Effect of titanium dioxide nanoparticles on the expression of apoptotic markers in mouse blastocysts

Oocyte maturation, embryo development and expression of apoptotic-specific genes were evaluated in blastocysts of mice treated with titanium dioxide nanoparticles. Female mice received 0, 50 or 100?mg/kg/day titanium dioxide intraperitoneally for five consecutive days. After the last injection, pregnant mare serum gonadotropin and, 48?h later, human chorionic gonadotropin were administered intraperitoneally for induction of ovulation. After 14?h, mice were sacrificed and oocytes were collected. The number of mature oocytes was evaluated and then fertilization was carried out in vitro and the numbers of fertilized and cleaved oocytes and of blastocysts and the expression of Bax, caspase 3, and Bcl-xL genes in blastocysts were evaluated. The number of mature, fertilized and cleaved oocytes and of blastocyst embryos in the experimental groups were not different from control. The expression of Bax and caspase 3 genes was significantly elevated in the experimental groups compared to control, while expression of the Bcl-xL gene was significantly lower in the high dose group. Uptake of titanium dioxide nanoparticles at daily doses of 50?mg/kg and more may affect embryo development by alteration of pro-apoptotic and anti-apoptotic gene expression.     

A metric-based assessment of climate and tourism in major cities of Pakistan

Environment, Development and Sustainability - Tourism plays an essential role in the economic development of a country and has become a growing phenomenon of global importance. The climate change...     

Real-world fuel use and gaseous emission rates for flex fuel vehicles operated on E85 versus gasoline

Flex fuel vehicles (FFVs) typically operate on gasoline or E85, an 85%/15% volume blend of ethanol and gasoline. Differences in FFV fuel use and tailpipe emission rates are quantified for E85 versus gasoline based on real-world measurements of five FFVs with a portable emissions measurement system (PEMS), supplemented chassis dynamometer data, and estimates from the Motor Vehicle Emission Simulator (MOVES) model. Because of inter-vehicle variability, an individual FFV may have higher nitrogen oxide (NO_x) or carbon monoxide (CO) emission rates on E85 versus gasoline, even though average rates are lower. Based on PEMS data, the comparison of tailpipe emission rates for E85 versus gasoline is sensitive to vehicle-specific power (VSP). For example, although CO emission rates are lower for all VSP modes, they are proportionally lowest at higher VSP. Driving cycles with high power demand are more advantageous with respect to CO emissions, but less advantageous for NO_x. Chassis dynamometer data are available for 121 FFVs at 50,000 useful life miles. Based on the dynamometer data, the average difference in tailpipe emissions for E85 versus gasoline is ?23% for NO_x, ?30% for CO, and no significant difference for hydrocarbons (HC). To account for both the fuel cycle and tailpipe emissions from the vehicle, a life cycle inventory was conducted. Although tailpipe NO_x emissions are lower for E85 versus gasoline for FFVs and thus benefit areas where the vehicles operate, the life cycle NO_x emissions are higher because the NO_x emissions generated during fuel production are higher. The fuel production emissions take place typically in rural areas. Although there are not significant differences in the total HC emissions, there are differences in HC speciation. The net effect of lower tailpipe NO_x emissions and differences in HC speciation on ozone formation should be further evaluated.

Implications: Reported comparisons of flex fuel vehicle (FFV) tailpipe emission rates for E85 versus gasoline have been inconsistent. To date, this is the most comprehensive evaluation of available and new data. The large range of inter-vehicle variability illustrates why prior studies based on small sample sizes led to apparently contradictory findings. E85 leads to significant reductions in tailpipe nitrogen oxide (NO_x) and carbon monoxide (CO) emission rates compared with gasoline, indicating a potential benefit for ozone air quality management in NO_x-limited areas. The comparison of FFV tailpipe emissions between E85 and gasoline is sensitive to power demand and driving cycles.     

Wavelet transform-based artificial neural networks (WT-ANN) in PM10 pollution level estimation, based on circular variables

Introduction  

In this paper, a novel method in the estimation and prediction of PM₁₀ is introduced using wavelet transform-based artificial neural networks (WT-ANN).     

Decision-making for sustainable location of a cement plant in the state of Florida

Site selection is a typical strategic decision for many industries that deals with specifying the most appropriate location for a facility. In the context of sustainable development, site selection decisions need to be improved by adopting environmental, economic and social requirements. This study aims to frame sustainable location decisions by conducting a case study of siting a new cement plant in the state of Florida. As a part of the study, a wide range of technical and sustainability criteria has developed. These criteria can help decision-makers in the cement industry evaluate the selection of a location with the requirements of sustainable development. The sustainability characteristics of alternative sites in the state of Florida are evaluated based on the criteria to identify the most appropriate ones. The analytical hierarchy processand geographic information system techniques are utilized to weight the criteria and evaluate the characteristics of site candidates.     

Dynamic risk assessment using failure assessment and Bayesian theory

To ensure the safety of a process system, engineers use different methods to identify the potential hazards that may cause severe consequences. One of the most popular methods used is quantitative risk assessment (QRA) which quantifies the risk associated with a particular process activity. One of QRA's major disadvantages is its inability to update risk during the life of a process. As the process operates, abnormal events will result in incidents and near misses. These events are often called accident precursors. A conventional QRA process is unable to use the accident precursor information to revise the risk profile. To overcome this, a methodology has been proposed based on the work of Meel and Seider (2006). Similar to Meel and Seider (2006) work, this methodology uses Bayesian theory to update the likelihood of the event occurrence and also failure probability of the safety system. In this paper the proposed methodology is outlined and its application is demonstrated using a simple case study. First, potential accident scenarios are identified and represented in terms of an event tree, next, using the event tree and available failure data end-state probabilities are estimated. Subsequently, using the available accident precursor data, safety system failure likelihood and event tree end-state probabilities are revised. The methodology has been simulated using deterministic (point value) as well as probabilistic approach. This Methodology is applied to a case study demonstrating a storage tank containing highly hazardous chemicals. The comparison between conventional QRA and the results from dynamic failure assessment approach shows the significant deviation in system failure frequency throughout the life time of the process unit.     

Cytotoxic and genotoxic evaluation of bisphenol S on onion root tips by Allium cepa and comet tests

Environmental Science and Pollution Research - Bisphenol S (BPS) is an analog of bisphenol A, which is used as substitute of BPA in many products like airport luggage tags, baby bottles, plastics,...     

A case–control study on the relationship between urine trace element levels and autism spectrum disorder among Iranian children

Autism spectrum disorder (ASD) is a type of neurodevelopmental disorder characterized mainly by qualitative deficiencies in social communication skills, accompanied by repetitive and restricted behavior patterns. This study was conducted to investigate the associations between the risk of ASD development in children and exposure to trace elements (arsenic (As), cadmium (Cd), chromium (Cr), cobalt (Co), copper (Cu), lead (Pb), nickel (Ni), and zinc (Zn)). Two groups of children, including 44 ASD and 35 typically developing (TD) children, were selected, and their fasting urine samples were obtained. The concentration levels of trace elements were assayed using ICP-MS. The results showed that as compared to the TD group, the concentration levels of As (p = 0.002) and Pb (p < 0.001) and also Cr (p < 0.001), Cu (p = 0.001), and Ni (p < 0.001) were significantly higher among ASD children. In terms of gender, boys with ASD showed elevated levels of Cr, Cu, Ni, and Pb, whereas the urine levels of As, Cr, Cu, Ni, and Pb were markedly higher among girls when compared to the non-ASD children. Under the logistic regression model, the risk difference for As, Co, Cr, Cu, Ni, Pb, and Zn remained significant when adjustment was applied for age and gender confounders.

     

Multivariate statistical evaluation of heavy metals in the urine of opium individuals in comparison with healthy people in Western Iran

Environmental Science and Pollution Research - The current study aimed to evaluate the levels of some toxic and essential elements (Pb, Cd, Cu, Ti, Ni, Cr, Co, Fe, Ca, Hg, Mn, Se, and Zn) in the...     

Modeling a periodic electric vehicle–routing problem considering delivery due date and mixed charging rates using metaheuristic method

The coupling of ever-increasing consumption of fossil fuels around the globe with the decrease in the availability of fossil fuel supplies has led to an increased cost of energy commodities, which together with ever-expanding requirements for reducing the level of environmental pollutions has resulted in an ever-increasing deal of attention to alternative transportation schemes such as electric vehicles (EVs). Since decades ago, national governments and environmental activists have initiated various efforts towards reducing atmospheric pollutions. A part of such effort has been focused on reducing the use of internal combustion vehicles and rather replacing them with EVs. In this research, we attempt to fill in this research gap by presenting a mathematical model for minimizing the sum of traveled distance and recharging cost of EVs per a given period and then solving it by simulated annealing (SA) algorithm. Results of the proposed algorithm were then compared to those of coding in GAMS for 30 different sample problems with different counts of customers, EVs, and charging stations. Numerical results indicated good efficiency of the metaheuristic algorithm in terms of processing time and solution quality. Indeed, with the SA algorithm, the processing time was seen to increase gradually with increasing the problem complexity, while the rate of increase in processing time was much steeper with the GAMS.