Ten different water samples were collected from Ratuwa River and its tributaries. The laboratory test was carried out by standard procedures (APHA methods), and the measured values were compared with the Nepal standard recommended by Nepal Drinking Water Quality Standards (NDWQS). Statistical analysis also had been used to calculate the correlation coefficients and to plot the regression equations of various parameters with electrical conductivity. The aim of the study was to identify the parameters that affect the electrical conductivity and evaluate the percentage contribution of these parameters. The correlation matrix shows that color, total dissolved solids (TDS), chloride (Cl), fluoride (F), total phosphorus (TP), total alkalinity (TA), calcium (Ca), magnesium (Mg), sodium (Na), and dissolved oxygen (DO) have a significant effect on the electrical conductivity (EC). Among these parameters, TDS has the highest contribution (39.65%) followed by total alkalinity (23.5%), total hardness (19.9%), chlorine (6.5%), and calcium (5.5%) ions, respectively. However, color, TP, fluoride, and DO have almost 1.45% contribution to the electrical conductivity.
Monitoring and prediction of the climatic phenomenon are of keen interest in recent years because it has great influence in the lives of people and their environments. This paper is aimed at reporting the variation of daily and monthly solar radiation, air temperature, relative humidity (RH), and dew point over the year of 2013 based on the data obtained from the weather station situated in Damak, Nepal. The result shows that on a clear day, the variation of solar radiation and RH follows the Gaussian function in which the first one has an upward trend and the second one has a downward trend. However, the change in air temperature satisfies the sine function. The dew point temperature shows somewhat complex behavior. Monthly variation of solar radiation, air temperature, and dew point shows a similar pattern, lower at winter and higher in summer. Maximum solar radiation (331 Wm-2) was observed in May and minimum (170 Wm-2) in December. Air temperature and dew point had the highest value from June to September nearly at 29°C and 25°C, respectively. The lowest value of the relative humidity (55.4%) in April indicates the driest month of the year. Dew point was also calculated from the actual readings of air temperature and relative humidity using the online calculator, and the calculated value showed the exact linear relationship with the observed value. The diurnal and nocturnal temperature of each month showed that temperature difference was relatively lower (less than 10°C) at summer rather than in winter.
This paper compares and contrasts the numeral classifier systems of two genetically unrelated languages: Newar of Kathmandu and “Hyoujungo”, Japanese spoken in Tokyo, the defacto official language of Japan. It is not the case either in Newar or in Japanese that nouns in general can be directly quantified by a number. For example, in Newar one cannot say*ni che two house ‘Two houses” for ‘two houses’. Rather, one must say ni-khache ‘two-CL house” Two houses” .The noun che ‘house’ requires that the numeral classifier -kha be affixed to numerals used for counting houses. One might say that che ‘house’ is not conceived of as a separate countable entity. Only when the unit -kha ‘CL’ is suffixed to the number do we have a countable entity. Numeral classifiers: The choice of noun determines the choice of classifier both in Newari and in Japanese. By looking at the nouns associated with a given classifier it is possible to identify the way in which a noun selects its classifier. In Newar there are three different ways in which nouns select their classifiers (1) according to semantic parameters (as when sentient nouns select the classifier -mha, (2) by unique lexical collocation (as when che ‘house’ selects -kha ‘CL’) and (3) by full or partial reduplication (as when ha: ‘leaf’ selects thehead noun ha: itself, where as salakhwa: ‘horse’s hoof’ selects -khwa:, only thelatter portion of the head noun (Hale 2005).These modes can be taken as the basis for a three-term typology of classifier selection: (1) semantic selection, (2) lexical selection, and (3)morphological selection. This paper provides a detailed comparison of Newar and Japanese classifiers within each of these three types of selection. Though all three types are attested in each language, there are mutual counterparts and skewing between the two languages.
Study of uncorrected and corrected Yukawa Potential show that at both Yukawa potential have same nature but strength is different. The strength of uncorrected Yukawa potential is identical at short range while corrected Yukawa potential strength is not identical at short range. Moreover, the strength of uncorrected and corrected Yukawa potential has the same strength at long distances when separated from each other. Uncorrected Yukawa potential is study gives more detail at a short distance while corrected not give such detail at the same distance, for considered elementary particles masses less than the mass of meson. The solution of corrected Yukawa potential show depends upon the quantum number and distance separation between two elementary particles masses less than meson.
This work helps to identify the source of pollution in water and characterize the water quality which is essential to water management for sustainable development. Therefore, the main objective of this work is to evaluate the spatial distribution of the water quality of Ratuwa river and its tributaries. The water samples were collected from six discrete sampling locations and fifteen parameters were tested using respective well-calibrated equipment and standard APHA methods. The physicochemical analysis, water quality index, and correlation matrix method were employed to evaluate the spatial variation of the water quality of Ratuwa river. Turbidity was the most polluting factor in river water. The results showed the spatial variation of the water quality index (WQI) from 39.3 to 70.5, which fell in the range of “good” to “poor” water quality status. None of the water samples was either “excellent” or “unsuitable for drinking.” The water quality was “Poor” upstream and downstream of Ratuwa river due to the high value of turbidity. Chaju river was found to have unpolluted whereas Dipeni river was slightly polluted due to domestic and municipal wastes. Hence, the deterioration of water quality can be attributed to natural and anthropogenic sources.
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