Global transition toward sustainable micro-mobility is an essential aspect of Saudi Vision 2030; however, high car dependency remains a significant barrier to public health and safety targets. In this context, this study explores the factors determining the adoption of electric bicycles (e-bikes) in Al-Qunfudhah, Saudi Arabia. The present research used a convenience sampling strategy through an online survey conducted via social media and texting, utilizing a designed questionnaire of 10 sections delivered to 171 participants, alongside a 5-point Likert scale. Additionally, the scientific validation and analysis were conducted utilizing internal consistency, validity and scale reliability via statistical analysis. The findings indicated a significant intention–action disparity; while respondents demonstrate a strong psychological intention to adopt e-bikes within 12 months (an average of 3.51), real household ownership was relatively low at 11.1%. In addition, a significant 71.9% of participants use private vehicles for short-distance travel (<5 km), influenced by an average bus stop distance of 21.22 km. The hierarchy of barriers indicates infrastructure and security as the main barrier, particularly the absence of dedicated bike lanes, and concerns regarding traffic safety. In contrast, a perception of physical fitness, and interpersonal interaction behave as significant facilitators. Public health data reveals an average weekly activity of 109.77 min, significantly lower than worldwide recommendations; however, 66.7% of individuals believe e-bikes may address the difference. The statistical evaluation acknowledged the questionnaire’s robustness, with significant Pearson correlation coefficients (p < 0.01) demonstrating internal consistency validity and Cronbach’s alpha values between 0.71 and 0.88 indicating high scale reliability, demonstrating a scientifically stable framework for assessing the measured behavioral determinants. The research recommends the establishment of shaded, dedicated micro-mobility networks and the enforcement of safety regulations to promote a healthy, multi-modal urban ecosystem.

Background: Body proportions and muscular development are closely linked to force production capacity, yet their application as predictive tools in Olympic weightlifting training and athlete selection remains insufficiently explored. Aims: The study aimed to quantify the relationships between specific relative indexes of body muscularity and maximal force generated during two classic multi-joint resistance exercises – the back squat and the clean and jerk deadlift. Methods: 17 athletes participated in the study, all of whom were national-level competitors. Linear regression equations were estimated between four relative body muscularity parameters (Height/Body mass3 (BMH), Height/Shin circumference (HS), Height/Thigh circumference (HT), Height/Arm circumference (HA), and Height/Chest circumference (HC)) and maximal strength in back squat and clean and jerk deadlift. Results: We calculated statistically significant Pearson correlation coefficients and linear regression coefficients between the studied relative body muscularity parameters and maximal muscle strength in the back squat and deadlift. The adjusted R-squared values ranged from 0.082 to 0.768 across the regression equations. Conclusion: All studied relative parameters were statistically significant predictors of maximal strength in the deadlift and squat, with only 3 exceptions (BMH for the deadlift and BMH and HS for the squat). These results (in conjunction with the high adjusted R-squared values of the regressions) indicate that the constructed statistical models explain a relatively high proportion of the variation in the results. These findings can be used in training practice as guidelines for anthropometric changes to improve sports performance.

The surgical treatment of symptomatic Arnold-Chiari malformation type I (CM-I) typically involves decompression of the posterior cranial fossa. A full-endoscopic approach is emerging as an alternative to traditional microsurgical techniques. However, this method presents challenges in intraoperative assessment of the decompression extent, potentially resulting in inadequate decompression. In neurosurgery, ultrasound is gaining increasing importance, as it avoids ionizing radiation and enables real-time examination. The aim of this anatomical study is to evaluate the suitability of ultrasound for assessing defect size compared to radiography and CT during uniportal full-endoscopic decompression of the posterior fossa. Six fresh-frozen adult human cadavers underwent endoscopic decompression of the posterior fossa. The endoscope used featured an oval shaft with a diameter of 9.3mm, a working length of 177mm, a 20° viewing angle, and an eccentric 5.6mm working channel. Computed tomography (CT), X-rays, and ultrasound images were obtained before and after decompression for measurement purposes. The average endoscopic decompression in the sagittal plane as measured by ultrasound was 26 ± 2mm, with fluoroscopy 27 ± 1mm and using CT 26 ± 1mm. A statistically significant Pearson correlation was found between ultrasound and CT (r = 0.94, p < 0.01); between ultrasound and fluoroscopy (r = 0.9, p < 0.05); and between fluoroscopy and CT (r = 0.8, p < 0.05). The average endoscopic decompression in the axial plane as measured by ultrasound was 37 ± 2mm, with fluoroscopy 26 ± 2mm and using CT 36 ± 1mm. A statistically significant Pearson correlation was found only between ultrasound and CT (r = 0.95, p < 0.01). The full-endoscopic approach enables effective decompression of the posterior fossa in an experimental setup. Intraoperative ultrasound proves reliable in assessing the extent of decompression, showing good correlation with X-rays and CT. This technique holds promise for wider use in CM-I treatment, particularly in pediatric neurosurgery, where ultrasound offers a radiation-free method for intraoperative evaluation of defect size.

Organic soybean seeds are susceptible to colonization by numerous fungal pathogens, which can reduce their germination capacity and nutritional quality. This study evaluated fungi transmitted by seeds and their effects on selected seed quality parameters, as well as the influence of variety, location and growing season. In total, 471 fungal isolates belonging to 24 genera and 37 species were obtained from three soybean varieties (Erica, Es Commandor and Cerez PZO) cultivated at two locations during the 2022-2023 seasons. All obtained isolates were identified based on ITS sequencing, and Fusarium isolates were further characterized to the species level using TEF and RPB2 markers. Fusarium spp. was the most frequently isolated genus, accounting for 35.7% of all isolates, followed by Alternaria spp. (15.9%) and Aspergillus spp. (11.9%). Fungal frequency and species diversity differed significantly between years. Seed germination capacity was significantly lower in 2023 than in 2022 and coincided with higher fungal colonization, lower spring temperatures, and increased rainfall. A significant negative Pearson's correlation (r = -0.58, p < 0.05) was found between fungi abundance and seed oil content, indicating a direct impact of fungal colonization on nutritional quality. These results highlight the role of environmental conditions in seed-borne pathogen communities and the need for monitoring and seed health management to ensure soybean seed quality.

In light of the universality of the Tangping phenomenon and the lack of measurement tools, this study aims to develop Academic Tangping Scale for assessing this phenomenon among for college students in China. A total of 644 valid Chinese university students participated in the research. Exploratory factor analysis supported the extraction of three dimensions, namely affective, cognitive and behavioral dimensions, and confirmatory factor analysis indicated a good model fit, further confirming the scale’s dimensional structure. High Cronbach’s alpha coefficients across the subscales further affirm its robustness as a psychometrically sound measurement instrument. Evidence for convergent and discriminant validity was rigorously substantiated, and significant Pearson correlations with the existing Lying Flat Tendency scale demonstrated criterion-related validity. Finally, the scale’s practical applicability was supported by significant correlations with depression, anxiety, and stress, indicating meaningful associations with students’ mental health outcomes. The scale acknowledges limitations and proposes corresponding suggestions. Overall, the scale demonstrates strong psychometric properties, providing a reliable tool to assess the Academic Tangping and support targeted interventions and research on student mental health.

Access to podiatric care analyzed through the CMS National Downloadable File and US census data.

Prostate cancer features profound transcriptional dysregulation within the androgen receptor (AR) signaling axis. The pioneer factor FOXA1, which facilitates AR binding to chromatin, is recurrently altered in 10-40% of tumors. Recent studies classify FOXA1 mutations as Class 1 Wing 2 mutations, which enhance AR-dependent tumorigenesis, and Class 2 C-terminal truncations, which promote lineage plasticity and therapy resistance. The interplay of FOXA1 alterations with TMPRSS2-ERG fusions and PROX1 remains incompletely understood. Data from The Cancer Genome Atlas (TCGA) Prostate Adenocarcinoma (PRAD) cohort (n=492) were analyzed via UCSC Xena and cBioPortal. FOXA1 mutations were categorized following Eyunni et al. Copy number was assessed by log2(tumor/normal) ratios. Mutual exclusivity and co-occurrence were evaluated using Fisher's exact test with false-discovery-rate correction. Associations between FOXA1 status and genomic instability were assessed using the fraction genome altered (FGA) metric. FOXA1 was broadly expressed, with subsets showing elevation. Class 1 mutations localized to the Wing 2 region, while Class 2 truncations clustered in the C-terminal domain. Copy number changes were infrequent, indicating mutation-driven reprogramming as the main oncogenic mechanism. TMPRSS2 and ERG strongly co-occurred (log2 OR >3, q<0.001), whereas FOXA1 was mutually exclusive with both TMPRSS2 and ERG (q<0.001). Although FOXA1 alterations showed no significant Pearson correlation with FGA (r=-0.01, p=0.76), a moderate Spearman correlation (ρ=0.52, p<0.001) suggested enrichment in genomically unstable tumors. FOXA1 defines a major oncogenic axis in prostate cancer, distinct from TMPRSS2-ERG fusion and PROX1 induction. Class 1 and 2 FOXA1 mutations drive alternative transcriptional programs leading to therapy resistance, highlighting FOXA1 as a critical biomarker and target for chromatin-directed interventions.

Optimal health is important for overall well-being and can significantly reduce the risk of chronic disorders and long-term illnesses. The present study aims to examine the distribution of fat, residual, muscle, and skeletal mass among the Chiru tribe of Manipur and assess how these body compartments can predict hypertension risk factors. The present study included a cohort of 416 Chiru individuals (209 males and 207 females) aged 20-79 years, residing in the hill districts of Manipur and gave informed consent. Blood pressure, 21 anthropometrics, and lifestyle factors data were collected using standardized methods and the questionnaire. Body composition was assessed using a four-compartments model based on Drinkwater and Ross. Significant t-tests, one-way ANOVAs, Chi-square tests, Pearson correlations, and multivariate logistic regression were employed. Predictive cut-off values were determined using the receiver operating characteristic (ROC) curve to enhance accuracy. The findings revealed that female participants had a greater overall fat mass (7.46 ± 2.55 kg) than their male counterparts. Conversely, males exhibited higher levels of residual mass (15.45 ± 2.02 kg), muscle mass (21.44 ± 2.52 kg), skeletal mass (9.94 ± 1.39 kg), as well as elevated systolic (120.90 ± 19.17 mm/Hg) and diastolic blood pressure (77.65 ± 12.15 mm/Hg). Multivariate logistic regression analysis indicated that fat mass (AOR = 1.36, P < 0.001 male) and female gender (AOR = 1.31, P < 0.001 female) were significant risk factors for hypertension across both sexes. ROC curve analysis further indicated that fat mass had the highest effectiveness for predicting hypertension, with Area Under Curve (AUC) values of 0.638 for males and 0.647 for females. The study concluded that fat mass predicts hypertension more precisely than the other three body composition metrics. Conversely, increasing muscle and skeletal mass has been demonstrated to lower hypertension.

This study looks into how artificial intelligence (AI), especially machine learning (ML), might improve workplace satisfaction and employee engagement among mid-level IT professionals in Bangalore. The report examines the strategic uses of AI in digital trust systems, employee profiling, and predictive analytics, based on a structured survey of 434 participants from well-known firms like Infosys, IBM, Wipro, and Accenture. Perceptions were measured on a 5-point Likert scale, and descriptive statistics, correlation, regression, and structural equation modeling (SEM) were employed to evaluate the data. Cronbach's Alpha scores for all constructs in the reliability report above 0.70, indicating good internal consistency. With a statistically significant Pearson correlation of 0.71 (p &lt; 0.001), the results show that machine learning-based engagement tools have a beneficial impact on workplace satisfaction. Today's organizations are leveraging AI technology to identify and attract qualified candidates that meet their regular requirements of experience and competencies. The objective of this type of study will be to provide organizations with a framework to better correlate employee engagement with organizational performance using Structured Modelling. Based on the research conducted on AI's success in addressing significant behavioural and organizational challenges, it has become evident that there is a high level of correlation between the level of employee engagement and the strategic factors that influence such engagement. Thus, this research supports the proposition that AI offers companies an excellent opportunity to develop innovative data-structured strategies for engaging their employees. Furthermore, the implementation of AI technologies within the Human Resources function will create a positive organizational culture, enhance founder morale and foster an overall increase in employee retention rates. Thus, it is vital for organizations to incorporate AI systems in order to create and implement the most appropriate employee engagement model for each of their respective company cultures and missions.

False lumen expansion is a major factor that determines long-term survival of uncomplicated type B aortic dissection (TBAD). The objective of this study was to investigate whether structural wall stress distributions computed from patient-specific acute TBAD geometries can be used to predict aortic growth rates. Three-dimensional (3D) computed tomography angiography (CTA) of 9 patients with acute uncomplicated TBAD was obtained at initial hospital admission and at their most recent follow-up visits. Patient-specific structural wall stress distributions were computed from the initial baseline CTA using a forward penalty method. Spatially varying blood pressure distributions, derived from computational fluid dynamics (CFD) simulations informed by patient-specific brachial blood pressure (BP) measurements, were incorporated into the forward penalty stress analysis. For 5 patients, transthoracic echocardiography (TTE) data were also available and used to prescribe patient-specific inlet flow conditions in the CFD simulations. Aortic growth rates were quantified and visualized within the 3D TBAD geometries using the initial baseline and follow-up scans. Linear mixed-effects regression analyses were performed to evaluate the spatial correlations between biomechanical markers (structural wall stress, wall shear stress, and pressure) and aortic growth rates. Utilizing initial baseline patient-specific CTA and BP data, along with TTE data when available, the forward penalty analyses revealed hemodynamic and structural mechanics insights of acute uncomplicated TBADs. The linear mixed-effects model indicated that the fixed-effect association between acute structural wall stress and estimated aortic growth rate distributions was statistically significant (p = 0.036), which demonstrated that aortic segments experiencing higher structural stress in the acute phase exhibited more rapid growth. Fixed-effect associations were not significant when predicting growth rate using wall shear stress (p = 0.88) or pressure (p = 0.65) distributions computed from the acute TBAD geometry. Significant Pearson correlation coefficients (p < 0.05) were observed between acute structural wall stress and aortic growth rate in all patients. Higher structural wall stress in the acute TBAD geometry was associated with regions of increased aortic growth rates. When modeled as a solid, false lumen thrombus was linked to lower structural wall stress and may have a protective effect against rapid aortic growth. Further studies are needed to investigate the biphasic nature of thrombus. Structural stress, which in this study was derived using the forward penalty approach, may be a novel predictor of aortic growth rate in acute TBAD.

Background: Metformin is the initial pharmacological intervention for managing type 2 diabetes mellitus (T2DM). However, its effectiveness for achieving optimal glycemic control diminishes over time, requiring the addition of other oral antidiabetic drugs (OADs) to the treatment regimen. The widespread adoption of metformin-based fixed-dose combinations (FDCs) in India necessitates an investigation into their impact on affordability and access. This study, therefore, undertook a cost variation analysis of available dual FDCs containing 500 mg of metformin to illuminate these implications. Methods: The cost data were sourced from retail websites. We analyzed cost variation by calculating the cost variation percentage (CV%) and the average cost of all FDCs. The relationship among cost variation, average cost, and the number of manufacturing companies was statistically assessed using Pearson's correlation in Microsoft Excel. Results: Among the 15 FDCs analyzed, the metformin + dapagliflozin combination exhibited the most substantial cost variation, reaching 436.2%. Conversely, the metformin + saxagliptin combination recorded the highest average cost per tablet, at 45.16 rupees (equivalent to 0.52$). A statistically significant negative Pearson's correlation was observed between the average cost of drugs and the number of manufacturing companies across all FDCs (r = −0.595, p = 0.019*) and in the metformin + dipeptidyl peptidase-4 inhibitors (DPP4is) group (r = −0.900, p = 0.037*). Conclusion: In our study, the co-administration of metformin with the newer therapeutic agents (dapagliflozin and saxagliptin) demonstrated the highest variability in pharmaceutical pricing. This finding underscores the necessity for regulatory intervention regarding the costs of these FDCs within the Indian market.

The Diabetes Obstacles Questionnaire-Short Version is a tool for measuring the quality of life in patients with diabetes mellitus. However, the validity and reliability of this tool has never been tested in Indonesia. This study was designed to adapt and validate a Bahasa Indonesia version of the Diabetes Obstacles Questionnaire-Short Version for Indonesians with type 2 diabetes mellitus. This was a cross-sectional study. Data were collected from July to November 2023, and accidental sampling was used to recruit and enroll 1,116 participants. Convergence testing used the Diabetes Quality of Life questionnaire. The validity test used construct and convergent validities with significant Pearson correlations, and construct validity included exploratory factor analysis and confirmatory factor analysis. Reliability testing used Cronbach's alpha, composite reliability, and average variance extracted. The results of the exploratory factor analysis showed nine factors with a factor loading per item of >.45, a Kaiser-Meyer-Olkin test score of .915, and significant Bartlett's test of sphericity results. The Cronbach's alpha value for all items was .930, and those of individual factors ranged from .730 to .848. The test-retest results with interclass correlation coefficients ranged from .910 to .973. The results of the confirmatory factor analysis indicate that this instrument has an acceptable model fit. The Bahasa Indonesia Diabetes Obstacles Questionnaire-Short Version produces valid and reliable results for measuring quality of life in people with type 2 diabetes mellitus in Indonesia. The sufficient but small number of items allows the questionnaire to be completed relatively quickly, making it useful in clinical settings. The subscales in this instrument may be used simultaneously or separately based on individual needs.

An investigative study was conducted to determine the heavy metal contamination in sediments from the Ntsini River in the protected area Akanda National Park to Libreville, Gabon. A total of twelve sediment samples were collected from four locations (Ngwamba, Moka, Pages and Nendé). Sediments were analyzed for the six selected metals: Cd, Cr, Cu, Ni, Pb, and Zn using an Inductively Coupled Plasma-Atomic Emission Spectroscopy (ICP-AES). The high metal concentrations in the sediments were as follows: Zn &gt; Cr &gt; Ni &gt; Pb &gt; Cu &gt; Cd. The highly significant positive Pearson correlations between the elements Cr, Cu, Ni, Pb and Zn indicate a common anthropogenic source of these metal elements. The CF shows an enrichment at all site for the metals Cd, Pb, and Zn. However, the CD indicates an exceptional Nendé station with moderate contamination for Cd. In this work, the results reveal low ecological risks (RI) for the metal Cr, Cu, Pb, Zn, and Ni in all stations, only Cd presents a moderate ecological risk in two stations: Ngwamba and Nendé. Therefore, effective mitigation strategies in response to metal contamination relevant to the Ntsini River in the Akanda National Park in Gabon are required to protect water quality and the health of local communities.

Oral daily probiotic and postbiotic supplementation (ODPPS) is a promising strategy for canine skin and gut health. Despite growing interest, the effects of ODPPS on the composition of the canine gut and skin microbiota remain largely unexplored. The advent of full-length 16S rRNA gene sequencing has opened new avenues in microbiome research, significantly enhancing the accuracy and completeness of microbial community profiling. This study employed PacBio long-read sequencing to profile longitudinal changes in canine fecal microbiota composition during ODPPS. Then, we evaluated the parallel dynamics between fecal and skin microbiota responses to ODPPS, addressing a critical gap in understanding systemic microbiome interactions in dogs. By Day 90, fecal microbiota composition shifted significantly (PERMANOVA p = 0.05), with increased beneficial bacteria by Day 30 and further by Day 90. In both axillae and fecal microbiota, ODPPS supplementation increased the relative abundance of beneficial species including Lactobacillus acidophilus, Lactobacillus johnsonii, and Limosilactobacillus reuteri. A significant positive Pearson correlation was found between the relative abundances of these bacteria in the skin and fecal microbiota (p = 0.05), suggesting a coordinated microbial response across body sites. The results highlight the significance of Lactobacillus acidophilus as a core probiotic strain, demonstrating exceptional capacity for colonisation and establishment in both the gastrointestinal and skin niches of dogs. These findings show the systemic influence of ODPPS in shaping microbial communities across both sites and support its use to promote overall canine health. Collectively, our results offer robust evidence for the dual benefits of daily oral ODPPS on both skin and gut microbiota.

The northeastern region of Nigeria has been experiencing a protracted humanitarian crisis, characterized by conflict, displacement, and a severely disrupted health system. The Early Warning Alert and Response System (EWARS) was implemented in 2016 to strengthen disease surveillance in this challenging context. This study employed a descriptive design to evaluate the performance of EWARS in Borno State, Nigeria, over a five-year period (2016-2021). The data sources included weekly health facility reports and the EWARS alert log. Key performance indicators, including timeliness and completeness of reporting, were analyzed. EWARS coverage expanded significantly, reaching 341 health facilities across 25 local government areas. The timeliness of reporting ranged from 6 to 85%, with a median of 65.5% (95% CI: 59-73%). A statistically significant positive Pearson correlation was observed between timeliness and the duration of implementation (r = 0.45, p < 0.001). Completeness of reporting ranged from 42 to 96%, with a median of 68% (95% CI: 62.0-76.25%) and a weaker but significant positive correlation (r = 0.19, p < 0.001). A total of 13,737 alerts were generated, of which 89.6% were verified within 24hours. However, only 0.1% required an immediate public health response. While systematically recorded data on response activities were limited, verified alerts-particularly for measles and cholera-reportedly triggered vaccination campaigns, case investigations, and WASH interventions. The EWARS system demonstrated significant operational value in strengthening disease surveillance and triggering early warning alerts in the conflict-affected Borno State. Despite not meeting all national performance targets, the system showed improvements over time and supported early detection and verification of potential outbreaks. Its utility as a first-line surveillance tool is evident, though future efforts should prioritize integrating response documentation and event-based surveillance components to strengthen public health impact assessment.

The study was conducted from January to November, 2022 at G.B. Pant University of Agriculture and Technology, Pantnagar, with the objective of ranking sires based on first lactation traits. The breeding values of 66 crossbred sires were evaluated for age at first calving, first lactation length, and first lactation milk yield using Best Linear Unbiased Prediction, Least Squares Method, and Restricted Maximum Likelihood methods. The average breeding values for age at first calving were 1153.41 days (Best Linear Unbiased Prediction), 1152.25 days (Least Squares Method), and 1153.93 days (Restricted Maximum Likelihood); for first lactation length, 340.51 days (Best Linear Unbiased Prediction), 353.24 days (Least Squares Method), and 354.04 days (Restricted Maximum Likelihood); and for first lactation milk yield, 3348.81 kg (Best Linear Unbiased Prediction), 3602.34 kg (Least Squares Method), and 3612.37 kg (Restricted Maximum Likelihood). Significant and highest Spearman's rank and Pearson correlation coefficients were observed between LSM and REML for the first lactation length and milk yield, indicating that these methods were highly correlated and equally accurate for ranking sires. Sire no. 15 showed consistently high breeding values for age at first calving across all methods, securing the top rank for this trait. For the first lactation length, sire no. 23 ranked first with BLUP, while sire no. 59 led in LSM and REML. Different sires topped the rankings for first lactation milk yield in each method. Overall, 4–5% of top-ranked sires maintained similar ranks across evaluation methods, providing insights into sire performance.

This study aims to develop a Problem-Based Learning (PBL)-based textbook to enhance students' understanding in the Financial Statement Analysis course. The research employed a quantitative approach using the ADDIE model (Analysis, Design, Development, Implementation, Evaluation). The validity, practicality, and effectiveness of the teaching materials were evaluated through statistical tests using questionnaires and learning outcome tests. The results indicate that the developed PBL-based textbook has high validity, with significant Pearson correlation values across all validity indicators. The practicality of the textbook was rated as adequate by students, although certain aspects require improvement. The effectiveness of the textbook is evident from the significant improvement in students' learning outcomes, demonstrating that the PBL-based approach enhances analytical and critical thinking skills. This study concludes that the PBL-based teaching material is effective and relevant for use in Financial Statement Analysis courses, while also supporting the development of skills applicable to the professional world.

The Fukushima Lumbar Spinal Stenosis Scale (FLS-25) is a disease-specific patient-reported outcome measure developed to assess the symptoms and functional impact of lumbar spinal stenosis (LSS). However, no Korean version of the FLS-25 has been validated to date. This study aimed to assess the reliability, validity, and responsiveness of a Korean adaptation of the FLS-25 (K-FLS-25) using a structured cross-cultural adaptation process. The original FLS-25 questionnaire was translated into Korean following established guidelines for cross-cultural adaptation, including forward translation, synthesis, back-translation, expert committee review, and pretesting. The finalized Korean version (K-FLS-25) was initially administered to 140 consecutive patients diagnosed with LSS. Of these, 123 patients completed both the baseline and follow-up assessments and were included in the final analysis. To evaluate construct validity, participants also completed the validated Korean version of the Oswestry Disability Index (ODI) and a Visual Analog Scale (VAS) for back and leg pain. Reliability was assessed through item-wise agreement using kappa statistics, test-retest reliability via the intraclass correlation coefficient (ICC [2,1]), and internal consistency using Cronbach's α. Construct validity was evaluated by calculating Pearson's correlation coefficients between K-FLS-25, ODI, and VAS scores. All items of the K-FLS-25 demonstrated substantial agreement, with kappa values exceeding 0.6. The test-retest reliability was excellent (ICC [2,1] = 0.93), and internal consistency was high (Cronbach's α = 0.901). Construct validity was supported by significant Pearson's correlation coefficients between the total and domain scores of K-FLS-25 and the scores of the ODI and VAS for both back and leg pain. As part of cultural adaptation, a prefinal version was tested in 30 Korean-speaking LSS patients, who reported good comprehension without major issues. The final version was confirmed by expert consensus. The K-FLS-25 was successfully translated and culturally adapted for Korean-speaking patients. It demonstrated excellent reliability, validity, and responsiveness, supporting its suitability as a disease-specific instrument for evaluating symptoms, functional disability, and treatment-related changes in patients with lumbar spinal stenosis in Korea.

The present study attempts to associate anthropometric markers and blood pressure, thereby determining the most effective predictive marker for hypertension. A total sample of 350 adults aged 20 to 70 years was included in the study after getting consent. Anthropometric data and blood pressure were collected using standard procedures. Significant t-tests, chi-square tests, one-way ANOVA and Pearson correlation analyses were performed between the anthropometric body adiposity measures and blood pressure. The adjusted odds ratio (AOR) was calculated to assess the risk of hypertension. The receiver operating characteristic (ROC) curve analysis was performed to find the anthropometric markers predictive cut-off values. The prevalence of hypertension was 23.4% in males and 22.3% in females, respectively. The nutritional status of overweight and obese individuals was greater in females (38.9% and 13.1%) compared to males (37.1% and 8.6%). Anthropometric indicators, including BMI, WC, WHR, and WHtR, strongly correlate with elevated blood pressure in both sexes. The ROC analysis shows WHtR has the highest area under curve (AUC) value of 0.669 in males, whereas BMI has an AUC of 0.804 in females, indicating it is a more effective predictor for high blood pressure. A multivariate logistic regression analysis showed that age (6.20; 5.30), anxiety (8.13; 6.69), alcohol use (11.81; 6.64), physical activity (8.32; 9.17), smoking (10.05; 10.44), and salt intake (6.31; 5.40) were all independently associated risk factors of hypertension, irrespective of sex. The study concluded that anthropometric markers such as BMI, WC, WHR, and WHtR could predict hypertension risk among the Phalee Tangkhul. Lifestyle factors such as physical activity, smoking, alcohol consumption, salt intake, age, and anxiety are independent risk factors for high blood pressure.

Interoperability is a critical requirement for effective data exchange and integration across institutional digital repositories. However, many repositories still operate in silos due to inconsistent metadata schemas, incompatible systems, and a lack of standardized communication protocols. This study empirically evaluates the role of Web APIs and Linked Data technologies in fostering interoperability across repositories. A descriptive correlational research design was employed, involving data collection from Egerton University and Moi University in Kenya using questionnaires and interviews. Normality testing indicated suitability for parametric analysis; therefore, Pearson correlation and simple linear regression were used. The findings reveal a moderate positive and statistically significant Pearson correlation (r = 0.340, p = 0.040) between Web API &amp; Linked Data and data interoperability. Regression analysis further showed that Web API and Linked Data account for 11.6% of the variance in interoperability (R² = 0.116, p = 0.004), with a regression coefficient of B = 0.450. These results indicate that as institutions enhance their implementation of Web APIs and Linked Data technologies, their capacity for interoperable data exchange significantly improves. The study concludes that institutions implementing RESTful APIs and Linked Data standards such as RDF and SPARQL experience improved semantic alignment and system integration. It recommends phased technological adoption, strategic policy reforms, and targeted capacity-building initiatives to promote repository interoperability in academic institutions.