The dramatic increase in the usage of short message service (SMS) technology has led service providers to seek for solutions that enable users of mobile devices to access services through SMS. This has resulted in the proposal of solutions towards SMS-based service invocation in service oriented environments. However, the dynamic nature of service-oriented environments coupled with sudden load peaks generated by service requests, pose performance challenges to infrastructures for supporting SMS-based service invocation. To address this problem, we proposed Client-aware Least Loaded Framework (CaLLF) which is a client-aware load balancing approach for SMS invocation of services environment. The proposed CaLLF builds upon existing load balancing techniques to handle unexpected load traffic and request prioritization techniques to handle service client requests according to their class of importance. In addition, we observed that service-oriented environments deliver services to different service clients (which are either premium or regular clients) requiring different service qualities which enforces guarantees. We designed CaLLF to take care of this requirement. The evaluation of CaLLF for scalability showed it can cope with traffic while providing better performance compare to Round Robin (RR) scheme; although with a trade-off of higher computational power requirement. CaLLF achieved better result with cost computationally resources. We also evaluated CaLLF for utility and we observed that CaLLF can provide better utility for premium client compared to non-client-aware Least Loaded (LL) load balancing approach but this was achieved with trade-off on regular clients’ utility.

A anticomplement protein atrase B was seperated and purified from the venom ( Naja atra ) by column chromatography. In our pre-study，inhibitory effects and mechanism of cobra venom anticomplement protein atrase B on platelet aggregation were studied by collagen, ADP, PAF, AA, ristocetin and thrombin induced. However, inhibitory effects of the anticomplement protein atrase B on platelet aggregation induced by activated complement were still few clearly presented.\nAim: To investigate the inhibitory effects and mechanism of anticomplement protein atrase B on platelet aggregation induced by activated complemnet.\nMaterials and methods: Atrase B was seperated and purified from the venom of Naja atra by sequential column chromatography (SP-Sephadex-C-25, HiTrap Heparin HP, HiTrap Q HP and HiTrap SP HP). Platelet aggregation was induced by employing cobra venom factor (CVF) to activate complements. ①Different concentrations atrase B mixed with human serum were incubated at 37℃ for different time (5, 10, 30, 60 min), then added into pre-incubation gel-filtrated platelets (GFP) and CVF to induce platelet aggregation; ②Different concentrations atrase B mixed with GFP were incubated at 37℃ for different time (5, 10, 30, 60 min), then added human serum and CVF; The maximum platelet aggregation rate of ① and ② were determined by platelet aggregation analyzer (time: 5min). atrase B（0.38, 0.75, 1.5 and 3.0 mg•ml-1）with human serum, pre-incubation gel-filtrated platelets (GFP) and Fura2/AM were incubated at 37℃ for 30 minutes in water bath by CVF to induce platelet aggregation were incubated for different time (5, 10, 30, 60 min), the expression levels of Ca2+ in platelet membrane was detected by the flow cytometry. \nResults: Atrase B can effectively inhibit activation and aggregation of platelet induced by activated complement. And the expression levels of Ca2+ in platelet membrane were decreased significantly. These effects were obvious in a time-dose dependent manner.\nConclusions: Taken together, these findings suggest Cobra venom anticomplement protein atrase B has significant inhibitory effects of platelet activation and aggregation by complement activation induced, which may be due to decrease the expression levels of Ca2+ in platelet membrane.

An important aspect of economic development in any country is the development of capital market. In any industry, managers are looking for identifying paradigm firms by which they can remove their deficiencies and move toward their efficiency, growth and excellence. Investors in capital market are identifying the best options for decision making and investment. In present paper, we try to provide a model on determining high performers by using FAHP – TOPSIS techniques. To this end, financial ratios in two selected industries are computed between 2007 and 2012. According to our analysis, Maron, Persian Gulf and Khark Petrochemical companies and Puyesh Components and Iran Automobile Components companies acquired the top performance in petrochemical and automobile industries respectively.

Purkinje system, one of the most important components of the ventricular conduction system, provides a significant insight into understanding the mechanisms of cardiac pathophysiologies. Construction of anatomical detail Purkinje fiber network, however, is a very challenging task. In this paper, we present a method for constructing the 3D purkinje system in the left ventricle by the locally linear embedding algorithm and the fast marching method. Motivated by the fact that the purkinje system is generally on the endocardial surface of the ventricle, we have collected a set of images on 2D fractal structure of canine left ventricle, then extract the 2D location information of the anatomical detail purkinje system, and then map the 2D information to 3D space with the 3D canine left ventricular model. In contrast to most construction models, the result shows that our construction is more effective and close to the real purkinje system.

In this study, a mathematical model was developed for multiple-effect evaporators. These evaporators have cocurrent, countercurrent, and parallel flow operation options. Each operation was investigated with and without preheaters. The effect of preheating on the evaporation process was investigated with respect to steam consumption efficiency. A sugar factory’s data was used with the applied models as a case study. The results obtained for preheated and non-preheated situations were compared. The best operation for economic steam consumption was found to be countercurrent operation with preheating, while the worst case was parallel flow operation without preheating. The steam savings obtained by preheating of unconcentrated solution for cocurrent, countercurrent, and parallel flow operation cases were 7,343.86 kg/h, 2767.06 kg/h, and 1,143.58 kg/h, respectively

Lymphangiomyomatosis (LAM) is a rare disease of unknown etiology that primarily affects premenopausal women. It is predominantly a lung disorder and characterized by proliferation of atypical smooth muscle cells, causing obstruction of small airways. However, cases that affect extrapulmonary sites, such as the mediastinum or retroperitoneum, have also been reported. Here, we report a case of extrapulmonary LAM located in the liver and presenting as a localized mass. Abdominal computed tomography revealed a low-attenuation liver mass in a 26-year-old woman. The diagnosis of LAM was pathologically confirmed by surgery. This patient had atypical extrapulmonary LAM with typical pathological manifestations.

Vocal functions from acoustical measures are used in the assessments of voice disorders and monitoring the subject’s improvement over the voice therapy. There are many treatments in the existing system, for the problem of voice disorders. They are conducted by speech and language pathologists by giving fluency in speech practice in general. In this paper, an hybrid approach is proposed to analyze, classify the pathological speech and to identify the acute spots in pathological speech signal. These acute spots are the spots where the speech disorder occurs. The speech training for that specific portion of speech in particular can be given for the enhancing the pathological speeches. Features are extracted first using Mel Frequency Cepstrum Coefficients (MFCC) and dimensionality reduction of features extracted is done using Principal Component Analysis (PCA). By applying statistical method to the features extracted, classification performance is proved that overall, 91.60 % of the words were classified correctly based on their clarity of words. The features were trained using Artificial Neural Network (ANN) and Support Vector Machines (SVM) for classification separately and compared. The abnormal words’ Fast Fourier Transform (FFT) is made use of the Fuzzy Inference system (FIS) and Genetic Algorithm (GA) separately for blemishing the acute spot in which the aberration is occurred in the word and their performance are compared. The performance between ANN and SVM are compared and found that 90% accuracy is got by SVM.The performance of GA and FIS is compared and found that FIS is better than GA. Therefore the Hybrid approach with the combination of SVM and FIS was found better of around 98% accuracy.

The present study was to establish a hypothesis of stroke originally cause by Liver dysfunction. Stroke in China surpassed myocardial infarction and cancer, and has become the leading cause of death. In the past 20 years although invested a huge sum of money, stroke incidence does not fall to rise instead. The reason might be the source of the stroke is unclear. According to the known causes of stroke, the core pathological changes of atherosclerosis: the abnormal blood lipids, bilirubin abnormality which caused by liver dysfunction. Therefore, we proposed that stroke may caused by the liver dysfunction which lost normal metabolism of lipids and bilirubin. The new strategy of stroke management should be the source control, and this hypothesis may have certain theoretical value and potential prospective clinical improvement.

Background and Aims: Hyperglycemia increases the surgical morbidity and mortality. This study was aimed to compare the outcome of patients undergoing open cardiac surgery by glucose control in two ways: modified tight versus conventional method.\nMaterial and methods: This open-labeled, randomized control trial was conducted on 75 diabetic patients, aged 18-70 years with ASA II- III undergoing open heart surgery from Shahid Faghihi Hospital, Shiraz, Iran. Patients were divided into modified tight control (Blood Sugar maintained between 100-120 mg/dl) and conventional method (Blood Sugar ≤200mg/dl). Mortality, sternal wound infection, duration of mechanical ventilation, cardiac arrhythmia, cerebrovascular attack and acute renal failure are considered as primary outcomes and length of ICU staying has been determined as secondary outcomes. Complications after 30 days of surgery were recorded. We used student’s t test, chi-square and repeated measurement tests.\nResults: Although the trend of change in blood glucose during surgery and in ICU was not significantly different between groups, blood sugar measurement showed a significant difference at the different times (P<0.001). In terms of primary postoperative outcomes the two groups were not significantly different while hypokalemia was the most prominent side effect in the 34 patients of modified tight control group compared with eight patients in the conventional group (P<0.001). After one month, sternal wound infection was one patient in treatment group versus seven case in control group (P<0.05) which was statistically significant. \nConclusion: Using a modified tight control of blood glucose level to a level that is close to normal values during cardiac surgery may reduce episodes of hypoglycemia and hyperglycemic complications.

This paper provides an overview of the Entity-Relationship Modelling (ERM), which is used to construct the Emitter DataBase (EDB) for current ELectronic INTelligence (ELINT) systems. The method described, delivers a data model of radar signal, called the Entity-Relationship Model (ERD). This model incorporates some of the important semantic information about the real radar signal and its platform, weapon system, location, antenna system, ect. A special diagrammatic technique is introduced as a tool for DataBase design, by using Barker’s notation. Also, semantic ambiguities in ERD for radar signal is analysed. The author pay special attention to the character and the meaning of the “radar signature” in DataBase, taking into consideration the difficulties that appear during the process of the parameter selection. This approach ensures the integrity of the measured data. The process of final emitter identification is based on “the knowledge-based approach” which was implemented during the process of constructing the Emitter DataBase, by using hierarchical data clustering. The results of clustering are presented in dendrograms. Special ERD of radars, presented in this paper, can be used in real time or non-real time on any PC computer with portable HDD containing the signals collected earlier. Such approach is very convenient to operators’ training as it gives them an opportunity to meet rare radar signals and reduces the cost of Electronic Warfare (EW) exercises.