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Dental caries is the single most common chronic childhood disease affects children ages five through seventeen years. Prevalence of dental caries five times more common than asthma and seven times more common than hay fever and it is very high in developing countries. Prevention of dental caries is very important in school children. So continuous educational programme should be conducted in schools. The study was carried out to assess the knowledge of regarding prevention of dental cries of mothers of preschooler children selected villages of Sasaram with a view to develop an information booklet. The study was based on health believe model. Objectives: To assess the existing knowledge regarding prevention of dental caries among mothers of preschooler children of selected villages of Sasaram. To find out association between the level of knowledge with their selected demographical data. To develop and distribute an information booklet. Methodology: A one Experimental descriptive approach his used to for this study as it is considered as suitable one to assess the level of knowledge regarding prevention of dental caries. The research design for the study Descriptive design. Result: In order to collect the data, we the result show of the study in there 50 sample (22%) preschooler children Average mothers of knowledge, (74%) preschooler children moderate mother knowledge and (4%) preschooler children mothers’ good knowledge. Those mothers know about dental carries prevent dental carries. Statically there is no any significant association was found. Recommendation: The findings of the present study can be used as a guide of future research. Interventional study can be undertaken to reduce the dental carries. A study can be conducted in preventing aspect of dental carries. To make the recommendation to the government to arrange compulsory medical check-upon they early basis for the nursing personnel. Conclusion: The present study was aimed at assessing the knowledge of mothers of prevention of dental caries among preschooler children sand its consequences. This show that these variables had influence dental caries in the study.

River bankline migration is a frequent phenomenon in the river of the floodplain region. Nowadays, channel dynamics-related changes in land use and land cover (LULC) are becoming a risk to the life and property of people living in the vicinity of rivers. A comprehensive evaluation of the causes and consequences of such changes is essential for better policy and decision-making for disaster risk reduction and management. The present study assesses the changes in the Brahmaputra River planform using the GIS-based Digital Shoreline Analysis System (DSAS) and relates it with the changing LULC of the floodplain evaluated using the CA-Markov model. In this study, the future channel of the Brahmaputra River and its flood plain’s future LULC were forecasted to pinpoint the erosion-vulnerable zone. Fortyeight years (1973–2021) of remotely sensed data were applied to estimate the rate of bankline migration. It was observed that the river’s erosion-accretion rate was higher in early times than in more recent ones. The left and right banks’ average shifting rates between 1973 and 1988 were 55.44 m/y and 56.79 m/ y, respectively, while they were 17.25 m/y and 48.49 m/y from 2011 to 2021. The left bank of the river Brahmaputra had more erosion than the right, which indicates that the river is shifting in the leftward direction (Southward). In this river course, zone A (Lower course) and zone B (Middle course) were more adversely affected than zone C (Upper course). According to the predicted result, the left bank is more susceptible to bank erosion than the right bank (where the average rate of erosion and deposition was 72.23 m/y and 79.50 m/y, respectively). The left bank’s average rate of erosion was 111.22 m/y. The research assesses the LULC study in conjunction with river channel dynamics in vulnerable areas where nearby infrastructure and settlements were at risk due to channel migration. The degree of accuracy was verified using the actual bankline and predicted bankline, as well as the actual LULC map and anticipated LULC map. In more than 90% of cases, the bankline’s position and shape generally remain the same as the actual bankline. The overall, and kappa accuracy of all the LULC maps was more than 85%, which was suitable for the forecast. Moreover, chi-square (x2 ) result values for classified classes denoted the accuracy and acceptability of the CA-Markov model for predicting the LULC map. The results of this work aim to understand better the efficient hazard management strategy for the Brahmaputra River for hazard managers of the region using an automated prediction approach.

Natural fibers have been in researchers’ attention these days for their low cost, availability, ease of manufacturing and potential environment friendliness for studying their feasibility as reinforcing agents in composites. Numerous research works are being carried out across the globe to increase the thermal, tribological as well as mechanical properties of these engineered biocomposites and they have proved their potential in wide range of applications including bio-medical and bio-technological fields. This review aims to discuss the mechanical properties attained by the composite after natural fiber reinforcement and the various factors affecting the mechanical properties of the natural fiber composites (NFCs). It also focuses on the applicability of natural fibers as a substitute for synthetic fibers in large domain of application.

Planning for a sustainable future involves understanding the past and present problems associated with urban centers. Rapid urbanization has caused significant adverse impacts on the environment and natural resources. In cities, one such impact is the unsettling urban growth, resulting in the urban heat island (UHI) effect, which causes considerable positive feedback in the climate system. It can be assessed by investigating the relationships between urban Land Use/Land Cover (LULC) changes and changes in land surface temperature. This study links the urban transformations in Bangalore, India, between 2001 and 2021, with the city’s changing average land surface temperatures. LULC classification was performed on Landsat satellite images for the years 2001, 2011, and 2021, using the support vector machine (SVM) classification algorithm. LULC change analysis revealed an increase in the built-up area coinciding with a decreasing trend of water bodies, vegetation, and the area under the others (wasteland/open land/barren land) category. The results show that built-up increased from 462.49 km2 to 867.73 km2, vegetation decreased from 799.4 km2 to 485.72 km2, and waterbody declined from 34.28 km2 to 24.69 km2 in 20 years. The impact of urbanization was evident in Bangalore’s land temperature changes between 2001 and 2021, showing the average temperature increased by 0.34 °C per year between the highest UHI events, contrary to 0.14 °C per year in non-urbanized areas. It is hoped that the results of this study can help the urban planners of Bangalore city identify critical areas where improvement in urban dwelling could be planned sustainably according to the global smart cities concept, an offshoot concept of the Sustainable Development Goal (SDG)-11.

Globally, estimating crop acreage and yield is one of the most critical issues that policy and decision makers need for assessing annual crop productivity and food supply. Nowadays, satellite remote sensing and geographic information system (GIS) can enable the estimation of these crop production parameters over large geographic areas. The present work aims to estimate the wheat (Triticum aestivum) acreage and yield of Maharajganj, Uttar Pradesh, India, using satellite-based data products and the Carnegie-Ames-Stanford Approach (CASA) model. Uttar Pradesh is the largest wheat-producing state in India, and this district is well known for its quality organic wheat. India is the leader in wheat grain export, and, hence, its monitoring of growth and yield is one of the top economic priorities of the country. For the calculation of wheat acreage, we performed supervised classification using the Random Forest (RF) and Support Vector Machine classifiers and compared their classification accuracy based on ground-truthing. We found that RF performed a significantly accurate acreage assessment (kappa coefficient 0.84) compared to SVM (0.68). The CASA model was then used to calculate the winter crop (Rabi, winter-sown, and summer harvested) wheat net primary productivity (NPP) in the study area for the 2020–2021 growth season using the RF-based acreage product. The model used for wheat NPP-yield conversion (CASA) showed 3100.27 to 5000.44 kg/ha over 148,866 ha of the total wheat area. The results showed that in the 2020–2021 growing season, all the districts of Uttar Pradesh had similar wheat growth trends. A total of 30 observational data points were used to verify the CASA model-based estimates of wheat yield. Field-based verification shows that the estimated yield correlates well with the observed yield (R2 = 0.554, RMSE = 3.36 Q/ha, MAE −0.56 t ha−1, and MRE = −4.61%). Such an accuracy for assessing regional wheat yield can prove to be one of the promising methods for calculating the whole region’s agricultural yield. The study concludes that RF classifier-based yield estimation has shown more accurate results and can meet the requirements of a regional-scale wheat grain yield estimation and, thus, can prove highly beneficial in policy and decision making.

In September 2014, Kashmir witnessed a catastrophic flood resulting in a significant loss of lives and property. Such massive losses could have been avoided if any structural support such as dams were constructed in the Jhelum basin, which has a history of devastating floods. The GIS-based multicriteria analysis (MCA) model provided three suitability zones for dam locations. The final suitable dam sites were identified within the highest suitability zone based on topography (cross-sections), stream order, high suitable zone, minimum dam site interval, distance from roads, and protected area distance to the dam site. It was discovered that 10.98% of the total 4347.74 km2 area evaluated falls in the high suitability zone, 28.88% of the area falls in the medium suitability zone, and 60.14% of the area falls in the low suitability zone. Within the study area, four viable reservoir sites with a holding capacity of 4,489,367.55 m3 were revealed.

The present study provides assessment of wasteland development in Bihar State based on satellite data. Wasteland covers 6.90 % (6,501 km2) of the state area and exhibits dominance of waterlogged areas in North Bihar (25.28 %) and scrubland (26.61 %) in South Bihar. The waterlogged areas in the state are dominantly associated with northern Bihar plains (94 %) with minor development (6 %) in southern Bihar plains. Such unequal distribution of waterlogged land areas in northern and southern Bihar plains is largely governed by high cumulative discharge generated in the large catchment area in Himalayan mountain ranges in the upland areas of northern Bihar plains in contrast to low cumulative discharge generated within small catchments in the Chota Nagpur Plateau in the southern Bihar plains. It is evaluated that the relief and groundwater level define the primary controlling factors, whereas rainfall, watershed area, and upland/plain ratio exert secondary control. Lower relief areas with high rainfall exhibit high soil moisture thereby inducing conditions of waterlogging. The study signifies the potential of satellite image-based evaluation of waterlogging through the use of Digital Elevation Model, Tropical Rainfall Measuring Mission-based rainfall measurement, and temporal waterlogging assessment together with other terrain parameters for conceptual understanding of waterlogging in northern Bihar plains.

In the present study, the multi-temporal satellite images of IRS P6 LISS III were used to map waterlogging dynamics over different seasons. An area of 594.36 km2 (6.75%) and 4.17 km2 (0.04%) was affected by surface waterlogging during pre and postmonsoon season, respectively. The average annual groundwater level fluctuations were calculated using 18 years (1990–2007) pre and postmonsoon groundwater level data to identify the areas which are under groundwater induced waterlogging conditions. The soil map clearly indicates that salinity and sodicity exhibit the highest severity and occur in areas with shallow groundwater levels. The hydrogeomorphical units mapped using IRS P6 LISS III satellite images are flood plain, alluvial plain, paleochannels, and oxbow lakes. The study revealed that 44.65% areas have very good to excellent groundwater resources. The litholog data clearly indicate an alternating sequence of clay and sand in which deep aquifers made up of coarse sand would be best suited for ad...

Historical to recent spatial variability in surface waterlogging was evaluated using a topographical map of 1925 and satellite images of 1975, 1988, 1999 and 2006. A visual satellite image interpretation technique was used to delineate waterlogged areas and associated infrastructure details. Areas of 31, 73.89, 163.86, 143.61 and 102.59 km2 were found to be affected by surface waterlogging during 1925, 1975, 1988, 1999 and 2006, respectively. A sharp increase in waterlogging from 1925 to 1975 is attributed to the functioning of irrigation projects in the region. The very high areas under waterlogging during 1988 and 1999 reflect intensification of agricultural activity. A substantial decrease in waterlogging during 2006 is attributed to the implementation of government wasteland reclamation measures. The area statistics of waterlogging computed for the buffer zone along select features showed that the maximum waterlogging occurs along canals and railways followed by rivers and the least along roads.