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Rainfall-runoff is the active agent of soil erosion which often resulted in land degradation and water quality deterioration. Its aggressiveness to induce erosion is usually termed as rainfall erosivity index or factor (R). R-factor is one of the factors to be parameterized in the evaluation of soil loss using the Universal Soil Loss Equation and its reversed versions (USLE/RUSLE). The computation of accurate R-factor for a particular watershed requires high temporal resolution rainfall (pluviograph) data with less than 30-minutes intensities for at least 20 yrs, which is available only in a few regions of the world. As a result, various simplified models have been proposed by researchers to evaluate R-factor using readily available daily, monthly or annual precipitation data. This study is thus aimed at estimating R-factor and to establish an approximate relationship between R-factor and rainfall for subsequent usage in the estimation of soil loss in Cameron highlands watershed. The results of the analysis showed that the least and peak (critical) R-factors occurred in the months of January and April with 660.82 and 2399.18 MJ mm ha -1 h -1 year -1 respectively. Also, it was observed that erosivity power starts to increase from the month of January through April before started falling in the month of July. The monthly and annual peaks (critical periods) may be attributed to increased rainfall amount due to climate change which in turn resulted to increased aggressiveness of rains to cause erosion in the study area. The correlation coefficient of 0.985 showed that there was a strong relationship rainfall and R-factor.

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The study examined the adsorption of hexavalent chromium [Cr(vi)] from aqueous solution by acidically prepared rice husk carbon (APRHC).

Land use land cover (LULC) has altered dramatically because of anthropogenic activities, particularly in places where climate change and population growth are severe. The geographic information system (GIS) and remote sensing are widely used techniques for monitoring LULC changes. This study aimed to assess the LULC changes and predict future trends in Selangor, Malaysia. The satellite images from 1991–2021 were classified to develop LULC maps using support vector machine (SVM) classification in ArcGIS. The image classification was based on six different LULC classes, i.e., (i) water, (ii) developed, (iii) barren, (iv) forest, (v) agriculture, and (vi) wetlands. The resulting LULC maps illustrated the area changes from 1991 to 2021 in different classes, where developed, barren, and water lands increased by 15.54%, 1.95%, and 0.53%, respectively. However, agricultural, forest, and wetlands decreased by 3.07%, 14.01%, and 0.94%, respectively. The cellular automata-artificial neural network (CA-ANN) technique was used to predict the LULC changes from 2031–2051. The percentage of correctness for the simulation was 82.43%, and overall kappa value was 0.72. The prediction maps from 2031–2051 illustrated decreasing trends in (i) agricultural by 3.73%, (ii) forest by 1.09%, (iii) barren by 0.21%, (iv) wetlands by 0.06%, and (v) water by 0.04% and increasing trends in (vi) developed by 5.12%. The outcomes of this study provide crucial knowledge that may help in developing future sustainable planning and management, as well as assist authorities in making informed decisions to improve environmental and ecological conditions.

The current study deals with the detailed morphology investigation of eight Cypsela species belonging to tribe Cichoreae. The different Cypsela types were described, explained, compared, and their taxonomic significance is discussed in detail. Light microscopy (LM) and scanning electron microscopy (SEM) have been used to highlight quantitative and qualitative characters of underestudied species. Cypsela exhibit great diversity in macro and micromorphological features such as shape, color, length, width, anticlinal and periclinal wall patterns, surface patterns, epicuticular projections. Majority of Cypsela species were brownish in color and their size ranges from 2.16 to 3.98 mm in length and 1.16 to 0.82 mm in breadth. A great diversity in Cypsela shapes like oblanceolate to obovate, obovoid to cylindrical, obvate, narrowly lanceolate were observed. Most of the platelets having epicuticular projections were observed. The surface pattern on the cypsela surface varied from rugose papillate, verrucose papillate, and striated. On the basis of considerable variations observed, the present study can assist as useful constraints at various taxonomic levels. The aim of the present study is to provide a comprehensive description of the Cypsela morphology and to determine the extent to which these micro morphological data can be used as a taxonomic character to delineate various taxa belonging to the tribe Cichoreae.

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