Search Results (2,343)

The siphon effect between airports has amplified the polarization in passenger throughput, undermining the balanced development and sustainability of airport clusters. The airport siphon effect occurs when one airport attracts a disproportionate share of passengers, concentrating traffic at the expense of others, which affects the overall resilience of the entire airport cluster. To address this issue, this study proposes a siphon index, expands the range of ground transportation options for passengers, and establishes a zero-siphon model to assess the impact of siphoning on the resiliency of airport clusters. Using this framework, four major airport clusters in China were selected as research subjects, with regional aviation accessibility serving as a measure of resilience. The results showed that among the four airport clusters, the siphon effect is most pronounced in the Guangzhou region. To explore the implications of this effect further, three airport disruption scenarios were simulated to assess the resilience of the Pearl River Delta airport cluster. The results indicated that the intensity and timing of disruptive events significantly affect airport cluster resilience, with hub airports being particularly sensitive. This study analyzes the risks associated with excessive route concentration, providing policymakers with critical insights to enhance the sustainability, equity, and resilience of airport clusters. The proposed strategies facilitate coordinated infrastructure development, optimized air–ground intermodal connectivity, and risk mitigation. These measures contribute to building more sustainable and adaptive aviation networks in rapidly urbanizing regions. Full article

Landslides are among the most hazardous natural phenomena affecting Greater Abidjan, causing significant economic and social damage. Strategic planning supported by geographic information systems (GIS) can help mitigate potential losses and enhance disaster resilience. This study evaluates landslide susceptibility using logistic regression and frequency ratio models. The analysis is based on a dataset comprising 54 mapped landslide scarps collected from June 2015 to July 2023, along with 16 thematic predictor variables, including altitude, slope, aspect, profile curvature, plan curvature, drainage area, distance to the drainage network, normalized difference vegetation index (NDVI), and an urban-related layer. A high-resolution (5-m) digital elevation model (DEM), derived from multiple data sources, supports the spatial analysis. The landslide inventory was randomly divided into two subsets: 80% for model calibration and 20% for validation. After optimization and statistical testing, the selected thematic layers were integrated to produce a susceptibility map. The results indicate that 6.3% (0.7 km²) of the study area is classified as very highly susceptible. The proportion of the sample (61.2%) in this class had a frequency ratio estimated to be 20.2. Among the predictive indicators, altitude, slope, SE, S, NW, and NDVI were found to have a positive impact on landslide occurrence. Model performance was assessed using the area under the receiver operating characteristic curve (AUC), demonstrating strong predictive capability. These findings can support informed land-use planning and risk reduction strategies in urban areas. Furthermore, the prediction model should be communicated to and understood by local authorities to facilitate disaster management. The cost function was adopted as a novel approach to delineate hazardous zones. Considering the landslide inventory period, the increasing hazard due to climate change, and the intensification of human activities, a reasoned choice of sample size was made. This informed decision enabled the production of an updated prediction map. Optimal thresholds were then derived to classify areas into high- and low-susceptibility categories. The prediction map will be useful to planners in helping them make decisions and implement protective measures. Full article

This study evaluates the impact of digital systems and IT audit frameworks on tax performance and integrity within tax administrations. Using international data from organizations like the World Bank, OECD (Organisation for Economic Co-operation and Development), and IMF (International Monetary Fund), the research examines the relationship between tax revenue as a percentage of GDP, digital infrastructure, corruption perception, e-government development, and cybersecurity readiness. Quantitative analysis, including correlation, regression, and clustering methods, reveals a strong positive relationship between digital maturity, e-governance, and tax performance. Countries with advanced digital governance systems and robust IT audit frameworks, such as COBIT, tend to show higher tax revenues and lower corruption levels. The study finds that e-government development and anti-corruption measures explain over 40% of the variance in tax performance. Cluster analysis distinguishes between digitally advanced, high-compliance countries and those lagging in IT adoption. The findings suggest that digital transformation strengthens fiscal integrity by automating compliance and reducing human contact, which in turn mitigates bribery risks and enhances fraud detection. The study highlights the need for adopting international best practices to guide the digitalization of tax administrations, improving efficiency, transparency, and trust in public finance. Full article

Forestry carbon sinks play a crucial role in mitigating climate change and protecting ecosystems, significantly contributing to the development of carbon trading systems. Remote sensing technology has become increasingly important for monitoring carbon sinks, as it allows for precise measurement of carbon storage and ecological changes, which are vital for forecasting carbon prices. Carbon prices fluctuate due to the interaction of various factors, exhibiting non-stationary characteristics and inherent uncertainties, making accurate predictions particularly challenging. To address these complexities, this study proposes a method for predicting carbon trading prices influenced by multiple factors. We introduce a Decomposition (DECOMP) module that separates carbon price data and its influencing factors into trend and cyclical components. To manage non-stationarity, we propose the KAN with Multi-Domain Diffusion (KAN-MD) module, which efficiently extracts relevant features. Furthermore, a Wave-MH attention module, based on wavelet transformation, is introduced to minimize interference from uncertainties, thereby enhancing the robustness of the model. Empirical research using data from the Hubei carbon trading market demonstrates that our model achieves superior predictive accuracy and resilience to fluctuations compared to other benchmark methods, with an MSE of 0.204% and an MAE of 0.0277. These results provide reliable support for pricing carbon financial derivatives and managing associated risks. Full article

Background: Artificial intelligence (AI) and machine learning (ML) have been reshaping maternal, fetal, neonatal, and reproductive healthcare by enhancing risk prediction, diagnostic accuracy, and operational efficiency across the perinatal continuum. However, no comprehensive synthesis has yet been published. Objective: To conduct a scoping review of reviews of AI/ML applications spanning reproductive, prenatal, postpartum, neonatal, and early child-development care. Methods: We searched PubMed, Embase, the Cochrane Library, Web of Science, and Scopus through April 2025. Two reviewers independently screened records, extracted data, and assessed methodological quality using AMSTAR 2 for systematic reviews, ROBIS for bias assessment, SANRA for narrative reviews, and JBI guidance for scoping reviews. Results: Thirty-nine reviews met our inclusion criteria. In preconception and fertility treatment, convolutional neural network-based platforms can identify viable embryos and key sperm parameters with over 90 percent accuracy, and machine-learning models can personalize follicle-stimulating hormone regimens to boost mature oocyte yield while reducing overall medication use. Digital sexual-health chatbots have enhanced patient education, pre-exposure prophylaxis adherence, and safer sexual behaviors, although data-privacy safeguards and bias mitigation remain priorities. During pregnancy, advanced deep-learning models can segment fetal anatomy on ultrasound images with more than 90 percent overlap compared to expert annotations and can detect anomalies with sensitivity exceeding 93 percent. Predictive biometric tools can estimate gestational age within one week with accuracy and fetal weight within approximately 190 g. In the postpartum period, AI-driven decision-support systems and conversational agents can facilitate early screening for depression and can guide follow-up care. Wearable sensors enable remote monitoring of maternal blood pressure and heart rate to support timely clinical intervention. Within neonatal care, the Heart Rate Observation (HeRO) system has reduced mortality among very low-birth-weight infants by roughly 20 percent, and additional AI models can predict neonatal sepsis, retinopathy of prematurity, and necrotizing enterocolitis with area-under-the-curve values above 0.80. From an operational standpoint, automated ultrasound workflows deliver biometric measurements at about 14 milliseconds per frame, and dynamic scheduling in IVF laboratories lowers staff workload and per-cycle costs. Home-monitoring platforms for pregnant women are associated with 7–11 percent reductions in maternal mortality and preeclampsia incidence. Despite these advances, most evidence derives from retrospective, single-center studies with limited external validation. Low-resource settings, especially in Sub-Saharan Africa, remain under-represented, and few AI solutions are fully embedded in electronic health records. Conclusions: AI holds transformative promise for perinatal care but will require prospective multicenter validation, equity-centered design, robust governance, transparent fairness audits, and seamless electronic health record integration to translate these innovations into routine practice and improve maternal and neonatal outcomes. Full article

Objectives: To determine whether plasma concentrations of anandamide (AEA) and 2-arachidonoylglycerol (2-AG) are elevated in adults with prediabetes, we explored their association with tissue advanced glycation end-products (AGEs) and assessed the influence of Mediterranean diet adherence. Methods: This cross-sectional single-centre study included 92 adults with prediabetes and 86 age-/sex-matched normoglycaemic controls. Anthropometry, blood pressure, biochemical indices, and skin autofluorescence-derived AGEs were measured. Serum AEA and 2-AG were quantified by competitive ELISA, while Mediterranean diet adherence was assessed using the Mediterranean Diet Serving Score (MDSS). Results: Prediabetes was associated with higher AEA (p = 0.004) but not 2-AG (p = 0.520). Also, AEA correlated positively with AGE values (r = 0.36; p = 0.002) and increased across AGE-based cardiovascular risk categories. In multivariable models, both prediabetes status and AGE burden independently predicted AEA. Participants achieving MDSS ≥ 14 exhibited lower AEA (p = 0.038); 2-AG remained unaffected. Finally, the multivariable analysis confirmed that both prediabetes (β = 11.9; p = 0.005) and AGE values (β = 0.25; p = 0.003) are positively associated with plasma AEA levels, independent of age, sex, BMI, and fasting plasma glucose levels. Conclusions: Circulating AEA, but not 2-AG, is elevated in prediabetes and independently linked to cumulative AGE burden, suggesting early endocannabinoid activation contributes to cardiometabolic risk. High adherence to a Mediterranean diet may mitigate this dysregulation. Full article

Background/Objectives: Chronic inflammation and Western-style diets elevate colorectal cancer (CRC) risk, particularly in individuals with colitis, a feature of inflammatory bowel disease (IBD). Diets rich in polyphenol-containing functional foods, such as cocoa, may reduce gut inflammation and modulate the gut microbiome. This study investigated the impact of cocoa polyphenol (CP) supplementation on inflammation and microbiome composition in mice with colitis, fed either a healthy or Western diet, before, during, and after the onset of disease. We hypothesized that CPs would attenuate inflammation and promote distinct shifts in the microbiome, especially in the context of a Western diet. Methods: A 2 × 2 factorial design tested the effects of the basal diet (AIN93G vs. total Western diet [TWD]) and CP supplementation (2.6% w/w CocoaVia™ Cardio Health Powder). Inflammation was induced using the AOM/DSS model of colitis. Results: CP supplementation did not reduce the severity of colitis, as measured by disease activity index or histopathology. CPs did not alter gene expression in healthy tissue or suppress the colitis-associated pro-inflammatory transcriptional profile in either of the two diet groups. However, fecal microbiome composition shifted significantly with CPs before colitis induction, with persistent effects on several rare taxa during colitis and recovery. Conclusions: CP supplementation did not mitigate inflammation or mucosal injury at the tissue level, nor did it affect the expression of immune-related genes. While CPs altered microbiome composition, most notably in healthy mice before colitis, these shifts did not correspond to changes in inflammatory signaling. Basal diet remained the primary determinant of inflammation, mucosal damage, and colitis severity in this model. Full article

This research examines the relationship between environmental, social safety and governance risks, and the mitigation strategies of the host country to enhance project performance in the China–Pakistan Economic Corridor (CPEC). The study concludes that the timely and effective completion of CPEC projects is challenged by environmental, social safety, and governance (ESG) risks, including environmental degradation, security threats, and governance issues. Based on the data of 618 respondents from Pakistan and using Structural Equation Modeling (SEM) through SMART PLS 4, the study investigates the impact of sustainable environmental practices, safety and security measures, governance risk mitigation actions, and project management systems on the project performance of CPEC projects. The results show that mitigation efforts implemented by the host country reduce the ESG investment risk and yield a positive effect on the project performance. Hence, this paper will show the importance of proactive measures such as sustainable development practices, security risk management systems, and transparent governance practices in matching challenges and enhancing project benefits. This research reinforces the potential for these risks to be mitigated through the adoption of innovative technologies. Innovation in environments, social protection, and governance frameworks can greatly mitigate the negative impacts of risks, directly improving the outcomes of project delivery. Infrastructure projects are extremely challenging to manage, and this study gives key hints for enhancing project safety and risk management in those types of infrastructure projects for practitioners, policymakers, project managers, and other stakeholders to establish innovative, sustainable strategies. Full article

Global warming and rapid urbanization have increased population exposure to heatwaves, with compound day- and night-time heatwaves (CDNH) posing greater health risks than individual heatwave events. Although air conditioning (AC) adaptation effectively mitigates heat-related impacts, its role in reducing CDNH exposure under climate change remains unknown. Using meteorological and socioeconomic data, this study quantified population exposure to CDNHs and the impacts that could be avoided through AC adaptation across China and its regional variations. Results show that CDNH exposure risks were particularly high in the middle–lower Yangtze–Huaihe Basin and south China, with an increasing trend observed over the period of 2001–2022. AC adaptation has reduced the exposure risk and its upward trend by 5.85% and 37.87%, respectively, with higher mitigating effects in urban areas. By breaking down the total exposure changes into climatic, demographic, and AC-driven changes, this study reveals that increased AC contributes 10.16% to exposure reduction, less than the effect of climate warming (59.80%) on the exposure increases. These findings demonstrate that expanding AC adaptation alone is insufficient to offset climate-driven increases in exposure, highlighting the urgent need for more effective adaptation measures to address climate change and thereby alleviate its adverse impacts on human beings. Full article

As the primary biological risk threatening safe dairy production, bovine mastitis control highly relies on environmental disinfection measures. However, the mechanisms by which chemical disinfectants influence host–environment microbial interactions remain unclear. This study systematically investigated the disinfection efficacy and regulatory effects on microbial community composition and diversity of glutaraldehyde-benzalkonium chloride (BAC) and glutaraldehyde-didecyl dimethyl ammonium bromide (DAB) at recommended concentrations (2–5%), using 80 environmental samples from intensive dairy farms in Xinjiang, China. Combining 16S rDNA sequencing with culturomics, the results showed that BAC achieved a disinfection rate of 99.33%, higher than DAB’s 97.87%, and reduced the environment–gut microbiota similarity index by 23.7% via a cationic bacteriostatic film effect. Microbiome analysis revealed that BAC selectively suppressed Fusobacteriota abundance (15.67% reduction) and promoted Bifidobacterium proliferation (7.42% increase), enhancing intestinal mucosal barrier function through butyrate metabolism. In contrast, DAB induced Actinobacteria enrichment in the environment (44.71%), inhibiting pathogen colonization via bioantagonism. BAC’s long-acting bacteriostatic properties significantly reduced disinfection costs and mastitis incidence. This study first elucidated the mechanism by which quaternary ammonium compound (QAC) disinfectants regulate host health through “environment-gut” microbial interactions, providing a critical theoretical basis for developing precision disinfection protocols integrating “cost reduction-efficiency enhancement-risk mitigation.” Full article

Background: Cerebral aneurysm (CA) is a focal or diffuse pathological dilation of the cerebral arterial wall that arises due to various etiological factors. It represents a serious vascular condition, particularly affecting the elderly, and carries a high risk of rupture and neurological morbidity. Clonidine (CL), an α2-adrenergic receptor agonist, has been reported to suppress aneurysm progression; however, its underlying molecular mechanisms, especially in relation to cerebral endothelial dysfunction, remain unclear. This study aimed to investigate the potential of CL to mitigate CA development by modulating apoptosis, inflammation, and oxidative stress in an Angiotensin II (Ang II)-induced endothelial injury model. Methods: Human brain microvascular endothelial cells (HBMECs) were used to establish an in vitro model of endothelial dysfunction by treating cells with 1 µM Ang II for 48 h. CL was administered 2 h prior to Ang II exposure at concentrations of 0.1, 1, and 10 µM. Cell viability was assessed using the MTT assay. Oxidative stress markers, including reactive oxygen species (ROS) and Nitric Oxide (NO), were measured using 2′,7′–dichlorofluorescin diacetate (DCFDA). Gene expression levels of vascular endothelial growth factor (VEGF), matrix metalloproteinases (MMP-2 and MMP-9), high mobility group box 1 (HMGB1), and nuclear factor kappa B (NF-κB) were quantified using RT-qPCR. Levels of proinflammatory cytokines; tumor necrosis factor-alpha (TNF-α), Interleukin-6 (IL-6), and interferon-gamma (IFN-γ); were measured using commercial ELISA kits. Results: Ang II significantly increased ROS production and reduced NO levels, accompanied by heightened proinflammatory cytokine release and endothelial dysfunction. MTT assay revealed a marked decrease in cell viability following Ang II treatment (34.18%), whereas CL preserved cell viability in a concentration-dependent manner: 44.24% at 0.1 µM, 66.56% at 1 µM, and 81.74% at 10 µM. CL treatment also significantly attenuated ROS generation and inflammatory cytokine levels (p < 0.05). Furthermore, the expression of VEGF, HMGB1, NF-κB, MMP-2, and MMP-9 was significantly downregulated in response to CL. Conclusions: CL exerts a protective effect on endothelial cells by reducing oxidative stress and suppressing proinflammatory signaling pathways in Ang II-induced injury. These results support the potential of CL to mitigate endothelial injury in vitro, though further in vivo studies are required to confirm its translational relevance. Full article

Laizhou Bay, a semi-enclosed bay, is prone to storm surges from cold waves due to its geographic and environmental characteristics. This study uses satellite data, in situ measurements, and the MIKE numerical model to analyze storm surges along Laizhou Bay’s coast under no-dike conditions. It examines the surges caused by cold waves with different intensities and directions. This study provides the storm surge disaster risk levels along Laizhou Bay’s coast. The results show that the maximum sustained wind speed during cold waves is distributed between the NW and NE. The NE wind direction causes the most severe storm surge along Laizhou Bay. Under NE-directed cold waves with level 12 wind, the maximum risk areas for Level III and IV are approximately 1341 km² and 1294 km², respectively. Dongying, Shouguang, and Hanting exhibit large Level I and II risk zones. The maximum seawater intrusion distance along the Kenli coast is about 41 km. The coastal segment from Kenli to Changyi is most severely affected by storm surges. It is recommended to effectively maintain and heighten seawalls along this segment to mitigate storm surge disasters caused by strong NE winds. Full article

Objective: To investigate the effect of an 8-week inspiratory muscle training (IMT) intervention on respiratory muscle strength and cardiovascular autonomic regulation in obese young men. Methods: The study included 36 obese young men who met the inclusion and exclusion criteria. Participants were randomly divided into two groups: the IG (inspiratory muscle training group, n = 17), which underwent high-intensity IMT intervention for 8 weeks, 5 times a week, and the CG (control group, n = 18), which was not given any additional intervention. Assessed parameters included maximum inspiratory pressure (MIP), maximum expiratory pressure (MEP), systolic blood pressure (SBP), diastolic blood pressure (DBP), and heart rate (HR), as well as heart rate variability metrics such as the standard deviation of normal-to-normal intervals (SDNN), root mean square of successive differences (RMSSD), standard deviation of successive differences (SDSD), low-frequency power component (LF), high-frequency power component (HF), and LF/HF ratio. These measurements were taken both at baseline and following the completion of the 8-week intervention period. Results: After 8 weeks of IMT, the MIP and MEP of the IG increased by 31.8% and 26.5%, respectively (p < 0.01). In addition, SBP, DBP, and HR decreased by 2.2%, 3.2%, and 2.1%, respectively (p < 0.01). In the HRV time domain, SDNN and RMSSD increased by 54.1% and 33.5%, respectively (p < 0.01), and there was no significant improvement in SDSD (p > 0.05); in the HRV frequency domain, LF decreased by 40.5%, HF increased by 59.4% (p < 0.01), and the LF/HF ratio decreased by 58.2% (p < 0.05). Conclusion: An 8-week 80%MIP IMT intervention significantly improves respiratory muscle strength and cardiovascular autonomic regulation in obese young men, suggesting that IMT is a promising non-pharmacological strategy for mitigating obesity-related cardiovascular risk. Full article

Cadmium is widely recognized as an important environmental toxicant that may give rise to kidney dysfunction, bone disease, and cancer in humans and animals. Kidney dysfunction occurs at very low exposures and is often considered as the most sensitive or critical effect. Cadmium exposures of concern occur in many countries. In low- and middle-income countries with small-scale mining, excessive exposure to cadmium and other metals occurs in occupational and environmental settings. This is of particular importance in view of the growing demand for metals in global climate change mitigation. Since the 1970s, the present authors have contributed evidence concerning the role of metallothionein and other factors in influencing the toxicokinetics and toxicity of cadmium, particularly as it relates to the development of adverse effects on kidneys in humans and animals. The findings gave a background to the development of biomarkers employed in epidemiological studies, demonstrating the important role of metallothionein in protection against cadmium-induced kidney dysfunction in humans. Studies in cadmium-exposed population groups demonstrated how biomarkers of kidney dysfunction changed during 8 years after drastic lowering of environmental cadmium exposure. Other epidemiological studies showed the impact of a good zinc status in lowering the prevalence of cadmium-related kidney dysfunction. Increased susceptibility to Cd-induced kidney dysfunction was shown in a population with high exposure to inorganic arsenic when compared with a group with low such exposure. Several national and international organizations have used part of the reviewed information, but the metallothionein-related biomarkers and the interaction effects have not been fully considered. We hope that these data sets will also be included and improve risk assessments and preventive measures. Full article

Background and Objectives: Thailand’s demographic shift toward an aging population increases vulnerability among older adults to the long-term mental health effects of childhood trauma. While childhood adversity is linked to heightened risks of late-life depression and PTSD, the moderating role of resilience remains underexplored in Thai older adults. This study investigated whether resilience moderates the association between childhood trauma and depressive or PTSD symptoms in this population. Materials and Methods: A cross-sectional survey was conducted with 201 older patients (mean age 68.6 years) from the Family Medicine and Geriatric Psychiatry Clinics at Maharaj Nakorn Chiang Mai Hospital. Participants completed validated measures on trauma history, resilience, depression, and PTSD symptoms. A moderation analysis was performed, adjusting for covariates including education, family support, and psychiatric history. Results: The findings revealed that resilience significantly buffered the impact of childhood trauma on depression but did not mitigate PTSD symptoms. Conclusions: These results underscore the protective role of resilience against depression following childhood trauma in older adults, yet also point to its limitations in alleviating trauma-specific responses such as PTSD. This study highlights the need for trauma-informed geriatric mental health strategies and calls for further research on resilience, focusing on cultural context and adaptive mechanisms, including emotion regulation and social connectedness, in older populations. Full article