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Background: Patient's self-discharge from the hospital is a process in which a patient leaves the hospital before completing his or her determined treatment period by his own will. This study is aimed to survey the factors affecting patient's self-discharge from the hospital in emergency ward of a referred hospital. Materials and Methods: This is a case-control study. The 280 selected samples were divided to two groups, each with 140 members. The data were gathered using a questionnaire evaluating the scale of patients and their companions' satisfaction of the hospital services. Chi-square test was used for analyzing the relationship between independent variables and the patient discharge type. Moreover logistic regression was used in order to identify the effect of significant independent variables on own will-discharge possibility. Results: Results indicate that there is a meaningful relationship between variables such as age, having supplementary insurance, residency, income rate, reference shift, reference day, satisfaction of the physicians, satisfaction of the physical environment and welfare facilities, the patient's satisfaction, the waiting time, satisfaction of the instructions given by nurses and physicians and total satisfaction with discharge type(p<0.05). Conclusion: The matter of patient's self-discharge is a multi-dimensional phenomenon and depends on patient's characteristics and structural and medical factors. Therefore predicting its scale and determining factors might play an effective role in controlling this phenomenon. [ABSTRACT FROM AUTHOR]

In this paper, we propose a new concurrency control algorithm based on multi-agent systems which is an extension of majority protocol. Then, we suggest a clustering approach to get better results in reliability, decreasing message passing and algorithm's runtime. Here, we consider n different transactions working on non-conflict data items. Considering execution efficiency of some different transactions simultaneously is one of our algorithm features. For evaluating performance of the proposed algorithm we applied it using the MPICH2 mechanism. [ABSTRACT FROM AUTHOR]

The effect of refrigerated storage temperature was studied at 2, 5 and 8°C on the viability of probiotics in ABY (Lactobacillus acidophilus, Bifidobacterium lactis BB-12 and yogurt bacteria. Bulgaricus , i.e. Streptococcus thermophilus and Lactobacillus delbrueckii ssp. Bulgaricus ) probiotic yogurt. The study was carried out during a 20-day refrigerated storage period to identify the best storage temperature(s). Also, the viability change of the probiotic micro-organisms was analysed at 5-day intervals throughout the refrigerated storage period. After 20 days, storage at 2°C resulted in the highest viability of L. acidophilus , whereas for Bifidobacterium lactis the highest viability was obtained when yogurt was stored at 8°C. [ABSTRACT FROM AUTHOR]

In this paper, an exact solution for the equation of two-dimensional transient heat conduction in a hollow sphere made of functionally graded material (FGM) and piezoelectric layers is developed. Transient temperature distribution, as a function of radial and circumferential directions and time with general thermal boundary conditions on the inside and outside surfaces, is analytically obtained for different layers, using the method of separation of variables and Legendre series. The results are the sum of transient and steady-state solutions that depend upon the initial condition for temperature and heat source, respectively. The FGM properties are assumed to depend on the variable r and they are expressed as power functions of r. [ABSTRACT FROM AUTHOR]

Organizations need to evaluate project proposals and select the ones that are the most effective in reaching the strategic goals by considering sustainability issue. In order to enhance the effectiveness and the efficiency of project oriented organizations, in this paper a new multi-objective decision making (MODM) approach of sustainable project portfolio selection is proposed which applies interval-valued fuzzy sets (IVFSs) to consider uncertainty. In the proposed approach, in addition to sustainability criteria, other practical criteria including non-financial benefits, strategic alignment, organizational readiness and project risk are incorporated. The presented approach consists of three main parts: In the first part, a novel composite risk re turn index based on the IVFSs is introduced and used to form the first model to evaluate the financial re turn and risk of the proposed projects. In the second p a rt, a new risk reduction compromise ratio model is introduced to evaluate projects versus non-financial criteria. Finally, an MODM model is presented to form the overall objective function of the approach. In order to make the approach more suitable for real-world situations, a group of applicable constraints is included in the proposed approach. The constraints are based on limitations and issues existing in practical project portfolio management. Due to importance of uncertainty and risk in project portfolio selection, they are addressed separately in three parts of the approach. In the first part, a novel downside risk measure is introduced and applied to assess financial risk of projects. In the second part of the approach, not only project risk is accounted for as a criterion, bu t also a new method is introduced to control and limit the risk of uncertainty and to use the advantages of IVFSs. Finally, the proposed IVF-MODM approach is applied to select the optimal sustainable project portfolio in real case study of a holding company in a developing country. The results show that the approach can successfully address highly uncertain environments. Moreover, risk has been fully explored from different perspectives Eventually, the approach provided the decision makers with more flexibility in focusing on financial and non-financial criteria in the selection process. [ABSTRACT FROM AUTHOR]

In this study we have investigated the effect of montmorillonite with alkyl quaternary ammonium salt that had been doped into the silicon acrylate (AC-Si)/ Epoxy Cresol Novolac (ECN)/ montmorillonite nano composites on structural, mechanical and thermal properties of composite samples. Moreover the effect of increase in weight percentages of fillers at 0.01, 0.02, 0.03 and 0.04 wt% on the amount of Impact and flexural strength had been investigated. Also impact and flexural strength were performed on two different systems namely (a) ECN filled nanoclay and (b) AC-Si ECN filled with nano montmorillonite as a function of clay respectively. By increase in the weight percentage of filler in the context of matrix up to the 0.03 wt%, the amount of flexural and impact strength were increased but by adding filler more that 0.03 wt%, the amount of flexural and impact strength will decrease. The resulting nanocomposites have optimal mechanical properties at 0.03 wt% montmorillonite content. Addition of The AC-Si will increase the interlamellar distance due to better dispersion of the clay within the matrix. Cross section of fracture surfaces that had been shown by SEM micrographs, specifies that, increase in viscosity had caused due to aggregation that is the main cause of fluctuation in samples properties. In addition the produced samples were characterized by X-ray diffraction (XRD) differential scanning calorimetry, Thermal gravimetric analysis, scanning electron microscopy and mechanical testing (impact and flexural). [ABSTRACT FROM AUTHOR]

Although there are different models for determining bond strength and development length of glass fiber-reinforced polymer bar in normal concrete, they cannot evaluate the interfacial behavior of glass fiber-reinforced polymer bar in self-consolidating concrete accurately. This study presents more precise and efficient models for bond strength and development length of glass fiber-reinforced polymer bar in self-consolidating concrete than existing equations. The performance of a model depends very much on test data. Previous researches do not have enough data of bond strength and development length of glass fiber-reinforced polymer bar in self-consolidating concrete. So, more extensive data are needed to investigate the efficiency and accuracy of a model. To solve this problem, direct pull-out tests are performed in this study. Unlike existing models for bond strength and development length, proposed models perform very well for predicting bond strength and development length of glass fiber-reinforced polymer bar in self-consolidating concrete. The new models considerably decrease the deviation of existing models. [ABSTRACT FROM AUTHOR]

In this work, Response Surface Methodology (RSM) and Artificial Neural Networks (ANN) were employed for the data reduction of a numerically simulated extraction process of sugar in an industrial RT2 extractor. The numerical model developed in OpenFOAM library was first validated using actual plant data and its stability and sensitivity to the processing variables was tested. Then, the model was used to generate data of juice and pulp sugar concentrations as affected by the main processing parameters including draft, Silin number, and capacity. The data were modelled using RSM and ANN. Both RSM and ANN were able to predict the data accurately, however, R² values obtained for ANN were slightly higher. Since the numerical model can be time consuming to be solved for all data ranges, the regression equation obtained by the RSM method or the network created according to the ANN model can be utilized as fast and ready to use tools to optimize the extractor. [ABSTRACT FROM AUTHOR]