Search Results (2,418)

The study investigates the contribution of technology (TECH), quantified by Internet penetration, in influencing tourism performance (TP) among the top ten touristic nations in Europe: France, Spain, Italy, Turkey, the United Kingdom, Germany, Greece, Austria, Portugal, and the Netherlands. Using panel data from 2000–2022, the study includes additional structural controls like environment quality, gross domestic production (GDP) per capita, exchange rate (ER), and safety index (SI). The Method of Moments Quantile Regression (MMQR) is employed to capture heterogeneous effects at different levels of TP, and Driscoll–Kraay standard error (DKSE) correction is employed to make the analysis robust against autocorrelation as well as cross-sectional dependence. Spectral–Granger causality tests are also conducted to check short- and long-run dynamics in the relationships. Empirical results are that TECH and SI are important in TP at all quantiles, but with stronger effects for lower-performing countries. Environmental quality (EQ) and GDP per capita (GDPPC) exert increasing impacts at upper quantiles, suggesting their importance in sustaining high-level tourism economies. ER effects are limited and primarily short-term. The findings highlight the need for integrated digital, environmental, and economic policies to achieve sustainable tourism development. The paper contributes to tourism research by providing a comprehensive, frequency-sensitive, and distributional analysis of macroeconomic determinants of tourism in highly developed European tourist destinations. Full article

Background: While epicardial adipose tissue (EAT) is a known predictor of adverse cardiovascular outcomes, lipomatous hypertrophy of the interatrial septum (LHIS) is composed of metabolically active fat such as brown adipose tissue, which may exert a different effect. This study investigates the coronary atherosclerosis profile in patients with LHIS using CTA, compared with a propensity score-matched control group. Methods: A total of 142 patients were included (n = 71 with LHIS and n = 71 controls) and propensity score-matched for age, gender, BMI, and the major CV risk factors (matching level, <0.05). CTA imaging parameters included HRP, coronary stenosis severity (CADRADS), and CAC score. Results: The mean age was 60.9 years +/− 10.6, there were nine (6.3%) women, and the mean BMI is 28.04 kg/m² +/− 4.99. HRP prevalence was significantly lower in LHIS patients vs. controls (21.1% vs. 40.8%; p < 0.011), while CAC (p = 0.827) and CADRADS (p = 0.329) were not different, and there was no difference in the obstructive disease rate. There was no difference in lipid panels (cholesterol, LDL, HDL, TG) and statin intake rate. Conclusions: HRP prevalence is lower in patients with LHIS than controls, while coronary stenosis severity and CAC score are not different. Clinical relevance: LHIS may serve as imaging biomarker for reversed CV risk. Full article

Evaluating the renewable energy potential, such as that of solar photovoltaics (PV), is important for developing renewable energy policies. This study investigated rooftop solar PV potential in Thailand based on open-source geographic information system (GIS) building footprints, solar PV power output, and the most recent land use data (2022). GIS-based overlay analysis, buffering, fishnet modeling, and spatial join operations were applied to assess rooftop availability across various building types, taking into account PV module installation parameters and optimal panel orientation. Economic feasibility and sensitivity analyses were conducted using standard economic metrics, including net present value (NPV), internal rate of return (IRR), payback period, and benefit–cost ratio (BCR). The findings showed a total rooftop solar PV power generation potential of 50.32 TWh/year, equivalent to 25.5% of Thailand’s total electricity demand in 2022. The Central region contributed the highest potential (19.59 TWh/year, 38.94%), followed by the Northeastern (10.49 TWh/year, 20.84%), Eastern (8.16 TWh/year, 16.22%), Northern (8.09 TWh/year, 16.09%), and Southern regions (3.99 TWh/year, 7.92%). Both commercial and industrial sectors reflect the financial viability of rooftop PV installations and significantly contribute to the overall energy output. These results demonstrate the importance of incorporating rooftop solar PV in renewable energy policy development in regions with similar data infrastructure, particularly the availability of detailed and standardized land use data for building type classification. Full article

Gastric-type cervical adenocarcinoma (GCA) is a rare and aggressive subtype of cervical adenocarcinoma. Despite its clinical significance, its molecular carcinogenesis and therapeutic targets remain poorly understood. This study aimed to compare the clinicopathological, immunohistochemical, and molecular profiles of GCA and usual-type cervical adenocarcinoma (UCA), exploring prognostic and therapeutic biomarkers in a Japanese population. A total of 110 cervical adenocarcinoma cases, including 16 GCA and 94 UCA cases, were retrospectively analyzed for clinicopathological features, and a panel of immunohistochemical markers was assessed. Sanger sequences were performed for the KRAS, PIK3CA, and BRAF genes, and survival and clinicopathological correlations were assessed using Kaplan–Meier and Cox regression analyses. GCA was significantly associated with more aggressive features than UCA, including lymph node involvement, advanced FIGO stages, increasing recurrence rate, and poor survival status. High ARID1B expression was observed in a subset of GCA cases and correlated with worse progression-free and overall survival. Additionally, PD-L1 expression was more frequent in GCA than UCA and was associated with unfavorable prognostic factors. Conversely, UCA cases showed strong p16 expression, supporting their HPV-driven pathogenesis. Molecular profiling revealed KRAS and PIK3CA mutations in both subtypes, while BRAF mutations were identified exclusively in GCA. These findings reveal distinct clinical and molecular profiles for both tumor types and underscore ARID1B and PD-L1 as predictive prognostic and therapeutic biomarkers in GCA, implicating the use of subtype-specific treatment strategies. Full article

Background/Objectives: Conventional blood collection can be challenging in a non-clinical or home-based setting. In response, vacuum-assisted lancing devices for capillary blood collection (typically from the upper arm) have gained popularity to broaden access to diagnostic testing. However, these devices are often costly relative to the reimbursement rate for common laboratory testing panels. This study describes the design and evaluation of Comfort Draw™, a simplified and economical vacuum-assisted capillary blood collection device. Methods: Comfort Draw™ was evaluated by 12 participants in a preliminary study and by 42 participants in a follow-up study. Metrics assessed included the following: vacuum pressure of the device, skin temperature generated by the Comfort Draw prep warmer, blood collection volume, and analytical accuracy (for 19 common serum-based analytes). Results: Acceptable blood volume (>400 µL) and serum volume (>100 µL) were collected by Comfort Draw in 85.5% and 95.1% of cases, respectively. Seventeen of the nineteen analytes examined were within CLIA acceptance limits compared to matched venous samples. Self-reported pain scores associated with Comfort Draw collection averaged 0.39 on a scale from 0 to 10. Conclusions: In this preliminary clinical study, Comfort Draw was found to be a valid and relatively painless method for collecting capillary blood specimens. The device’s simple design and lower cost could enable broader applications compared to more complex alternative capillary blood collection devices. Full article

In recent years, recovering precious and base metals such as silver and copper from end-of-life products has become a fundamental factor in the sustainable development of many countries. This not only supports environmental goals but is also a profitable economic activity. Therefore, in this study, we investigate the recovery of silver and copper from an end-of-life photovoltaic panel powder using an alternative leaching system containing sulfuric acid and ferric sulfate instead of nitric acid-based leaching systems, which are susceptible to producing hazardous gases such as NO_x. To obtain this goal, a series of experiments were designed with the Central Composite Design (CCD) approach using Response Surface Methodology (RSM) to evaluate the effect of reagent concentrations on the leaching rate. The leaching results showed that high recovery rates of silver (>85%) and copper (>96%) were achieved at room temperature using a solution containing only 0.2 M sulfuric acid and 0.15 M ferric sulfate. Analysis of variance was applied to the leaching data for silver and copper recovery, resulting in two statistical models that predict the leaching efficiency based on reagent concentrations. Results indicate that the models are statistically significant due to their high R² (0.9988 and 0.9911 for Ag and Cu, respectively) and the low p-value of 0.0043 and 0.0003 for Ag and Cu, respectively. The models were optimized to maximize the dissolution of silver and copper using Design Expert software. Full article

Background and Objectives: this pilot study aimed to evaluate the diagnostic accuracy of ChatGPT-4o in analyzing oral mucosal lesions from clinical images. Materials and Methods: a total of 110 clinical images, including 100 pathological lesions and 10 healthy mucosal images, were retrieved from Google Images and analyzed by ChatGPT-4o using a standardized prompt. An expert panel of five clinicians established a reference diagnosis, categorizing lesions as benign or malignant. The AI-generated diagnoses were classified as correct or incorrect and further categorized as plausible or not plausible. The accuracy, sensitivity, specificity, and agreement with the expert panel were analyzed. The Artificial Intelligence Performance Instrument (AIPI) was used to assess the quality of AI-generated recommendations. Results: ChatGPT-4o correctly diagnosed 85% of cases. Among the 15 incorrect diagnoses, 10 were deemed plausible by the expert panel. The AI misclassified three malignant lesions as benign but did not categorize any benign lesions as malignant. Sensitivity and specificity were 91.7% and 100%, respectively. The AIPI score averaged 17.6 ± 1.73, indicating strong diagnostic reasoning. The McNemar test showed no significant differences between AI and expert diagnoses (p = 0.084). Conclusions: In this proof-of-concept pilot study, ChatGPT-4o demonstrated high diagnostic accuracy and strong descriptive capabilities in oral mucosal lesion analysis. A residual 8.3% false-negative rate for malignant lesions underscores the need for specialist oversight; however, the model shows promise as an AI-powered triage aid in settings with limited access to specialized care. Full article

Enhancing market integration levels is crucial for advancing sustainable regional collaborative development and achieving ecological protection and high-quality development goals within the Yellow River Basin, fostering a balance between economic efficiency, social equity, and environmental resilience. This study analyzed the retail price data of goods from prefecture-level cities in the Yellow River Basin from 2010 to 2022, employing the relative price method to measure the market integration index. Additionally, it examined the temporal and spatial evolution patterns and driving factors using the Dagum Gini coefficient and panel regression models. The results indicate the following. (1) The market integration index of the Yellow River Basin shows a fluctuating upward trend, with an average annual growth rate of 9.8%. The spatial pattern generally reflects a situation where the east is relatively high and the west is relatively low, as well as the south being higher than the north. (2) Regional disparities are gradually diminishing, with the overall Gini coefficient decreasing from 0.153 to 0.104. However, internal differences within the downstream and midstream areas have become prominent, and contribution rate analysis reveals that super-variable density has replaced between-group disparities as the primary source. (3) Upgrading the industrial structure and enhancing the level of economic development are the core driving forces, while financial support and digital infrastructure significantly accelerate the integration process. Conversely, the level of openness exhibits a phase-specific negative impact. We propose policy emphasizing the need to strengthen development in the upper reach of the Yellow River Basin, further improve interregional collaborative innovation mechanisms, and enhance cross-regional coordination among multicenter network nodes. Full article

In this study, whole grain sorghum flour was used to partially substitute the gluten-free flour blend in cookie formulation at 20% (C20) and 40% (C40) replacement levels. The goal was to explore its potential to improve the nutritional value and sensory appeal of cookies relative to conventional and commercially available gluten-free alternatives. Nutritional analysis revealed that cookies with added sorghum flour showed increased levels of protein, ash, and polyphenolic compounds, while maintaining favorable macronutrient profiles. Notably, several bioactive compounds, such as gallic acid, caffeic acid, and apigenin, were detected exclusively in sorghum-containing samples, suggesting enhanced functional properties. Despite these compositional changes, textural measurements showed no significant differences in hardness or fracturability compared with the control. Sensory profiling using the Rate-All-That-Apply (RATA) method demonstrated that both samples (C20 and C40) achieved balanced results in terms of aroma as well as texture and were generally well accepted by the panel. The results indicate that moderate inclusion of sorghum flour (20% and 40%) can improve the sensory and nutritional profiles of gluten-free cookies without compromising product acceptability. Sorghum thus offers a promising pathway for the development of high-quality, health-oriented, gluten-free bakery products. Full article

Accurate estimation of available rooftop areas for PV power generation at the city scale is critical for sustainable energy planning and policy development. In this study, using publicly available high-resolution satellite imagery, rooftop solar energy potential in urban, rural, and industrial areas is estimated using deep learning models. In order to identify roof areas, high-resolution open-source images were manually labeled, and the training dataset was trained with DeepLabv3+ architecture. The developed model performed roof area detection with high accuracy. Model outputs are integrated with a user-friendly interface for economic analysis such as cost, profitability, and amortization period. This interface automatically detects roof regions in the bird’s-eye -view images uploaded by users, calculates the total roof area, and classifies according to the potential of the area. The system, which is applied in 81 provinces of Turkey, provides sustainable energy projections such as PV installed capacity, installation cost, annual energy production, energy sales revenue, and amortization period depending on the panel type and region selection. This integrated system consists of a deep learning model that can extract the rooftop area with high accuracy and a user interface that automatically calculates all parameters related to PV installation for energy users. The results show that the DeepLabv3+ architecture and the Adam optimization algorithm provide superior performance in roof area estimation with accuracy between 67.21% and 99.27% and loss rates between 0.6% and 0.025%. Tests on 100 different regions yielded a maximum roof estimation accuracy IoU of 84.84% and an average of 77.11%. In the economic analysis, the amortization period reaches the lowest value of 4.5 years in high-density roof regions where polycrystalline panels are used, while this period increases up to 7.8 years for thin-film panels. In conclusion, this study presents an interactive user interface integrated with a deep learning model capable of high-accuracy rooftop area detection, enabling the assessment of sustainable PV energy potential at the city scale and easy economic analysis. This approach is a valuable tool for planning and decision support systems in the integration of renewable energy sources. Full article

To meet the European Green Deal targets, the construction sector must improve building thermal performance via advanced insulation systems. Eco-friendly sandwich panels offer a promising solution. Therefore, this work aims to develop and validate a new eco-friendly composite sandwich panel (basalt fibres and recycled extruded polystyrene) with enhanced multifunctionality for lightweight and energy-efficient building façades. Two panels were produced via vacuum infusion—a reference panel and a multifunctional panel incorporating phase change materials (PCMs) and silica aerogels (AGs). Their performance was evaluated through lab-based thermal and acoustic tests, numerical simulations, and on-site monitoring in a living laboratory. The test results from all methods were consistent. The PCM-AG panel showed 16% lower periodic thermal transmittance (0.16 W/(m²K) vs. 0.19 W/(m²K)) and a 92% longer time shift (4.26 h vs. 2.22 h), indicating improved thermal inertia. It also achieved a single-number sound insulation rating of 38 dB. These findings confirm the panel’s potential to reduce operational energy demand and support long-term climate goals. Full article

Background/Objectives: Genetic testing is important for diagnosing inherited retinal diseases (IRDs), but further evidence is needed on the utility of singleton genetic testing in an Australian cohort. Methods: A consecutive series of individuals with clinically diagnosed IRDs without prior genetic testing underwent commercial panel-based sequencing (Invitae or Blueprint Genetics), clinical assessment, and multimodal imaging. Retinal images were graded using the Human Phenotype Ontology terms. Binary logistic regression was used to evaluate clinical predictors of a positive molecular diagnosis. Results: Among 140 participants (mean age 49 ± 19 years), genetic testing was undertaken, on average, 23 ± 17 years after the initial clinical IRD diagnosis. Of the 60% who received a probable molecular diagnosis, 40% require further phase testing, highlighting the limitations of singleton genetic testing. USH2A, ABCA4, and RPGR were the most common encountered genes; 67% of the probably solved participants had causative genes with targeted experimental treatments in ongoing human clinical trials. Symptom onset before the age of 30 (OR = 3.06 [95% CI: 1.34–7.18]) and a positive IRD family history (OR = 2.87 [95% CI: 1.27–6.78]) were each associated with higher odds of receiving a molecular diagnosis. Diagnostic rates were comparable across retinal imaging phenotypes (atrophy and autofluorescence patterns in widespread IRD, and the extent of dystrophy in macular IRDs). Conclusions: In an Australian IRD population without prior genetic testing, commercial panels yielded higher diagnostic rates in individuals with IRD onset before the age of 30 and those with an IRD family history. Further research is needed to understand the genetic basis of IRDs, especially isolated and late-onset cases, to improve diagnosis and access to emerging therapies. Full article

Highway accessibility plays a vital role in supporting local economic development, particularly in regions lacking access to sea or river ports. Recognizing the functional transformation of road infrastructure, the Chinese government has made substantial investments in its expansion. Nevertheless, a theoretical gap remains in justifying whether such investments yield significant economic returns. Drawing on the theory of economic externalities, this study investigates the causal relationship between highway development and regional economic growth, and assesses whether highway construction leads to an acceleration in growth rates. Utilizing panel data from 14 Chinese cities spanning 2000 to 2014, the synthetic control method (SCM) is employed to evaluate the economic externalities of highway investment. The results indicate a positive impact on surrounding industries. Furthermore, a growth rate forecasting analysis based on Back-Propagation Neural Networks (BPNNs) is conducted using industrial enterprise data from 2005 to 2014. The growth rate in the treated city is 1.144%, which is close to the real number 1.117%, higher than the number for the weighted control group, which is 1.000%. The findings suggest that the growth rate of total industrial output improved significantly, confirming the existence of positive spillover effects. This not only enriches the empirical literature on transport infrastructure but also provides targeted enlightenment for the sustainable development of urban economy in terms of policy guidance. Full article

Demands for companies to comply with environmental, social, and governance (ESG) requirements are growing, and companies are also expected to play a role in promoting sustainable development. For companies to achieve sustainable growth while addressing ESG, it must be understood whether ESG activities promote improved corporate financial performance. We conducted a five-year panel data analysis of 635 Japanese firms from FY 2019 to FY 2023, using the PBR, PER, and ROE financial indicators as the dependent variables and CSR ratings in the human resource utilization (HR), environment (E), governance (G), and social (S) categories as the independent variables. The results revealed that, depending on the combination of ESG field and financial indicators, companies with advanced ESG initiatives had greater financial performance, with some cases showing a nonlinear relationship; differences in the results between manufacturing and nonmanufacturing industries were also observed. For companies to effectively advance ESG activities, it is important to clarify the objectives and results for each ESG category. For policymakers to consider measures to encourage companies’ ESG activities, it is also important to design finely tuned regulations and incentives according to the ESG category and industry characteristics. Full article

Background/objective: Tailoring involves adapting research findings and evidence to suit specific contexts and audiences. This study examines how international stroke guidelines can be tailored to address gait issues after a stroke. Methods: A three-phase consensus method approach was used. A 10-member health experts panel extracted recommendations from three national clinical guidelines in the first phase. In the second phase, 362 physiotherapists completed an online questionnaire to assess the feasibility of adopting the extracted recommendations. In the third phase, a 15-physical therapist consensus workshop was convened to clarify factors that might affect the tailoring process of the extracted recommendations of gait disorder rehabilitation. Results: In phase one, 21 recommendations reached consensus. In the second phase, 362 stroke physiotherapists rated the applicability of these recommendations: 14 rated high, 7 rated low, and none were rejected. The third phase, a nominal group meeting (NGM), explored four themes related to tailoring. The first theme, “organizational factors”, includes elements such as clinical setting, culture, and regulations. The second theme, “individual clinician factors”, assesses aspects like clinical experience, expertise, abilities, knowledge, and attitudes toward tailoring. The third theme, “patient factors”, addresses issues related to multimorbidity, comorbidities, patient engagement, and shared decision-making. The final theme, “other factors”, examines the impact of research design on tailoring. Conclusions: Tailoring international clinical guidelines involves multiple factors. This situation brings home the importance of a systematic strategy for tailoring that incorporates various assessment criteria to enhance the use of clinical evidence. Future research should investigate additional implementation theories to enhance the translation of evidence into practice. Full article