Comparison between conventional pump and adsorption sampling method with passive solid phase microextraction ( SPME ) sampling to investigate changes in the concentration of benzene, toluene , and xylene ( BTX ) in urban ambient air

Background and Aims: Besides toxic effects on human, animals and plants, aromatic hydrocarbons may also be effective in the formation of photochemical smog. The measurement of these hydrocarbons, therefore, play aprominent part in evaluating their health and environmental impacts. The purpose of this study was to compare pump and adsorption sampling method with solid phase microextraction (SPME) to investigate changes in theconcentration of benzene, toluene, and xylene (BTX).Materials and Methods: SPME samplers in sampling protective holders were placed in ambient air at a relatively high traffic routes for 5 days. Sampling was carried out in two seasons. Samples were analyzed at the end of sampling period. In addition, pump and adsorption sampling method was also used to measure the concentrations of benzene, toluene, and xylene. Ethical issues were all considered in conducting the study and citation.Results: The obtained results in solid phase microextraction sampling method were compared with those obtained using the conventional pump and adsorbent method. Correlation coefficients (R2) between these methods were 0.98, 0.9 and 0.95 for benzene, toluene, and xylene, respectively. The results obtained with pump and adsorption method showed a higher values in general.Conclusion: The comparison between obtained results with these methods indicates a relatively similar values. It may be concluded that SPME sampling method can also present reliable results for the measurement of benzene,toluene and xylene concentrations in the ambient air.Keywords: Passive sampling, SPME, Benzene, Toluene, XyleneFor downloading the full text please click here

Molecular identification of Pseudomonas aeruginosa recovered from cystic fibrosis patients

Objective. Precise identification of various morphotypes of Pseduomonas aeruginosa which developed during cystic fibrosis (CF) is of prime importance. We aimed to identify the isolates of P. aeruginosa recovered from CF patients at the genus and species level through primers targeting oprI and oprL genes via PCR. Methods. Sputum samples or throat swabs were taken from 100 CF patients and plated on cetrimide agar. All suspected colonies were primarily screened for P. aeruginosa by a combination of phenotypic tests. Molecular identification of colonies was per- formed using specific primers for oprI and oprL genes.Results. Based on phenotypic tests, P. aeruginosa isolates were recovered from 40% of CF patients. Forty isolates yielded ampli- con of oprI gene using genus-specific primers confirming the identity of fluorescent pseudomonads. However, 37 of 40 isolates yielded amplicon of oprL gene using species-specific primers, verifying the identity of P. aeruginosa. Conclusion. This study showed that the species-specific PCR tar- geting oprL gene can be used as accurate test for identification of highly adaptable P. aeruginosa in CF patients. This procedure may provide a simple and reliable method for identification of various morphotypes

Anticonvulsive Effects of Licofelone on Status Epilepticus Induced by Lithium-pilocarpine in Wistar Rats: a Role for Inducible Nitric Oxide Synthase

BACKGROUND AND PURPOSE: Status epilepticus (SE) is a neurological disorder with high prevalence and mortality rates, requiring immediate intervention. Licofelone is a cyclooxygenase (COX) and 5-lipoxygenase (5-LOX) inhibitor, which its effectiveness to treat osteoarthritis has been approved. Increasing evidence suggests an involvement of COX and LOX enzymes in epileptic disorders. Thus, in the present study we investigate possible effects of licofelone on prevention and termination of SE. We also evaluated whether the nitrergic system could participate in this effect of licofelone. METHODS: We have utilized lithium-pilocarpine model of SE in adult Wistar rats to assess the potential effect of licofelone on seizure susceptibility. Licofelone was administered 1 h before pilocarpine. To evaluate probable role of nitric oxide (NO) system, L-arginine (60 mg/kg, i.p.), as a NO precursor; L-NAME (15 mg/kg, i.p.), as a non-selective nitric oxide synthase (NOS) inhibitor; aminoguanidine (100 mg/kg, i.p.), as an inducible NOS (iNOS) inhibitor and 7-nitroindazole (60 mg/kg, i.p.), as a neuronal NOS inhibitor were injected 15 min before licofelone. Also, licofelone and diazepam 10 mg/kg were administered 30 minutes after onset of SE. RESULTS: Pre-treatment with licofelone at the dosage of 10 mg/kg, significantly prevented the onset of SE in all subjects (p \u3c 0.001). L-arginine significantly inverted this anticonvulsant effect (p \u3c 0.05). However, L-NAME and aminoguanidine, potentiated the anticonvulsant effect of licofelone (p \u3c 0.05, p \u3c 0.01). Licofelone could not terminate seizures after onset which was terminated by diazepam. CONCLUSIONS: Our findings showed that anticonvulsive effects of licofelone on SE could be mediated by iNOS. Also, we suggest that COX/5-LOX activation is possibly required in the initial stage of onset but SE recruits extra excitatory pathways with prolongation

Optimal Design of Steel Structures Using Innovative Black Widow Algorithm Hybridized with Greedy Sensitivity-Based Particle Swarm Optimization Technique

This paper presents a Greedy Sensitivity-based analysis implemented on the Particle Swarm Optimization search engine (GSPSO). The effectiveness of the method focuses mainly on providing an intelligent population to enter meta-heuristic algorithms. As a meta-heuristic method in the second stage, the recently introduced Black Widow Optimization (BWO) algorithm was selected and improved by the authors. It is based on three operators: cannibalism, crossover, and mutation, whose main stage is Cannibalism. The advantage of this stage is that those designs that do not match the solutions close to the global optimal are eliminated, and the more effective solutions remain. To examine the proposed approach, five optimization examples, including three two-dimensional benchmark frames and two three-dimensional structures, have been used. The results show that the greedy sensitivity-based PSO technique can improve computational efficiency in solving discrete variable structural optimization problems. The hybridized BWO (BGP) with this technique was able to obtain very good results in terms of convergence speed and performance accuracy. Overall, compared to the performance of BWO, between 50 and 75% improvement in the total number of analyzes was achieved. In addition, a slight improvement in the weight of the evaluated structures was also reported. Compared to other hybrid algorithms, very competitive and promising results were obtained

A Cost-Aware Mechanism for Optimized Resource Provisioning in Cloud Computing

Due to the recent wide use of computational resources in cloud computing, new resource provisioning challenges have been emerged. Resource provisioning techniques must keep total costs to a minimum while meeting the requirements of the requests. According to widely usage of cloud services, it seems more challenging to develop effective schemes for provisioning services cost-effectively; we have proposed a novel learning based resource provisioning approach that achieves cost-reduction guarantees of demands. The contributions of our optimized resource provisioning (ORP) approach are as follows. Firstly, it is designed to provide a cost-effective method to efficiently handle the provisioning of requested applications; while most of the existing models allow only workflows in general which cares about the dependencies of the tasks, ORP performs based on services of which applications comprised and cares about their efficient provisioning totally. Secondly, it is a learning automata-based approach which selects the most proper resources for hosting each service of the demanded application; our approach considers both cost and service requirements together for deploying applications. Thirdly, a comprehensive evaluation is performed for three typical workloads: data-intensive, process-intensive and normal applications. The experimental results show that our method adapts most of the requirements efficiently, and furthermore the resulting performance meets our design goals

Dynamic Pricing of Applications in Cloud Marketplaces using Game Theory

The competitive nature of Cloud marketplaces as new concerns in delivery of services makes the pricing policies a crucial task for firms. so that, pricing strategies has recently attracted many researchers. Since game theory can handle such competing well this concern is addressed by designing a normal form game between providers in current research. A committee is considered in which providers register for improving their competition based pricing policies. The functionality of game theory is applied to design dynamic pricing policies. The usage of the committee makes the game a complete information one, in which each player is aware of every others payoff functions. The players enhance their pricing policies to maximize their profits. The contribution of this paper is the quantitative modeling of Cloud marketplaces in form of a game to provide novel dynamic pricing strategies; the model is validated by proving the existence and the uniqueness of Nash equilibrium of the game

Reactive Power Planning for Loss Minimization Using Simulated Annealing

Abstract: This paper addresses an optimal Reactive Power Planning (RPP) of power system. The Static Var Compensator (SVC) is introduced into power system in order to reactive power support and voltage control. The locations and the outputs of SVCs are determined using our proposed optimal reactive power planning model. The proposed method optimizes several objective functions at the same time within one general objective. The optimized objectives are minimization of total investment in reactive power support, average voltage deviation and minimization of total system loss. These objective functions are one of the most important objectives for every transmission and distribution systems. Simulated Annealing technique (SA) is used to solve the optimization problem. The validity of the proposed method is tested on a typical power system

Decadal Spatial-Temporal Variations in the Spatial Pattern of Anomalies of Extreme Precipitation Thresholds (Case Study: Northwest Iran)

This study focused on decadalvariations of extreme precipitation thresholds within a 50-year period (1961–2010) for 250 stations of Iran’s northwest. The 99th percentile was used as the threshold of extreme precipitation. In order to analyze threshold cycles and spatial autocorrelation pattern dominating extreme precipitation thresholds, spectral analysis and Gi (known as HOTSPOT) were used respectively. The results revealed that the highest threshold of extreme precipitation occurred along the Ghoosheh Dagh mountain range. Additionally, in all the five studied decades, the highest positive anomalies were observed in the same region (i.e., the Ghoosheh Dagh). The findings also showed that the intensity of positive spatial autocorrelation pattern of extreme precipitation thresholds experienced a declining trend in recent decades. At the same time, extreme precipitation weighted mean center indicated that they followed an ordered pattern during the studied period. The results of harmonic analysis demonstrated that, in all decades, short-term (2–4 years) and mid-term (4–8 years) cycles of extreme precipitation thresholds were dominated. However, especially the southwest of the studied area, the return period of extreme precipitation thresholds was as long as the studied period, a phenomenon that indicates the existence of a trend in extreme precipitation thresholds of these regions.Peer Reviewe