Search Results (192)

The reaction of 2-(3-chloro-5-phenyl-4H-1,2,6-thiadiazin-4-ylidene)malononitrile with ammonia in anhydrous THF, at ca. 20 °C, for 24 h, gave 6-amino-4-phenylpyrrolo[2,3-c][1,2,6]thiadiazine-5-carbonitrile in 95% yield. The product was characterized by ¹H and ¹³C NMR, SC-XRD, MALDI-TOF mass spectrometry, FTIR, and UV-vis spectroscopy. Intermolecular hydrogen bonding interactions were observed in the solid state between the C≡N and N-H groups of adjacent molecules. Full article

Urban pluvial flooding (UPF) is an increasingly critical issue due to rapid urbanization and intensified precipitation driven by climate change that yet remains understudied in the Caribbean. This study analyzes the effects of UPF resulting from the transformation of a natural karstic landscape into an urbanized area considering a sub-watershed in Chetumal, Southern Mexican Caribbean, as a case study. Hydrographic numerical modeling was conducted using the IBER 2.5.1 software and the SCS-CN method to estimate surface runoff for a critical UPF event across three stages: (i) 1928—natural condition; (ii) 1998—semi-urbanized (78% coverage); and (iii) 2015—urbanized (88% coverage). Urbanization led to the orthogonalization of the drainage network, an increase in the sub-watershed area (20%) and mainstream length (33%), flow velocities rising 10–100 times, a 52% reduction in surface roughness, and a 32% decrease in the potential maximum soil retention before runoff occurs. In urbanized scenarios, 53.5% of flooded areas exceeded 0.5 m in depth, compared to 16.8% in non-urbanized conditions. Community-based knowledge supported flood extent estimates with 44.5% of respondents reporting floodwater levels exceeding 0.50 m, primarily in streets. Only 43.1% recalled past flood levels, indicating a loss of societal memory, although risk perception remained high among directly affected residents. The reported UPF effects perceived in the area mainly related to housing damage (30.2%), mobility disruption (25.5%), or health issues (12.9%). Although UPF events are frequent, insufficient drainage infrastructure, altered runoff patterns, and limited access to public shelters and communication increased vulnerability. Full article

Water scarcity remains critical in Rwanda’s Eastern Savanna Agroecological Zone due to erratic rainfall, prolonged dry seasons, and rising water demands. This challenge threatens agricultural productivity, food security, and livelihoods. Stormwater harvesting presents a sustainable solution that increases water availability and mitigates the impacts of climate variability. This study utilizes Geographic Information System (GIS) tools and SCS-CN to assess stormwater harvesting potential in the region. The methodology includes analyzing land use, soil type, rainfall data (30 years, from 1994 to 2023), and topography. Key research steps involve delineating catchment areas, estimating runoff volumes, and selecting optimal storage sites using multi-criteria decision analysis. Findings include eight main water reservoirs, each with a unique code (W_R1 to W_R8), geographic coordinates (X and Y), and 10 million cubic meters storage volumes. W_R1 has the smallest volume at 0.242 × 10⁶ m³, while W_R2 has the largest volume at 8.51 × 10⁶ m³. W_R3, W_R5, and W_R7 are additional noteworthy reservoirs with sizable capacities. The findings contribute to policy formulation and Sustainable Development Goals (SDGs) related to clean water, food security, and climate action. This research provides a replicable framework for addressing water scarcity and enhancing long-term resilience in water-stressed regions. Full article

Latilactobacillus sakei (L. sakei) and Staphylococcus carnosus (S. carnosus) are common starters for fermented sausages. However, the mechanism underlying the effects of these two microorganisms on co-cultivation in sausages remains unclear. This study compared the changes in metabolomics following fermentation by L. sakei and S. carnosus individually and in combination. After two days of fermentation, the pH values of the LS (Latilactobacillus Single), SC (Staphylococcus Single), and LSSC (Latilactobacillus-Staphylococcus Combined) groups were 4.59, 5.19, and 4.86. By comparing the common differential metabolites among the three groups, it was found that the content of N2-acetyl-L-ornithine decreased after single fermentation with L. sakei, while the content of N2-acetyl-L-ornithine increased after single fermentation with S. carnosus and combined fermentation with L. sakei. Additionally, KEGG pathway analysis identified eight key metabolic pathways, including purine metabolism, starch and sucrose metabolism. In addition, it was found that L. sakei produced D-Galactose during fermentation, which could be utilized by S. carnosus. The co-fermentation of L. sakei and S. carnosus promoted the production of D-sorbitol. Our results suggest that the metabolic interactions between L. sakei and S. carnosus increase the number of functional metabolites in co-fermented sausages. These findings provide valuable insights and new research directions for the study of LAB and CNS interactions, as well as for the development of fermentation agents. Full article

Green roofs are increasingly recognized as effective Nature-Based Solutions (NBS) for urban stormwater management, contributing to sustainable and climate-resilient cities. The Soil Conservation Service Curve Number (SCS-CN) model is commonly used to simulate their hydrological performance due to its simplicity and low data requirements. However, the standard assumption of a fixed initial abstraction ratio (Ia/S = 0.2), long debated in hydrology, has been largely overlooked in green roof applications. This study investigates the variability of Ia/S and its impact on runoff simulation accuracy for a green roof under a humid subtropical climate. Event-based analysis across multiple storms revealed Ia/S values ranging from 0.01 to 0.62, with a calibrated optimal value of 0.17. This variability is primarily driven by the physical and biological characteristics of the green roof rather than short-term rainfall conditions. Using the fixed ratio introduced consistent biases in runoff estimation, while intermediate ratios (0.17–0.22) provided higher accuracy, with the optimal ratio yielding a median Curve Number (CN) of 89 and high model performance (NSE = 0.95). Additionally, CN values followed a positively skewed Weibull distribution, highlighting the value of probabilistic modeling. Though limited to one green roof design, the findings underscore the importance of site-specific parameter calibration to improve predictive reliability. By enhancing model accuracy, this research supports better design, evaluation, and management of green roofs, reinforcing their contribution to integrated urban water systems and global sustainability goals. Full article

This study presents a flood risk assessment of five rural bridges along the monsoon-prone Khar–Mohmand Gat corridor in Northwestern Pakistan using an integrated hydrologic and hydraulic modeling framework. Hydrologic simulations for 50- and 100-year design storms were performed using the Hydrologic Engineering Center’s Hydrologic Modeling System (HEC-HMS), with watershed delineation conducted via Geographic Information Systems (GIS). Calibration was based on regional rainfall data from the Peshawar station using a Soil Conservation Service Curve Number (SCS-CN) of 86 and time of concentration calculated using Kirpich’s method. The resulting hydrographs were used in two-dimensional hydraulic simulations using the Hydrologic Engineering Center’s River Analysis System (HEC-RAS) to evaluate water surface elevations, flow velocities, and Froude numbers at each bridge site. The findings reveal that all bridges can convey peak flows without overtopping under current climatic conditions. However, Bridges 3 to 5 experience near-critical to supercritical flow conditions, with velocities ranging from 3.43 to 4.75 m/s and Froude numbers between 0.92 and 1.04, indicating high vulnerability to local scour. Bridge 2 shows moderate risk, while Bridge 1 faces the least hydraulic stress. The applied modeling framework effectively identifies structures requiring priority intervention and demonstrates a practical methodology for assessing flood risk in ungauged, data-scarce, and semi-arid regions. Full article

The Minghuazhen Formation in the Cangdong Sag of the Bohai Bay Basin is a key sedimentary unit for investigating regional provenance evolution, paleoclimate variations, and hydrocarbon potential in Eastern China. This study integrates mineralogical and geochemical analyses to explore sedimentary characteristics. Techniques include X-ray diffraction (XRD), major/trace element compositions, rare earth element (REE) distributions, and organic carbon content. XRD data and elemental ratios (e.g., Al/Ti, Zr/Sc) suggest a predominant felsic provenance, sourced from acidic magmatic rocks. The enrichment with light rare earth elements (LREE: La–Eu) and notable negative Eu anomalies in the REE patterns support the interpretation of a provenance from the Taihangshan and Yanshan Orogenic Belts. Geochemical proxies, such as the Chemical Index of Alteration (CIA) and trace element ratios (e.g., U/Th, V/Cr, Ni/Co), indicate a warm and humid depositional environment, characterized by predominantly oxic freshwater conditions. Organic geochemical parameters, including total organic carbon (TOC), total nitrogen (TN), and C/N ratios, suggest that organic matter primarily originates from aquatic algae and plankton, with C/N values predominantly below 10 and a strong correlation between TOC and TN. The weak correlation between TOC and total carbon (TC) indicates that the organic carbon is mainly biological in origin rather than carbonate-derived. Although the warm and humid climate promoted the production of organic matter, the prevailing oxic conditions hindered its preservation, resulting in a relatively low hydrocarbon generation potential within the Minghuazhen Formation of the Cangdong Sag. These findings provide new insights into the sedimentary evolution and hydrocarbon potential of the Bohai Bay Basin. Full article

Mastitis significantly impacts both the yield and quality of milk. The somatic cell count (SCC) and differential somatic cell count (DSCC), which are related to immune cells, are primary indicators for assessing mammary gland health. In this study, eight previously established mid-infrared spectroscopy models were utilized to predict the content of milk protein fractions (αs1-CN, β-CN, κ-CN, total CN, α-LA, β-LG, IgG, and LF) in milk samples from 21,388 lactating cows across 33 herds. Four linear mixed models were applied to analyze the secretion patterns of milk protein fractions by days in milk (DIM) and parity, their variations under different mastitis conditions, and their associations with the somatic cell score (SCS), DSCC, and immune cell counts (PMN + LYM score (PMN + LYMS) and MAC score (MACS)). The primary findings of the investigation comprised the following: (1) IgG was higher in early lactation, decreased with advancing lactation days, and slightly increased in late lactation, while seven other protein factions decreased from early to peak lactation and increased during mid-to-late lactation. Parity influenced all milk protein fractions except αs1-CN, with total CN, β-CN, and α-LA decreasing and κ-CN, β-LG, IgG, and LF increasing as parity increased (p < 0.05). (2) Mastitis significantly reduced the milk yield, fat percentage, protein percentage, and the contents of total CN, β-CN, κ-CN, and α-LA while increasing β-LG, IgG, and LF. (3) The SCS was negatively correlated with milk yield and α-LA but positively correlated with the fat percentage, protein percentage, κ-CN, β-LG, IgG, and LF. (4) When the DSCC increased to 50%, the milk yield decreased, while the milk protein percentage and κ-CN content significantly increased (p < 0.05). When the DSCC exceeded 50%, the fat percentage, protein percentage, total casein, αs1-CN, β-CN, κ-CN, β-LG, IgG, and LF decreased, while the α-LA content increased (p < 0.05). (5) When the PMN + LYMS increased, the milk yield and α-LA content rose, while the milk fat percentage, the milk protein percentage, and the contents of αs1-CN, β-CN, κ-CN, total CN, β-LG, IgG, and LF decreased (p < 0.05). Conversely, when the MACS increased, the milk yield and α-LA content declined, whereas the milk fat percentage, the milk protein percentage, and the contents of αs1-CN, β-CN, κ-CN, total CN, β-LG, IgG, and LF increased (p < 0.05). This study offers valuable insights into enhancing milk product quality, advancing the early diagnosis and mechanistic research of bovine mastitis, and the sustainable development of the dairy farming industry. Full article

Background/Objectives: This study aimed to assess and compare the elimination of the smear layer and microhardness of dentin in root canals after sequential versus continuous chelation using different agitation techniques. Methods: Sixty-four palatal roots of upper first molars were instrumented to size X3 (Protaper Next files). According to the irrigant solution, samples were assigned to two groups (N = 32/group), 3% NaOCl irrigation followed by 17% EDTA (sequential chelation (SC)), or dual-rinse (3% NaOCl/9% HEDP) irrigation (continuous chelation (CC)). Each group has been divided into four subgroups (n = 8/subgroup), based on agitation techniques used: conventional needle (CN) (control group), EndoActivator (EA), ultrasonic agitation (UAI), and Er.Cr.YSGG 2780 nm (laser). SEM images assessed the smear layer, and Vicker microhardness (VHN) was performed at 50 and 100 µm depths. Data were analyzed using: Kruskal–Wallis, Wilcoxon, and the Mann–Whitney U test. Statistical significance was set at p < 0.05. Results: In the UAI and laser agitation, CC significantly reduced the smear layer presence compared to SC in the apical and coronal thirds, respectively (p < 0.05), and no significant differences were observed in the CN and EA groups between SC and CC (p > 0.05). There were significantly higher VHNs of dentine in CC groups than in SC groups in all sections and depths, except in the apical of the CN group at 50 µm and the coronal section of EA and UAI groups at 100 µm. Conclusions: CC was comparable to SC in smear layer removal. CC had a less detrimental effect on dentin compared with SC. Full article

With the intensification of global climate change, the underground rail transit system of Guangzhou, as a major coastal city, faces severe flood risks. Through field investigations of 313 metro stations, this study identified 472 flood-related risk points, primarily involving water backflow at low-lying stations, insufficient elevation of structural components, and the threat of overbank flooding from adjacent rivers. By integrating GIS-based spatial analysis with the SCS-CN runoff model, an extreme rainfall scenario (534.98 mm) was simulated, revealing a maximum runoff depth of 484.23 mm. Based on these results, it is recommended to raise the flood protection design elevation to 582 mm and install additional waterproof barriers. Optimization strategies include establishing flood protection standards for new stations based on site topography and runoff volume, elevating station platforms or adding waterproof structures at existing stations, and upgrading drainage systems with real-time monitoring and early-warning mechanisms. This study emphasizes the necessity for Guangzhou’s metro system to integrate climate-adaptive urban planning and technological innovation to enhance flood resilience and promote sustainable urban development. Full article

With the acceleration of urbanization and the increased frequency of extreme rainfall events, flooding has emerged as one of the most serious natural disaster problems, particularly affecting riparian cities. This study conducted a flooding risk assessment and an analysis of the driving factors behind flood disasters in the Songhua River Basin utilizing an improved Soil Conservation Service Curve Number (SCS-CN) model. First, the model was improved by slope adjustments and effective precipitation coefficient correction, with its performance evaluated using the Nash–Sutcliffe efficiency coefficient (NSE) and the Root Mean Square Error (RMSE). Second, flood risk mapping was performed based on the improved model, and the distribution characteristics of the flooding risk were analyzed. Additionally, the Geographical Detector (GD), a spatial statistical method for detecting factor interactions, was employed to explore the influence of natural, economic, and social factors on flooding risk using factor detection and interaction detection methods. The results demonstrated that the improvements to the SCS-CN model encompassed two key aspects: (1) the optimization of the CN value through slope correction, resulting in an optimized CN value of 50.13, and (2) the introduction of a new parameter, the effective precipitation coefficient, calculated based on rainfall intensity and the static infiltration rate, with a value of 0.67. Compared to the original model (NSE = 0.71, rRMSE = 19.96), the improved model exhibited a higher prediction accuracy (NSE = 0.82, rRMSE = 15.88). The flood risk was categorized into five levels based on submersion depth: waterlogged areas, low-risk areas, medium-risk areas, high-risk areas, and extreme-risk areas. In terms of land use, the proportions of high-risk and extreme-risk areas were ranked as follows: water > wetland > cropland > grassland > shrub > forests, with man-made surfaces exacerbating flood risks. Yilan (39.41%) and Fangzheng (31.12%) faced higher flood risks, whereas the A-cheng district (6.4%) and Shuangcheng city (9.4%) had lower flood risks. Factor detection results from the GD revealed that river networks (0.404) were the most significant driver of flooding, followed by the Digital Elevation Model (DEM) (0.35) and the Normalized Difference Vegetation Index (NDVI) (0.327). The explanatory power of natural factors was found to be greater than that of economic and social factors. Interaction detection indicated that interactions between factors had a more significant impact on flooding than individual factors alone, with the highest explanatory power for flood risk observed in the interaction between annual precipitation and DEM (q = 0.762). These findings provide critical insights for understanding the spatial drivers of flood disasters and offer valuable references for disaster prevention and mitigation strategies. Full article

The Okavango River is a transboundary waterway that flows through Angola, Namibia, and Botswana, forming a significant alluvial fan in northwestern Botswana. This fan creates a Delta that plays a vital role in the country’s GDP through tourism. While research has primarily focused on the Delta, the river’s catchment area in the Angolan highlands—its main water source and critical for downstream flow—has been largely overlooked. The basin is under pressure from development, water abstraction, and population growth in the surrounding areas, which negatively affect the environment. These challenges are intensified by climate change, leading to increased water scarcity that necessitates improved management strategies. Currently, there is a lack of published research on the basin’s hydrology, leaving many hydrological parameters related to streamflow in the catchments inadequately understood. Most existing studies have employed single-site calibration methods, which fail to capture the diverse characteristics of the basin’s catchments. To address this, a SWAT model has been developed to simulate the hydrologic behaviour of the basin using sequential multisite calibration with data from five gauging stations, including the main river systems: Cubango and Cuito. The SUFI2 program was used for sensitivity analysis, calibration, and validation. The initial sensitivity analysis identified several key parameters: the Soil Evaporation Compensation Factor (ESCO), the SCS curve number under moisture condition II (CN2), Saturated Hydraulic Conductivity (SOL_K), and Moist Bulk Density (SOL_BD) as the most influential. The calibration and validation results were generally satisfactory, with a coefficient of determination ranging from 0.47 to 0.72. Analysis of the water balance and parameter sensitivities revealed the varied hydrologic responses of different sub-watersheds with distinct soil profiles. Average annual precipitation varies from 1116 mm upstream to 369 mm downstream, with an evapotranspiration-to-precipitation ratio ranging from 0.47 to 0.95 and a water yield ratio between 0.51 and 0.03, thereby revealing their spatial gradients, notably increasing evapotranspiration and decreasing water yield downstream. The SWAT model’s water balance components provided promising results, with soil moisture data aligned with the TerraClimate dataset, achieving a coefficient of determination of 0.63. Additionally, the model captured the influence of the El Niño–Southern Oscillation (ENSO) on local hydrology. However, limitations were noted in simulating peak and low flows due to sparse gauge coverage, data gaps (e.g., groundwater abstraction, point sources), and the use of coarse-resolution climate inputs. Full article

More than half of the cultivated land belongs to the Irrigation Association. Therefore, there have been no farmland consolidation, irrigation, and drainage projects. The cultivation in the non-irrigation area suffers from poor geographical conditions and a lack of water sources. A practical planning strategy is required for expanding irrigation services. The mountainous area of Nantou County, Taiwan, has 7477 ha of available land and 4656 ha of agricultural land outside the irrigation area. Rain and streams are the main water source. There are 82 ponds, 80% of which belong to the loam soil, and the rainfall from October to February is limited. The water requirement of crops is 1.5–3.1 mm/day. Wild streams, groundwater, and rainwater are the only potential water sources due to elevation and terrain. The potential runoff is estimated to be 0–0.927 cms (m³/s) when using the SCS-CN method. Water supply and demand from October to April are limited, and the rainfall comprises 22% of the total water supply. Large reservoirs and water storage towers are required for flooding and in dry seasons. To address water storage challenges and stabilize the balance between water supply and demand, it is essential to construct additional ponds. Full article

Background: Inherited white matter (WM) disorders of the central nervous systems (CNS), or leukodystrophies, are devastating diseases that primarily affect children, many of whom die early in life or suffer from long-term disability. Methods: q-Space diffusion MR imaging (QSI) and diffusion tensor MR imaging (DTI) with the same resolution and timing parameters were used to study the spinal cords (SCs) of two myelin mutants that are experimental models of WM diseases of different severity, namely the 28-day-old taiep and Long–Evans Shaker (les) rats. The aim was to verify if and which of the diffusion methodologies used is more suitable for early detection of the milder taiep pathology and to characterize its early phase. We also aimed to compare the diffusion MRI results with quantitative electron microscopy (EM) findings. Results: We found that at this early age (28 days), both QSI and DTI were able to detect the severe les WM pathology, while the milder WM pathology in the SC of the taiep rats was detected only by QSI. An increase in the mean radial displacement (RaDis), representing the MRI axon diameter (AD), and a decrease in the probability for zero displacement (PZD) were observed in the dorsal column (ROI 1) of the taiep SCs. In other WM areas, the same trends were observed but the differences were not of statistical significance. In DTI, we found some lower fractional anisotropy (FA) values in the taiep SCs compared to the controls; however, these differences were not statistically significant. For the more severe les pathology, we observed a dramatic increase in the RaDis values and a large decrease in PZD values in all ROIs examined. There, even the FA values were lower than that of the control SCs in all ROIs, albeit with much smaller statistical significance. These MRI results, which show a higher detectability of WM pathology with heavier diffusion weighting, followed histological findings that showed significant myelin deficiency in the dorsal column in the taiep SCs and a practically complete myelin loss in all WM areas in the les SCs. This study also revealed that, under the experimental conditions used here, the apparent increase in RaDis agrees better with myelin thickness and not with average AD extracted form EM, probably reflecting the effect of water exchange. Conclusions: These results, corroborated by diffusion time-dependent QSI, also imply that while diffusion MRI in general and QSI in particular provide acceptable apparent axon diameter estimations in heathy and mature WM, this appears not to be the case in severely damaged WM where exchange appears to play a more important role. Full article

This study utilizes ArcGIS, the InVEST model, and the SCS model to analyze remote sensing data from the central urban areas of Chengdu. The analysis simulates water yield and runoff within the study area while calculating the water conservation capacity for each land use type using the water balance method. This study aims to address the challenges faced by Chengdu in implementing its sponge city initiatives. The results reveal that the spatial distribution of direct runoff generally follows a pattern of “low in the periphery and high in the center”. Transportation, commercial, industrial, and residential land types account for 74.7% of the total surface runoff within the study area, emphasizing their importance in urban rainwater management and sponge city development. Water yield varies across different land use types, with water bodies exhibiting the lowest capacity and artificial land exhibiting the highest capacity. This pattern initially exhibited a downward trend before increasing, with land use type, climatic factors, and vegetation coverage identified as the primary drivers of water yield. The water conservation capacity of the study area gradually decreased, with higher values observed in the east and south and lower values in the north and west. These trends and spatial differences can be attributed to urban expansion and alterations in land cover. Based on these findings, this study assessed the risk of urban waterlogging and provided recommendations for optimizing low-impact development (LID) strategies. This study provides a scientific foundation for the development of sponge city initiatives, urban waterlogging mitigation, and rainwater management strategies in Chengdu. Full article