COVID-19 and beliefs about tobacco use: an online cross-sectional study in Iran

Environmental Science and Pollution Research - There is mixed evidence surrounding the relationship between tobacco use and COVID-19 infection/progression. The current study investigates beliefs...     

The effect of diazinon on blood glucose homeostasis: a systematic and meta-analysis study

Environmental Science and Pollution Research - Though evidence exists on the association between diazinon (DZN), an organophosphate pesticide, with hyperglycemia, contrasting reports also exist....     

Association between perceived demands and musculoskeletal disorders among hospital nurses of Shiraz University of Medical Sciences: a questionnaire survey.

Excessive demands on nurses may result in high rates of musculoskeletal disorders (MSDs). This study was conducted among hospital nurses of Iran's Shiraz University of Medical Sciences (SUMS) to determine the prevalence of MSDs and to examine the relationship between perceived demands and reported MSDs. In this study, 641 randomly selected nurses from 12 SUMS hospitals participated. The Nordic musculoskeletal disorders questionnaire and Job Content Questionnaire were used as collecting data tools. The results showed that 84.4% of the participants had experienced some form of symptoms of MSDs during the past 12 months. Lower back symptoms were found to be the most prevalent problem. Perceived physical demands were significantly associated with MSDs (OR = 1.5-2.7). No association was found between perceived psychological demands and reported symptoms. It was concluded that any intervention program for preventing MSDs among SUMS hospital nurses had to focus on reducing physical demands, particularly excessive postural demands.     

The interactions of Cr (VI) concentrations and amendments (biochar and manure) on growth and metal accumulation of two species of Salicornia in contaminated soil

Environmental Science and Pollution Research - Heavy metals are among the most dangerous contaminants in the environment. Organic components and plant species that can accumulate and stabilize...     

Strong correlations between metal in mollusk soft tissue and nonresistant sediment fraction: a tool for biomonitoring intertidal zone of the Persian Gulf,Iran

Cadmium (Cd) and lead (Pb) were determined in three species of mollusks and associated sediment. Samples were collected from two locations along the intertidal zone of the Persian Gulf near Bandar Abbas. The study was conducted during the spring of 2011, 10 sediment samples and 15 mollusks from each of the following species: Saccostrea cucullata, Solen brevis, and Callista umbonella, were simultaneously collected. Soft tissue, shell, and sediment were tested for metals using an atomic absorption spectrophotometer. Geochemical fractions of the sediment were examined for metals using a sequential extraction technique. Our results indicate that over half of Cd and Pb in the sediment had natural origins. Independent sample t test showed statistically significant (p?<?0.05) inter-tissue differences in accumulation of Cd and Pb. Soft tissue of C. umbonella contained highest levels of Cd. Pb accumulation was highest in S. brevis shell. Significant correlations (p?<?0.05) were found between Cd in the soft tissue of C. umbonella and its levels in the geochemical fractions of the sediment. Lead levels in the resistant geochemical fractions of the sediment and S. brevis shell were significantly correlated. Our results suggest that soft tissue of C. umbonella and shell of S. brevis are reliable biomonitoring tools for Cd and Pb, respectively.     

Wood Plastic Composite Panels: Influence of the Species,Formulation Variables and Blending Process on the Density and Withdrawal Strength of Fasteners

In this work, the influence of four variable parameters including fiber types (poplar and rice straw), fiber contents (45, 60, and 75 wt%), fiber sizes (20–40 and 40–60 mesh), and blending methods (hot-pressing and extrusion) on the physico-mechanical properties of wood plastic composite panels were studied. Generally, the results showed that each of the above-mentioned parameters had significant effect on the nail and screw withdrawal strength (pull-out load) and density, whereas their interactions did not have highly impressive effects on the properties. All tested properties vary significantly with fiber origin. Composites filled with larger fiber size, produced panels with higher withdrawal strength and density. The effect of blending method on density was maximal. Withdrawal strength values of each sample decreased with increase in fiber loading. The lowest withdrawal strength values of nail and screw were obtained from the samples filled with rice straw. It was found that strength properties of the composites can be improved moderately by adding 45 wt% fiber, 20–40 mesh particle and poplar flour. According to the results, the blending method is a significant variable in the determination of withdrawal strength. Therefore, the blending method can be recommended based on the end product applications.     

Estimation of soil specific surface area using some mechanical properties of soil by artificial neural networks

Soil specific surface area (SSA) is an important property of soil. Depending on the measurement techniques, determination of the SSA is costly and time consuming. Hence, a limited number of studies have been conducted to predict the SSA from the soil variables. In this study, the soil samples were taken from the literature. Fractal parameters (FP) were calculated by the model of Bird et al. (European Journal of Soil Science 51, 55–63, 2000) used as the input variables to predict the SSA. Some studies have been carried out on the prediction capability of the different parameters using the artificial neural networks (ANNs). The ANNs were further used and 20 models were developed to investigate the value of input variables to predict the SSA. The results showed that the PTF13 (RMSE?=?0.13) and PTF18 (RMSE?=?0.13) with the input variables of particle-size distribution and Atterberg limits revealed better performance than the other PTFs (in the training step). It is because of the fact that free swelling index (FSI) and Atterberg limits were closely correlated to the soil clay mineralogy as one of the important factors controlling the SSA. In general, this results demonstrated that the PTF9 with the variables of sand, clay, plastic limit (PL), liquid limit (LL), and FSI showed the best (RMSE?=?0.37) results in the estimation of the SSA. In conclusion, there was not a strong correlation between the soil mechanical properties and SSA but also ANNs were a suitable method to predict the SSA from the soil variables.     

Statistical analysis of arsenic contamination in drinking water in a city of Iran and its modeling using GIS

In this research, probable arsenic contamination in drinking water in the city of Ardabil was studied in 163 samples during four seasons. In each season, sampling was carried out randomly in the study area. Results were analyzed statistically applying SPSS 19 software, and the data was also modeled by Arc GIS 10.1 software. The maximum permissible arsenic concentration in drinking water defined by the World Health Organization and Iranian national standard is 10 μg/L. Statistical analysis showed 75, 88, 47, and 69% of samples in autumn, winter, spring, and summer, respectively, had concentrations higher than the national standard. The mean concentrations of arsenic in autumn, winter, spring, and summer were 19.89, 15.9, 10.87, and 14.6 μg/L, respectively, and the overall average in all samples through the year was 15.32 μg/L. Although GIS outputs indicated that the concentration distribution profiles changed in four consecutive seasons, variance analysis of the results showed that statistically there is no significant difference in arsenic levels in four seasons.     

Electrosorption and photocatalytic one-stage combined process using a new type of nanosized TiO2/activated charcoal plate electrode

In the present study, an activated charcoal (AC) plate was prepared by physical activation method. Its surface was coated with TiO₂ nanoparticles by electrophoretic deposition (EPD) method. The average crystallite size of TiO₂ nanoparticles was determined approximately 28 nm. The nature of prepared electrode was characterized by X-ray diffraction (XRD), scanning electron microscopy (SEM), and Brunauer–Emmett–Teller (BET) surface area measurement before and after immobilization. The electrosorption and photocatalytic one-stage combined process was investigated in degradation of Lanasol Red 5B (LR5B), and the effect of dye concentration, electrolyte concentration, pH, voltage, and contact time was optimized and modeled using response surface methodology (RSM) approach. The dye concentration of 30 mg L^?1, Na₂SO₄ concentration of 4.38 g L^?1, pH of 4, voltage of 250 mV, and contact time of 120 min were determined as optimum conditions. Decolorization efficiency increased in combined process to 85.65 % at optimum conditions compared to 66.03 % in TiO₂/AC photocatalytic, 20.09 % in TiO₂/AC electrosorption, and 1.91 % in AC photocatalytic processes.