Silver nanoparticle reinforced polylactic acid and gelatin composite films for advanced wound dressing.

Multifunctional and biodegradable dressings with high mechanical strength and good antibacterial activity are crucial in fundamental health services. This study was initiated to prepare a novel curative wound dressing film consisting of natural biodegradable gelatin (G) and polylactic acid (PLA) with silver nanoparticles (AgNPs) where glutaraldehyde (GA) was used as compatibilizer. The prepared composite films addressed the poor thermal and biological stability of G and the limited fluid retention capacity of PLA. Silver nanoparticles were prepared by basic chemical reduction and reinforced on polymer films using simple solvent casting, which obviated common clinical infections and accelerated wound closure rate (p < .05). Fourier transform infrared (FTIR) studies confirmed composite formation through H-bonding and X-ray diffraction (XRD) revealed increased crystallinity due to incorporating AgNPs. Films with G, PLA & GA (50:50:5 by volume) introduced the best elasticity & strength with excellent fluid retention properties (p < .05). Scanning electron microscopy (SEM) images unfolded surface morphology and presence of agglomerated AgNPs on film surfaces. Prepared films exhibited significant antimicrobial efficacy against Staphylococcus aureus and Pseudomonas sp. and showed excellent cell viability (>97 %) in Vero cell line. Finally, an in vivo mouse model study showed 99.7 % contraction (p < .05) within 12 days, which was most effectual and 12 % faster than conventional gauge bandages. These results demonstrated the promising and cost-effective potential of the prepared film for wound healing.

Spatial pattern identification and crash severity analysis of road traffic crash hot spots in Ohio.

Safety experts and transportation departments are focused on reducing road accidents and their societal and economic effects. The most crucial step in establishing a successful road safety practice is identifying dangerous highway zones through the study of crashes and looking at how the location of accidents relates to surrounding geography and other factors. Using the latest cutting-edge GIS analytical methods, this study aims to map the locations of accident hot spots and evaluate the severity and spatial extent of crash occurrences in Ohio. Road traffic crash (RTC) data has been analyzed using sophisticated GIS-based hot spot analysis for decades by safety researchers. Using four years' worth of crash data from the state of Ohio and spatial autocorrelation analysis, this study aims to show how a GIS technique can be used to find places where accidents are likely to happen (2017-2020). The study analyzed and ranked crash hotspot areas using the matching severity levels of RTCs. Cluster zones of high and low crash severity were discovered using the spatial autocorrelation tool and the Getis Ord Gi* statistics tool to evaluate the distribution of RTCs. The analysis used Getis Ord Gi*, the crash severity index, and Moran's I spatial autocorrelation of accident events. The findings indicated that these techniques were useful for identifying and rating crash hotspot locations. Since the sites of the identified accident hotspots are located in significant cities in the state of Ohio, such as Cleveland, Cincinnati, Toledo, and Columbus, the organizations in charge of traffic management should make it their top priority to minimize the negative socioeconomic impact that RTCs have and should also conduct a thorough investigation. This study's contribution is the incorporation of crash severity into hot spot analysis using GIS, which could lead to better-informed decision-making in the realm of highway safety.

Development of potential map for groundwater abstraction in the northwest region of Bangladesh using RS-GIS-based weighted overlay analysis and water-table-fluctuation technique.

The increasing trend of population growth along with the rapid groundwater-based agricultural expansion and decreasing trend of mean annual rainfall in the Northwest region of Bangladesh has been exacerbating the declination of groundwater for further expansion. Therefore, the present study attempts to demarcate the potential groundwater abstraction zones from the assessment of potential recharge and available recharge. Potential recharge was obtained with commonly used geospatial-based weighted linear combination (WLC) technique. Here, WLC analysis was based on eight factors related to physiographic (e.g. drainage density, lineament density, slope), geomorphologic (e.g. geomorphology, lithology, soil), land use and land cover (LULC) and hydrology (i.e. rainfall). Available net recharge was assessed for the period 1993-2017 by employing the water table fluctuation method. Finally, the resultant map on potential abstraction was characterized into five different classes, viz. 'very low', 'low', 'moderate', 'high' and 'very high'. The derived map reveals that 'very high' potential zone is distributed along the Teesta river floodplain, especially the northeastern part. In contrast, the Barind Tract (i.e. the southwestern and the southcentral parts) area shows 'very low' groundwater prospect. Such fused interpretations are expected to contribute to the planning of integrated management of water resources.

Risk factors, incidence, and prevalence of diabetes among rural farm and non-farm residents of Saskatchewan, Canada; a population-based longitudinal cohort study.

PURPOSE: Saskatchewan has a high prevalence of diabetes. It is the largest, rurally populated, predominantly agricultural province in Canada. This research aims to determine the risk factors associated with the incidence and longitudinal changes in the prevalence of diabetes among Saskatchewan's adult rural farm and non-farm residents. METHODS: The Saskatchewan Rural Health Study (SRHS) is a prospective cohort study conducted in two phases: a baseline survey (2010, 8261 participants) and a follow-up survey (2014, 4867 participants). Generalized estimation equations and survival analysis techniques were used to determine diabetes prevalence and incidence risk factors, respectively. RESULTS: Incidence of diabetes among rural residents was 2.75%. Positive family history, high BMI, sleep apnea and an abnormal Epworth Sleepiness Score (ESS) were significant predictors for diabetes incidence. A substantial increase (1.98%) of diabetes prevalence was observed after four years of follow-up. Risk factors of diabetes prevalence were increasing age, male, low income, positive family history, high BMI, hypertension and heart attack. CONCLUSION: A mix of individual and contextual factors interacting in complex pathways were responsible for the high incidence and prevalence of diabetes among rural residents. The most original finding of that study was a positive association of sleep apnea, and ESS with incident diabetes warrants further research to identify a causal linkage. Increased diabetes risk among rural male insecticide users indicates an adverse consequence of unprotected chemical exposures in the agricultural field. Urgent population-based preventive measures should initiate to slow the increasing trend of diabetes prevalence among rural residents.

Entropy of mixing for Ag(x)In(1-x) and Ag(x)Sn(1-x) liquid binary alloys.

The entropy of mixing for Ag(x)In(1-x) and Ag(x)Sn(1-x) liquid binary alloys has been systematically investigated by using the perturbation theory. The interionic interactions as one of the basic ingredients are described by a local model pseudopotential. Since the metals forming the concerned alloys are less simple in nature the effect of the sp-d hybridization is appropriately taken into account through the interionic interactions. Results of our calculations across the full range of Ag concentrations are found to be good in agreement with the available experimental data.