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Exposure to leadership activities plays a crucial role in enhancing self-efficacy, which is essential for developing effective student leaders. This study assessed the level of exposure and self-efficacy in school leadership among Supreme Student Government (SSG) leaders in the DepEd Bohol Division for the school year 2019-2020. Descriptivecorrelational research design was employed to evaluate the relationship between the exposure levels to leadership activities and the self-efficacy of 1,900 student leaders across 100 high schools which were chosen randomly. Two sets of questionnaires, validated by Youth Formation officers, were used to collect data on eight leadership areas: technical aspects, organizing school events, project implementation, policy/program execution, team building, financial management, time management, and mandated SSG programs. Descriptive statistics and Spearman rank correlation were used to analyze the data. The findings revealed a strong positive correlation between leadership exposure and self-efficacy, with the highest correlation in organizing school events and the lowest in time management. The results indicate that increased exposure to leadership tasks significantly boosts students' confidence in their leadership abilities. These insights suggest the need for comprehensive leadership training programs to enhance student leaders' skills and confidence, ultimately promoting better leadership outcomes. [ABSTRACT FROM AUTHOR]

The aim of this research is to evaluate the effect of visual education for the basic needs of people with disabilities on the health literacy and life quality of caregivers. The study sample comprised 268 caregivers evaluated in a pretest-posttest pattern. The data were collected using a Personal Information Form, the Health Literacy Scale, and the World Health Organization [WHO] Life Quality Scale-Short Form. Data were evaluated with the Wilcoxon test and Spearman correlation analysis. Following the education given to caregivers, an increase was determined in the Health Literacy Scale sub-dimension of information comprehension and in the WHO Life Quality Scale-Short Form sub-dimension of social relations. Thus it was seen that the visual education increased the health literacy and life quality of the caregivers. [ABSTRACT FROM AUTHOR]

AbstractThe study investigated the effect of grief cognitions on grief and meaning reconstruction levels and explored how sociodemographic factors and loss-related variables relate to these outcomes, using a sample of 155 older bereaved spouses in Türkiye. The sample for the study, which used a relational screening model, consisted of 155 participants aged 60 and over from Çankaya district of Ankara. Data were collected using the socio-demographic information form, the grief cognition questionnaire, and the grief and meaning reconstruction inventory. Spearman correlation analyses were conducted to evaluate the correlations between variables, and multiple and hierarchical regression analyses were performed to ascertain the predictors of the scales. The analysis revealed a negative correlation between grief cognitions and grief and meaning reconstruction levels. Expectedness of death and the time elapsed since the spouse’s death were predictors of both grief cognitions and levels of grief and meaning reconstruction. [ABSTRACT FROM AUTHOR]

Background Purpose Methods Results Conclusions Deep learning‐based computed tomography (CT) ventilation imaging (CTVI) is a promising technique for guiding functional lung avoidance radiotherapy (FLART). However, conventional approaches, which rely on anatomical CT data, may overlook important ventilation features due to the lack of motion data integration.This study aims to develop a novel dual‐aware CTVI method that integrates both anatomical information from CT images and motional information from Jacobian maps to generate more accurate ventilation images for FLART.A dataset of 66 patients with four‐dimensional CT (4DCT) images and reference ventilation images (RefVI) was utilized to develop the dual‐path fusion network (DPFN) for synthesizing ventilation images (CTVIDual). The DPFN model was specifically designed to integrate motion data from 4DCT‐generated Jacobian maps with anatomical data from average 4DCT images. The DPFN utilized two specialized feature extraction pathways, along with encoders and decoders, designed to handle both 3D average CT images and Jacobian map data. This dual‐processing approach enabled the comprehensive extraction of lung ventilation‐related features. The performance of DPFN was assessed by comparing CTVIDual to RefVI using various metrics, including Spearman's correlation coefficients (R), Dice similarity coefficients of high‐functional region (DSCh), and low‐functional region (DSCl). Additionally, CTVIDual was benchmarked against other CTVI methods, including a dual‐phase CT‐based deep learning method (CTVIDLCT), a radiomics‐based method (CTVIFM), a super voxel‐based method (CTVISVD), a Unet‐based method (CTVIUnet), and two deformable registration‐based methods (CTVIJac and CTVIHU).In the test group, the mean R between CTVIDual and RefVI was 0.70, significantly outperforming CTVIDLCT (0.68), CTVIFM (0.58), CTVISVD (0.62), and CTVIUnet (0.66), with p < 0.05. Furthermore, the DSCh and DSCl values of CTVIDual were 0.64 and 0.80, respectively, outperforming CTVISVD (0.63; 0.73) and CTVIUnet (0.62; 0.77). The performance of CTVIDual was also significantly better than that of CTVIJac and CTVIHU.A novel dual‐aware CTVI model that integrates anatomical and motion information was developed to synthesize lung ventilation images. It was shown that the accuracy of lung ventilation estimation could be significantly enhanced by incorporating motional information, particularly in patients with tumor‐induced blockages. This approach has the potential to improve the accuracy of CTVI, enabling more effective FLART. [ABSTRACT FROM AUTHOR]

Background: Synaptic degeneration, axonal injury, and white matter disintegration are among the pathological events in Alzheimer's disease (AD), for which growth-associated protein 43 (GAP-43) and diffusion tensor imaging (DTI) could be an indicator. In this study, the cerebrospinal fluid (CSF) GAP-43 clinical trajectories and their association with progression and AD hallmarks with white matter microstructural changes were evaluated. Methods: A total number of 133 participants were enrolled in GAP-43 and DTI values were compared between groups, both cross-sectionally and longitudinally with two and four-year follow-ups. Subsequently, the correlation between GAP-43 levels in the CSF and DTI values was investigated using Spearman's correlation. Results: The CSF level of GAP-43 is negatively correlated with the mean diffusivity measures in Fornix (Cres)/Stria terminals in early and late MCI (rs=-0.478 p = 0.021 and rs=-0.425 p = 0.038). Additionally, the CSF level of GAP-43 is negatively correlated with fractional anisotropy in the cingulum in late MCI (rs=-0.437 p = 0.033). Moreover, the axial diffusivity in superior corona radiate (rs=-0.562 p = 0.005 and rs=-0.484 p = 0.036) and radial diffusivity in superior fronto-occipital fasciculus was negatively correlated with GAP-43 level in the early and mid-MCI participants (rs=-0.520 p = 0.011 and rs=-0.498 p = 0.030). Conclusions: Presynaptic marker GAP-43 in combination with DTI can be used as a novel biomarker to identify microstructural synaptic degeneration in the early MCI. In addition, it can be used as a biomarker for tracking the progression of AD and monitoring treatment efficacy. [ABSTRACT FROM AUTHOR]

Water richness evaluation of coal seam roofs is a crucial prerequisite for preventing and controlling water hazards in coal seam roofs. For this purpose, Spearman correlation and GeoDetector were employed for factor optimization to investigate the significance of lithological and structural factors and the impact of interactions among different factors on the water richness of coal seam roofs. Water richness evaluation models of coal seam roofs were separately established via the entropy weight method (EWM), coefficient of variation method (CVM), and random forest method (RFM), and the predictive accuracies of these models were compared. Eleven lithological and structural factors were collected. Through Spearman correlation analysis, 6 factors were identified to have significant influences on water richness. By utilizing the interaction detection of GeoDetector, the effects of interfactor interactions on water richness were explored, and 3 combination factors were selected. AICc was used to determine the model's superiority. The evaluation results of the study area based on factor optimization and three methods were further compared and validated via pumping tests, workface water inflow tests, and three-dimensional high-density electrical method. The results indicated that the RFM exhibited higher prediction accuracy than did the entropy weight and coefficient of variation methods. Additionally, within each method, factor optimization led to improved model accuracy. [ABSTRACT FROM AUTHOR]

Background: Recently, there has been an increase in scabies cases among young children in low- and middle-income countries. With the rise of online health information, platforms such as YouTube have become popular sources of disease-related content, but the accuracy of this information remains a concern. Aim: This study evaluates the reliability and quality of YouTube videos concerning scabies in children to address the lack of research in this area. Materials and methods: A cross-sectional analysis was conducted on April 1, 2024, reviewing the first 200 relevant YouTube videos with the search terms "scabies" and "scabies in children." Videos were assessed using modified DISCERN (mDISCERN), Global Quality Score (GQS), and Journal of the American Medical Association (JAMA) scoring systems. Statistical analysis included descriptive statistics, Kruskal-Wallis tests, and Spearman correlation analysis. Results: Out of 200 videos, 107 met the inclusion criteria. The average mDISCERN score was 2.17, GQS was 2.63, and JAMA was 2.05, indicating generally poor quality. Videos by patients had the highest quality scores, while those from academic institutions had the highest JAMA scores. Longer videos with higher view counts were associated with better quality. Conclusion: This study reveals that the majority of YouTube videos on scabies in children are of low quality. There is a need for healthcare professionals to produce more accurate and reliable content to improve the quality of information available on YouTube. Further research should focus on enhancing the quality of health information on digital platforms. [ABSTRACT FROM AUTHOR]

Purpose: The objective of this study was to evaluate the feasibility of using Artificial Intelligence (AI) to measure the long-diameter of tumors for evaluating treatment response. Methods: Our study included 48 patients with lung-specific target lesions and conducted 277 measurements. The radiologists recorded the long-diameter in axial imaging plane of the target lesions for each measurement. Meanwhile, AI software was utilized to measure the long-diameter in both the axial imaging plane and in three dimensions (3D). Statistical analyses including the Bland-Altman plot, Spearman correlation analysis, and paired t-test to ascertain the accuracy and reliability of our findings. Results: The Bland-Altman plot showed that the AI measurements had a bias of -0.28 mm and had limits of agreement ranging from − 13.78 to 13.22 mm (P = 0.497), indicating agreement with the manual measurements. However, there was no agreement between the 3D measurements and the manual measurements, with P < 0.001. The paired t-test revealed no statistically significant difference between the manual measurements and AI measurements (P = 0.497), whereas a statistically significant difference was observed between the manual measurements and 3D measurements (P < 0.001). Conclusions: The application of AI in measuring the long-diameter of tumors had significantly improved efficiency and reduced the incidence of subjective measurement errors. This advancement facilitated more convenient and accurate tumor response evaluation. [ABSTRACT FROM AUTHOR]

ABSTRACT Aim Design Sample Methods Results Conclusions To explore public health nurses' competence (namely knowledge, skills, and attitudes) in relation to long‐term breastfeeding and their experience of the need for additional training on the subject.The study design was quantitative, descriptive, and cross‐sectional.Public health nurses (n = 270).Data were collected with the Long‐Term Breastfeeding Competence Scale (LBCS) online survey. Data analysis was done with Spearman's correlation analysis and binary logistic regression analysis.Slightly more than half of the respondents had a good level of knowledge and skills. The majority had a baseline positive attitude toward long‐term breastfeeding, but the attitude became more negative as the age of the breastfed child increased. Better competence was associated with younger age, parenthood, an additional degree in midwifery, and breastfeeding specialist certification. Knowledge and skills, and attitudes revealed a high correlation: the higher the knowledge and skills level, the more positive attitudes. Respondents with better knowledge and skills experienced more often the need for additional training on the subject.This study addresses that public health nurses lack competence in relation to long‐term breastfeeding. This may compromise the quality of breastfeeding guidance for families in healthcare settings. [ABSTRACT FROM AUTHOR]

Objective Methods Results Interpretation This study aimed to evaluate the diagnostic accuracy of dried blood spot (DBS) compared with conventional serum Aquaporin‐4‐IgG (AQP4‐IgG) testing.Prospective multicenter diagnostic study was conducted between April 2018 and October 2023 across medical centers in the United States, Uganda, and the Republic of Guinea. Neuromyelitis optica spectrum disorder (NMOSD) patients and controls collected blood on filter paper cards along with concurrent serum samples. These samples underwent analysis using flow cytometric live‐cell‐based assays (CBA) and enzyme‐linked immunosorbent assay (ELISA) to determine AQP4 serostatus. The accuracy of AQP4‐IgG detection between DBS and serum (gold standard) was compared.Among 150 participants (47 cases, 103 controls), there was a strong correlation between DBS and serum samples (Spearman's correlation coefficient of 0.82). The AUC was 0.97 (95% CI: 0.92–0.99). AQP4‐IgG detection through DBS showed 87.0% sensitivity (95% CI: 0.74–0.95) and 100% specificity (95% CI: 0.96–1.00) using CBA, and 65.2% sensitivity (95% CI: 0.43–0.84) and 95.2% specificity (95% CI: 0.76–0.99) using ELISA. Serum ELISA demonstrated 69.6% sensitivity (95% CI: 0.47–0.87) and 98.4% specificity (95% CI: 0.91–0.99). The stability of DBS in detecting AQP4‐IgG persisted over 24 months for most cases.The DBS represents a viable alternative for detecting AQP4‐IgG in resource‐limited settings to diagnose NMOSD, offering high sensitivity and specificity comparable to serum testing. Moreover, DBS has low shipping costs, is easy to administer, and is suitable for point‐of‐care testing. [ABSTRACT FROM AUTHOR]

Background: The soluble CD163 (sCD163) was elevated in systemic lupus erythematosus (SLE) patients. Purpose: To study whether serum sCD163 could be used to predict the occurrence and prognosis of lupus nephritis (LN). Research Design: The recruited patients were classified into different groups according to standard identification criteria. Study Sample: The patients with LN. Data Collection and Analysis: 11 indices were analyzed and compared in SLE and LN patients. Furthermore, the level of serum sCD163 was detected using an enzyme-linked immunosorbent assay. Meanwhile, the receiver operating characteristic analysis was performed to evaluate the prediction effect of sCD163. Additionally, spearman correlation analysis of serum sCD163 with indices was conducted. Results: There were six positive indices and one negative risk factor correlated to LN. sCD163 was elevated in LN patients and could be used to diagnose LN. Importantly, sCD163 was increased in LN patients with a heavy SLE disease activity index. Finally, it was revealed that the level of sCD163 was higher in the LN patients with no response than that with complete or partial response, which also could predict the prognosis of LN. Conclusions: Serum sCD163 was elevated in LN patients than in SLE patients, which could be used to predict the occurrence and prognosis of LN. [ABSTRACT FROM AUTHOR]

Background: Chronic airway disease (CAD) is characterized by chronic airway inflammation and colonization of the lungs by pro-inflammatory pathogens. However, while various other bacterial species are present in the lower airways, it is not fully understood how they influence inflammation. We aimed to identify novel anti-inflammatory species present in lower airway samples of patients with CAD. Methods: Paired sputum microbiome and inflammatory marker data of adults with CAD across three separate cohorts (Australian asthma and bronchiectasis, Scottish bronchiectasis) was analyzed using Linear discriminant analysis Effect Size (LEfSE) and Spearman correlation analysis to identify species associated with a low inflammatory profile in patients. Results: We identified the genus Aggregatibacter as more abundant in patients with lower levels of airway inflammatory markers in two CAD cohorts (Australian asthma and bronchiectasis). In addition, the relative abundance of Aggregatibacter was inversely correlated with sputum IL-8 (Australian bronchiectasis) and IL-1β levels (Australian asthma and bronchiectasis). Subsequent in vitro testing, using a physiologically relevant three-dimensional lung epithelial cell model, revealed that Aggregatibacter spp. (i.e. A. actinomycetemcomitans, A. aphrophilus) and their cell-free supernatant exerted anti-inflammatory activity without influencing host cell viability. Conclusions: These findings suggest that Aggregatibacter spp. might act to reduce airway inflammation in CAD patients. [ABSTRACT FROM AUTHOR]

Background: Massive irreparable rotator cuff tears can cause significant shoulder pain and disability. Treatment options include physiotherapy or surgery, with a lack of research comparing treatment options. For physiotherapy there is uncertainty about which patients will have a successful or unsuccessful response to treatment and a lack of consensus on what constitutes the best physiotherapy programme. With these significant gaps in the research, it is challenging for clinicians seeing patients with massive irreparable rotator cuff tears to advise on what is their best treatment pathway. Methods: A three round Delphi study was conducted with expert shoulder physiotherapists and orthopaedic surgeons to gain consensus on the important factors associated with response to physiotherapy in this patient population. Round 1 was an information-gathering round to identify predictors of response to physiotherapy in patients with massive irreparable rotator cuff tears. Rounds 2 and 3 were consensus-seeking rounds on the importance and modifiability of the predictors. Consensus criteria were determined a priori using median, interquartile range, percentage agreement and Kendall's Coefficient of Concordance. Results: Participants were recruited April–October, 2023. 88 experts participated in Round 1 and of these, 70 completed Round 3 (79.54%). In Round 1, content analysis of 344 statements identified 45 predictors. In Round 2, 29 predictors reached consensus as important and 2 additional predictors were identified. In Round 3, of the 31 predictors from Round 2, 22 reached consensus as important and 12 of these reached consensus as modifiable by physiotherapists. Both patient factors and clinician factors from a broad range of domains reached consensus: biomechanical, psychological, social, co-morbidities, communication / healthcare interactions and pain. Conclusions: The results of this Delphi study suggest that clinicians assessing patients with massive irreparable rotator cuff tears should assess across all these domains and target the modifiable factors with interventions. Particular emphasis should be placed on optimising modifiable clinician factors including therapeutic alliance, comprehensive explanation of the condition and collaborative and realistic goal-setting. These in turn may influence modifiable patient factors including patient expectations, engagement with the physiotherapy programme, motivation and self-efficacy thus creating the ideal environment to intervene on a biomechanical level with exercises. [ABSTRACT FROM AUTHOR]

This study analyzed long-term hydro-metrological drought under climate change in the Kesem sub-basin, Middle Awash basin, Ethiopia. The comparative analysis was employed using three drought indices (the streamflow drought index, standard precipitation index, and reconnaissance drought index). These indices were evaluated using the ordinal by ordinal Spearman's correlation, interval by interval Pearson, and kappa measure of agreement. The three drought indices have statistically significant (α < 0.01) strong correlation (> 0.78) and degree of agreement (0.2 fair agreement to 0.8 near-perfect agreement) tested at 99% confidence interval. The potential evapotranspiration (PET) estimation shows an increase of + 25.9 mm (1.6%) from the base period to RCP 4.5 (2020) and + 26.7 mm (1.67%) to RCP 8.5 (2020), and + 55 mm (3.4%) to RCP 4.5 (2050) and + 56.8 mm (3.5%) to RCP 8.5 (2050). This increase in PET is an indication that the watershed is very susceptible to water deficit and drought in the coming periods. Mild to extreme hydro-metrological drought was experienced during the baseline period (1984–2010) and is projected to occur in the current (2011–2044) and future (2045–2075) periods under both RCP 4.5 and 8.5 emission scenarios at 6- and 12-month timescales. Droughts will likely become more frequent in the future in the study area. Currently, extreme droughts that last 6 and 12 months occur every 13 to 19 years. Under the RCP 4.5, these droughts could happen every 6–7 years by 2050. The RCP 8.5 suggests even more frequent extreme droughts every 14 years. These findings are substance information for the water users and development works in the basin including the Kesem dam reservoir. [ABSTRACT FROM AUTHOR]

Background: Recent advances in microbiome research have revealed the presence of diverse microbial communities in human tissues previously thought to be sterile. The present study delves into the emerging field of seminal plasma microbiomics, examining the relationship between semen microbes and semen parameters and post-freezing tolerance. Methods: The study involved a cohort of healthy fertility males and microbial genome analysis using 16S rRNA to characterize the microbial diversity of seminal plasma. Microbial diversity analysis identified unique amplicon sequence variants (ASVs) and genera dominant in seminal plasma. Spearman’s correlation coefficient was used to assess the relationship between flora and semen parameters. A paired t-test was used to compare the changes in microbiome expression in seminal plasma before and after cryo-resuscitation. Results: The relevant results show that the top five phyla in terms of abundance of seminal plasma microbiome were Firmicutes, Bacteroidota, Proteobacteria, Actinobacteriota, and Campylobacterota. Spearman correlation analysis highlighted the association between specific microbial species and semen parameters, between Porphyromonas_asaccharolytica and sperm concentration. Microbial changed significantly after cryo-resuscitation, affecting taxonomic units such as Campylobacter and Muribaculaceae, and KEGG enrichment analyses, suggesting that metabolic pathways are associated with sperm freezing. Eubacterium_coprostanoligenes and Eptoniphilus_duerdenii exhibited a potential impact, while Orynebacterium_tuberculostearicum demonstrated a positive correlation with the recovery rate of progressive motile sperm. Conclusion: The semen of normal fertile individuals contains a microflora component that is closely related to semen quality, including the sperm’s ability to withstand freezing. [ABSTRACT FROM AUTHOR]

Purpose: The aim was to investigate sexual function and fertility in female adults operated on for anorectal malformations (ARM). Methods: This was a cross-sectional questionnaire-based study including female adult patients treated for ARM at our institution between 1994 and 2003. Sexual function in females was assessed using the Profile of Sexual Function (PFSF). Additional questions regarding fertility were answered by the participants. Patient characteristics were retrospectively retrieved from the medical records and descriptive statistics were used for analysis. Sexual function outcomes were compared to a control group from a previously published group of females. Composite outcome analysis was performed using previously published data to determine the potential impact of bowel function and health-related quality of life on sexual function. The ethics review authorities approved the study. Results: A total of 14 of 30 (46.7%) females responded to the questionnaires and had a mean age of 21.1 years (range 18–26). No association was found between PFSF and age or bowel function (Bowel Function Score), however, a strong correlation was found between PFSF and health-related quality of life (HRQoL) with a Spearman correlation of ρ 0.82 (p = 0.0011). The general satisfaction question was strongly associated with their total PFSF score (ρ = 0.71, p = 0.0092). Except for the "desire" item, the females in this cohort did not have significantly worse sexual function than the control population(p = 0.015). Ten of fourteen (71.4%) females had had their sexual debut at a mean age of 16.3 years and two of these women (20%) have been pregnant. All females had had menarche at a mean age of 12.7 years. Conclusion: Sexual function in adult females was comparable to healthy controls except for the "desire" item where the cohort reported poorer outcomes. The cohort's sexual function had a direct association with their reported HRQoL where individuals with worse HRQoL also reported poorer sexual function. Level of evidence: III [ABSTRACT FROM AUTHOR]

This study aimed to investigate the activation of error-prone DNA repair pathway in response to Helicobacter pylori infection. Relative changes in the expression levels of genes involved in the non-homologous end-joining pathway (NHEJ) in H. pylori-infected (Cases) and non-infected patients (Controls) with chronic gastritis were measured. A significant increase in the relative expression level of TP53, and significant decrease in the relative transcription of lncRNA LINP1 and XRCC5 were detected in the case group. The transcription of Lig4 and XRCC6 was increased in the case group, which was not statistically significant. The Spearman's Correlation Coefficient analysis showed a significant positive-correlation between the transcriptional levels of LINP1 and XRCC4/XRCC5/Lig4, and between XRCC5 and TP53/Lig4 both in the case and control groups. Moreover, a significant positive correlation between LinP1 and XRCC6 in the case, and a significant positive correlation between XRCC4 and Lig4, and a negative correlation between TP53 and LinP1/XRCC4/XRCC5 in the control group was detected. Although a relative difference was detected in transcriptional levels of the NHEJ gene mediators, downregulation of LinP1 in H. pylori-infected patients proposed the activation of a negative feedback loop, which may interfere with the NHEJ activity at the early stages of gastritis. [ABSTRACT FROM AUTHOR]

Climatic conditions are a key determinant of malaria transmission intensity, through their impacts on both the parasite and its mosquito vectors. Mathematical models relating climatic conditions to malaria transmission can be used to develop spatial maps of climatic suitability for malaria. These maps underpin efforts to quantify the distribution and burden of malaria in humans, enabling improved monitoring and control. Previous work has developed mathematical models and global maps for the suitability of temperature for malaria transmission. In this paper, existing temperature-based models are extended to include two other important bioclimatic factors: humidity and rainfall. This model is combined with fine spatial resolution climatic data to produce a more biologically-realistic global map of climatic suitability for Plasmodium falciparum malaria. The climatic suitability index developed corresponds more closely than previous temperature suitability indices with the global distribution of P. falciparum malaria. There is weak agreement between the Malaria Atlas Project estimates of P. falciparum prevalence in Africa and the estimates of suitability solely based on temperature (Spearman Correlation coefficient of ρ = 0.24 ). The addition of humidity and then rainfall improves the comparison ( ρ = 0.62 when humidity added; ρ = 0.70 when both humidity and rainfall added). By incorporating the impacts of humidity and rainfall, this model identifies arid regions that are not climatically suitable for transmission of P. falciparum malaria. Incorporation of this improved index of climatic suitability into geospatial models can improve global estimates of malaria prevalence and transmission intensity. [ABSTRACT FROM AUTHOR]

Background: Women's quality of life and self-efficacy play pivotal roles in task accomplishment and overall health improvement within families and society. This study determination the intricate relationship between quality of life and self-efficacy among women utilizing care services from Mashhad health centers. Methods: A cross-sectional study involving 366 women accessing Mashhad health centers in 2023 was conducted. Clustering sampling was employed, and data were gathered using the Schwartz self-efficacy questionnaire and the short form of quality of life. Statistical analysis utilized Spearman correlation coefficient, Kruskal-Wallis test, Mann-Whitney U-test, Wilcoxon test, and Chi-square test in SPSS25, with a significance level set at 0.05. Results: Participants' mean age was 36.42 ± 11.13 years. A statistically significant relationship was observed between self-efficacy and total quality of life score, as well as its dimensions (physical health, psychological health, social relationships, social environment and quality of life, and general health) (P < 0.001). Conclusion: The study underscores a significant association between self-efficacy and both the overall quality of life and its specific dimensions among women. These findings highlight the reciprocal influence of self-efficacy and quality of life. Consequently, tailored interventions aimed at enhancing self-efficacy and quality of life are recommended. [ABSTRACT FROM AUTHOR]

ABSTRACT Objectives Material and Methods Results Conclusions The primary aim of this study was to investigate the prevalence of peri‐implant diseases in a randomly selected Norwegian population. The secondary aims were to explore risk indicators for peri‐implant diseases and to validate self‐reported outcome measures from a survey with clinical parameters.Patients (n = 3083) rehabilitated with dental implants in 2014 were mailed a questionnaire and invited to a clinical examination. A randomly selected subset of responders underwent a clinical examination (n = 242). Full mouth clinical and radiographic examinations were conducted. Multiple logistic regression was used to assess patient‐related risk indicators for peri‐implantitis. Self‐reported data were compared with data from the clinical examination using Spearman correlation and binary logistic regression.The prevalence of peri‐implantitis was 17.0% at patient level and 8.6% at implant level, according to the 2018 classification. Risk indicators for peri‐implantitis included smoking and periodontitis in the adjusted model. The correlation was strong (r = 0.91, p < 0.001) between number of self‐reported implants and clinical counts, whereas self‐reported peri‐implant inflammation was associated with peri‐implantitis (OR 6.4 [95% CI 3.0, 13.7]).Smoking and periodontitis were identified as key risk indicators for peri‐implantitis. Questionnaire data rendered clinically valid estimates of implant number, and self‐reported peri‐implant inflammation was associated with clinical peri‐implantitis. [ABSTRACT FROM AUTHOR]

Background: The Ages and Stages Questionnaire 3rd edition (ASQ-3) could be a feasible tool in resource-poor settings. Little is known on the relationship between scores on the ASQ-3 and later intellectual abilities in these settings. Aims: To examine the relationship between ASQ-3 scores during the first and second year of life and intellectual abilities at 4 years of age in Nepalese children. Methods: In a cohort of 600 children at-risk of stunting, the ASQ-3 was performed at 6–11 and 18–23 months, and the Wechsler Preschool and Primary Scales of Intelligence, fourth edition (WPPSI-IV) at 4 years. We examined the relationship between the ASQ-3 scores and WPPSI-IV full scale IQ (FSIQ) using Spearman correlation coefficients and linear regression models. Results: Correlations between ASQ-3 total scores and FSIQ was 0.17 (95% CI 0.07, 0.27) at 6–11 and 0.34 (95% CI 0.26, 0.44) at 18–23 months explaining 2 and 12% of the variance respectively. Except for the communication subscale at 18–23 months with moderate correlations, correlations between the ASQ-3 subscales and FSIQ were weak. Conclusion: Our findings suggest a modest relationship between ASQ-3 scores in early childhood and intellectual abilities at 4 years. [ABSTRACT FROM AUTHOR]

Background: Fluorine 18-labelled tetrafluoroborate ([18F]TFB) is a substrate for the sodium/iodide symporter. In thyroid cancer, [18F]TFB-PET/CT may be an alternative to iodine imaging to evaluate the extent of disease, eligibility for radioiodine treatment, and success of redifferentiation therapies. We report the results of a pilot study to determine tumor uptake of [18F]TFB and compare its properties to [124I]IodinePET/CT in patients with metastatic thyroid cancer. Methods: Five patients were included in a prospective study. All patients received PET/CT 1 h after injection of 356 ± 12 MBq [18F]TFB and were given 230 ± 9 MBq [124I]Iodine orally on the same day, followed by PET/CT after 48 h. Before redifferentiation therapy, patients underwent an additional baseline [124I]Iodine PET/CT. Cases were analyzed by two board-certified specialists. Detection rates and Spearman correlation for [18F]TFB and [124I]Iodine were calculated. Results: Three patients had poorly differentiated thyroid cancer and received trametinib in a redifferentiation trial. Two patients had papillary thyroid cancer and did not receive redifferentiation therapy. Of the 33 lesions seen before/without redifferentiation therapy, 19 (58%) were visible on [18F]TFB and 30 (91%) on [124I]Iodine imaging. In the patients who underwent redifferentiation therapy, 48 lesions were newly seen on [124I]Iodine PET/CT with a median SUVmax of 3.3 (range, 0.4–285.0). All of these lesions were [18F]TFB-negative. Conclusion: [18F]TFB failed to predict radioactive iodine uptake in patients with poorly differentiated thyroid cancer who underwent redifferentiation therapy with trametinib. It is unclear whether such discrepancies may also occur in other redifferentiation therapies or may even be encountered in redifferentiation-naïve thyroid cancer. Trial registration number: NCT03196518, registered on June 22, 2017. [ABSTRACT FROM AUTHOR]

Objective: Constructing a demand-oriented Internet + community home care service indicator system, starting from the actual needs of the elderly, and quantifying the demand into specific service contents that can be provided, so as to realize the effective supply of services. It aims to provide a theoretical basis for the government to formulate relevant aging policies and provide a reference basis for promoting the innovation and development of the Internet + elderly care model. Methods: Based on existence needs, relationship needs and growth needs abbreviated as "Existence, Relatedness, Growth (ERG)" demand theory, through the discussion in the group meeting, form the expert consultation questionnaire of the demand-oriented Internet + community home care service indicator system, select experts in related fields to conduct two rounds of Delphi expert consultation, summarize the experts' opinions to determine the indicator system items, and use the Analytic Hierarchy Process (AHP) method to construct the judgment matrix to derive the weighting coefficients of the indicators, and establish the ultimate demand-oriented Internet + community home care service indicator system. Results: The effective recovery rates for the two rounds of expert consoulation questionnaires were 100%, with expert authority coefficients of 0.852 and 0.868, respectively. The Kendall coefficients for the second round of expert views varied from 0.226 to 0.431, with coefficients of variation for all indexes less than 0.25.The finalized demand-oriented Internet + community home care service indicator system includes 3 first-level indicators, 10 s-level indicators, and 46 third-level indicators. The consistency ratios of indicator judgment matrices at all levels are less than 0.10, suggesting that the hierarchical analysis findings are consistent, implying that the weight coefficient distribution is appropriate. Conclusion: The demand-oriented Internet + community home care service Indicator System, which was created through expert consultation and AHP method, has reasonable content and is more dependable as an evaluation tool for reliably assessing demand for elderly servic. [ABSTRACT FROM AUTHOR]

Films are composed of different sequentially ordered shots limited by cuts, which bound the last frame of the outcoming shot and the first frame of the incoming shot. In turn, film editing is known to impact its aesthetics, and has been widely studied in film theory. The objective of this research was to locate and identify neuronal response patterns that make it possible to differentiate between specific types of shot changes by cut. The analysis was conducted on the neuronal rhythms of the electroencephalogram (EEG) by means of an EEG power spectral analysis. This enabled us to identify changes in neuronal excitation and inhibition based on the type of shot changes by cut. Specifically, we compared the neuronal records to locate the time windows for each electrode and frequency range exhibiting differences for various types of shot changes by cut. We combined this method with the permutation test and Spearman correlation to determine when the time windows for each electrode by frequency band are reacting to the cut event in a correlated manner among the different films. This analysis revealed that the neuronal responses to the cut depend on the variation between shots, rather than solely on the new input. Secondly, the findings allowed us to differentiate between shot changes according to the variation of the shot scale and changes due to the filming angle, or the absence thereof (i.e., cut on axis). The results expand our understanding of viewers' neurological sensitivity to and comprehension of an important film feature. [ABSTRACT FROM AUTHOR]

Background: We evaluated the validity of surrogacy of progression‐free survival (PFS) or time‐to‐progression (TTP) and overall response rate (ORR) in phase II trials of pancreatic ductal adenocarcinoma (PDAC). In addition, we explored the impact of predictive variables on overall survival (OS) and developed an optimal OS model. Methods: We analyzed 1867 clinical endpoint from 619 phase II PDAC trials with a systematic search from PubMed. Endpoint correlations were determined by Spearman's rank correlation. The assessed predictive factors included PFS/TTP, treatment size, therapy type, stage, and previous treatment. The relationship between predictors and OS was explored by a gamma generalized linear model (GLM) with a log‐link function and compared with linear models. Results: The Spearman rank correlation coefficient between PFS/TTP and OS was 0.88 (95% confidence interval [CI] 0.85–0.89; p < 0.0001; n = 610) and between ORR and OS was 0.58 (0.52–0.64; p < 0.0001; n = 514). Model comparison favored the GLM model over the linear model, offering more accurate predictions for higher OS values. Consequently, PFS/TTP was the strongest predictor (pseudo‐R2 = 0.75), with 1 added median PFS/TTP month associated with 13% (95% CI 13%–14%) increase in median OS. Subgroup analysis revealed that chemotherapy conferred significantly longer OS compared to targeted therapy in 1‐Agent and 2‐Agent trials, exhibiting a "very large" and "medium" effect size, respectively (rank biserial, rrb = 0.40 [95% CI 0.22–0.56] and rrb = 0.29 [0.16–0.41], both p < 0.0001), although inconsistent efficacy in 3‐Agent trials (rrb = 0.12 [−0.07–0.30], p = 0.21). Conclusions: PFS/TTP is a more reliable surrogate than ORR and a strong predictor of OS in phase II trials of pancreatic cancer. Moreover, gamma GLM (log‐link function) is a robust tool for modeling positively skewed survival data with non‐constant variance, thus can be applied to other cancers' OS data of such nature. [ABSTRACT FROM AUTHOR]

Purpose: Multiple dimensions of language dominance, such as language proficiency and demand for language use, can be reflected in bilinguals' speech-in-speech recognition scores. This paper explores the feasibility of using a novel measure to estimate language dominance for bilinguals: relative speech-in-speech recognition thresholds (SRTs) or the within-person difference in SRTs between their two languages. Method: Participants were 25 Spanish/English bilingual adults (M age = 30 years). SRTs for sentence recognition in a language-matched two-talker masker were measured in English and in Spanish using an adaptive, open-set task. Relative SRTs were calculated by subtracting the Spanish SRT from the English SRT. Language dominance and proficiency were assessed by established measures. Analysis: Spearman correlations were used to assess the association between measures. Findings: Relative SRTs were correlated with dominance scores derived from both a questionnaire (r s = −.80) and standardized testing (r s = −.80). Originality: We tested and validated a novel measure, relative SRTs, to predict language dominance in bilingual adults. This time-efficient method could be used by bilingual researchers interested in assessing language dominance for descriptive or experimental purposes. Significance: Relative SRTs show promise as a valid method to assess language dominance in Spanish/English bilingual adults. [ABSTRACT FROM AUTHOR]

In this study, we investigate the adaptability of artificial agents within a noisy T-maze that use Markov decision processes (MDPs) and successor feature (SF) and predecessor feature (PF) learning algorithms. Our focus is on quantifying how varying the hyperparameters, specifically the reward learning rate ( α r ) and the eligibility trace decay rate (λ), can enhance their adaptability. Adaptation is evaluated by analyzing the hyperparameters of cumulative reward, step length, adaptation rate, and adaptation step length and the relationships between them using Spearman's correlation tests and linear regression. Our findings reveal that an α r of 0.9 consistently yields superior adaptation across all metrics at a noise level of 0.05. However, the optimal setting for λ varies by metric and context. In discussing these results, we emphasize the critical role of hyperparameter optimization in refining the performance and transfer learning efficacy of learning algorithms. This research advances our understanding of the functionality of PF and SF algorithms, particularly in navigating the inherent uncertainty of transfer learning tasks. By offering insights into the optimal hyperparameter configurations, this study contributes to the development of more adaptive and robust learning algorithms, paving the way for future explorations in artificial intelligence and neuroscience. [ABSTRACT FROM AUTHOR]

Introduction: Psoriasis is a chronic immune-mediated skin disease with several comorbidities and a considerable influence on quality of life. Many patients with moderate-to-severe psoriasis are undertreated and have a substantial disease duration before effective treatment is started. This study analyzed patient and disease characteristics and time to effective treatment of patients with psoriasis who consulted PsoPlus. It also examined whether a treat-to-target (T2T) approach, which is implemented in PsoPlus, has an impact on treatment choice and disease progression. Methods: Through a single center, retrospective study, 170 patients in the PsoPlus dedicated clinic were compared at moment of enrollment in PsoPlus and at the last recorded consultation in 2021. Results: Median disease duration at the first PsoPlus consultation was 16.0 (interquartile range (IQR) 19.0) years. There was a significant difference in Psoriasis Area and Severity Index (PASI) and Dermatology Life Quality Index (DLQI) between the first and the last recorded PsoPlus consultation (PASI 6.0 (IQR 6.4) vs. 0.6 (IQR 2.6); DLQI 11 (IQR 11) vs. 2 (IQR 6); p < 0.001). A weak positive Spearman correlation (rs) was found between disease duration and PASI at the first PsoPlus consultation (rs = 0.175; p = 0.034), while a weak negative correlation (rs = − 0.2; p = 0.013) was found at the last registered PsoPlus consultation. Patients with a disease duration of more than 20 years had significantly more switches of treatment than those with a shorter disease duration (p < 0.001). Median time from psoriasis onset until PASI ≤ 2 was 16.0 years. Median time from the first PsoPlus consultation until PASI ≤ 2 was 7.0 months. Conclusion: The PsoPlus program with its T2T approach effectively improves clinical outcomes and quality of life for patients with psoriasis in a relatively short period, emphasizing the value of a structured, personalized treatment plan for long-term management. [ABSTRACT FROM AUTHOR]

In the era of dual carbon, the rapid development of various types of microgrid parks featuring multi-heterogeneous energy coupling presents new challenges in accurately modeling spatial and temporal load characteristics due to increasingly complex source–load characteristics and diversified interaction patterns. This study proposes a short-term load forecasting method for an interconnected park-level integrated energy system using a data center as the case study. By leveraging spatially transferable load characteristics and the heterogeneous energy correlation among electricity–cooling–heat loads, an optimal feature set is selected to effectively characterize the spatial and temporal coupling of multi-heterogeneous loads using Spearman correlation analysis. This optimal feature set is fed into the multi-task learning (MTL) combined with the convolutional neural network (CNN) and long- and short-term memory (LSTM) network model to generate prediction results. The simulation results demonstrate the efficacy of our proposed approach in characterizing the spatial and temporal energy coupling across different parks, enhancing track load "spikes" and achieving superior prediction accuracy. [ABSTRACT FROM AUTHOR]

Statistical baraminology has been a common research topic in creation biology for the last several decades. Several statistical methods have been employed but none have been tested against simulated data where the result is known. Therefore, both the original Pearson method and newly deployed Spearman method are tested in this paper against simulated data where the existing patterns were known. Multiple patterns of varying strengths were tested. In every case, the Pearson method outperformed the Spearman method. Based on these preliminary results, the Pearson method (aka the Pearson correlation coefficient) should be the preferred method of statistical baraminology. However, much more research is needed to ensure that baraminology is placed on a strong empirical foundation. [ABSTRACT FROM AUTHOR]

Introduction: It has been recently acknowledged that deficits in experiencing and processing one's own emotions, also termed alexithymia, may possibly feature the frontotemporal-spectrum disorders. This study aims to determine whether alexithymia could be included within the frontotemporal syndromes of amyotrophic lateral sclerosis (ALS). Methods: Alexithymic traits were estimated in a cohort of 68 non-demented ALS patients with the 20-item Toronto Alexithymia Scale (TAS-20). Patients were assessed for the identification of motor-phenotypes and frontotemporal syndromes based on current classification criteria. Spearman's coefficients explored the correlates of TAS-20 measures with motor-functional profiles, global cognitive, social-cognitive (emotion recognition and empathy) and behavioral status. Results: Abnormal TAS-20 scores were found in 13% of patients, and their distribution did not vary within motor and frontotemporal phenotypes. Significant associations were detected between TAS-20 and executive (p ≤.011), memory (p =.006), state-anxiety (p ≤.013) and depression measures (p ≤.010). By contrast, TAS-20 scores were unrelated to social-cognitive performances, dysexecutive and apathetic profiles. Disease duration was the only motor-functional feature being related to the TAS-20 (p ≤.008). Conclusions: Alexithymia of potential clinical relevance occur in a minority of ALS patients, and its neuropsychological correlates mostly resemble those featuring the general population. Hence, it is unlikely that alexithymia is a specific feature of frontotemporal-spectrum characterizing ALS, rather it could be an expression of psychogenic factors as a reaction to the disease. [ABSTRACT FROM AUTHOR]

Purpose: To evaluate whether trans-thyroid cartilage nerve monitoring for thyroid surgeries is as effective and safe as endotracheal tube monitoring. Methods: Fifty-one thyroidectomies (38 hemithyroidectomies and 13 total thyroidectomies, analyzed as two separate hemi-thyroidectomies) were included. Patients undergoing surgery from 6/2020 to 8/2021 were monitored simultaneously with the NIM® Nerve Monitoring System TriVantage™ Electromyography (EMG) endotracheal tube and EMG trans-thyroid cartilage. Electrophysiological responses of 64 vagus and recurrent laryngeal nerves were obtained. Peri-operative evaluation and 12-month post-operative follow-up were conducted to examine nerve function. Wilcoxon signed-rank and Spearman coefficient tests were used to determine whether there were differences between the methods. Results: The average initial amplitude measured with the trans-thyroid cartilage method was higher in the recurrent laryngeal and vagus nerves (p = 0.002, p = 0.003, respectively). The mean difference in EMG amplitude from start to end of surgery for 10 damaged nerves (7 temporary and 3 permanent) differed from intact nerves in both methods and nerves (p < 0.05 for all). Among intact recurrent laryngeal nerves, 20.4% had 20–80% decrease in amplitude in endotracheal tube electrodes and 16.7% in trans-thyroid cartilage electrodes (p = 0.92). All cases with stable EMG signals or with increased EMG amplitude (with both types of electrodes and with both nerves) had normal post-operative vocal function. No significant difference was found between the two methods when measuring the vagus and recurrent laryngeal nerves. No complications occurred when using trans-thyroid cartilage electrodes. Conclusions: Trans-thyroid cartilage nerve monitoring for thyroid surgeries is as effective and safe as the current standard monitoring using an endotracheal tube. Lay Summary: During thyroid surgery, patients are monitored to avoid damaging nerves near the vocal cords. This study compared monitoring through a throat tube with the easier method of monitoring outside of the throat to see if it is as effective and safe. No major difference was found between the two methods and there were no problems. [ABSTRACT FROM AUTHOR]

We introduce a new type of influence function, the asymptotic expected sensitivity function, which is often equivalent to but mathematically more tractable than the traditional one based on the Gâteaux derivative. To illustrate, we study the robustness of some important measures of association, including Spearman's rank correlation and Kendall's concordance measure, and the recently developed Chatterjee's correlation. [ABSTRACT FROM AUTHOR]

With the advancement of Industry 4.0, Time-Sensitive Networking (TSN) has become essential for ensuring prompt and reliable data transmission. As an augmentation of Ethernet, TSN aims to supply services capable of low latency, minimal jitter, and low packet loss for urgent data in decentralized, user-oriented networks. Efficient detection techniques are integral to TSN for swiftly determining the practicability of network configurations, as existing schedulability analysis proves insufficient. This paper delves into the potential of backpropagation neural networks (BPNN) in schedulability analysis efficiency. We optimize BPNN using spearman correlation feature selection combined with a voting ensemble method and Particle Swarm Optimization (PSO), forming two models: Spearman-Vote-BPNN and Spearman-PSO-BPNN. Testing on 5,000 network configurations in computer simulations, both models demonstrated high generalization accuracy, around 97.4%. Spearman-Vote-BPNN achieved the fastest training speed at 0.63 s and an accuracy of 98.2%. Meanwhile, Spearman-PSO-BPNN showed the highest accuracy (98.5%) with the quickest detection speed (5.6 ms). The outcomes of this research significantly advance the efficacy and precision of TSN network configuration detection and establish a formidable groundwork for future scholarly pursuits in this area. [ABSTRACT FROM AUTHOR]

Objective image quality assessment involves the use of mathematical models to quantitatively describe image quality. FR-IQA (Full-Reference Image Quality Assessment) methods using reference images are also often used to evaluate image processing and computer vision algorithms. Quality indices often use gradient operators to express relevant visual information, such as edges. Fractional calculus has been applied in the last two decades in various fields such as signal processing, image processing, and pattern recognition. Fractional derivatives are generalizations of integer-order derivatives and can be computed using various operators such as the Riemann-Liouville, Caputo-Fabrizio, and Grünwald-Letnikov operators. In this paper, we propose a modification of the FSIMc image quality index by including fractional derivatives to extract and enhance edges. A study of the usefulness of fractional derivative in the FSIMc model was conducted by assessing Pearson, Spearman and Kendall correlations with MOS scores for images from the TID2013 and KADID-10k databases. Comparison of FD_FSIMc with the classic FSIMc shows an increase of several percent in the correlation coefficients for the modified index. The results obtained are superior to those other known approaches to FR-IQA that use fractional derivatives. The results encourage the use of fractional calculus. [ABSTRACT FROM AUTHOR]

Depressive and anxiety symptoms commonly manifested throughout the progression of schizophrenia. However, the prevalence of these symptoms, alongside their co-occurrence, remains uncertain, and clinical correlates remain elusive. This study seeks to investigate the prevalence of such symptoms and their demographic and clinical associations among patients diagnosed with schizophrenia. The study included 19,623 patients diagnosed with schizophrenia based on the ICD-10 criteria. Participants were recruited from community-dwelling patients registered in the local health system in Hangzhou of China between August 1 and October 30, 2022. The prevalence rates of depressive and anxiety symptoms, as well as their co-occurrence, were determined to be 19 % (95%CI = 18.5–19.6 %), 37.4 % (95%CI = 36.8–38.0 %), and 17.7 % (95%CI = 17.2–18.2 %), respectively. Patients prescribed quetiapine, olanzapine, and risperidone exhibited significantly lower prevalence rates of these symptoms (P < 0.01). Spearman's correlation analysis revealed a significant correlation between depressive symptoms and anxiety symptoms (r = 0.60, P = 0.006). Additionally, age, social relationships, and sleep status were significantly associated with depressive and anxiety symptoms, and their co-occurrence, in both univariate and multivariate analyses. Given the pervasive nature and detrimental consequences of these symptoms among individuals diagnosed with schizophrenia, comprehensive evaluation and implementation of efficacious interventions are highly recommended. • High occurrence of depressive and anxiety symptoms, often co-occurring, in individuals with schizophrenia. • Reduction of depressive and anxiety symptoms in schizophrenia patients through various antipsychotics. • Correlation observed between depressive symptoms and anxiety symptoms in schizophrenia patients. • Demographic and clinical characteristics shape depressive and anxiety symptoms in schizophrenia. [ABSTRACT FROM AUTHOR]

Increasing evidence has shown that the microbiota-gut-brain axis (MGB) is involved in the mechanism of major depressive disorder (MDD). However, the relationship between the gut microbiome and brain function in MDD patients has not been determined. Here, we intend to identify specific changes in the gut microbiome and brain function in first-episode, drug-naïve MDD patients and then explore the associations between the two omics to elucidate how the MGB axis plays a role in MDD development. We recruited 38 first-episode, drug-naïve MDD patients and 37 healthy controls (HC). The composition of the fecal microbiome and neural spontaneous activity alterations were examined using 16S rRNA gene amplicon sequencing analysis and regional homogeneity (ReHo). Spearman correlation analyses were conducted to assess the associations between the gut microbiome and brain function. Compared with HC, MDD patients exhibited distinct alterations in the gut microbiota and elevated ReHo in the frontal regions. In the MDD group, a positive relationship was noted between the relative abundance of Blautia and the HAMD-17 and HAMA scores, as well as between the relative abundance of Oxalobacteraceae and the HAMD-17 score. The relative abundances of Porphyromonadaceae and Parabacteroides were negatively correlated with the ReHo values of frontal regions. Our study utilized a cross-sectional design, and the number of subjects was relatively small. We found that some specific gut microbiomes were associated with frontal function, and others were associated with clinical symptoms in MDD patients, which may support the role of the MGB axis underlying MDD. • Major depressive disorder (MDD) patients exhibited elevated ReHo in frontal regions. • MDD patients exhibited specific alterations in gut microbiota. • Blautia and Oxalobacteraceae are associated with clinical symptoms of MDD. • Porphyromonadaceae and Parabacteroides are correlated with frontal function in MDD. [ABSTRACT FROM AUTHOR]

To detect careless and insufficient effort (C/IE) survey responders, researchers can use infrequency items – items that almost no one agrees with (e.g., "When a friend greets me, I generally try to say nothing back") – and frequency items – items that almost everyone agrees with (e.g., "I try to listen when someone I care about is telling me something"). Here, we provide initial validation for two sets of these items: the 14-item InvalidResponding Inventory for Statements (IDRIS) and the 6-item Invalid Responding Inventory for Adjectives (IDRIA). Across six studies (N1 = 536; N2 = 701; N3 = 500; N4 = 499; N5 = 629, N6 = 562), we found consistent evidence that the IDRIS is capable of detecting C/IE responding among statement-based scales (e.g., the HEXACO-PI-R) and the IDRIA is capable of detecting C/IE responding among both adjective-based scales (e.g., the Lex-20) and adjective-derived scales (e.g., the BFI-2). These findings were robust across different analytic approaches (e.g., Pearson correlations; Spearman rank-order correlations), different indices of C/IE responding (e.g., person-total correlations; semantic synonyms; horizontal cursor variability), and different sample types (e.g., US undergraduate students; Nigerian survey panel participants). Taken together, these results provide promising evidence for the utility of the IDRIS and IDRIA in detecting C/IE responding. [ABSTRACT FROM AUTHOR]

This study aimed to investigate the training load through external and internal load dynamics across the preparation and competition of a top-level national team during a Rink Hockey European Championship. A non-experimental descriptive method was developed. A two-way mixed design ANOVA and a Spearman correlation test were used to compare and understand the relationship between players' external and internal load across microcycles during training sessions and competitive matches. Results revealed significantly higher values between training match day −3 to training match day −1 for player load (p ≤ 0.05), distance covered, and high-speed skating (p ≤ 0.001). Competition weeks exposed significantly higher values in comparison with training weeks. Interestingly, during competition, high impacts (p ≤ 0.001, r = 0.64) and decelerations (p ≤ 0.001, r = 0.43) had a greater influence on players' session RPE than in training weeks. Different external and internal load dynamics were observed in the competition and training weeks, with high impacts and decelerations appearing to create a physiological impact on players, but the same does not occur in the training sessions. Results highlight the need to understand the competitive dynamics of each sport and the use of the most appropriate metrics to monitor the preparation process. [ABSTRACT FROM AUTHOR]

Purpose: The radionuclides pollution base on MMs (metals and metalloids) near uranium mines has been drawing broad attention, but the extent of their impact on soil and human health is still unclear. Therefore, the aim of this study was to investigate the distribution and health risk assessments of 238U, 226Ra, 232Th and 40 K base on MMs (Cr, Ni, Cu, Zn, As, Cd, and Pb) in different surface soils near an uranium mine. Materials and methods: Surface soil samples were extracted from 35 representative sites near the Lefu uranium mine. Radionuclides and MMs were measured using high-purity germanium (HPGe) N-type coaxial detector and inductively coupled plasma mass spectrometer, respectively. Pollution status was evaluated using DR, Raeq, AEDE, Hext, and ELCR for radionuclides and Pi, Igeo, RI and health risk index for MMs. Their correlation was analyzed through Pearson/Spearman correlation analysis. Results and discussion: The average activity concentration of 238U, 226Ra, 232Th, and 40 K are 504, 1227, 118, and 769 Bq·kg−1 respectively and the average concentration of Cr, Ni, Cu, Zn, As, Cd, and Pb are 200, 33.9, 41.3, 132, 18.4, 0.26, and 78.7 mg·kg−1, respectively. Values of DR, Raeq, AEDE, Hext, and ELCR all exceed the world average to varying degrees and values of Pi, Igeo, RI and the health risk index are within the acceptable ranges. Correlation analyses showed that 238U, 226Ra, 232Th and Pb are strongly correlated (correlation coefficient > 0.6) with each other. Conclusions: On the basis of the obtained values, it can be concluded that generally higher radionuclides and MMs were distributed near the Lefu uranium. There are potential health risks associated with the elevated radioactivity. The overall situation of MMs is controllable, however, particular attention is warranted for Cr and Cd, as they approach values-at-risk. The strong correlations between 238U, 226Ra, 232Th and Pb imply a uniform pollution level or a possible shared source. [ABSTRACT FROM AUTHOR]

The response of mesozooplankton is critical in assessing the health of an estuarine ecosystem. Reports on the spatial and temporal dynamics of mesozooplankton community in estuarine and backwaters of the Southern parts of India are scanty. In this scenario, we appraised the community structure of mesozooplankton and their spatio-temporal dynamics based on various multivariate statistical assessments. A total of 31 taxa were identified and the abundance was principally dominated by Copepoda followed by Luciferidae during three sampling seasons. The most abundant species were: Paracalanus parvus parvus, Pseudodiaptomus aurivillii, Temora stylifera, and Pseudodiaptomus serricaudatus. Canonical correspondence analysis and Spearman's correlation coefficients underlined that salinity, turbidity, conductivity, temperature, dissolved oxygen, chlorophyll a (Chl-a), and nutrients were the principal environmental variables strongly linked with mesozooplankton dynamics in Munroe Island. The highest abundance of mesozooplankton was recorded in MoN (monsoon), followed by PrM (pre-monsoon), and PoM (post-monsoon). Hierarchical clustering confirmed that the grouping of sampling stations is based on the estuarine and freshwater influences on mesozooplankton abundance. During the entire investigation, various ecological indices were observed in good condition. Moreover, the optimum environmental conditions during the PoM season are marked with the highest indices values. Overall, multivariate investigations undoubtedly proved the suitability of mesozooplankton communities as potential bioindicators for spatial and seasonal ecological assessments. Our investigation emphasizes the high assemblages of mesozooplankton and their responses to various environmental variables and highlights the significance of long-term ecological monitoring in a threatened ecosystem like Munroe Island. [ABSTRACT FROM AUTHOR]

Anger impairs a driver's control and risk assessment abilities, heightening traffic accident risks. Constructing a multimodal dataset during driving tasks is crucial for accurate anger recognition. This study developed a multimodal physiological -vehicle driving dataset (DPV-MFD) based on drivers' self-reported anger during simulated driving tasks. In Experiment 1, responses from 624 participants to anger-inducing videos and driving scenarios were collected via questionnaires to select appropriate materials. In Experiments 2 and 3, multimodal dynamic data and self-reported SAM emotion ratings were collected during simulated and real-vehicle tasks, capturing physiological and vehicle responses in neutral and anger states. Spearman's correlation coefficient analysis validated the DPV-MFD's effectiveness and explored the relationships between multimodal data and emotional dimensions. The CNN-LSTM deep learning network was used to assess the emotion recognition performance of the DPV-MFD across different time windows, and its applicability in real-world driving scenarios was validated. Compared to using EEG data alone, integrating multimodal data significantly improved anger recognition accuracy, with accuracy and F1 scores rising by 4.49% and 9.14%, respectively. Additionally, real-vehicle data closely matched simulated data, confirming the dataset's effectiveness for real-world applications. This research is pivotal for advancing emotion-aware human–machine- interaction and intelligent transportation systems. [ABSTRACT FROM AUTHOR]

Due to its fundamental position in the aquatic food chain linking primary producers (phytoplankton) to higher trophic levels (fish), zooplankton has a crucial influence on the structure and function of lakes. The scientific literature shows that zooplankton is an effective indicator of eutrophication. However, according to the requirements of the Water Framework Directive, zooplankton is still not included as one of the biological components for assessing the ecological status of lakes. In Poland, the zooplankton-based method (ZIPLAs) has been developed to assess the ecological status of deep stratified lakes. Shallow lakes function differently from deep lakes, and literature data show that the response of zooplankton indices to eutrophication parameters is much weaker than in deep lakes. This paper presents the Zooplankton Index for Shallow Lakes' Assessment (ZISLA), a new method for assessing ecological status based on zooplankton community structure. The ZISLA includes the body size index of Daphnia cucullata (BSI), the percentage share of high trophy-indicating rotifer species (IHTROT), the number of rotifer species (NROT), and the Margalef index (D). The ZISLA shows a strong, significant correlation with total phosphorus and total nitrogen (Spearman's coefficient (R = −0.77, R = −0.74; p < 0.0001) and slightly weaker with Secchi disk visibility (R = 0.72; p < 0.0001). The ZISLA index shows a statistically significant good/moderate distinction for all water quality parameters. [ABSTRACT FROM AUTHOR]

The thorough dissection of prominent scholarly contributions can shed light on the evolution of research trajectories. Using marketing research as a case, this study aims to probe into the recognition and resonance that research enjoys across social media landscapes, employing the power of Altmetric. We employed an analytical approach involving descriptive statistics coupled with the Spearman correlation test, scrutinizing Altmetric data for the most heavily cited works in the marketing discipline (n: 137). Our examination illuminates that the United States and the United Kingdom are the dominant contributors to the majority of tweets and readership relating to these works. Noteworthily, marketing research featured in top-tier publications registered the highest Altmetric scores from both Twitter and Mendeley. An intriguing pattern surfaced in our exploration, highlighting a positive relationship between Altmetric scores drawn from social media platforms and citation counts on the Web of Science (WoS), as well as between Mendeley readership and WoS citations. These Altmetric insights underscore the pivotal role social media plays in propelling citation rates of research, implying that researchers can significantly amplify the visibility and citation impact of their work by strategically employing social media platforms and tapping into Altmetric indicators' potential. [ABSTRACT FROM AUTHOR]

Objective. The aim of this study was to develop and psychometrically validate a self-report instrument to assess (1) competencies, (2) needs, and (3) satisfaction among youth transitioning from pediatric to adult rheumatology. Methods. The Transition-KompAZ was developed in several steps with conceptual and psychometric analyses. To test its psychometric properties, the instrument was administered to adolescents and young adults (AYAs; 16-25 years) with inflammatory rheumatic diseases before (group 1) or after (group 2) transfer to adult rheumatology. A 2-factor, higher-order confirmatory factor analysis (CFA) model was applied to test the hypothesized factor structure. Internal consistency was estimated using the approach of Raykov with the factor loadings and error variances estimated in the CFA. Spearman rank correlation coefficients were used to assess construct validity. Results. The Transition-KompAZ includes the following modules: (1) competencies in transition (knowledge, self-management), (2) needs (healthcare services, information), and (3) satisfaction (general, transitional care). A total of 173 AYAs (group 1: n = 86; group 2: n = 87) from 12 rheumatology sites completed the Transition-KompAZ. It showed good model fit (comparative fit index > 0.9; Tucker-Lewis index > 0.9; weighted root mean square residual < 0.9) with good internal consistency. The instrument demonstrated moderate-to-good construct validity and good test-retest reliability. Conclusion. The Transition-KompAZ appears to be a reliable tool for assessing important dimensions of transition. It may support a structured and individualized transition, as well as the evaluation of transition services. However, further studies are required to assess its predictive value in terms of transfer readiness and successful transition. [ABSTRACT FROM AUTHOR]

This paper proposes a hybrid model to improve Information Content (IC) related metrics of semantic similarity between words, named IC+SP, based on the essential hypothesis that IC and the shortest path are two relatively independent semantic evidences and have approximately equal influences to the semantic similarity metric. The paradigm of IC+SP is to linearly combine the IC-related metric and the shortest path. Meanwhile, a transformation from the semantic similarity of the concepts to that of the words is presented by maximizing every component of IC+SP. 13 improved IC-related metrics based on IC+SP are formed and implemented on the experimental platform HESML Lastra-Díaz (Inf Syst 66:97–118, 2017). Pearson's and Spearman's correlation coefficients on well-accepted benchmarks for the improved metrics compare to those for the original ones to evaluate IC+SP. I introduce the Wilcoxon Signed-Rank Test needing no standard distribution hypothesis, while, this hypothesis is required by T-Test on the sample of small size. T-Test, as well as the Wilcoxon Signed-Rank Test, conduct on the differences of the correlative coefficients for improved and original metrics. It is expected that the improved IC-related metrics could significantly outperform their corresponding original ones, and the experimental results, including the comparisons of mean and maximum of correlation coefficients as well as the p-value and confidence interval of both tests, accomplish the anticipation in the vast majority of cases. [ABSTRACT FROM AUTHOR]

Credit card fraud is a widespread cybercrime that threatens financial security. Effective cybersecurity measures are essential to mitigate these risks. Machine learning has shown promising results in detecting credit card fraud by analyzing transaction data and identifying patterns of suspicious behavior. Feature selection is crucial in machine learning because it simplifies the model, improves its performance, and prevents overfitting. This research introduces a machine learning model designed for credit card fraud detection. The model makes use of three types of correlations. Pearson, Spearman, and Kendall, to identify features and enhance the fraud detection process. Testing on datasets yielded impressive results achieving category accuracies of 99.95% and 99.58% surpassing alternative approaches. Also, the results showed that Kendall correlation is the best among the three types of correlation in selecting attributes in all approved datasets. [ABSTRACT FROM AUTHOR]

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