Search Results (1,709)

This study examines the macroeconomic impacts of major earthquakes in Türkiye using annual data from 1990 to 2023. Despite growing global interest in disaster economics, evidence on how large seismic events shape national economic performance over extended periods remains limited, particularly in emerging economies. Using data from the World Bank, the Central Bank of the Republic of Türkiye, and the Disaster and Emergency Management Authority, the analysis incorporates real gross domestic product, gross fixed capital formation, consumer prices, and export capacity. A dummy variable identifies years with high-fatality earthquakes. After confirming stationarity, Johansen cointegration and a Vector Error Correction Model were applied. Results indicate that earthquakes exert a statistically significant negative influence on long-term economic growth. Based on the log-level specification, the long-run equilibrium level of real gross domestic product in earthquake years is approximately 45 percent lower than in non-earthquake years. Investment, price stability, and trade capacity support long-term growth. Model diagnostics confirm stability, normality, and no autocorrelation. These findings highlight the structural economic vulnerabilities created by major earthquakes and underscore that disaster risk reduction and resilient infrastructure policies must be integral components of sustainable growth strategies. The study contributes updated national time-series evidence from a structurally fragile context. Full article

Unmanned Aerial Vehicles (UAVs) have become essential instruments for precision agriculture and forest monitoring, offering rapid, high-resolution data collection over wide areas. This review synthesizes global advances (2015–2024) in UAV-derived vegetation indices (VIs), combining bibliometric and content analyses of 472 peer-reviewed publications. The study identifies key research trends, dominant indices, and technical progress achieved through RGB, multispectral, hyperspectral, and thermal sensors. Results show an exponential growth of scientific output, led by China, the USA, and Europe, with NDVI, NDRE, and GNDVI remaining the most widely applied indices. New indices such as GSI, RBI, and MVI demonstrate enhanced sensitivity for stress and disease detection in both crops and forests. UAV-based monitoring has proven effective for yield prediction, water-stress evaluation, pest identification, and biomass estimation. Despite significant advances, challenges persist regarding illumination correction, soil background influence, and limited forestry applications. The paper concludes that UAV-derived vegetation indices—when integrated with machine learning and multi-sensor data—represent a transformative approach for the sustainable management of agricultural and forest ecosystems. Full article

Autosomal Dominant Polycystic Kidney Disease (ADPKD) is caused by mutations in PKD1 or PKD2 genes, encoding polycystin-1 (PC1) or polycystin-2 (PC2), respectively, characterized by excessive cell proliferation and fluid secretion, resulting in renal cyst formation and growth. PC1 and PC2 form a complex localized on the plasma membrane, endoplasmic reticulum, and primary cilia. PC2 is a non-selective cation channel which, in renal epithelial cells, contributes to calcium transport and signaling. It has been previously shown in renal cells that high external calcium increases whole-cell currents likely mediated by PC2. In this study, we explored the possibility that the Calcium Sensing Receptor (CaSR) is involved in the functional regulation of PC2. To test this hypothesis, human conditionally immortalized Proximal Tubular Epithelial cells, isolated from urine sediments, wt or with stably downregulated PKD1 (PC1KD) or PKD2 (PC2KD) were used. Interestingly, CaSR and PC2 co-immunoprecipitated and Proximity Ligation Assay demonstrated a direct physical interaction at endogenous protein levels. Membrane potential measurements demonstrated that selective CaSR activation, elicited by the calcimimetic R568, caused plasma membrane depolarization, consistent with the modulation of PC2-mediated cation currents, which was significantly lower in PC2KD with respect to wt and PC1KD cells. To conclude, this study provides evidence for a functional coupling of CaSR and PC2, which might be relevant for therapeutic strategies to correct dysregulations occurring in ADPKD. Full article

This study investigates the impact of Internet of Things (IoT) demand on Digital Economic Growth (DEG) in Saudi Arabia between 2015 and 2023, employing both linear regression and a panel Autoregressive Distributed Lag (ARDL) model. The results show a long-term, significant, and positive association between IoT adoption and DEG, supported by the Technology Organization Environment (TOE) framework, highlighting the relevance of technology readiness and organizational capacity. Moreover, Internet penetration is a significant driver of digital transformation, aligned with the Diffusion of Innovations (DOI) theory, which emphasizes the role of connectivity in facilitating the adoption of digital devices. IoT will have little or no impact in the short term, but in the long run, the benefits are clear. Furthermore, despite the long- and short-term benefits of 5G deployment indicated by the results, a divergence between 5G deployment and electricity consumption is signaled by the significance of the error-correction term, which may be attributed to infrastructure and deployment prerequisites. Additionally, as an extension of the Resource-Based View (RBV) paradigm, the ultimate drivers of DEG through innovation and strategic resources highlight the importance of Research and Development (R&D) investment and Foreign Direct Investment (FDI) in inducing its growth. In contrast, inflation has an adverse impact on DEG, confirming macroeconomic instability as an obstacle to digital advancement, which relates to the environmental pillar of TOE. Policymakers can maximize Saudi Arabia’s digital economic growth on a sustainable, stronger path by investing in IoT infrastructure, increasing internet access and adoption, enhancing R&D and institutional support, and addressing challenges related to macroeconomic stability and 5G deployment. This study adds to the extant research by empirically evaluating the short- and long-term effects of IoT adoption on Saudi Arabia’s digital economic development, thereby providing insights into the roles of innovation, infrastructure, and institutional support in driving digital transformation. Full article

This study examines the patterns of renewable energy consumption across 29 European countries from 2000 to 2024. We utilised Bias-Corrected estimation techniques to analyse the relationship between renewable energy consumption, Human Development Index (HDI), labour force, and population dynamics, employing three distinct estimation models: global, rural, and urban. The results indicate that higher levels of human development and a larger labour force are positively associated with renewable energy consumption in the global and rural models, while the urban model shows an opposite effect for the labour force. Conversely, population growth is negatively related to renewable energy consumption in the global and rural contexts but positively in urban areas. These findings underscore the importance of socio-economic and demographic contexts in shaping renewable energy outcomes. They suggest that renewable energy can support economic and social development, but its effectiveness depends on regional structural conditions. From a policy perspective, the renewable transition should be approached as both an environmental and socio-economic strategy, aligning clean energy goals with employment generation, education, and inclusion, particularly in line with SDGs 7, 8, 10, and 13. Policies that promote green skills, innovation, and equitable regional investment can enhance social acceptance, competitiveness, and sustainable growth across Europe. Full article

Cymbidium faberi Rolfe is a Chinese flower famous due to its beautiful floral pattern and strong floral scent and is also a threatened terrestrial orchid. Moreover, the traditional propagation method through tillers and symbiotic seed germination with the correct fungus under nature conditions could not meet conservation and commercial needs. Here, an efficient procedure for asymbiotic seed germination and in vitro seedlings development of C. faberi was successfully established through evaluation of time of seed collecting, seed pretreatments, light conditions and composition of culture media, respectively. Seed pretreatment with 1% NaClO for 30 min, dark culture on 1/4 MS medium containing 0.5 mg·L⁻¹ 6-BA and 0.1 mg·L⁻¹ NAA for 30 days and subsequent long day condition (14 h light/10 h dark photoperiod) culture on this medium for 30 days could obviously enhance the seed germination rate of C. faberi. The highest germination rate (85.0 ± 0.79%) was achieved when seeds were collected at 120 d after cross-fertilization, and then germination percentages progressively decreased. Furthermore, histological analyses from protocorm formation to seedling growth were explored. This study not only offers a reliable and scalable system for mass propagation to meet commercial and conservation demands but also serves as a foundational reference for physiological and molecular studies in Cymbidium and related orchids. Full article

Background/Objectives: Children receiving chemotherapy are highly susceptible to infection, and bloodstream infection (BSI) is a major cause of morbidity in febrile neutropenia. Post-transfusion fever represents a specific diagnostic dilemma, where febrile non-hemolytic transfusion reactions may be clinically indistinguishable from early BSI. We aimed to develop and internally validate a simple bedside score to predict BSI in children presenting to the ED with post-transfusion fever. Methods: We performed a retrospective, single-center diagnostic prediction study of consecutive ED encounters between 2015 and 2024 in a tertiary children’s hospital. Eligible encounters involved patients ≤ 18 years with an underlying malignancy receiving systemic chemotherapy who presented with fever within 24 h of red blood cell or platelet transfusion, had neutropenia, and with at least one blood culture obtained. BSI was defined as growth of a clinically significant pathogen within 48 h; episodes with only contaminants or colonizing flora were classified as non-BSI. Multivariable logistic regression with four prespecified predictors—transfusion-to-ED arrival interval, body temperature, absolute neutrophil count (ANC), and C-reactive protein (CRP)—was used to develop the model and derive a 0–5 point bedside score. Performance was assessed using AUC, diagnostic indices at prespecified cut-offs, calibration, and bootstrap internal validation. Results: Of 507 screened encounters, 287 met inclusion criteria; 39 (13.6%) were adjudicated as BSI. The full model showed good discrimination (AUC 0.82). The derived score (2 points for ANC = 0/µL; 1 point each for temperature ≥ 38.5 °C, CRP ≥ 2.5 mg/dL, and transfusion-to-ED interval ≥ 7 h) achieved an AUC of 0.84. At a cut-off ≥2, sensitivity was 97.4% and negative predictive value 98.8%, misclassifying 1 of 39 BSIs as low risk; at ≥3, specificity was 59.7% with sensitivity 89.7%. Bootstrap-corrected AUC was 0.83. Conclusions: In children receiving chemotherapy who present with post-transfusion fever, a simple 0–5 point bedside score based on temperature, ANC, CRP, and transfusion-to-ED interval provided useful early stratification of BSI risk in this single-center cohort. Prospective multicenter validation is needed before clinical implementation. Full article

In this paper we investigate the short-run and long-run determinants of the informal economy in Romania using Dynamic General Equilibrium (DGE)-based estimates of informal output as the dependent variable. An ARDL model is used to analyze macroeconomic and institutional variables for Romania during the period of 1995–2023, including inflation (INF), primary net lending/borrowing (NLB), the political stability index (PSI), interest payments (INTPAY), gross domestic product per capita (GDP), and self-employment (SEMP). The findings show that inflation, fiscal balance, political stability, interest payments, and GDP per capita have a short- and long-run impact on informal output. In the long run, a 1% increase in inflation raises informal output by 0.03%, while a 1% rise in GDP per capita reduces it by 0.29%. The error correction term suggests a rapid adjustment speed of 79% toward the long-run equilibrium. These findings suggest that institutional reforms, sustained economic growth, and stable macroeconomic policies play an important role in reducing informality and promoting sustainable economic resilience in Romania. Full article

Background: Bracing is an effective treatment for idiopathic scoliosis (IS), and Adherence is one of the most important factors influencing outcomes. However, evidence on the effectiveness of objective monitoring using thermal sensors in everyday clinical settings remains limited. Objective: To evaluate the impact of Adherence and brace-wearing consistency on short-term outcomes in IS patients during growth in a real clinical setting. Methods: This retrospective cohort study included 114 patients (100 with adolescent idiopathic scoliosis (AIS) and 14 with juvenile idiopathic scoliosis (JIS)) treated with a three-dimensional (3D) rigid brace equipped with a thermal sensor. Adherence was calculated as the ratio of actual to prescribed wear time; consistency was defined using the interquartile range (IQR) of daily wear time (IQR ≤ 1 h = consistent). Cobb angle was measured at baseline, in-brace, and after 6 months. Logistic regression, receiver-operating characteristic (ROC) analysis, and general linear model (GLM) analyses were performed, supported by sensitivity analyses, to assess model robustness. Results: Mean Adherence was 85.3 ± 18.9%; high Adherence was observed in 71.4% of JIS and 57.0% of AIS patients, while 19.3% showed high consistency. In-brace correction averaged 52.5 ± 23.2% (68.1% JIS vs. 50.3% AIS; p = 0.007). At 6 months, 55% improved, 42% were stable, and 3% worsened. Adherence was the only significant predictor of consistency (OR = 1.511; 95% CI 1.181–1.933; p = 0.001). The ROC analysis showed excellent discriminative ability (Area Under the Curve (AUC) = 0.908). Adherence category (p = 0.041) and Risser stage (p = 0.041) were significant predictors of short-term outcome. Conclusions: Adherence and brace-wearing consistency are key predictors of short-term bracing outcomes in IS. Objective monitoring with thermal sensors enables precise tracking, improves patient engagement, and supports individualised treatment. Full article

Leaf area estimation using multispectral imaging in grafted cucumber seedlings is often underestimated due to leaf overlap at later growth stages. This study investigates the use of multispectral imaging technology to estimate leaf area in grafted cucumber seedlings and proposes a method to improve estimation accuracy by introducing “days after grafting” (DAG) as a correction variable. For the experiments, the scion varieties ‘Goodmorning Backdadagi’, ‘NakwonSeongCheongJang’, and ‘Sinsedae’ were grafted onto the same rootstock ‘Heukjong’ (Cucurbita ficifolia), and images were acquired at 7, 14, and 21 days after grafting. The results show that including DAG as a correction variable significantly enhances the accuracy of image-based leaf area estimation, particularly in plug tray units, where R² increased from 0.89 to 0.96 for ‘Goodmorning Backdadagi’, by effectively reducing errors caused by leaf overlap. Across all three varieties and both seasons (spring and summer), models incorporating DAG consistently showed higher accuracy in leaf area estimation than models without DAG. These results suggest that the method’s broad applicability is validated through comparisons across different seasons and varieties. Overall, this study provides a practical and accurate method for correcting leaf area estimation, with strong potential for application, particularly in seedling production and cultivation management. Full article

Escherichia coli (E. coli) pathotypes present in contaminated food, street food, or water are major contributors to foodborne illnesses. Polymerase chain reaction (PCR) methods are widely applied to detect and confirm E. coli pathotypes in food samples, thereby supporting outbreak prevention efforts. The objective of this study was to provide a comprehensive and reliable review of the molecular identification of E. coli isolated from street foods and to examine its public health implications. The review followed the “Preferred Reporting Items for Systematic Reviews and Meta-Analyses” (PRISMA) guidelines and included data retrieved from seven electronic scientific databases covering the period from 1 January 2015, to 15 August 2025. Relevant full-text articles were identified using the search string (“Street food”) AND (Escherichia coli), and only those that met established inclusion and exclusion criteria were selected. A total of 23 studies from Asia, Africa, Europe, and Latin America were included. These studies analyzed a wide range of street foods and beverages. MacConkey Agar and Eosin Methylene Blue Agar were the primary culture media used for the growth and isolation of E. coli. PCR was employed in 50% of the studies to amplify specific DNA segments, enabling the identification of eight E. coli pathotypes: EHEC, ETEC, EAEC (Eagg), EIEC, EPEC, UPEC, DAEC, and APEC. Additionally, a few studies reported phylogroups such as A, B1, B2, C, D, E, and Clade 1. The prevalence of E. coli in street foods varied widely, ranging from 0.5% in Chile to 100% in Mexico. Overall, this systematic review provides an updated scientific overview highlighting persistent challenges in street food safety and E. coli contamination. Across studies, three recurring issues were identified: (1) inadequate and unhygienic vending locations, (2) poor quality of food, and (3) inappropriate food preparation practices. These findings underscore the need for strategic interventions. The evidence presented could support governments and the scientific community in advancing research on E. coli in street foods and implementing corrective measures at local or regional scales, such as educational campaigns for vendors and consumers. Full article

This study investigates the impact of renewable energy, environmental technology, foreign direct investment (FDI), and globalization on green economic growth in South Africa within the framework of the country’s National Development Plan (NDP) Vision 2030, covering the period from 1997 to 2024. Using annual data and applying advanced panel techniques, including the CS-ARDL model supported by AMG and CCEMG estimators, the analysis captures both long-run and short-run dynamics. The quantitative findings indicate that renewable energy exerts a strong positive influence on green economic growth, with long-run and short-run coefficients of 0.318 and 0.142 (both significant at the 1% level). Environmental technology also shows a positive and significant impact, with coefficients of 0.274 in the long run (1% level) and 0.105 in the short run (10% level). FDI contributes positively to green growth, as reflected in the long-run and short-run coefficients of 0.186 (at the 1% level) and 0.083 (at the 10% level). In contrast, globalization exhibits a weak and slightly negative long-run effect, with a coefficient of –0.097 (significant at the 10% level). The significant negative error-correction term confirms a stable long-run adjustment process. These findings imply that renewable energy expansion, technological innovation, and environmentally responsible FDI are crucial pillars of South Africa’s sustainable growth strategy. Based on these results, the study recommends intensifying efforts to promote renewable energy investment, strengthen research and development in environmental technologies, and attract green-oriented FDI through clear regulatory incentives. In addition, trade and globalization policies should be redesigned to ensure ecological balance and compliance with sustainability standards. Overall, the study offers practical policy insights to support South Africa’s transition toward a low-carbon, resilient economy. Full article