The influence of sociopolitical,natural, and cultural factors on international tourism growth: a cross-country panel analysis

This study employed a cross-country panel data model to investigate the relative contributions of sociopolitical, natural and cultural characteristics and national tourism policies to international tourism growth. International tourism receipt data were adjusted for country-specific inflation and then analyzed in relation to standardized measures of the World Economic Forum’s “pillars of tourism competitiveness.” Results indicated that international tourism receipts are more responsive to policies and regulations favoring tourism, abundance of natural resources, richness in cultural heritage, and health and hygiene than they are to infrastructure, safety, price competitiveness, and other variables. Findings highlight key factors associated with international tourism receipts and provide a general framework that could inform policies and management strategies designed to promote sustainable international tourism development.     

Solar oxidation and removal of arsenic from water: An experimental study

Arsenic poses a significant threat to both human health and the environment. Arsenic removal through solar oxidation has been investigated in a batch process. Arsenic was artificially added to both deionized and tap water to conduct the experiments. Clean, colorless, transparent, Polyethylene Terephthalate (PET) bottles were used for Solar Oxidation and Removal of Arsenic (SORAS) experiments. Various parameters including concentration of arsenic, iron, and photo-catalyst were varied during the experiments. The maximum arsenic removal efficiency obtained was 94% and 88% for deionized water and tap water respectively when ferrous ammonium sulphate and lemon juice were used. Maximum efficiency of 88% and 82% was obtained for deionized and tap water respectively when locally available ferrous alum and glacial acetic acid were used. The change in volume of the photo-catalyst (lemon juice and glacial acetic acid) also did not affect the SORAS process significantly. Therefore, the recommended volume for the photo-catalyst was 1–2 ml/L. SORAS can very well be used for areas contaminated with arsenic having concentrations less than 100 μg/L.     

Decolorization of structurally different synthetic dyes using cobalt(II)/ascorbic acid/hydrogen peroxide system

The cobalt(II)/ascorbic acid/hydrogen peroxide system was used for decolorization of azo, acridine, anthraquinone, thiazine and triphenylmethane dyes. More than 90% decolorization was obtained with all dyes except Remazol Brilliant Blue R (75%). With other transition metals the system was less efficient. With copper, higher concentration and prolonged incubation time was necessary to obtain the same extent of decolorization. The rate of decolorizaton was not affected by pH in the range of 3-9. The reaction is very fast, with more than 90% decolorization being attained within 15 min. The system produces hydroxyl radicals which are responsible for the decolorization.     

Copper-ligand complex for the decolorization of synthetic dyes

The reaction system containing Cu(II), hydrogen peroxide and D-arabinono-1,4-lactone was found to be effective in the decolorization and reduction of toxicity of azo, thiazine-, triphenylmethane- and anthraquinone-based synthetic dyes. More than 85% decolorization was obtained with 100ppm Acridine Orange, Azure B, Chicago Sky Blue 6B, Crystal Violet, Evans Blue, Poly B-411, Reactive Blue 2, Reactive Blue 5, and Remazol Brilliant Blue R incubated for 24h in the presence of 10mM CuSO(4), 20mM D-arabinono-1,4-lactone and 80 mM H(2)O(2). The rate of decolorization was not affected by pH in the range of 3-9. The rapid decolorization was accompanied by a fast decomposition of H(2)O(2) in the reaction mixture and by a fast production of hydroxyl radicals.     

Gender differences in the metabolism of benzene,toluene and trichloroethylene in rat with special reference to certain biochemical parameters

Metabolites viz. phenol, hippuric acid and total trichloro compounds of benzene, toluene and trichloroethylene respectively were estimated in the urine samples of male and female rats after exposure for a period of 30 days. The results exhibited higher metabolism in female rats than the male rats. Their metabolism might be regulated by cytochrome P450 isozymes in a gender specific manner. However, sex differences in the activity of glutathione-S-transferases of the liver have also been found to determine their toxicity. Results have been discussed with quantitative profiles of other enzymes established in the liver of male and female rats.     

A data-mining approach to predict influent quality

In wastewater treatment plants, predicting influent water quality is important for energy management. The influent water quality is measured by metrics such as carbonaceous biochemical oxygen demand (CBOD), potential of hydrogen, and total suspended solid. In this paper, a data-driven approach for time-ahead prediction of CBOD is presented. Due to limitations in the industrial data acquisition system, CBOD is not recorded at regular time intervals, which causes gaps in the time–series data. Numerous experiments have been performed to approximate the functional relationship between the input and output parameters and thereby fill in the missing CBOD data. Models incorporating seasonality effects are investigated. Four data-mining algorithms—multilayered perceptron, classification and regression tree, multivariate adaptive regression spline, and random forest—are employed to construct prediction models with the maximum prediction horizon of 5 days.     

Optimizing removal of ibuprofen from water by magnetic nanocomposite using Box–Behnken design

Purpose  

The present research aims to optimize the removal of ibuprofen (IBP), a non-steroidal anti-inflammatory, analgesic, and antipyretic drug from the aqueous solution using a synthesized magnetic carbon–iron nanocomposite, and to investigate the individual and combined effects of the independent process variables.