Serum level of lactate dehydrogenase, homocystein, hemoglobin and platelet in preeclampsia

Objectives: Pre-eclampsia affects approximately 5-8% of pregnant women. The aim of this study was to compare the serum level of Lactate dehydrogenase (LDH), Homocystein, Hemoglubin and platelet in pregnant women diagnosed as pre-eclampsia and a normal group in Gorgan city, Northeastern Iran from 2007-2008. Methodology: In this case control study, 50 cases of pre-eclampsia were compared with the control group women hospitalized in Dezyani hospital. Pre-eclampsia criteria were: Blood pressure more than or equal to 140/90 mm hg and Proteinuria greater or equal to 300 mg/ 24 hours urine sample in the third trimester. Hemoglobin, platelet, LDH and hemocystein were measured. Data were analyzed by the mean of SPSS-14 program & Chi-2 or t-student were used. Results: The difference of BMI and family incomes was significant between two groups (P-value0.01). Hemocystein level was more than normal range in five patients with pre-eclampsia (P-value<0.001). Conclusions: In this study, hemocystein level was significantly higher in pre-eclampsia patients but LDH, hemoglobin and platelet level had no significant difference

Non-Smooth Economic Dispatch Solution by Using Enhanced Bat-Inspired Optimization Algorithm

Economic Dispatch (ED) is one of the most important problems in the operation of power plants which can help to build up effective generating management plans. The practical ED problem has non-smooth cost function with nonlinear constraints which make it difficult to be effectively solved. This paper presents a novel heuristic and efficient optimization approach for a constrained non-smooth economic dispatch (ED) problem using the new Bat algorithm (BA). The proposed algorithm easily takes care of different constraints. Different modifications in moving patterns of the bat optimization method are proposed to search the feasible space more effectively. The simulation results on IEEE 40-unit test system obtained by the proposed algorithms are compared with the results obtained using other recently develop methods available in the literature

An Intelligent Approach Based on Meta-Heuristic Algorithm for Non-Convex Economic Dispatch

One of the significant strategies of the power systems is Economic Dispatch (ED) problem, which is defined as the optimal generation of power units to produce energy at the lowest cost by fulfilling the demand within several limits. The undeniable impacts of ramp rate limits, valve loading, prohibited operating zone, spinning reserve and multi-fuel option on the economic dispatch of practical power systems are scrutinized in this paper. Thus, the proposed nonlinear non-convex formulation is solved by a new modified version of bio-inspired bat algorithm. Due to the complexities associated with the large-scale optimization problem of economic dispatch, adaptive modifications are added to the original bat algorithm. The modification methods are applied at two separate stages and pledge augmentation in convergence rate of the algorithm as well as extricating the algorithm from local optima. Veracity of the proposed methodology are corroborated by performing simulations on three IEEE test systems

Dynamic Modeling and Simulation of a STATCOM/SMES Compensator in Power Systems

The advent of Flexible AC Transmission Systems (FACTS) is giving rise to a new family of electronic equipment emerging to controlling and optimizing the performance of power system, e.g. STATCOM. Static synchronous compensator (STATCOM) is one of the most widely used FACTS devices. This paper presents the integration of STATCOM coupled with superconducting magnetic energy storage (SMES) device in order to provide power oscillation damping in power systems. The additional of energy storage allows the combined compensator to exchange both reactive and active power with the ac network and also capability of the STATCOM is enhanced. This paper describes the structure and characteristics of STATCOM/SMES. In addition, using a proper control scheme, STATCOM/SMES is tested on an IEEE 3-bus system and more effective performance of the presented STATCOM/SMES compensator is evaluated with alone STATCOM through the dynamic simulation by using PSCAD/EMTDC software

Detection of titanium oxide in the atmosphere of a hot Jupiter.

As an exoplanet transits its host star, some of the light from the star is absorbed by the atoms and molecules in the planet's atmosphere, causing the planet to seem bigger; plotting the planet's observed size as a function of the wavelength of the light produces a transmission spectrum. Measuring the tiny variations in the transmission spectrum, together with atmospheric modelling, then gives clues to the properties of the exoplanet's atmosphere. Chemical species composed of light elements-such as hydrogen, oxygen, carbon, sodium and potassium-have in this way been detected in the atmospheres of several hot giant exoplanets, but molecules composed of heavier elements have thus far proved elusive. Nonetheless, it has been predicted that metal oxides such as titanium oxide (TiO) and vanadium oxide occur in the observable regions of the very hottest exoplanetary atmospheres, causing thermal inversions on the dayside. Here we report the detection of TiO in the atmosphere of the hot-Jupiter planet WASP-19b. Our combined spectrum, with its wide spectral coverage, reveals the presence of TiO (to a confidence level of 7.7σ), a strongly scattering haze (7.4σ) and sodium (3.4σ), and confirms the presence of water (7.9σ) in the atmosphere

Atmospheric retrieval of exoplanets

Exoplanetary atmospheric retrieval refers to the inference of atmospheric properties of an exoplanet given an observed spectrum. The atmospheric properties include the chemical compositions, temperature profiles, clouds/hazes, and energy circulation. These properties, in turn, can provide key insights into the atmospheric physicochemical processes of exoplanets as well as their formation mechanisms. Major advancements in atmospheric retrieval have been made in the last decade, thanks to a combination of state-of-the-art spectroscopic observations and advanced atmospheric modeling and statistical inference methods. These developments have already resulted in key constraints on the atmospheric H2O abundances, temperature profiles, and other properties for several exoplanets. Upcoming facilities such as the JWST will further advance this area. The present chapter is a pedagogical review of this exciting frontier of exoplanetary science. The principles of atmospheric retrievals of exoplanets are discussed in detail, including parametric models and statistical inference methods, along with a review of key results in the field. Some of the main challenges in retrievals with current observations are discussed along with new directions and the future landscape