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This paper designs and models a fully decentralized peer-to-peer (P2P) energy token market for small-scale prosumers using blockchain technology in a smart grid environment in the presence of the demand response (DR) program and demurrage mechanism. As the market players, prosumers in the local distribution network are considered in two groups, producers (sellers) and consumers (buyers). Using smart contracts, all sellers and buyers in the proposed market can engage in bilateral energy token transactions (P2P) with each other under an agreed price and with the retail market at a certain price. Furthermore, the local consumers can participate in price-based DR programs and shift their consuming load to the periods with high local generation. Demurrage mechanism is applied to avoid energy token accumulation and enhance attraction for local transactions. With demurrage in place, the redemption value of energy-backed tokens reduces with time. A fully decentralized approach called the primal-dual sub-gradient method is developed to clear this fully decentralized energy market in the presence of DR programs and demurrage. The proposed market-clearing scheme guarantees the global and feasible solution without requiring the players' private information. Numerical studies demonstrated the feasibility and effectiveness of the proposed energy token market and the decentralized approach for its clearing.

In this paper, the energy management of a microgrid including wind turbine, PhotoVoltaic (PV) modules, Combined Heat and Power (CHP) systems, fuel cells, power only units, heat only unit, Plug-in Electric Vehicles (PEVs), and thermal energy storage resources for supplying electrical and thermal loads is presented. For achieving a better management on demand side, both price-based and incentive-based Demand Response Programs (DRPs) have been used and their impacts on reducing the operational cost of microgrid in both grid-connected and island modes have been investigated. Also, the uncertainty of price, load, wind speed and solar radiation are taken into account in order to obtain more realistic results. By discretization of Probability Distribution Function (PDF) of each uncertain parameter, a set of scenarios is generated. Then, using a scenario reduction method based on mixed-integer linear optimization, the set of reduced scenarios is obtained. Two-stage stochastic programming approach is used to minimize the operational cost in microgrid energy management. The proposed method for microgrid energy management has been evaluated in three modes: grid-connected, grid-connected with DRPs, and island mode with DRPs.

Objective: Studies have assessed the association between aspartic acid (D)-repeat polymorphism in the gene encoding Asporin (ASPN) and knee osteoarthritis (KOA) risk, but the results were inconclusive and contradictory. Therefore, we performed a meta-analysis to investigate the association between ASPN gene D-repeat polymorphism and KOA risk. Methods: Eligible studies were identified by searching several electronic databases for relevant reports published before September 2016. The pooled odds ratios (ORs) for the association between ASPN polymorphism and KOA and their corresponding 95% confidence intervals (CIs) were estimated using the random- or fixed-effect model. Results: A total of eleven case-control studies in ten publications with 4610 KOA cases and 3621 controls were included for the ASPN D-repeat polymorphism. Overall, no significant association was detected for D14 allele carrier (D14 vs. D13: OR = 1.10, 95% CI = 0.90–1.36, p = 0.32). Meta-analysis of D14 vs. other alleles and D13 vs. other alleles showed the same pattern of KOA association as the D14 vs. D13 (OR = 1.30, 95% CI = 1.00–1.70, p = 0.06; OR = 0.93, 95% CI = 0.82–1.06, p = 0.33, respectively). Also, in the stratified analysis by ethnicity, no significant association of this polymorphism with risk of KOA was found in the European and Asians populations (OR = 1.05, 95% CI = 0.91–1.21, p = 0.49; OR = 0.98, 95% CI = 0.78–1.23, p = 0.88, respectively). Conclusions: The present meta-analysis suggests that the ASPN D-repeat polymorphism is not associated with an increased KOA risk. However, future large studies with gene–gene and gene–environment interactions are needed to validate these findings. Level of evidence: Level III diagnostic study. Keywords: Osteoarthritis, Knee, Asporin, D13 and D14 alleles, Polymorphism

Funding Acknowledgements Nil OnBehalf Nil Introduction Echocardiography is used as a useful and common method for the assessments of left and right ventricular (LV & RV) systolic and diastolic functions. Valsalva Maneuver (VM) with the increase in the intra-thoracic and intra-abdominal pressure is often used as a simple, inexpensive and non-invasive method to diagnose some clinical conditions such as heart murmurs. However, in terms of echocardiography, the use of VM is limited to a few parameters for many years. On the other hand, blood level of N-Terminal Pro–B-Type Natriuretic Peptide (NT Pro–BNP) indirectly discriminates normal or high ventricular filling pressure (FP). Purpose The purposes of this research is to provide a comprehensive review of the technique and to compare the effect of VM in ACS patients, with and without elevated FP on either RV and LV diastolic and systolic echocardiographic parameters. Methods Thirty-eight patient, who were diagnosed with possible ACS; Unstable Angina Pectoris, NSTEMI and STEMI, underwent coronary angiography enrolled in this double–blinded clinical trial study. The mild Coronary Artery Disease (CAD) with normal levels of NT Pro–BNP were included in study group one and patients with significant CAD and high level of NT Pro–BNP who underwent PCI were included in study group two. All the systolic and diastolic indicators of both ventricles, totally twenty-four parameters those had mentioned in the academic literature previously, have been evaluated; once before Valsalva and once during stage 2 of the maneuver. Echocardiography is performed by an advanced echo machine and by an expert cardiologist- echocardiographer, which the recorded images were reviewed by the second echocardiographer separately. Results Between the two groups, LV parameter analysis showed significant difference in LV EF pre and post VM. However, there was statistically insignificant difference regarding other systolic as well as diastolic parameters. Between the two groups, RV parameters analysis showed no significant difference in systolic and diastolic parameters pre and post VM. Conclusion To the best of our knowledge, this is the first report assessing post VM changes in four chambers as well as mitral and tricuspid valves parameters in ACS patients with normal versus high level of FP. Previously, LV diastolic dysfunction and Doppler mitral inflow pattern correlation with VM were approved. In the present study, in addition to those known findings from before, except the LV ejection fraction (LVEF) that showed there was statistically significant difference in pre– and post-VM, other systolic parameters, as well as diastolic indicators in either RV and LV, were identical. Therefore, we do not recommend conducting Valsalva maneuver on the rest of the other parameters to diagnose systolic and diastolic dysfunction in ACS patients with mild versus significant CAD who were assumed to have normal or elevated filling pressures.

To date, several methods have been proposed to explain the complex process of air pollution prediction. One of these methods uses neural networks. Artificial neural networks (ANN) are a branch of artificial intelligence, and because of their nonlinear mathematical structures and ability to provide acceptable forecasts, they have gained popularity among researchers. The goal of our study as documented in this article was to compare the abilities of two different ANNs, the multilayer perceptron (MLP) and radial basis function (RBF) neural networks, to predict carbon monoxide (CO) concentrations in the air of Pardis City, Iran. For the study, we used data collected hourly on temperature, wind speed, and humidity as inputs to train the networks. The MLP neural network had two hidden layers that contained 13 neurons in the first layer and 25 neurons in the second layer and reached a mean bias error (MBE) of 0.06. The coefficient of determination (R2), index of agreement (IA), and the Nash–Scutcliffe efficiency (E) between the observed and predicted data using the MLP neural network were 0.96, 0.9057, and 0.957, respectively. The RBF neural network with a hidden layer containing 130 neurons reached an MBE of 0.04. The R2, IA, and E between the observed and predicted data using the RBF neural network were 0.981, 0.954, and 0.979, respectively. The results provided by the RBF neural network had greater acceptable accuracy than was the case with the MLP neural network. Finally, the results of a sensitivity analysis using the MLP neural network indicated that temperature is the primary factor in the prediction of CO concentrations and that wind speed and humidity are factors of second and third importance when forecasting CO levels.

Management of reactive power resources is essential for secure and stable operation of power systems in the standpoint of voltage stability. In power systems, the purpose of optimal reactive power dispatch (ORPD) problem is to identify optimal values of control variables to minimize the objective function considering the constraints. The most popular objective functions in ORPD problem are the total transmission line loss and total voltage deviation (TVD). This paper proposes a hybrid approach based on imperialist competitive algorithm (ICA) and particle swarm optimization (PSO) to find the solution of optimal reactive power dispatch (ORPD) of power systems. The proposed hybrid method is implemented on standard IEEE 57-bus and IEEE 118-bus test systems. The obtained results show that the proposed hybrid approach is more effective and has higher capability in finding better solutions in comparison to ICA and PSO methods.

Overcurrent relays are widely used as main protection in sub-transmission and distribution systems. In mesh and multi-source networks, application of directional relay is unavoidable. Traditional directional overcurrent relays use the reference voltage phasor as the polarizing quantity to estimate the direction of the fault. Traditional direction distinguishing scheme is unreliable in the case of close-in faults. In this paper, a novel algorithm for directional overcurrent relay is proposed. The new algorithm uses only current signals for determining the fault direction. It uses superimposed component of the current signal and does not require phasor estimation. This new algorithm uses pre-fault current signal as the polarizing quantity. The proposed method is tested on simple power system in different situations. The results show it leads to fast and reliable directional protection.

In this paper, cuckoo optimization algorithm is implemented to solve energy production cost minimization in a combined heat and power (CHP) generation system. This problem is also known as combined heat and power economic dispatch problem, which looks for optimal values of power and heat generation of each CHP unit to minimize the total production cost. Cuckoo optimization algorithm is a new metaheuristic algorithm. It is inspired by the life of a bird family, called cuckoo, that special lifestyle of these birds and their characteristics in egg laying and breeding has been the basic motivation for development of this algorithm. Unlike of the some previous approaches, the effect of valve point is considered in the cost function and clearly formulated in the conventional polynomial cost function as absolute sinusoidal term. The proposed method is applied to three small (with three different test cases), medium, and large test systems in order to evaluate its efficiency and feasibility. The obtained results demonstrated a higher quality solution and superior performance of the proposed cuckoo optimization algorithm method in comparison with many existing methodologies.

These smaller consumers usually prefer to purchase at a constant price that is adjusted at most a few times per year. Electricity retailers are in business to bridge the gap between the wholesale market and these smaller consumers. This paper proposes a hybrid approach based on binary imperialist competitive algorithm (BICA) and binary particle swarm optimization (BPSO) to find the optimal energy procurement for electricity retailer with multiple procurement options such as self-generating facility, bilateral contracts and pool market purchase in restructured electricity markets. The solutions of these problems provide adequate information to obtain an energy procurement strategy for retailers. Also, the results of proposed hybrid approach are compared with conventional ICA and PSO methods. Test results show that the proposed hybrid approach is more effective and has higher capability in finding optimum solutions in comparison to ICA and PSO methods. A case study is used to illustrate the efficiency of the proposed hybrid approach.

Air pollution is a challenging issue in some of the large cities in developing countries. In this regard, data interpretation is one of the most important parts of air quality management. Several methods exist to analyze air quality; among these, we applied the Multilayer Perceptron (MLP) and Radial Basis Function (RBF) methods to predict the hourly air concentration of benzene in 14 districts in the municipality of Tehran. Input data were hourly temperature, wind speed and relative humidity. Both methods determined reliable results. However, the RBF neural network performance was much closer to observed benzene data than the MLP neural network. The correlation determination resulted in 0.868 for MLP and 0.907 for RBF, while the Index of Agreement (IA) was 0.889 for MLP and 0.937 for RBF. The sensitivity analysis related to the MLP neural network indicated that the temperature had the greatest effect on prediction of benzene in comparison with the wind speed and humidity in the study area. The temperature was the most significant factor in benzene production because benzene is a volatile liquid.

Background: Previous studies have shown that shallomin, one of the active constituents of Persian shallot, has a broad range of antimicrobial properties. Objectives: The safety of shallomin must be established before it can be used in clinical applications. Therefore, the aim of the present study was to evaluate the acute toxic effects of shallomin and to estimate its lethal dose low (LDLo) value. Materials and Methods: Two series of experiments were performed: In the first series, we used functional testing to assess the acute toxic effects of shallomin on the blood, liver, and kidney and examined histopathological changes in the liver, kidney, lung, and heart, following 7 days of daily intraperitoneal administration of 3 standard doses (10, 20, and 30 µg/g body weight of mice). In the second series, the LDLo value was estimated by determining daily mortality in mice after 7-day administration of escalating doses of shallomin (10 to 240 µg/g body weight of mice). Results: The results showed that shallomin (at the anticipated in vivo doses), unlike the placebo (ethanol), did not produce any adverse effects on the tested organs. The LDLo value was observed to be 160 µg/g body weight; this value is 8- to 32-times the anticipated in vivo dose that produces antimicrobial effects under in vitro conditions against vari ous pathogenic organisms. Conclusions: In conclusion, the results of the present study show that shallomin is a relatively safe agent, although its use needs to be carefully monitored. Further in vivo chronic toxicity tests need to be performed to establish the therapeutic potential of shallomin as an antimicrobial agent.

The aim of this study was to determine the presence and nature of bacterial flora on hearing aids earmoulds in a children's population. The study population consisted of 119 children referred to Imam Ali and Rudaky Schools in Ahvaz, Iran. Three samples were taken from surface of hearing aids earmoulds; canal in hearing aid wearers and ear without hearing aids earmoulds. The samples were cultured directly onto blood agar and MacConkey agar plates. According to preliminary examination, necessary standard biochemical tests were performed on grown bacteria and the organisms were identified as per standard identification criteria. Totally, 66 samples (61.1%) from hearing aids earmoulds and 124 samples (52.1%) from both ear canal without hearing aids earmoulds were culture positive, which 73 (58.9%) and 51 (41.1%) were from right and left ears, respectively. The majority of isolated bacteria from earmoulds were Coagulase-Negative Staphylococci (CNS) 40 (60.6%) and Polybacterial flora 14 (21.2%) and the least isolated bacteria were Pseudomonas aeruginosa and Staphylococcus aureus. In conclusion, although the majority of isolated bacteria were common normal flora of the ear, however a few pathogens were isolated as well. So, it is very important to educate the people with hearing aids earmoulds about proper cleaning and disinfection procedure to prevent any serious ear canal infection.

The aim of the present study was to investigate the incidence of fungal and bacterial contaminations of in-use eye drop products in the teaching department of ophthalmology, Imam Khomeini Hospital, Ahvaz. Two hundred and eighty seven eye drop bottles were randomly collected at the end of day 1, day 2, day 3, day 4 and day 7 of use. The eye drop residues, swabs from internal caps and droppers were inoculated onto MacConkey agar, blood agar and Sabouraud's dextrose agar. The identification of the recovered organisms was accomplished using standard microbial identification techniques. The incidence of microbial contamination of in-use eye drop products was 17.8%, with the highest rate (24.6%) and the lowest rate (9.0%) noted with day 1 and day 3 samples, respectively. The most contaminated part of the eye drop products was the caps (45.9%) followed by droppers (41.0%) and residual contents (13.1%). Considering mendicants contents, those with pilocarpine (41.7%) had the highest rate of contamination followed by atropine (31.8%), tropicamide (28.6%) and betamethasone (23.3%). Our study revealed the potential risk of contamination of in-use eye drop products in hospitals, but we did not find a direct relationship between usage duration and contamination rate.

In many fields of digital signal processing such as acoustic echo path estimation, modelingof the unknown systems has been required. Since the selection of the model order isvery important in such modeling, various methods of selection have already been proposed.However, the order estimation of the ARMA model is very difficult due to thenoise of the observed data, even in the case of known input data. Since, in the presenceof additive noise in the output data, traditional methods fail to select a reasonable order, we propose a new algorithm to overcome this problem. Our proposed algorithm forARMA model order selection is based on singular value decomposition (SVD) and newcriteria of threshold values for the smallest singular value of the noisy data matrix. Inthe simulation, we show that our proposed algorithm is very effective for obtaining anappropriate rank of the noisy data matrix. We also show the good performance of our algorithm for practical estimation of the room acoustic transfer function.

Background The watershed of Dez and Karoon rivers located in middle Zagrous mountain with area about 68481-, Thus watershed is a part of Persian gulf watershed. Cholera , an acute intestinal infection caused by the bacterium Vibrio cholerae ( V. cholerae ) is a historically feared epidemic diarrheal disease that remains a major public health problem in many parts of Africa, Asia, and Latin America. V. cholerae O1 exists as two major serotypes, Inaba and Ogawa, a member of the family Vibrionaceae is transmitted through Fresh water contaminated with fecal matter. Foodborne infections have been traced to raw. The target of study the Segregate V. cholerae 01 ( Vibrionaceae ) in the Karoon Ahvaz River. Methods In four stages (April, to July 2010), a total 100 samples of water from Karoon River Ahvaz were collected. During the study period the recorded river temperature was about 25–28°C and pH ranged from 7 to 8. Swabs were cultured onto thiosulphate citrate bile sucrose and MacConkey, and morphological colonies compatible with Vibrio were characterized by oxidase test and agglutinated with antiserum for serotype determination. Also V. cholerae biochemical tests with API 20E. Results From 100 samples of water Karoon River in Ahvaz, Iran, 8 (8%) sample were positive for Vibrio cholerae strains. The isolated strains from water Karoon River in Ahvaz, Iran, were Vibrio cholerae O1 (inaba). Conclusion The priorities for cholera control remain public health interventions through improved water and sanitation, improved surveillance and access to health care facilities, and further development of appropriate vaccines.

Methods: The criteria for inclusion in the study were the following findings: infection was suspected when patients had at least 2 of the 4 criteria of systemic inflammatory response syndrome (SIRS). Following these criteria, the Test EAA was performed on 71 patients (29 liver transplant and 42 kidney transplant). Twenty eight patients(39,5%) with EA>0.60 were enrolled in this study and received treatment to remove endotoxins (PMX-DHP). Each treatment was performed for two hours with a blood flow rate of 100mL/min. All the patients were treated with PMX-DHP until an EA

Bacterial vaginosis is caused by an imbalance of the organisms that naturally exist in the vagina. The importance of bacterial vaginosis with respect to pregnant women’s health is emphasized by the association betweenbacterial vaginosis and adverse outcome of pregnancy. The aim of present study was to evaluate the direct smear microscopy and culture for determination of bacteria from vaginal discharge of pregnant women. In total, 240 vaginal swabs were collected from 120 pregnant women and were screened for bacterial population. For each patient one swab was used for smear preparation and Gram staining and the second swab was used for cultivation. The prepared Gram-stained smears were observed for various morphotypes. Each morphotype was quantified on a scale from 0 to 4 and weighed to yield a score of 0 to 10, as per Nugent’s system. The bacteria grown in preliminary culture media were identified using standard identification tests. The majority of isolated bacteria in culture were Diphtheroid, Lactobacillus spp., Coagulase-negative Staphylococci and yeast. In Gram-stained smears, 78 (65%) Gram positive rods and 54 (45%) Gram positive cocci were detected. According to Nugent’s criteria, 64 cases (53.33%) were classified as having normal vaginal flora, 45 (37.5%) intermediate flora and 11 cases (9.2%) having bacterial vaginosis. The prevalence of bacterial vaginosis is not very high. However we recommend the regular screening of women with Gram stain method using Nugent’s criteria which is reliable, easy to perform and well suited for the routine clinical laboratory. Key words: Vaginal discharge, bacterial vaginosis, Nugent’s criteria, Gram stain, culture.