Search Results (66,576)

The availability of reliable and spatially distributed rainfall data is a key element flood and landslide risk assessment, both for forecasting and post-event analysis. In this context, this study evaluates the contribution of radar-based rainfall estimates to enhancing the spatial accuracy of precipitation fields with respect to those derived from rain gauge networks alone. The analysis was conducted over a ~100 km² area in the Liguria Region, north-western Italy, characterized by a dense rain gauge network, with an average density of one gauge per 10 km², and covers seven years of hourly rainfall observations. Radar-derived rainfall fields, available at a 1 × 1 km² spatial resolution, were locally corrected across the study area by interpolating gauge-based local correction factors through an Inverse Distance Weighting (IDW) scheme. The corrected radar fields were then assessed through Leave-P-Out Cross-Validation and rainfall-intensity-based classification, also simulating scenarios with progressively reduced gauge density. The results demonstrate that radar-corrected estimates systematically provide a more accurate spatial representation of rainfall, especially for high-intensity events and in capturing the actual magnitude of local rainfall peaks, even in areas covered by a dense rain gauge network. Regarding the implications for rainfall-induced landslide hazard assessment, the analysis of 56 landslides from the ITALICA (Italian Rainfall-Induced Landslides Catalogue) database showed that including radar information can lead to significant differences in the estimation of rainfall thresholds for landslide initiation compared with gauge-only data. Full article

The decoupling properties and low-inertia characteristics of large-scale wind power have heightened concerns regarding power grid frequency stability, particularly as modern power systems impose stringent frequency regulation requirements on wind integration, leading to an increased complexity of frequency response characteristics under fault conditions. To address this challenge in high-wind-penetration grids, this paper proposes a post-fault frequency dynamics analysis method capable of concurrently accommodating multi-wind-speed scenarios through three key innovations: the linearization of traditional AC system components (including network equations, composite load models, and generator prime mover-governor systems) to establish nodal power increment equations; the development of wind turbine frequency regulation models under diverse wind conditions using small-signal analysis, incorporating regional operational disparities and refined by information entropy-based reliability quantification for adaptive parameter adjustment; and the derivation of the system state equation for post-fault frequency response using wide-area measurement system (WAMS) data, yielding an analytical model that captures region-specific regulation characteristic disparities for physically faithful frequency analysis. Validation via tailored IEEE 39-node simulations convincingly demonstrates the method’s effectiveness and superiority in handling fault-induced transients and wind variability. Full article

This study conducts a diagnostic analysis of an extremely heavy rainfall event and its causative factors that occurred in Libya, North Africa on 10 September 2023. The Weather Research and Forecasting (WRF) model was also employed to perform some sensitivity experiments for this heavy rainfall event and further reveal its causes. Results indicate that the primary synoptic system responsible for this extreme precipitation event was an extratropical cyclone (storm) named “Daniel”. During the formation and development of this cyclone, the circulation at the 500 hPa level from the eastern Atlantic to western Asia exhibited a stable “two troughs and one ridge” pattern, with a upper-level cold vortex over the eastern Atlantic, a high-pressure ridge over central Europe, and a cut-off low over western Asia, collectively facilitating the formation and development of this cyclone. As this cyclone moved southward, it absorbed substantial energy from the Mediterranean Sea; following landfall, the intrusion of weak cold air enabled the cyclone to continue intensifying. Meanwhile, the northwest low-level jet stream to the west of the extratropical cyclone moved alongside the cyclone to the coastal regions of northeastern Libya, where it converged with water vapor transport belts originating from the Ionian Sea, the Aegean Sea, and the coastal waters of northeastern Libya. This convergence provided abundant water vapor for the rainstorm event, and under the combined effects of convergence and orographic lifting on the windward slopes of the coastal mountains, extreme precipitation was generated. In addition, the atmosphere over the coastal regions of northeastern Libya exhibited strong stratification instability, which was conducive to the occurrence of extreme heavy precipitation. Although WRF successfully reproduced the precipitation process, the precipitation amount was underestimated. Sensitivity experiments revealed that both the topography in the precipitation area and the sea surface temperature (SST) of the Mediterranean Sea contributed to this extreme heavy precipitation event. Full article

Rett syndrome (RTT) presents with a wide range of symptoms spanning various clinical areas. Capturing symptom change as the disorder progresses is challenging. Wearable sensors offer a non-invasive and objective means of monitoring disease states in neurodevelopmental disorders. The goal of this study was to conduct a systematic literature review to critically appraise the literature on the use of wearable sensors in individuals with RTT. The PRISMA criteria were used to search four databases without time restriction and identified 226 records. After removing duplicates, the titles and abstracts of 184 records were screened, 147 were excluded, and 37 were assessed for eligibility. Ten (10) articles remained, and a further two were included after additional searching. In total, 12 articles were included in the final analysis. The sample size ranged from 7 to 47 subjects with an age range of 1 to 41 years. Different wearable biosensor devices were used across studies, with the Empatica E4 wearable device being most frequently used in 33% (4/12) of the studies. All the studies demonstrated a high methodological quality with a low risk of bias. Evidence from wearable sensors, combined with machine learning methods, enabled the prediction of different sleep patterns and clinical severity in RTT. Given the small sample size and the limitations of available data for training machine learning models, we highlight areas for consideration. The review emphasises the need to enhance research on the application of wearable sensors in epilepsy and gastrointestinal manifestations/morbidity in RTT. Increased electrodermal activity (EDA), % of maximum heart rate (HRmax%) and the heart rate to low-frequency power (HR/LF) ratio were identified as physiological measures potentially associated with disease states. Based on the evidence synthesis, the role of physiological parameters and their association with symptom management in RTT is discussed. Full article

Background: There have been no previous comprehensive reports on interstitial lung diseases (ILD) in Israeli population, that may have unique epidemiological features. We aimed to explore ILD in Israel, with an emphasis on disparities between different regions of the country. Methods: The study included consecutive patients with a multidisciplinary diagnosis of ILD, using data from registries of four tertiary medical centers (MC) located in Central and Northern Israel. Multivariate regression models were used to assess the region of residence (peripheral vs. central) as an independent predictor for ILD subtypes. Results: Included were 927 patients with ILD (mean age 67 ± 13, 40% females). Most patients (56–61%) reported working in at least one job that involved relevant inhalational exposures. Despite the geographic proximity of MCs (all within 100 km), significant variations in demographic and clinical characteristics were observed, including age, sex, exposures, and ILD diagnoses (p < 0.01). The most prevalent diagnoses were Idiopathic pulmonary fibrosis (IPF, range 13–58%) and autoimmune-related ILD (11–30%). In peripheral areas, the diagnosis of IPF was more frequent (53% vs. 24%, p < 0.01), while exposure-related ILD (5% vs. 16%, p < 0.01) and autoimmune-related ILD (16% vs. 25%, p < 0.01) were more frequent in central Israel. In multivariate analysis, peripheral residence remained an independent predictor for IPF (AOR 2.95, 95% CI 2.1–4.1) and central residence for exposure-related ILD (AOR 0.46, 95% CI 0.33–0.63). Conclusions: Variations in ILD characteristics were observed between centers in close geographic proximity, highlighting disparities between peripheral and central Israel, and the need for personalized assessment based on local frequencies and exposures. Full article

As a form of living cultural heritage, local residential landscapes manifest the essence of long-term, resilient human–land interactions. The Wuling Corridor, a vital ethnic and cultural passage connecting the Central Plains with Southwest China in Chinese history, serves as a crucial region for the mixed residence and cultural exchange of Tujia, Miao, Dong, Han, and other ethnic groups. Within this region, Ganlan stands as both the most representative vernacular architectural heritage and a residential form that is still extensively used, constituting a continuous and unique residential landscape. The spatial distribution patterns of Ganlan are the physical witness of the history of ethnic groups adapting to the complex topographic and cultural conditions. Current research focuses on the case description of single Ganlan forms, failing to systematically investigate the spatial formation mechanisms of Ganlan as a residential landscape from a geographical continuum perspective. Therefore, this study establishes a geographical database encompassing 9425 Ganlan samples from the Wuling Corridor. It integrates the geographic information system (GIS) with clustering algorithms to systematically identify the distribution patterns of Ganlan within specific geographic–cultural units and their coupling relationships with natural environments. It conducts quantitative analysis on the key driving factors concerning the emergence and evolution of Ganlan in the study area; the findings reveal the following: (1) Ganlan buildings exhibit a spatially aggregated distribution pattern along major water systems, demonstrating characteristics of multi-ethnic sharing and spatial interweaving. (2) Their distribution is constrained by natural geographical factors and influenced by the transmission pathways of construction techniques during ancient ethnic migrations to the southwest China. (3) Within multi-ethnic settlement structures, inter-ethnic cultural interactions (particularly with Central Plains culture) serve as a key driving force for the typological evolution of Ganlan. (4) The evolutionary lineage of “full-Ganlan,” “semi-Ganlan,” and “courtyard-style Ganlan” systematically demonstrates the dynamic adaptive capacity of local residential systems. Additionally, by integrating massive Ganlan heritage data with multiple spatial analysis methods, the study serves as a typical case study illuminating the adaptive strategies and resilience mechanisms of Ganlan as a local residential landscape formed in response to the environmental conditions and social changes. Also, it provides a scientific basis for the holistic conservation of architectural heritages shared by multiple ethnic groups and the integrated development of local cultural tourism industries. Full article

In precast concrete shear wall structures, the joints formed during the vertical connection of precast units are referred to as the “horizontal joint”. Serving as vertical connection nodes in this structure system, the construction quality of theses horizontal joints significantly influences the structural integrity. To investigate the influence of horizontal joint quality defects on the mechanical behaviour of precast concrete shear walls, three precast concrete shear wall specimens with quality defects in different regions and three control specimens were designed. Quasi-static tests under a constant axial load were conducted to investigate the effects of defect area, location and other factors on the mechanical behaviour of the walls. Results demonstrate that the quality defects in horizontal joints significantly affect the mechanical behaviour of precast concrete shear walls. When the ratio of the quality defect area to the cross-sectional area of the boundary member reaches 100%, the yield load and peak load of the precast concrete shear wall decrease by 13% and 20%, respectively. Additionally, the structural stiffness exhibited a 13% degradation at a drift angle of 1/1000. Although the failure mode remains largely unchanged, yielding of longitudinal reinforcement in the boundary members is observed. Moreover, as the proportion of the quality defect area to the cross-sectional area decreases, its adverse effects on the mechanical behaviour of the precast concrete shear wall gradually diminish. The established numerical analysis model is shown to be reasonable and reliable. When the defective area of the horizontal joints is less than 25% of the total cross-sectional area, the quality defects essentially have no influence on the mechanical behaviour of the precast concrete shear walls. Full article

By 2050, the global population will be predominantly living in urban areas, and climate change mitigation planning will be crucial for addressing the climate emergency. Local governments are well-positioned to lead in adopting effective climate mitigation strategies. This systematic literature review examines the barriers, enablers, and systems that local governments will need to consider when implementing climate mitigation and strategies. A search across Scopus, Web of Science, and ProQuest databases yielded 411 results, from which 28 articles were selected for detailed analysis. Using Covidence and NVivo 14 software, the study employed a combination of deductive and inductive coding to identify key themes. The study identified themes specific to enablers, such as technology, collaboration, leadership, and management culture, as well as barrier themes, including short-term thinking, uncertainty avoidance, lack of knowledge among decision-makers, resource shortages, and organizational challenges. The findings underscore the importance of addressing organizational issues and allocating appropriate resources to bolster local-level systems change in support of climate change mitigation efforts. Full article

There is a growing need for comprehensive and transparent frameworks in bibliometric evaluation that support fairer assessments and capture the multifaceted nature of research performance. This study proposes a novel methodology for identifying top-performing researchers based on a composite performance index (CPI). Unlike existing rankings, this framework presents a multidimensional approach by integrating sixteen weighted bibliometrics metrics, spanning research productivity, citation, publications in top journal percentiles, authorship roles, and international collaboration, into a single CPI, enabling a more nuanced and equitable evaluation of researcher performance. Data were retrieved from SciVal for 1996–2025. Two ranking exercises were conducted with Kazakhstan as the analytical unit. Subject-specific rankings identified the top 1% authors within different research areas, while subject-independent rankings highlighted the overall top 1%. CPI distributions varied markedly across disciplines. A comparative analysis with the Stanford/Elsevier global top 2% list was conducted as additional benchmarking. The results highlight that academic excellence depends on a broad spectrum of strengths beyond just productivity, particularly in competitive disciplines. The CPI provides a consistent and adaptable tool for assessing and recognizing research performance; however, future refinements should enhance data coverage, improve representation of early-career researchers, and integrate qualitative aspects. Full article

High-Andean lakes are strategic freshwater ecosystems whose monitoring is essential for effective water resource management. However, their optical complexity limits the applicability of conventional methods. In this study, the water quality conditions of the Ozogoche lakes, located in Sangay National Park (PNS), were assessed using Sentinel-2 (S2), Landsat-8 OLI (L8), and Landsat-9 (L9) imagery processed with automated water products from the Case 2 Regional Coast Colour (C2RCC) processor, including the C2RCC, C2X-COMPLEX, and C2X versions. Comparisons between in situ chlorophyll-a (Chl-a) measurements and satellite-derived products confirmed that C2RCC achieved the lowest error (RMSE = 0.68 mg/m³). The multitemporal analysis (2016–2024) of Chl-a, total suspended solids (TSSs), and the diffuse attenuation coefficient (kd_z90max) revealed interannual variations. The results consistently classified the lakes as ultra-oligotrophic, providing an integrated perspective of their environmental quality. This study demonstrates the reliability of C2RCC products for monitoring high-Andean aquatic ecosystems and underscores the potential of remote sensing to overcome accessibility and cloud cover constraints, delivering valuable insights for the sustainable management of water resources in protected areas. Full article

Local leaf size diversity (LLSD) is an essential functional indicator of plant biodiversity; however, massive challenges are encountered when quantifying it and decoding its global ecological patterns. To address this limitation, the present study defined a quantitative indicator of LLSD, termed coefficient of variation index (CVI), for the leaf sizes, regardless of plant species, collected in each sampling site. Then, we innovatively derived a set of global CVI values from a published dataset, which was obtained through a meta-analysis of global leaf area samples and their related climate factors. Our macroecological analyses indicate that the CVI values vary across continents and fluctuate with latitude. The global CVI values are predominantly influenced by the mean temperature of the coldest month during the growing season in the negative correlation mode. When two leading climate drivers are considered, the global CVI values are primarily influenced by the mean temperature during growing season and the mean annual sum precipitation. Overall, all of these contributions are pioneering in their implications for characterizing the global distribution and ecological patterns of LLSD and advancing the cutting-edge research domain of leaf functional biodiversity to a new quantitative stage. Full article

Background: Acute lymphoblastic leukemia (ALL) is the most common childhood malignancy, yet diagnosis still relies primarily on invasive bone-marrow procedures and advanced laboratory assays. Non-invasive, rapid, and cost-effective tools remain an unmet need. Fourier-transform infrared (FTIR) spectroscopy has shown promise for detecting cancer-associated biochemical changes in biofluids and cells. Methods: Serum from pediatric ALL patients and controls (n = 103; ALL = 45, controls = 58: healthy = 14, hematology controls = 44 with anemia, thrombocytopenia, leukopenia, and pancytopenia) was analyzed using FTIR. Spectra (800–1800, 2800–3500 cm⁻¹) were preprocessed with baseline correction, derivative filtering, and normalization. Group differences were assessed statistically, and logistic regression with stratified 10-fold cross-validation was applied; Receiver operating characteristic (ROC)\precision–recall (PR) analyses were based on out-of-fold predictions. Results: Distinct spectral alterations were observed between ALL and controls. Leukemia samples showed higher amide I (~1640 cm⁻¹) and amide II (~1545 cm⁻¹) absorbance, lower lipid-related bands (~1450, ~2920 cm⁻¹), and increased nucleic-acid–associated signals (~1080 cm⁻¹). Differences were significant (q < 0.05) with moderate effect sizes. Logistic regression achieved area under the curve (AUC) ≈ 0.80 with sensitivity ~0.73–0.84 across practical decision thresholds (0.50 → 0.30) and higher recall attainable at the expense of specificity. Principal component analysis (PCA)\hierarchical cluster analysis (HCA) indicated partial but consistent group separation, aligning with supervised performance. Conclusions: Serum FTIR spectroscopy shows promise for distinguishing pediatric ALL from controls by reflecting disease-related metabolic changes. The technique is rapid, label-free, and requires only small serum volumes. Our findings represent proof-of-concept, and validation in larger, multi-center studies is needed before clinical implementation can be considered. Full article

Mathematical modeling is a key tool for describing and predicting the dynamic behavior of anaerobic digestion. Studies combining the co-digestion of aquaponics effluent (AE) and cattle manure (CM) with kinetic modeling remain scarce, particularly regarding the estimation of the apparent kinetic constant of hydrolysis constants and energy conversion indicators. Accordingly, this study aimed to evaluate the bioenergy potential of co-digesting aquaponics effluent (AE) and cattle manure (CM), with an emphasis on kinetic modeling and energy conversion. The experiments were carried out in a bench-scale Indian-type anaerobic biodigester. Different AE, CM, and water (W) (0:1, 1:0, 1:1, 1:3, 3:1 W:CM, and 1:1, 1:3, and 3:1 AE:CM) ratios were tested to identify the most efficient substrate combination for biogas production. The 1:3 AE:CM ratio achieved the best performance, with the Gompertz model providing the best fit for cumulative production and the first-order model accurately estimating k. This ratio yielded the highest cumulative biogas production (72.2 L kg⁻¹ substrate), shorter lag phase, higher production rate, and greater energy conversion efficiency. Comparative analysis revealed that 1:3 AE:CM outperformed both 1:3 A:CM and CM alone, highlighting the positive influence of aquaponics effluent on microbial activity and process stability. These results demonstrate that anaerobic co-digestion of AE and CM, particularly at the 1:3 ratio, is a viable and efficient strategy for renewable energy generation in rural areas, while promoting waste valorization and enhancing environmental and energy sustainability. Full article

Common bacterial blight (CBB) is a significant disease caused by the seed-borne pathogen Xanthomonas axonopodis pv. phaseoli (Xap), which devastates global bean production. This study evaluated the effects of Bacillus subtilis (Bst26), Lactobacillus plantarum (Lpkb10), their combination (Bst26 + Lpkb10), copper hydroxide (CH), and an untreated control on controlling CBB in three bean cultivars (Göynük, Saltan, and Tezgeldi). Disease incidence (CI), disease severity index (DSI), severity score (SC), area under disease progress curve (AUDPC), and disease control (DC), along with agronomic traits such as plant height, number of primary branches, root length, and fresh root weight, were recorded to assess both infection rates and plant health under each treatment. The findings revealed significant differences in DI, DSI, SC, AUDPC, and DC (p ≤ 0.01) among the bean cultivars for CBB. Among the cultivars, the Bst26 treatment and the combination of Bst26 and Lpkb10 showed the highest control effectiveness, with DI values of 33.11% and 33.46% in Saltan, 35.65% and 44.16% in Göynük, and 37.71% and 42.43% in Tezgeldi, respectively, at 21 days after inoculation (DAI). Bst26 alone and in combination with Lpkb10 effectively controlled CBB, with disease reduction of 56.80% and 46.49% in Göynük, 57.08% and 56.62% in Saltan, and 52.18% and 46.19% in Tezgeldi, respectively. Disease progression was highest in the untreated control, with DI ranging from 77.15% to 82.54% across Göynük, Saltan, and Tezgeldi cultivars. Significant differences (p ≤ 0.01) in plant height, root length, and root weight were observed among treatments and cultivars. Disease parameters were negatively correlated with plant growth traits, and multi-treatment analysis demonstrated that combining bacterial strains effectively reduced disease severity in susceptible cultivars, highlighting their potential for improved CBB management. Full article

Osorno volcano (41.1° S, 72 W) is located in the Andean Southern Volcanic Zone. The volcano lies within a national park as part of the protected areas system. This setting provides an opportunity to compare soil microbial communities between sectors with (H) and without (NI) anthropogenic activities within a volcanic territory. To do so, we selected one of the most visited volcanoes in Chilean Patagonia to examine composition, diversity (taxonomic and phylogenetic), and co-presence and mutual exclusion interaction networks between members of volcanic soil bacterial communities. Soil DNA was extracted, and the 16S rRNA gene was analyzed by high-throughput DNA sequencing, followed by taxonomic identification. The most prevalent phylum across all sites (H and NI) was Pseudomonadota, followed by Acidobacteriota, Actinobacteriota, and Chloroflexota. Based on taxonomic and phylogenetic indices, we found that the diversity of bacteria was significantly less in the humanized area than in the non-intervened areas. Beta diversity analysis also revealed a clear separation between humanized and non-intervened soils. Additionally, a decrease in network connectivity was observed at NI sites. Our results provide clear evidence that anthropogenic factors, such as tourism, vehicle parking, and combustion processes, are key drivers shaping bacterial community structure in volcanic soils, with potential consequences for ecosystem health and the capacity to provide ecosystem services. Full article