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The thermal management processes for PhotoVoltaic (PV) cooling applications, increase PV systems’ overall efficiency and yield to a maximized power generation. Accordingly, this paper investigates recent PV thermal management methods, which involve the use of Phase Change Material (PCM) under the back of PV modules. Compared to other cooling methods (such as air and water based methods) PCM based techniques show less need for maintenance, are environment-friendly, and have a longer life cycle. Since PCM are diverse in nature, and many methods exist to guide their selection procedure, this paper begins by revealing different types of PCM, which are found to be as Organic, Inorganic, Eutectic and Commercial PCM, with the characteristics of each. After acknowledging different PCM natures, a selection process is established based on either the melting temperature, latent heat, or thermal conductivity of PCM. Results have shown that Commercial PCM are the best option followed by Organic PCM, due to their improved chemical aspects when compared with Inorganic and Eutectic PCM. Concerning PCM selection criteria, the easiest yet sufficient process is based on the melting temperature method, due to the simplified calculations when compared to other thermic quantities. At the end, future work recommendations are declared, related to PCM lifecycle assessment and cooling/heating cycles effects on PV entropy.

One of the most challenging issues in the domain of renewable energy is the instability of produced power. To put it another way, renewable resources such as solar energy cannot provide continuous energy supply because they rely on natural phenomena that vary randomly. That said, to cover the potential lack of energy that may occur, hybrid renewable energy system can be adopted. In other terms, instead of using single renewable energy source, two different sources can be utilized in order to optimize the output power all over the year. Furthermore, complementary energy system is needed along with renewable sources, to store energy and insure the supply during shortage period. With this in mind, a Green-Green energy system can be constructed by using green storage system such as Fuel Cell to be coupled with the renewable sources. In the light of green-green energy concept, the present paper examines a triple wind-solar-fuel cell combination in the aim of overcoming the energy shortage that occurs during several months of the year. A case study on the region of Dahr Al-Baidar in Lebanon is conducted to present the advantage of the proposed system. Results show that combining wind energy system with thermal solar system allows overcoming the low power produced by solar thermal system especially in winter. For illustration 16 kW are produced by wind turbine during the month of January, by contrast the thermal solar system provides 2 kW during the same period. Nevertheless, in June thermal solar offers 17 kW and wind turbine produces 11 kW.

The current tendency in energy domain is to reduce fuel consumption in favor of sustainable energy approaches. In this frame, the present work suggests an efficient way of heat recovery from boilers using concentric tube. The motivation behind the suggested concept is that it could be considered the cheapest, easiest to construct and simplest to use among all the existing heat recovery systems. In other words, the goal is to suggest a technique that could be utilized by a wider range of users regardless their technical level. Another advantage of the proposed concept is that is can be applied even on small scale boilers. With this in mind, a numerical tool is also developed allowing to make pre-studies to optimize the geometric parameters such as diameters and length, as well as to perform post-studies that allows to optimize operational parameters such as flow rates and fluids configurations. Furthermore, an experimental study is carried-out to validate the numerical results of the adopted heat exchanger. It was shown that water can be heated up to 100 °C depending on the flow rate and that the recovered heat increases through a rational function.

Geothermal heat pump is an efficient application derived from geothermal energy. It exploits earth as a heat provenance to extract heat from it and heat space in winter, or it uses earth as heat sink to transform heat to it and cool the space during summer. This paper presents a parametric study to investigate the effects of inlet and outlet water temperatures and ground temperature on the length of the pipe of a horizontal geothermal heat pump system during cooling process. The type of the considered pipe is Poliplex - PE100 Series 1 – polyethylene of 16 mm inner diameter and 20 mm outer diameter. The obtained results revealed that at 30 °C water inlet temperature, 27 °C water outlet temperature and 21 °C ground temperature the length of pipe needed is 716 m. Also, the results showed that higher water inlet temperature and ground temperature increases the required pipe length; however, higher water outlet temperature decreases the needed length of the pipe.

In this paper, a three dimensional navigation algorithm is proposed for a swarm of medical micro-robots navigating in human blood vessels. The micro robot swarm is intended to be used for treating vascular obstructions, or for precise drug delivery to diseased sites. The proposed algorithm is based on potential functions theory that add an attractive force to the desired path ensuring precise following. Potential functions are also used to ensure a collision-free cohesiveness among the micro-robot swarm elements. Simulation results under MATLAB environment are promising, showing the applicability of the proposed navigation algorithm in possible medical applications.

Background: Breast cancer is the most prevalent kind of cancer among women in Iran. Regarding the importance of cancer prevention and considerable variation of breast cancer incidence in different parts of the country, it is necessary to recognize regions with high incidence of breast cancer and evaluate the role of potential risk factors by use of advanced statistical models. The present study focussed on incidence of breast cancer in Iran at the province level and also explored the impact of some prominent covariates using Bayesian models. Materials and Methods: All patients diagnosed with breast cancer in Iran from 2005 to 2008 were included in the study. Smoking, fruit and vegetable intake, physical activity, obesity and the Human Development Index (HDI), measured at the province level, were considered as potential modulating factors. Gamma-Poisson, log normal and BYM models were used to estimate the relative risk of breast cancer in this ecological investigation with and without adjustment for the covariates. Results: The unadjusted BYM model had the best fit among applied models. Without adjustment, Isfahan, Yazd, and Tehran had the highest incidences and SistanBaluchestan and Chaharmahal-Bakhtiari had the lowest. With the adjusted model, Khorasan-Razavi, Lorestan and Hamedan had the highest and Ardebil and Kohgiluyeh-Boyerahmad the lowest incidences. A significantly direct association was found between breast cancer incidence and HDI. Conclusions: BYM model has better fit, because it contains parameters that allow including effects from neighbors. Since HDI is a significant variable, it is also recommended that HDI should be considered in future investigations. This study showed that Yazd, Isfahan and Tehran provinces feature the highest crude incidences of breast cancer.

This paper deals with nonlinear dynamic modeling of the Proton Exchange Membrane Fuel Cell (PEMFC) dedicated for automotive applications. A time-variant state space model taking into account most of internal phenomena is built. Based on electrical and diffusion approaches, the model proposes a more complete equivalent circuit including all cell components. The proposed circuit couple between gas diffusion, membrane water content, temperature, activation, ohmic and concentration losses, as well as double layer and geometrical capacitances. Similarly to engine vehicles, the model consider the hydrogen flow rate as input controlled by the pilot to change vehicle’s speed. Urban and highway driving cycles similar to those of Nissan LEAF are simulated. Simulation results show that the model responds to both low and high dynamics of power demand. Results reveal that membrane humidity has a considerable effect on the cell’s efficiency. This offer the opportunity to use the model, in a future work, to improve the fuel cell’s efficiency through the control of humidity. The model is validated by experimental tests on a 50 W PEMFC.

As a result of the increasing environmental concern, more and more electricity is generated from renewable sources. Wind power is one of the most reliable sources of renewable energy in the 21st century and helps to meet the national energy demand when there is diminishing trend in terms of non-renewable resources. The performance and efficiency of any wind energy conversion system (WECS) depends upon the characteristics of the components constituting it. One of the most predominant WECS in literature consists of a doubly fed induction generator (DFIG) and a unidirectional power converter controlled by a vector control strategy. In this paper, a DFIG-based wind power system is analyzed, modeled and simulated. The effect of real time simulation and the choice of the used fixed step are discussed and evaluated. The technology's advantages, requirements and related improvements are underlined and results are generalized.

The main purpose of this paper is to design a clean and stand-alone power generator for isolated sites using renewable energy sources. The proposed system is able to operate without the need of refueling. The idea is to combine Photovoltaic Panels (PVs) with Fuel Cell (FC) to build an uninterrupted power generator. In presence of solar energy, PVs are used to feed the site with the required power as well as to produce hydrogen and oxygen using an electrolyzer. When solar energy becomes insufficient, the stored hydrogen and oxygen are used to feed the FC and produce electricity. The proposed system is modeled and controlled using Matlab-Simulink.

In the present work, we develop a dynamical model for single cell of the Proton Exchange Membrane Fuel Cell (PEMFC). The model studies the phenomena of charge and mass transport through the cell elements. It integrates also the electrical aspect related to reaction kinetics by proposing an electrical equivalent circuit of the cell. The influence of gas consumption and humidification rates on water diffusion and membrane humidity are considered. Simulation results are used to verify the model and to build an appropriate control of the membrane humidity. The control which is done by regulating the water mole fractions in gases aims to minimize energy losses. Simulation results show that the control proposed ensures an improvement in the dynamic electrical efficiency.

This paper concerns an experimental study on a system of heat recovery applied to domestic drain water pipes. The concept suggested consists of using the heat still present in the drain water as a preheating/heating source to the cold water supply of the building. To proceed, an appropriate experimental setup is developed and a coil heat exchanger is used as heat transfer device in the recovery system. Several scenarios are simulated and corresponding parameters are recorded and analyzed. It was shown that the suggested recovery concept can considerably preheat the cold water supply and then decrease the energy consumption. Particularly, up to 8.6 kW of heat were recovered when the cold water supply is initially at 3 °C.

Background: Prostate cancer is the most commonly diagnosed form of cancer and the sixth leading cause of cancer-related deaths among men in the entire world. Reported standardized incidence rates are 12.6, 61.7, 11.9 and 27.9 in Iran, developed countries, developing countries and the entire world, respectively. The present study investigated the relative risk of PC in Iran at the province level and also explored the impact of some factors by the use of Bayesian models. Materials and Methods: Our study population was all men with PC in Iran from 2005 to 2008. Considered risk factors were smoking, fruit and vegetable intake, physical activity, obesity and human development index. We used empirical and full Bayesian models to study the relative risk in Iran at province level to estimate the risk of PC more accurately. Results: In Iran from 2005 to 2008 the total number of known PC cases was 10,361 with most cases found in Fars and Tehran and the least in Ilam. In all models just human development index was found to be significantly related to PC risk Conclusions: In the unadjusted model, Fars, Semnam, Isfahan and Tehran provinces have the highest and Sistan-and-Baluchestan has the least risk of PC. In general, central provinces have high risk. After adjusting for covariates, Fars and Zanjan provinces have the highest relative risk and Kerman, Northern Khorasan, Kohgiluyeh Boyer Ahmad, Ghazvin and Kermanshah have the lowest relative risk. According to the results, the incidence of PC in provinces with higher human development index is higher.

This paper proposes a non-linear state-space dynamic model for planar proton exchange membrane fuel cell (PEMFC). Our objective is the realization of a model that evokes a more realistic approach of dynamic behavior of the fuel cell by considering most of elements that influence the system evolution. For instance, pressure, temperature and humidification rate effects on the cell resistance are taken into account. The model is based on both thermodynamic and electrical aspects, proposing a realistic equivalent circuit which integrates most of the fuel cell components. Simulation results show that our proposed model is in agreement with fuel cell real operating principles.

Background: Bronchial hyperresponsiveness and/or bronchospasm are recognized complications of sickle cell disease. Objective: The aim of this study was to investigate the presence of bronchospasm during painful crises, using simple spirometry in patients with sickle cell disease. Methods: A prospective, non-randomized study was undertaken in patients with homozygous sickle cell disease, who presented with increasing pain. A painful crisis was defined as any increase in bodily pains necessitating hospital admission. A 15% increase in FEV1 following salbutamol nebulization was considered significant. Results: Thirty-nine patients took part in the study. Significant bronchodilator responses were demonstrable in 48.7% of patients during painful crises. Patients with such a response had a significantly lower peripheral blood eosinophil count (mean count 0.17 × 109/L vs. 0.445 × 109/L, P = 0.02, confidence interval for difference between groups, 0.0, 0.39). Furthermore, the magnitudes of the bronchodilator responses were related to the degree of lowering of peripheral blood eosinophil counts (rs = −0.344, P = 0.037). Conclusion: Significant bronchospasm is demonstrable in a sizeable proportion of patients presenting with painful sickle cell crises. There seems to be a negative correlation between the magnitude of bronchospasm and the peripheral blood eosinophil count. We postulate a possible role for pulmonary sequestration of eosinophils in the pathophysiology of bronchospasm in sickle cell disease patients.

This paper focuses on the feasibility and the implementation of the hardware in the loop ‘HIL’ technique in a power electronic environment for an optimal management and efficiency in term of energy, time and cost savings. This study will deal with the power electronics of a power traction system. The power system containing a chopper, two three-phase current fed inverters and induction motors is analyzed and simulated according to real time simulation ‘RTS’ requirements. The technology's advantages and related improvements are discussed and results are generalized.

10.8 mos (range: 0.7-37.8). The median primary renal mass size was 8.3cm with 5.9cm sized necrosis. Among the three different times of CT scans, higher correlation of first CT with prognosis of progression (OR 5.843, p1⁄40.022) was found than the others. The tumor size reduction with necrotic size increasing (0.72cm, HR 2.505, CI 1.348-4.655; p1⁄40.004) at initial CT after 1st or 2nd cycle of TT, enhancing HU changes after TTS compared to baseline CT (HR 0.967, CI 0.938-0.996; p1⁄40.025), and RCC histology (HR 0.004 CI 0.000-0.597, p1⁄40.031) were significantly related to the prognosis of survival in patients with mRCC in multivariate analysis (p

This paper presents an artificial neural network (ANN) model for predication global solar radiation (GSR) for main cities in the UAE namely, Abu Dhabi, Al-Ain and Dubai. Multi-Layer Perceptron (MLP) and Radial Basis Function (RBF) techniques with comprehensive training algorithms, architectures, and different combinations of inputs are used to develop these models. The measured data include the maximum temperature (°C), mean wind speed (knot), sunshine hours, mean relative humidity (%) and mean daily global solar radiation on a horizontal surface (kWh/m2). This data was provided by the National Center of Meteorology and Seismology (NCMS) of Abu Dhabi. The results show the generalization capability of ANN approach and its ability to generate accurate prediction of GSR in UAE.

This paper aims to study the dynamic behavior of the fuel cell by focusing on the cell temperature and the membrane humidity effects. The objective is to build a non-linear dynamic model based on the electrical aspect. We consider most of the phenomena that occur inside the fuel cell by assimilating it to an equivalent electrical circuit that associates several elements. The simulations show the influence of the cell temperature and the membrane humidification rate on the power economy. The model built in this paper constitutes an important step towards the optimization of the energy loss inside the cell

The overall efficiency of a PV system is strongly affected by the PV cell raw materials. Since a reliable renewable energy source is expected to produce maximum power with longest lifetime and minimum errors, a critical aspect to bear in mind is the occurrence of PV faults according to raw material types. The different failure scenarios occurring in PV system, decrease its output power, reduce its life expectancy and ban the system from meeting load demands, yielding to severe consecutive blackouts. This paper aims first to present different core materials types, material based fault occurring on the PV cell level and consequently the fault detection techniques corresponding to each fault type.