Search Results (428)

Using efficient voice alarms to ensure safe evacuation is important during emergencies, especially for the elderly. Factors that have important influence on speech perceptions have been investigated for several years. However, relatively few studies have specifically explored the key factors influencing perceptions of voice alarms in emergency situations. This study investigated the combined effects of speech rate (SR), signal-to-noise ratio (SNR), and reverberation time (RT) on older people’s perception of voice alarms. Thirty older adults were invited to evaluate speech intelligibility, listening difficulty, and perceived urgency after hearing 48 different voice alarm conditions. For comparison, 25 young adults were also recruited in the same experiment. The results for older adults showed that: (1) When SR increased, speech intelligibility significantly decreased, and listening difficulty significantly increased. Perceived urgency reached its maximum at the normal speech rate for older adults, in contrast to young adults, for whom urgency was greatest at the fast speech rate. (2) With the rising SNR, speech intelligibility and perceived urgency significantly increased, and listening difficulty significantly decreased. In contrast, with the rising RT, speech intelligibility and perceived urgency significantly decreased, while listening difficulty significantly increased. (3) RT exerted a relatively stronger independent influence on speech intelligibility and listening difficulty among older adults compared to young adults, which tended not to be substantially moderated by SR or SNR. The interactive effect of SR and RT on perceived urgency was significant for older people, but not significant for young people. These findings provide referential strategies for designing efficient voice alarms for the elderly. Full article

Insects constitute a vital component of terrestrial ecosystems, yet their ongoing global decline underscores the urgency of identifying the factors that facilitate or hinder public engagement in their conservation. This study identifies the key psychological drivers of insect-related conservation behavior within a Romanian context, an understudied geographical and sociocultural setting. Using data collected from 346 adult respondents via an online questionnaire, the predictive performance of the Value–Belief–Norm (VBN) theory, the Theory of Planned Behavior (TPB), and an integrated VBN–TPB framework was examined through Partial Least Squares Structural Equation Modeling (PLS-SEM). The VBN model exhibited superior explanatory power relative to TPB, with biospheric values, ecological worldviews, and personal moral norms emerging as the most influential determinants of behavioral intention and self-reported action. Although participants demonstrated moderate levels of general entomological knowledge, awareness of specific insect-friendly practices was notably limited and frequently characterized by misconceptions. Perceived barriers, particularly informational deficits, time constraints, and financial considerations, exerted significant inhibitory effects on conservation engagement. The findings indicate that effective interventions must extend beyond knowledge transmission, incorporating strategies that activate moral norms, strengthen affective and identity-based motivations, and reduce structural barriers to action. Full article

The production of reliable turbo machinery, particularly gas turbine blades, is a major global challenge. This capability serves as a key indicator of a nation’s industrial base, technological prowess, and comprehensive strength. Critical components in aircraft engines and gas turbines operate under extreme conditions, including high temperatures, high pressures, and substantial mechanical stresses. Consequently, there is a growing urgency to develop cost-effective and time-efficient repair strategies to enhance engine performance and efficiency. However, many mission-critical parts, especially high-pressure (HP) blades, are prone to severe damage. Moreover, taking equipment offline for blade maintenance and repair is a time-consuming process. It is also highly costly to restore these essential components to full functionality. Since 1996, researchers have focused on applying laser metal deposition (LMD) additive manufacturing technology for high-performance repair and remanufacturing of aerospace engines and industrial gas turbine (IGT) blades. Empirical studies have demonstrated that depositing a high-quality, erosion-resistant protective coating on the leading edge of HP blades effectively extends the service life of turbine blades in both aircraft engines and industrial gas turbines. This study systematically outlines the technical workflow of the proposed methodology and provides a concise perspective on emerging development trends. Full article

Senegal, like many West African countries reliant on natural resources and agriculture, faces severe impacts from climate change. This study provides an analysis undertaken by the United States Agency for International Development (USAID) under the Senegal Water Resources Management Activity, investigating historical and projected rainfall extremes to assess potential risks to water resources under future climate scenarios. Using bias-corrected CMIP6 data validated against the Enhancing National Climate Services (ENACTS) dataset for 1985–2014, we assess model performance through time series analysis, spatial distribution, and Taylor diagrams. We examine changes across three time periods—1985–2013 (historical), 2021–2040 (near future), and 2041–2060 (distant future)—focusing on nine key rainfall indices relevant to agriculture and water security. The results indicate that CMIP6 models capture historical rainfall patterns well. The models MPI-ESM1-2-HR, MIROC-ES2L, MRI-ESM2-0, CanESM5, and GISS-E2-1-G show the best performance and are recommended for climate impact assessments. Spatial analysis reveals prolonged dry periods in the north and heavier rainfall in the south. Under SSP585, the near future shows an increase in consecutive dry days (CDDs) and a decline in extreme rainfall events in northern Senegal, whereas the distant future projects a reversal with intensified rainfall (Rx5day). The south shows contrasting patterns, with increasing rainfall intensities in the long term. These findings highlight shifts in rainfall regimes and underscore the urgency of integrating future climate scenarios into adaptation planning. This study recommends extending analysis to temperature extremes due to their implications for agriculture and public health. Full article

Background/Objectives: The healthcare data sector is experiencing unprecedented growth, fueled by advances in genomics, medical imaging, and wearable devices. The convergence of universal data standards now provides the common ground needed to translate this data into medical advances. However, a significant implementation gap persists, preventing effective deployment in routine clinical practice, particularly in specialized areas like diabetic foot care. Methods: This paper examines the opportunities presented by modern data methodologies to bridge this gap, contextualized within diabetic foot care, where the paramount goals are patient well-being, tissue preservation, and amputation prevention. Results: The analysis indicates that the synergy of interoperable data and advanced management tools is poised to fundamentally transform healthcare delivery. Interdisciplinary collaboration is identified as the foundational element enabling the timely, coordinated, and evidence-based interventions necessary to achieve critical clinical objectives. Conclusions: The pivotal challenge has shifted from technological capability to effective implementation. Leveraging modern data methodologies is essential for translating potential into tangible improvements in diabetic foot outcomes. In this context, collaborative data management must be recognized as a critical treatment modality itself. Here, “data is tissue”; it must be managed with the same urgency and care to enable success. Full article

Head and neck cancer (HNC) diagnostics are undergoing a transformative shift. Recent research published in Cancers highlights a paradigm shift in the comprehensive management of HNC, driven by precision oncology and disruptive technologies. AI-enhanced imaging and non-invasive biomolecular fingerprinting are redefining early detection, with tools like infrared spectroscopy and hyperspectral imaging delivering near-perfect accuracy and real-time surgical guidance. Liquid biopsy is emerging as a powerful surveillance modality, capable of detecting recurrence months before conventional imaging and offering prognostic insights via cell-free DNA analysis. Theranostic agents in nuclear medicine show promise for rare HNC subtypes, though broader molecular targets remain a challenge. These technologies may have utility for complex presentations such as proliferative verrucous leukoplakia (PVL)-associated oral squamous cell carcinoma (OSCC), which disproportionately affects women, and peri-implant OSCC, which is often misdiagnosed and requires aggressive intervention. Collectively, these innovations directly address long-standing challenges: early detection, accurate staging, treatment personalization, monitoring of minimal residual disease and timely cancer care—where diagnostics not only inform treatment but actively shape outcomes. This editorial underscores the urgency of integrating such tools into clinical pathways to improve survival and quality of life for HNC patients globally. Full article

Background: The widespread adoption of digital systems in healthcare has produced large volumes of unstructured text data, including outpatient messages sent through electronic medical record (EMR) portals. Efficient classification of these messages is essential for improving workflow automation and enabling timely clinical responses. Methods: This study investigates the use of large language models (LLMs) for classifying real-world outpatient messages collected from a healthcare system in central Illinois. We compare general-purpose (GPT-4o) and domain-specific (BioBERT and ClinicalBERT) models, evaluating both fine-tuned and few-shot configurations against a TF-IDF + Logistic Regression baseline. Experiments were performed under a HIPAA-compliant environment using de-identified and physician-labeled data. Results and Conclusions: Fine-tuned GPT-4o achieved 97.5% accuracy in urgency detection and 97.8% in full message classification, outperforming BioBERT and ClinicalBERT. These results demonstrate the feasibility and validity of applying modern LLMs to outpatient communication triage while ensuring both interpretability and privacy compliance. Full article

This study examines long-term trends in maximum (Tmax) and minimum (Tmin) near-surface air temperatures and precipitation across South America, focusing on Brazilian biomes and national capitals, using ERA5 reanalysis data for 1979–2024. To isolate the underlying climate signal, seasonal cycles were removed using Seasonal-Trend decomposition based on Loess (STL), which effectively separates short-term variability from long-term trends. Temperature trends were quantified using ordinary least squares (OLS) regression, allowing consistent estimation of linear changes over time, while precipitation trends were assessed using the non-parametric Mann–Kendall test combined with Theil–Sen slope estimation, a robust approach that minimizes the influence of outliers and serial correlation in hydroclimatic data. Results indicate widespread but spatially heterogeneous warming, with Tmax increasing faster than Tmin, consistent with reduced cloudiness and evaporative cooling. A meridional precipitation dipole is evident, with drying across the Cerrado, Pantanal, Caatinga, and Pampa, contrasted by rainfall increases in northern South America linked to ITCZ shifts. The Pantanal emerges as the most vulnerable biome, showing strong warming (+0.51 °C decade⁻¹) and the steepest rainfall decline (−10.45 mm decade⁻¹). Satellite-based fire detections (2013–2024) reveal rising wildfire activity in the Amazon, Pantanal, and Cerrado, aligning with the “hotter and drier” climate regime. In the capitals, persistent Tmax increases suggest enhanced urban heat island effects, with implications for public health and energy demand. Although ERA5 provides coherent spatial coverage, regional biases and sparse in situ observations introduce uncertainties, particularly in the Amazon and Andes, these do not alter the principal finding that the magnitude and persistence of the 1979–2024 warming lie well above the range of interdecadal variability typically associated with the Atlantic Multidecadal Oscillation (AMO) and the Pacific Decadal Oscillation (PDO). This provides strong evidence that the recent warming is not cyclical but reflects the externally forced secular warming signal. These findings underscore growing fire risk, ecosystem stress, and urban vulnerability, highlighting the urgency of targeted adaptation and resilience strategies under accelerating climate change. Full article

Climate change arguably constitutes the most significant environmental challenge of our time, making the enhancement of urban resilience a global priority. Nature-based Solutions (NbS) have emerged as effective instruments to mitigate some of its impacts, particularly by reducing flood risk and moderating urban temperatures. However, their implementation is often reactive, focusing on existing problems rather than anticipating future ones. This underscores the need for robust methodological frameworks that enable the proactive integration of NbS within urban planning processes. This study proposes a spatial planning methodology supported by Geographic Information Systems (GIS), which, through the application of opportunity, priority, and feasibility criteria, identifies optimal areas for NbS integration, determines appropriate typologies, and establishes levels of intervention urgency. Although the methodology has been developed for the city of Granada, its structure allows for replication in other urban contexts. The findings reveal that one-third of Granada’s urban area is suitable for NbS implementation, with approximately 7% exhibiting a high or very high risk of surface runoff accumulation. The proposed tool has the potential to strengthen urban resilience and enhance citizens’ quality of life. Full article

Background: The accelerating global population aging underscores the urgency of addressing public health challenges. Sarcopenia and depression are prevalent, interrelated conditions in older adults, yet prevailing research often treats depression as a static state, neglecting its longitudinal progression and limiting predictive capability for sarcopenia. Methods: Using data from four waves (2011–2018) of the China Health and Retirement Longitudinal Study (CHARLS), we identified distinct depressive symptom trajectories via Group-Based Trajectory Modeling. Seven machine learning algorithms were employed to develop predictive models for sarcopenia risk, incorporating these trajectory patterns and baseline characteristics. Results: Three depressive symptom trajectories were identified: ‘Persistently Low’, ‘Persistently Moderate’, and ‘Persistently High’. Tree-based ensemble methods, particularly Random Forest and XGBoost, demonstrated superior and robust performance (mean accuracy: 0.8265 and 0.8178; mean weighted F1-score: 0.8075 and 0.8084, respectively). Feature importance analysis confirmed depressive symptoms as a core, independent predictor, ranking third (5.7% importance) in the optimal Random Forest model, only after BMI and cognitive function, and surpassing traditional risk factors like age and waist circumference. Conclusions: This study validates that longitudinal depressive symptom trajectories provide superior predictive power for sarcopenia risk compared to single-time-point assessments, effectively mapping mental health trajectories to physical risk. The robust ML framework not only enables early identification of high-risk individuals but also reveals a multidimensional risk profile, highlighting the intricate mind–body connection in aging. These findings advocate for integrating dynamic mental health monitoring into routine geriatric assessments, demonstrating the potential of AI to facilitate a paradigm shift towards proactive, personalized, and scalable prevention strategies in public health and clinical practice. Full article

The growing threat of airborne biological agents necessitates rapid, sensitive, and portable detection systems to mitigate risks to public health and national security. We present a comprehensive overview of biosensor technologies developed for airborne biothreat detection, with a focus on aptamer-based electrochemical sensors. These sensors offer key advantages in portability, chemical stability, and adaptability for multiplexed detection in field settings. The urgency for real-time surveillance tools capable of identifying viral, bacterial, and toxin-based agents is discussed, particularly in the context of biodefense. Aerosolized particle capture strategies are reviewed, focusing on microfluidics for micron-sized particles and condensation-based systems for submicron-sized particles, which are preferred for their small-volume operation and seamless integration with biosensors. Key biosensor components are described, including recognition elements—such as aptamers—and transduction mechanisms like electrochemical impedance spectroscopy. EIS is highlighted for its label-free, miniaturizable, and real-time readout capabilities, making it well-suited for portable biosensors. Advances in sensing strategies for both viral and bacterial targets are explored, featuring innovations in nanoporous membrane platforms, nanomaterials, and multiplexed assay formats. Recent developments demonstrate improved sensitivity through nanopore-based signal amplification and enhanced selectivity using engineered aptamer libraries. The review concludes by addressing current limitations, including environmental stability, system integration, and the need for validation with complex real-world samples. Future directions point toward the development of fully integrated, field-deployable biosensing platforms that combine effective aerosol capture with robust and selective biosensing technologies. Full article

Background: Emergency contraception (EC), also known as postcoital contraception, is a method used to prevent an unintended pregnancy following unprotected or inadequately protected sexual intercourse. The available options include emergency contraceptive pills or the insertion of an intrauterine device (IUD). Emergency contraception pills contain either levonorgestrel (a single 1.5 mg dose, effective within 72 h) or ulipristal acetate (a single 30 mg dose, effective within 120 h), both of which are most effective when taken as soon as possible after unprotected intercourse. Another highly effective option is the insertion of a copper or levonorgestrel-releasing intrauterine device, although IUDs are not registered for EC use in all countries. The aims of this cross-sectional, comparative, observational study were to collect data on the emergency contraception methods used by adolescent girls and young women to examine their association with various factors, such as religious beliefs, and to evaluate the effectiveness of different emergency contraception methods, including hormonal options and intrauterine devices. Methods: Data were collected from 240 women who attended our Family Planning Clinic using a structured questionnaire that included items on their demographic characteristics, religious beliefs, medical history, lifestyle factors, contraceptive use and side effects, prior use of emergency contraception, method selected, and reasons for seeking emergency contraception. Descriptive statistics were used to summarize the data, comparisons between religious groups were conducted using chi-square tests, and factors related to the timing of emergency contraceptive use were investigated using multinomial logistic regression analysis. Results: Most of the reasons for emergency contraception use did not differ significantly between Christian and Muslim participants. However, Christians were significantly more likely to use emergency contraception due to missed contraceptive doses (20.9% vs. 6.7%, p = 0.004) or the failure to take a progesterone-only pill (19.1% vs. 3.3%, p = 0.001). Levonorgestrel was the most frequently used method in both groups (48.9% of Christians vs. 60% of Muslims, p = 0.132), followed by ulipristal acetate (30.9% vs. 40%, p = 0.180). Notably, 18.5% of Christian participants used an intrauterine device (IUD) for emergency contraception, while no Muslim participants reported IUD use (p < 0.001), indicating a significant difference potentially influenced by cultural or religious factors. Conclusions: Both religious and individual sociodemographic factors affect not only the choice of emergency contraception but also the urgency with which the emergency contraception is used. Interventions aimed at improving contraception education, addressing partner-related challenges, and promoting timely access could improve reproductive health outcomes. Full article

Prized since antiquity in Greek cultural heritage as a fountain of health and healing and nature’s golden nectar, honey remains one of the world’s most valued natural products. Celebrated for its nutritional, therapeutic, and antimicrobial virtues, honey is now faced with the emerging threat of microplastic contamination. Here, we present direct evidence of microplastic migration into honey, examining real honey samples packaged in flexible plastic pouches, which are commonly offered in cafes all around the world. Such honey samples were tested under different environmental storage conditions (common dry and dark outdoors) and prolonged refrigeration conditions at low temperature, which replicate consumer use. We have identified microplastics using filters and spectroscopic methods in honey from commercial honey pouches, which prove plastic packaging as a contamination source. Additionally, plasticizers were detected in honey that migrated from plastic packaging. The mere fact that microplastics were found in every single storage condition tested and at every time point examined (from day zero of this experiment), while increasing through time, is of great concern for the long-term safety of honey packaging. Our findings emphasize the urgency of reevaluating packaging for honey and other foods, and they open up new perspectives in the study of microplastic migration under real-world conditions. Full article

Ethiopia is among the most climate-vulnerable countries in Africa, with agriculture, water resources, health, and disaster risk management highly exposed to climate variability and change. This study examines the role of climate services in supporting climate change adaptation in Ethiopia by combining analyses of historical climate trends, future projections, national policy frameworks, and survey data from both users and providers of climate information. Results show that rainfall and temperature time-series exhibit significant variability, with increasing frequency of droughts and rising temperatures already threatening livelihoods and food security. Climate projections indicate continued warming and uncertain but increasingly extreme rainfall patterns, underscoring the urgency of adaptation. National strategies—including the Climate Resilient Green Economy (CRGE) Strategy, Growth and Transformation Plans (GTP I and II), and the National Adaptation Plan (NAP-ETH)—highlight the centrality of climate services in guiding adaptation across sectors. Survey findings reveal that climate services provided by the Ethiopian Meteorological Institute (EMI) are widely valued, particularly seasonal climate predictions, but challenges persist in accessibility, capacity, infrastructure, and alignment with user needs. Despite high satisfaction levels among users and providers, gaps remain in technical expertise, dissemination mechanisms, and service co-production. Strengthening climate services—through improved technical capacity, institutional coordination, and user-driven design—will be critical for enhancing Ethiopia’s resilience. The lessons drawn are also relevant to other African countries where climate services can play a critical role in bridging the gap between climate science and climate-resilient development. Full article

The COVID-19 pandemic caused by the SARS-CoV-2 virus has exposed the urgency of research on rapid and efficient virus detection and strategies to inhibit its replication. Previous studies have mostly focused on traditional immunoassay or optical methods, but they have limitations in terms of sensitivity, timeliness, and in-depth analysis of molecular interaction mechanisms. Solid-state nanopore single-molecule detection methods, which can monitor molecular conditions in real time at the single-molecule level, bring new opportunities to solve this problem. The nucleocapsid protein (N protein) of SARS-CoV-2 was systematically investigated under different conditions, such as external drive voltage, pH, nanopore size, and N protein concentration. The translocation of the N protein through the nanopore was then analyzed. Subsequently, we analyzed the translocation characteristics of the N protein, RNA, and N protein–RNA complexes. With the aid of EMSA experiments, we conclusively confirmed that RNA binds to the N protein. Building on this finding, we further explored small molecules that could affect the nanopore translocation of N protein–RNA complexes, such as gallocatechin gallate (GCG), epigallocatechin gallate (EGCG), and the influenza A viral inhibitor Nucleozin. The results show that GCG can disrupt the liquid-phase condensation of the N protein–RNA complex and inhibit the replication of the N protein. Meanwhile, the structural isomer EGCG of GCG and the small molecule Nucleozin can also block RNA-triggered N protein liquid–liquid phase separation (LLPS). Our results confirmed that GCG, EGCG, and Nucleozin exhibit antagonistic effects on the N protein, with differences in their effective concentrations and the potency of their antagonism. Herein, using solid-state nanopore single-molecule detection technology, we developed an experimental method that can effectively detect RNA-induced changes in N protein properties and the regulatory effects of small molecules on the LLPS of N protein–RNA complexes. These findings not only provide highly valuable insights for in-depth research on the molecular interactions involved in viral replication, but also open up promising new avenues for future responses to similar viral outbreaks, the development of a rapid and effective detection method based on solid-state nanopores and single-molecule detection, and antiviral therapies targeting N protein–RNA interactions. Full article