this paper, different usages of poultry manure at biogas plants, such as alone itself, with water addition and with cattle manure alternatives, feasibility studies of various scenarios have been done. Among these alternatives, co-fermentation of poultry manure and cow manure in cylindrical and wet processed systems is the best possible economic investment choice.

Abstract- This paper investigates the performance, emission and combustion characteristics of biodiesel (Neem oil methyl ester: NOME) blend in a single-cylinder water-cooled diesel engine at a constant speed of 1500 rpm. The experiments were carried out at in a diesel engine with 20% biodiesel-diesel blend and neat biodiesel with different compression ratios such as 17.5:1, 18.5:1 and 19.5:1 under different load conditions. The measured values are analyzed are compared with diesel fuel. The results showed that the higher brake thermal efficiency and lower brake specific fuel consumptions for B20 with CR 19.5 and have lower carbon monoxide, unburned hydrocarbon at full load. The nitrogen oxide (NOx) emission was increased and smoke emissions were decreased for B20 compared with diesel fuel. The peak pressure and heat release rate were higher for B20 blend with compression ratio 19.5 compared to diesel fuel at full load. It is concluded that the 20% biodiesel blend with 19.5 compression ratio gave better performance, emission reduction and combustion of biodiesel without any other hardware modifications of the engine.

The maximal flow problem is consider as one of the classic combinatorial optimization problems and hence gradually becomes the area of interests for the researchers and engineers. But in real life there exist uncertainty in the capacity as well as in the flow parameters of an arc of a network. Finding the maximum flow between the source and destination nodes of a network with uncertainties in its flow and capacities has many applications in different domains such as electrical powers, traffics, communications, computer networks and logistics. In this paper the classical Ford-Fulkerson algorithm for maximal flow problem has been modified to find the maximum flow of an network where the flow capacity of each arc is expressed as intuitionistic normal fuzzy numbers (INFNs) having degree of acceptance and degree of rejection. The Improved Intuitionistic Fuzzy Maximal Flow Algorithm (IIFMFA) proposed in this paper can solve intuitionistic normal fuzzy maximal flow problem (INFMFP) using intuitionistic normal fuzzy order weighted geometric averaging (INFOWGA) aggregation operator. To validate the proposed algorithm a numerical example is presented where we compare the augmenting flow chains of a crisp network with that of an intuitionistic fuzzy network.

In order to improve the conditions of exploitation and development of electric power distribution networks, systematic researches of optimization methods and calculation of system models, by using modern analytic techniques, have been performed recently. Therefore, several specialized algorithms for power flow calculation in electric power distribution networks are developed. A part of the 10 kV distribution network is analyzed in this paper. The analysis is performed by applying stochastic optimization method, i.e. simulated annealing method by using the original program code. The aim of analysis is to determine the optimal network configuration from minimum losses aspect, with the condition of keeping the stable voltages on the buses. The analysis is performed on the network with 212 buses and 72 switches. Simulations are performed for two initial configurations with different initial annealing temperatures and cooling speeds. All parameters of network elements had constant values. The results show that the obtained solutions are better than those that are chosen initially.

In geophysical processes electronic sensors are required to measure and automate different tasks types. Throughout history, people have created multiple types of sensors, but the acoustic devices have an important application such as the content form description in deep wells, watersheds, lakes, caves, among others. The acoustic signal is capable of reflecting where other types of signals cannot operate, either by drawbacks or where fluid is displaced.\nThis paper presents a mathematical model in state space described as a basic acoustic sensor; the objective is to adjust the parameters allowing the acoustic device to describe a signal in its trajectory, representing in geophysical manner the cavity form. Therefore, the control is performed on the response of the acoustic sensor model with the parameter estimation adjusted with a process technique. The simulation results allow viewing counts convergence.

A new method for defuzzification based on the radius of gyration point is proposed and some of its desirable properties are studied. This point of each fuzzy number plays an important role in fuzzy sets and systems, specifically in physics, mathematics and dynamics. Also, the researcher explains the development of a decision- making model using the neural network with an error back propagation learning algorithm and a fuzzy numerical process

The parabolic stochastic filter estimation based on a first differences order and second grade model with uncorrelated innovation conditions with two auxiliary inequalities bounding the spatial operation region allowing an approximation to real parameters set with a sufficient convergence rate in a probability sense. The stochastic first differences order second grade with uncorrelated parameters and stationary conditions through the parabolic surface with bounded drift around the mean value was considered. The recursive parameters estimation was built without lost generality. Adaptive identification state resulted in a high convergence condition, observed in the functional error. Simulated results considering the recursive filter achieved and observed the great convergence with respect to the reference model. Finally, the advantage that it has to traditional parameters estimation is viewed in the functional error figure.

【Abstract】 Objectuve It has been shown that Inflammation plays an important role in the initiation and progression of acute cardiovascular events，especially the AMI. There is a possible association between ventricular dysfunction following acute myocardial infarction and high Sensitivity C-reactive protein (HS-CRP) and Mannose-binding lectin (MBL). Methods In this study we assessed the relationship between HS-CRP and MBL with LVEF and Killip Class in patients with acute myocardial infarction (AMI). In a cross sectional study, 188 patients(63 females and 125 males) with AMI (STEMI) who were admitted in CCU ward in the Affiliated Hospital of Qingdao University, and The Qingdao Hiser Medical Center, were entered. MBL and HS-CRP were measured within first day of admission. We measured ejection fraction (LVEF) and used Killip classification system. Results The mean age of patients was 60.4±9.2 years. The mean of MBL was 5.9±1.6, 6.6±2.1, 7.1±2.1 and 9.4±1.3 in patients with Killip Class I, II, III and IV, respectively (P=0.005). The mean of HS-CRP was 1.9±1.4, 14.2±10.9, 12.2±10.9 and 15.7±6.7 in patients with Killip Class I, II, III and IV, respectively (P=0.005). There was a relationship between HS-CRP and LVEF (Correlation coefficient= -0.788, P<0.001), but there was not between MBL and LVEF (Correlation coefficient= -0.111, P=0.129), The plasma concentration of C-reactive protein correlated with LVEF and Killip Class in patients with AMI but serum MBL was just correlated with Killip Class IV. Conclusion It seems that plasma concentrations of HS-CRP and MBL are useful for prediction of development of heart failure in AMI patients. More future studies are necessary for final judgment.

To study the proteome expression profile of different metastatic potential muscle invasive bladder cancer and compared with the published urine proteome expression profile, thus, the possibility of using biomarker panels from urine to determine personal metastatic risk was discussed. To achieve this destination, laser capture microdissection was employed as initial step to get purified cancer cell subgroup from high, low, median metastatic risk bladder cancer. Next, iTRAQ was used to get the proteome expression profile as well as the expression difference among three risk groups. By combination of LCM and iTRAQ, we identified 1049 differentially expressed proteins from the clinical samples. Among which, 760 have GO biological process annotation, 804 proteins have cellular component annotation. Compared with the entire list of the International Protein Index, there were 55/11 and 43/8 Gene ontology (GO) terms found to be enriched/depleted within the biological process and cellular component annotation, respectively. Further compared with the urine proteome expression profile, we found that GO enrichment/depletion analysis was consistent with the results of urine proteome analysis. There are 14 and 10 GO terms manifested as enriched in biological process and cellular component both in cancer and urine expression profile, respectively. Based on previous statements, proteins classified under the terms of cell adhesion, cell proliferation and cell differentiation are good candidate biomarkers to evaluate metastatic risk from urine. Meanwhile, proteins originated from some special cellular components may contribute to different metastatic risks and tend to be detected from urine sample.

One of the threats to global environmental health is solid waste generation. Land filling is now accepted as the most widely used method for addressing this problem in all countries of the world. However, appropriate site selection for land filling is a problem in waste management and therefore needs to be addressed. This study aims to identify a suitable landfill site for waste disposal in Mahshahr South Local Iran. Geographical Information System (GIS) were applied in order to display and rank candidate sites. The analysis was limited to criteria that were selected and relevant to the area under investigation. The results obtained provide clear areas for landfill sites in the study area and finally arrives at suitable areas. At the end of the analysis, two candidate sites were selected and one was chosen as the best site using super decision software from the AHP component. Municipal authorities can now have ability to benefit from GIS and AHP solutions by leveraging on them to address the problem of waste management.