshold (PT) of 0.8 for tooth shade, as well as the 50%:50% PT of 1.72 and the 50%:50% AT of 4.08 for gingival (pink) shade. After surface treatment, the gloss was measured using a glossmeter, surface roughness was measured with optical profilometry, and wettability was measured by contact angle measurements using an optical tensiometer. The significance of surface treatment on color changes for each color variant was evaluated using one-sided, one-sample t-tests against the AT and PT. The effects of surface treatment on surface gloss, surface roughness, contact angle, and ΔC* were analyzed using t-tests for each color variant. Pairwise comparisons between groups were made using Fisher’s Protected Least Significant Differences (α = 0.05). Results: In most cases, glazing caused the color change (ΔE₀₀) to exceed the AT and PT, with a few exceptions. Most materials exhibited a more vibrant (more saturated) appearance and statistically higher chroma, with glazed surface treatments compared to polished ones, though there were some exceptions. For all materials, the glazed samples had significantly higher gloss units than the polished ones (p < 0.0001). Additionally, all materials showed significantly higher surface roughness in glazed samples compared to polished ones (p < 0.0001 for most). The polished samples had significantly higher contact angles (p < 0.0001 for most). Conclusions: Surface treatments significantly influenced the color, surface gloss, surface roughness, and wettability of MJT 3D-printed denture materials. Glazing led to increased chroma and gloss and produced more hydrophilic surfaces, although it also increased surface roughness. These results highlight the importance of surface treatment selection in optimizing the clinical performance of MJT-fabricated dentures. Full article

Objectives: Transcranial alternating current stimulation (tACS) can enhance primary motor cortex (M1) excitability and improve motor skill when delivered unilaterally to the dominant hemisphere. However, the impact of tACS on contralateral M1 excitability both during and after application has not been studied. The purpose of this study was to examine the effects of tACS delivered to the dominant left M1 on the excitability of the unstimulated contralateral non-dominant right M1. Methods: This study implemented a double-blind, randomized, SHAM-controlled, within-subjects, crossover experimental design. Eighteen young adults completed a tACS condition and a SHAM condition on two different days in counterbalanced order with a week washout period between days. Transcranial magnetic stimulation (TMS) was utilized to assess excitability of the contralateral right M1 while tACS was delivered to the left M1. TMS was administered in five test blocks (termed Pre, D5, D10, D15, and Post) relative to a 20 min application of tACS (70 Hz, 1 mA current strength). The Pre and Post TMS test blocks were conducted before and immediately after tACS was applied to the left M1, whereas the TMS test blocks performed during tACS were completed at time points starting at the 5, 10, and 15 min marks of the 20 min stimulation period. The primary dependent variable was the 1 mV motor evoked potential (MEP) amplitude. MEP data were analyzed with a 2 condition (tACS, SHAM) × 5 test (Pre, D5, D10, D15, Post) within-subjects ANOVA. Results: The main effect for condition (p = 0.704) and condition × test interaction (p = 0.349) were both non-statistically significant. There was a significant main effect for test (p = 0.003); however, post hoc analysis indicated that none of the pairwise comparisons were statistically significant. Conclusions: Overall, the findings indicate that tACS applied to the left M1 does not significantly modulate contralateral right M1 excitability during or immediately after stimulation, at least when utilizing the present tACS parameters. Full article

This study applies multivariate data analysis to deconvolute the spectral profiles of the Amide III region in the infrared spectra of gingival crevicular fluid (GCF). This reveals the impact of major oral diseases, such as dental caries and periodontal diseases, on the transformation of the secondary structure of GCF proteins. A two-stage analytical approach was employed: first, principal component analysis (PCA) was performed to establish the main factors of variation in the data, followed by pairwise comparisons of the samples based on the results of the Amide III profile deconvolution. The analysis also accounted for comorbidities, such as oncological and gastrointestinal diseases. This approach allowed for the identification of subtle differences in the composition and conformation of the secondary structure of GCF proteins while accounting for the superposition of multiple influencing factors. This methodology was effective in identifying biomarkers of oral diseases in GCF. For the first time, it has been demonstrated that the relative content of the β-sheet-associated component in the spectral profile of the secondary structure element of the protein fraction of GCF serves as a statistically significant marker for dental caries, regardless of the presence or absence of other diseases. Additionally, a significant decrease in the relative content of α-helix structures was observed in GCF from patients with oncological diseases. The changes in the spectral profile of the Amide III band of GCF identified in this study have not been previously detected using molecular spectroscopy, correlated with the secondary structure of proteins, or analyzed using multivariate analysis methods. Full article

Background: Depression is one of the leading causes of disability worldwide. Among pharmacological treatments, fluvoxamine—an early SSRI with a distinct pharmacological profile—has been recently reappraised for its broader clinical relevance. Objective: To assess the efficacy of fluvoxamine in the treatment of depression compared to placebo and other antidepressants through a comprehensive overview of systematic reviews and meta-analyses. Methods: A systematic search was conducted in MEDLINE and the Cochrane Central Register of Controlled Trials, including systematic reviews and meta-analyses of randomized controlled trials evaluating fluvoxamine’s efficacy. Reviews were eligible if they included adults diagnosed with depressive disorders based on the DSM or ICD criteria. Reviews focusing on other psychiatric disorders, comorbidities, tolerability, or economic evaluations were excluded. Data extraction included effect size measures and methodological quality assessments using the AMSTAR-2 tool. Results were synthesized by comparing fluvoxamine to placebo, tricyclic antidepressants (TCAs), selective serotonin reuptake inhibitors (SSRIs), serotonin-norepinephrine reuptake inhibitors (SNRIs), and other antidepressants. Results: A total of 74 reviews were identified, of which 14 systematic reviews met the inclusion criteria after screening and full-text analysis. These reviews, published between 1994 and 2021, predominantly involved nine pairwise meta-analyses and five network meta-analyses, comparing fluvoxamine with placebo and various antidepressants. Fluvoxamine demonstrated consistent superiority over placebo in achieving treatment response and remission outcomes. Comparisons with imipramine, clomipramine, amitriptyline, dothiepin, paroxetine, fluoxetine, citalopram, mianserin, nortriptyline, and moclobemide generally revealed no significant differences in efficacy. However, some reviews indicated that venlafaxine and mirtazapine were superior to fluvoxamine in certain outcomes, while fluvoxamine demonstrated greater efficacy than desipramine in one review. Sertraline and milnacipran showed mixed or review-quality-dependent results, with one low-quality review favoring milnacipran. Most reviews assessed outcomes over a median follow-up of six weeks using standardized depression rating scales. Conclusions: Fluvoxamine is a robust and effective antidepressant, demonstrating consistent efficacy comparable to other antidepressants and superior to placebo. While no single antidepressant was universally superior, fluvoxamine’s unique pharmacological profile and favourable safety characteristics support its clinical utility. Further research is needed to explore its role in personalized treatment strategies and emerging therapeutic contexts, such as comorbid anxiety and post-traumatic stress disorder. Full article

Objectives: Resistance training can improve body composition and physical function during and after breast cancer treatment and improve quality of life. It is unclear whether these changes persist once a person is no longer actively enrolled in a structured exercise regimen. Thus, we analyzed participants from the EXERT-BC protocol, assessing an intense exercise regimen in women with breast cancer at one year. Methods: All the participants were asked to undergo reassessment at one year. Current exercise habits, injuries, changes in medical history, body composition, handgrip strength, functional mobility and balance, and patient-reported quality of life were assessed. Pairwise comparison was performed via the paired t test. Results: Out of 40 initial participants, 33 returned for reevaluation, with 6 lost to follow-up and 1 with unrelated hospitalization. The median age was 57.8 years, and stage at diagnosis was 1. Weekly exercise was reported by 16 participants (48.5%), with 14 of the 16 following structured resistance training. Between completion of the EXERT-BC and one year follow-up, five women (15.2%) experienced musculoskeletal injuries, which inhibited their ability to exercise. Three women (9%), who were no longer exercising experienced orthopedic injuries requiring medical intervention. The significant reduction in percent body fat, total body fat, excess fat, and increases in muscle mass, resting metabolic rate, and whole-body phase angle dissipated at 1 year. Activity levels and quality of life were no longer significantly improved. However, strength, mobility, and balance remained significantly improved versus pre-exercise measurements, whether a participant was still engaged in exercise or not. Conclusions: After a 3-month dose-escalated resistance training regimen, exercise compliance was poor at one year. The anthropomorphic benefits of the regimen regressed by one year; however, the improvements in strength, balance, and mobility persisted. Full article

Mastitis is an important disease limiting milk production in dairy cows. Somatic cell score is commonly used as one of the main ways to gauge the level of mastitis in dairy cows, with higher somatic cell scores usually indicating possible mastitis. However, the main molecular markers affecting somatic cell scores remain unknown. The aim of this study was to investigate the association between single nucleotide polymorphisms in the SLC11A1 gene and somatic cell score in Chinese Holstein cows. In this study, 210 Chinese Holstein cows were genotyped and potential SNPs were detected by DNA sequencing, PCR-SSCP and PCR-RFLP analysis. Our results revealed two SNPs were identified in the CDS region of SLC11A1: c.723C>T and c.1144C>G. For the c.723C>T polymorphic site, two genotypes (AA, AB) were found and the genotype frequencies were 0.790 and 0.210, respectively. The results of the association analysis showed that the mean somatic cell score of the AA genotypes were significantly lower than those of the AB genotypes, suggesting that the A allele is a potential marker for improving mastitis resistance in Chinese Holstein cows. For the c.1144C>G polymorphic site, three genotypes (CC, CD, and DD) were found and the genotype frequencies were 0.629, 0.352 and 0.019, respectively. The association analysis revealed that the mean somatic cell score of CC genotypes was lower than that of CD and DD genotypes, however, no significant differences were observed among the various genotype groups when subjected to pair-wise comparisons. The bioinformatic analysis showed that these mutations affected the secondary and tertiary structure of SLC11A1 mRNA, suggesting that they may affect gene expression or protein translation and function. Finally, we predicted the SLC11A1 protein interaction network and found that SPI1, NOD2, TLR2 and S100A12 interacted with SLC11A1 and were reported as candidate genes associated with mastitis resistance. The results indicated that the SNP (c.723C>T) could be potential molecular marker for improving mastitis resistance traits in Chinese Holstein cows. We recommend further validation of this SNP in larger populations and its potential integration into breeding programs to enhance mastitis resistance in dairy cows. Full article

Social relationship recognition (SRR) holds significant value in fields such as behavior analysis and intelligent social systems. However, existing methods primarily focus on modeling individual visual traits, interaction patterns, and scene-level contextual cues, often failing to capture the complex dependencies among these features and the hierarchical structure of social groups, which are crucial for effective reasoning. In order to overcome these restrictions, this essay suggests a SRR model that integrates Gated Graph Neural Network (GGNN) and Transformer. The task for SRR in this model is image-based. Specifically, the purpose of a novel and robust hybrid feature extraction module is to capture individual characteristics, relative positional information, and group-level cues, which are used to construct relation nodes and group nodes. A modified GGNN is then employed to model the logical dependencies between features. Nevertheless, GGNN alone lacks the capacity to dynamically adjust feature importance, which may result in ambiguous relationship representations. The Transformer’s multi-head self-attention (MSA) mechanism is integrated to improve feature interaction modeling, allowing the model to capture global context and higher-order dependencies effectively. By fusing pairwise features, graph-structured features, and group-level information. Experimental results on public datasets such as PISC demonstrate that the proposed approach outperforms comparison models including Dual-Glance, GRM, GRRN, Graph-BERT, and SRT in terms of accuracy and mean average precision (mAP), validating its effectiveness in multi-feature representation learning and global reasoning. Full article

Since the discovery of the Differential Evolution algorithm, new and improved versions have continuously emerged. In this paper, we review selected algorithms based on Differential Evolution that have been proposed in recent years. We examine the mechanisms integrated into them and compare the performance of algorithms. To compare their performances, statistical comparisons were used as they enable us to draw reliable conclusions about the algorithms’ performances. We use the Wilcoxon signed-rank test for pairwise comparisons and the Friedman test for multiple comparisons. Subsequently, the Mann–Whitney U-score test was added. We conducted not only a cumulative analysis of algorithms, but we also focused on their performances regarding the function family (i.e., unimodal, multimodal, hybrid, and composition functions). Experimental results of algorithms were obtained on problems defined for the CEC’24 Special Session and Competition on Single Objective Real Parameter Numerical Optimization. Problem dimensions of 10, 30, 50, and 100 were analyzed. In this paper, we highlight promising mechanisms for further development and improvements based on the study of the selected algorithms. Full article

Background and Objectives: Acute coronary syndrome (ACS) is a life-threatening cardiovascular condition with high mortality rates, necessitating accurate and early risk assessment to optimize patient outcomes. While traditional lipid markers, such as low-density lipoprotein-cholesterol (LDL-C) and high-density lipoprotein-cholesterol (HDL-C), are widely used, non-traditional lipid indices, including the lipoprotein combined index (LCI), atherogenic index of plasma (AIP), atherogenic index (AI), Castelli risk indices (CRI-I, CRI-II), and atherogenic combined index (ACI) may offer additional prognostic insights by reflecting the underlying atherogenic and inflammatory processes. This study aimed to assess the prognostic value of these non-traditional lipid indices, along with traditional lipid and biochemical markers, for in-hospital mortality in ACS patients. Materials and Methods: This retrospective observational study analyzed data from ACS patients admitted to the coronary care unit (CCU) between January 2019 and September 2024. A cohort of 920 patients was divided into survivor (n = 823, 89.46%) and non-survivor (n = 97, 10.54%) groups based on in-hospital mortality outcomes. Demographic, hematological, biochemical, and lipid profile data, including traditional and non-traditional lipid indices, were collected. Separate logistic regression models were developed for each index, adjusting for demographic and clinical variables in order to assess the independent predictive power of each non-traditional lipid index. Results: Significant differences were observed between survivor and non-survivor groups in terms of age, c-reactive protein (CRP), white blood cell count (WBC), hemoglobin (HGB), and creatinine levels (all p-values < 0.05). While traditional lipid markers, such as LDL-C and HDL-C, showed limited predictive value, non-traditional lipid indices demonstrated stronger associations. The highest Exp (Beta) values were observed for the CRI-II, AI, and CRI-I. An ROC analysis further confirmed that the CRI-II, AI, and CRI-I had the highest AUC values, with pairwise comparisons underscoring the CRI-II’s superior accuracy. These findings suggest that non-traditional lipid indices predict atherogenic risk better than traditional markers alone. Conclusions: Non-traditional lipid indices, particularly the CRI-I and II, AI, LCI, ACI, and AIP, were found to be significantly associated with in-hospital mortality in ACS patients. These indices may provide additional prognostic value beyond traditional lipid parameters; however, further prospective studies are needed to confirm their clinical utility. These results underscore the importance of integrating non-traditional lipid indices into routine risk assessments to improve mortality predictions and inform targeted interventions in high-risk ACS patients. Full article

Background: Axial involvement in psoriatic arthritis (axPsA) presents clinical and radiological differences from ankylosing spondylitis (AS), which may influence the therapeutic response. While Guselkumab has demonstrated efficacy in peripheral PsA, its role in axPsA is less well established, particularly in real-world settings. Objective: To evaluate the positive effects of Guselkumab therapy in patients with psoriatic arthritis (PsA), 58.6% of whom have axial involvement, in a 12-month, single-center, longitudinal, prospective observational cohort study conducted in a real-life setting. Methods: A cohort of 99 patients with PsA, including 58 with axial involvement (axPsA), was treated with Guselkumab for 12 months. Treatment efficacy was assessed by evaluating the reduction in mBASDAI, ASDAS, DAPSA, VAS Pain, LEI, and HAQ scores. The Friedman test was used to analyze whether the overall changes from baseline to 12 months were statistically significant. Patients with axial involvement were assessed by MRI, with scores measured at baseline (t₀), after 6 months (t₆), and after 12 months (t₁₂) of therapy. Statistical evaluation was conducted using the Friedman test, followed by pairwise comparisons of values obtained at different follow-up time points using the Wilcoxon signed-rank test. Additionally, the drug’s retention rate was examined using a Kaplan–Meier curve. Results: After 12 months of therapy, a statistically significant reduction was observed in all clinimetric parameters. Patients with axial involvement were also evaluated by MRI at baseline, after 6 months, and after 12 months of therapy. MRI images showed a reduction in bone marrow edema and a decrease in signal intensity, indicating a significant reduction in inflammation and confirming the drug’s efficacy. Retention rate values demonstrate that Guselkumab is well tolerated and effective in the long term for the majority of patients. Conclusions: This 12-month real-world study of 99 PsA patients confirms the efficacy of Guselkumab in reducing disease activity in both peripheral and axial forms. The findings align with previous RWE and clinical trials (DISCOVER-1 and -2), supporting its clinical utility in PsA and axPsA, with high treatment retention. Full article