An integrated methodology to control the risk of cardiovascular disease in patients with hypertension and type 1 diabetes

Today, air pollution, smoking, use of fatty acids and ready‐made foods, and so on, have exacerbated heart disease. Therefore, controlling the risk of such diseases can prevent or reduce their incidence. The present study aimed at developing an integrated methodology including Markov decision processes (MDP) and genetic algorithm (GA) to control the risk of cardiovascular disease in patients with hypertension and type 1 diabetes. First, the efficiency of GA is evaluated against Grey Wolf optimization (GWO) algorithm, and then, the superiority of GA is revealed. Next, the MDP is employed to estimate the risk of cardiovascular disease. For this purpose, model inputs are first determined using a validated micro‐simulation model for screening cardiovascular disease developed at Tehran University of Medical Sciences, Iran by GA. The model input factors are then defined accordingly and using these inputs, three risk estimation models are identified. The results of these models support WHO guidelines that provide medicine with a high discount to patients with high expected LYs. To develop the MDP methodology, policies should be adopted that work well despite the difference between the risk model and the actual risk. Finally, a sensitivity analysis is conducted to study the behavior of the total medication cost against the changes of parameters.     

Classification of primitive shapes using brain–computer interfaces

Brain–computer interfaces (BCIs) are recent developments in alternative technologies of user interaction. The purpose of this paper is to explore the potential of BCIs as user interfaces for CAD systems. The paper describes experiments and algorithms that use the BCI to distinguish between primitive shapes that are imagined by a user. Users wear an electroencephalogram (EEG) headset and imagine the shape of a cube, sphere, cylinder, pyramid or a cone. The EEG headset collects brain activity from 14 locations on the scalp. The data is analyzed with independent component analysis (ICA) and the Hilbert–Huang Transform (HHT). The features of interest are the marginal spectra of different frequency bands (theta, alpha, beta and gamma bands) calculated from the Hilbert spectrum of each independent component. The Mann–Whitney U-test is then applied to rank the EEG electrode channels by relevance in five pair-wise classifications. The features from the highest ranking independent components form the final feature vector which is then used to train a linear discriminant classifier. Results show that this classifier can discriminate between the five basic primitive objects with an average accuracy of about 44.6% (compared to naïve classification rate of 20%) over ten subjects (accuracy range of 36%–54%). The accuracy classification changes to 39.9% when both visual and verbal cues are used. The repeatability of the feature extraction and classification was checked by conducting the experiment on 10 different days with the same participants. This shows that the BCI holds promise in creating geometric shapes in CAD systems and could be used as a novel means of user interaction.     

Investigation of basic molecular gas structural effects on hydrodynamics and thermal behaviors of rarefied shear driven micro/nano flow using DSMC

In the present work, rarefied gas flow between two parallel moving plates maintained at the same uniform temperature is simulated using the direct simulation Monte Carlo (DSMC) method. Heat transfer and shear stress behavior in the micro/nano-Couette flow is studied and the effects of the important molecular structural parameters such as molecular diameter, mass, degrees of freedom and viscosity–temperature index on the macroscopic behavior of gases are investigated. Velocity, temperature, heat flux and shear stress in the domain are studied in details. Finally, a discussion on the role of the molecular structural parameters in the decrease or increase of amounts of hydrodynamics and thermal properties of the gas is presented.     

Microstructure and mechanical properties of a laser welded low carbon–stainless steel joint

This article reports on an experimental investigation to understand and subsequently control the alloying composition in laser welding of austenitic stainless steel and low carbon steel. An energy dispersive spectrometer was used to analyse the alloying composition, while microscopy and tensile tests were used to study the microstructure, and mechanical performance of the welded joint respectively. The investigation revealed that above a certain specific point energy the material within the melt pool is well mixed and the laser beam position can be used to control the mechanical properties of the joint. This finding was confirmed using a numerical model based on computational fluid dynamics (CFD) of melt pool dynamics. Strategies to control the composition leading to dramatic changes in hardness, microstructure and mechanical properties of the dissimilar laser welded joint are discussed.     

A multiobjective integrated multiproject scheduling and multiskilled workforce assignment model considering learning effect under uncertainty

Today, organizations try to decline academically expenses using humans and resources in addition to rising managers and operators' satisfaction. Meantime, a very important step in the process of decision is the assignment of human resources, particularly in connection with research and development (R&D) projects in which the system is highly dependent on the capabilities of human resources. In this study, we tried all the assumptions that come true in the real world, considered a model for applied R&D projects to reduce costs and increase the efficiency of projects. Therefore, an integrated multiproject scheduling and multiskill human resource assignment model under uncertainty has developed for R&D projects. Furthermore, it is assumed that the activity processing time is related to human resources assignment that means the learning effect is considered. To demonstrate the proposed model efficiency, the various dimensions instance problem was solved accurately and efficiently in GAMS software, and the results have been reported. In addition, the proposed model is validated through the input parameter sensitivity analysis. The results indicate a suitable performance of the proposed fuzzy mathematical programming model is due to the complexity of the problem.     

Evaluation of multiloop chemical dosage control strategies for total phosphorus removal of enhanced biological nutrient removal process

We developed several control algorithms and compare their control performances for controlling the total phosphorous (TP) concentration in wastewater treatment plant, which has strong influent disturbances and the disturbance effects should be removed while maintaining better effluent quality. An anaerobic - anoxic - oxic (AAO) process, which is a well-known advanced nutrient removal process, was selected as a case study, which is modeled with activated sludge model no. 2. Six control strategies for TP control with a polymer addition were implemented in AAO process and evaluated by the plant’s performance, where the costs of the dosed chemical were compared among the six controllers. The experimental work showed that the advanced control techniques with feedback, feedforward and feedratio controllers were able to control the TP concentration in the effluent, which must be less than 1.50 g P/m³ which is the legal limitation, while reducing the necessary chemical cost. The results showed that the best TP removal performance in the effluent TP removal could be achieved by advanced feedback controller with the tuned control parameters, which showed the best effluent quality and control performance index as well as the cheapest cost of chemical dosage among the six TP control strategies.     

Feasibility study and performance assessment for the integration of a steam-injected gas turbine and thermal desalination system

This study proposes a systematic approach for retrofitting a steam-injection gas turbine (SIGT) with a multi-effect thermal vapor compression (METVC) desalination system. The retrofitted unit's product cost of the fresh water (RUPC) was used as a performance criterion, which comprises the thermodynamic, economic, and environmental attributes when calculating the total annual cost of the SIGT–METVC system. For the feasibility study of retrofitting the SIGT plant with the METVC desalination system, the effects of two key parameters were analyzed using response surface methodology (RSM) based on a central composite design (CCD): the steam air ratio (SR) and the temperature difference between the effects of the METVC system (?T_METVC) on the fresh water production (Q_freshwater) and the net power generation (W_net) of the SIGT–METVC system. Multi-objective optimization (MOO) which minimizes the modified total annual cost (MTAC) and maximizes the fresh water flow rate was performed to optimize the RUPC of the SIGT–METVC system. The best Pareto optimal solution showed that the SIGT–METVC system with five effects is the best one among the systems with 4–6 effects. This system under optimal operating conditions can save 21.07% and 9.54% of the RUPC, compared to the systems with four and six effects, respectively.     

Reductive removal of hexavalent chromium from aqueous solution using sepiolite-stabilized zero-valent iron nanoparticles: Process optimization and kinetic studies

We studied the optimization of hexavalent chromium (Cr(VI)) removal from aqueous solution using the synthesized zero-valent iron nanoparticles stabilized with sepiolite clay (S-ZVIN), under various parameters such as reaction time (min), initial solution pH and concentration of S-ZVIN (g·L^?1) using response surface methodology (RSM). The kinetic study of Cr(VI) was conducted using three types of the most commonly used kinetic models including pseudo zero-order, pseudo first-order, and pseudo second-order models. The rate of reduction reaction showed the best fit with the pseudo first-order kinetic model. The process optimization results revealed a high agreement between the experimental and the predicted data (R²=0.945, Adj-R²=0.890). The results of statistical analyses showed that reaction time was the most impressive factor influencing the efficiency of removal process. The optimum conditions for maximum response (98.15%) were achieved at the initial pH of 4.7, S-ZVIN concentration of 1.3 g·L^?1 and the reaction time of 75 min.     

Integrated Index for Assessment of Vulnerability to Drought,Case Study: Zayandehrood River Basin,Iran

Drought is an extended period of deficient precipitation that causes damage to crops and reducing their performance, causes temporary scarcity of water for human/livestock consumption. Over the years, various indices have been proposed to identify onset, characterize and quantify the attributes of meteorological, hydrological and agricultural drought by various researchers. Because of the spatial and temporal variability and multiple impacts of drought, it is necessary to develop an integrated index for assessment of vulnerability of this natural phenomenon. The aim of this paper is presenting an integrated index for assessment of vulnerability to drought using multiple factors which includes hydrological, meteorological, land use and other factors. Spatial information of various factors was categorized in to various sub-classes and maps were prepared in spatial domain using Geographic Information System (GIS). This study has been carried out in the Zayandehrood River basin located in west-central Iran with semi-arid region. Due to continue droughts at recent decade, this area has been chosen as a case study. The long-term climate data (1991–2011) used for assessment. The results show that Zayandehrood River basin has experienced 11 dry years, 4 normal years, and 6 wet years in the 21 years. The results have been validated with intensive field surveys.