Robust Coordinated Design of PSS and TCSC using PSO Technique for Power System Stability Enhancement

Power system stability improvement by coordinated design of a Power System Stabilizer (PSS) and a Thyristor Controlled Series Compensator (TCSC) controller is addressed in this paper. Particle Swarm Optimization (PSO) technique is employed for optimization of the parameterconstrained nonlinear optimization problem implemented in a simulation environment. The proposed controllers are tested on a weakly connected power system. The non-linear simulation results are presented for wide range of loading conditions with various fault disturbances and fault clearing sequences as well as for various small disturbances. The eigenvalue analysis and simulation results show the effectiveness and robustness of proposed controllers to improve the stability performance of power system by efficient damping of low frequency oscillations under various disturbances

Prevalence of multidrug resistant uropathogenic bacteria in pediatric patients of a tertiary care hospital in eastern India

SummaryToday, because systemic infections such as urinary tract infection (UTI) affect even pediatric patients, antibiotic resistant bacteria have become a constant clinical challenge. In the present study, a total of 1054 urine samples were collected from pediatric patients over 18 months. From these samples, 510 isolates of pathogenic bacteria were collected using HiCrome UTI agar. Antibiotic sensitivity tests of isolates were performed using the Kirby–Bauer method. Two Gram-positive bacteria (Enterococcus faecalis and Staphylococcus aureus) and 7 Gram-negative bacteria (Citrobacter freundii, Enterobacter aerogenes, Escherichia coli, Klebsiella oxytoca, K. pneumoniae, Proteus vulgaris and Pseudomonas aeruginosa) were isolated. Antibiograms of isolated bacteria were ascertained using antibiotics of 4 classes: aminoglycosides, β-lactams, fluoroquinolones and 2 stand-alones (co-trimoxazole and nitrofurantoin). Based on percent values of antibiotic resistance, isolated bacteria were (in decreasing order of number of isolated isolates): E. coli (109)>S. aureus (65)>E. faecalis (82)>E. aerogenes (64)>C. freundii (41)>P. aeruginosa (32)>K. pneumoniae (45)>K. oxytoca (50)>P. vulgaris (22). Surveillance results show that MDR isolates of 9 pathogenic bacteria were prevalent in the environment around the hospital. Thus, revisions to the antimicrobial stewardship program in this area of the country are required to increase clinician confidence in empiric therapy, which is often used for UTI cases

Prevalence and identification of Candida sp. in pregnant women using VITEK-2

Background: Candida sp. is seen in several areas of body such as, mouth, groin area including vagina and digestive tract as thrush or gastroenteritis. The slide-culture technique and the VITEK-2 automated system were used for species-identification of the fungus; nonetheless, a gold standard or any first identification method would have inherent errors in arriving at a correct identification of a microorganism at species level.Methods: Morphological fungal criteria were ascertained with germ tubes, glucose agar, sugar fermentation and sugar assimilation tests Candida from vaginal swabs and other clinical samples of 85 infected pregnant women with diabetes, by growing swab lots on Sabouraud’s Dextrose Agar (SDA) plates, the slide culture technique and the VITEK-2 automated system.Results: Of 85 patients, 122 isolates in SDA culture were determined as 7 Candida sp.  with number of isolates of each species, as follows: 47 C. albicans, 9 C. famata, 11 C. glabrata, 13 C. guilliermondii, 8 C. krusei, 3 C. parapsilosis and 37 C. tropicalis from vaginal swabs. From 60 vaginal swabs, 46 urine samples and 12 throat swabs it was seen that C. albicans was most prevalent. However, withVITEK-2, 201 fungal strains were identified; Candida sp. was isolated in all samples: 59 C. albicans, 19 C. famata, 21 C. glabrata, 23 C. guilliermondii,18 C. krusei, 13 C. parapsilosis and 48 C. tropicalis.Conclusions: The most prevalent species among the isolated fungi was C. albicans, causing VC in diabetic pregnant women

Large-scale unit commitment under uncertainty: an updated literature survey

The Unit Commitment problem in energy management aims at finding the optimal production schedule of a set of generation units, while meeting various system-wide constraints. It has always been a large-scale, non-convex, difficult problem, especially in view of the fact that, due to operational requirements, it has to be solved in an unreasonably small time for its size. Recently, growing renewable energy shares have strongly increased the level of uncertainty in the system, making the (ideal) Unit Commitment model a large-scale, non-convex and uncertain (stochastic, robust, chance-constrained) program. We provide a survey of the literature on methods for the Uncertain Unit Commitment problem, in all its variants. We start with a review of the main contributions on solution methods for the deterministic versions of the problem, focussing on those based on mathematical programming techniques that are more relevant for the uncertain versions of the problem. We then present and categorize the approaches to the latter, while providing entry points to the relevant literature on optimization under uncertainty. This is an updated version of the paper "Large-scale Unit Commitment under uncertainty: a literature survey" that appeared in 4OR 13(2), 115--171 (2015); this version has over 170 more citations, most of which appeared in the last three years, proving how fast the literature on uncertain Unit Commitment evolves, and therefore the interest in this subject

Artificial intelligence and intelligent systems

New Yorkxvoo, 614 p.; fig.; 24 cm