Retrospect, resurgence and prospects of micelles

Recent studies on micellar systems were systematically overviewed, paying special attention to Gemini surfactants, mixed micelles, clouding phenomena and microemulsions. Gemini surfactants are surfactants that have two hydrophilic groups and two hydrophobic groups per amphiphilic molecule, rather than the single hydrophilic and single hydrophobic group of conventional surfactants. The greater efficiency and effectiveness of geminis over comparable conventional surfactants make them more cost effective as well as environmentally desirable. Mixed micelles have received wide attention for several decades, both in theoretical studies and in practical applications, because of their distinctive behaviour in comparison with normal micellar systems. Clouding (cloud point, CP) is a well known phenomenon observed in non-ionic surfactants. For charged micelles (i.e., ionic surfactants), the phenomenon rarely occurs, however, under special conditions, the CP in ionic surfactant solutions is observed. Some amphiphilic drugs, like ionic surfactants, also undergo pH-, concentration-, and temperature- dependent phase separation. It was observed that their CP can vary with additives. Due to their unique properties, namely, thermodynamic stability, ultralow interfacial tension, large interfacial area and the ability to solubilize otherwise immiscible liquids, microemulsions have attained increasing significance both in basic research and in industry. The uses and applications of microemulsions have been numerous. Several reviews on micellar systems and their applications have been published. However, this topic is developing quite rapidly and it is hoped that this review will help newcomers in the field as well as those already involved in this field

The effectiveness of introducing Group Prenatal Care (GPC) in selected health facilities in a district of Bangladesh: study protocol.

Background Despite high rates of antenatal care and relatively good access to health facilities, maternal and neonatal mortality remain high in Bangladesh. There is an immediate need for implementation of evidence-based, cost-effective interventions to improve maternal and neonatal health outcomes. The aim of the study is to assess the effect of the intervention namely Group Prenatal Care (GPC) on utilization of standard number of antenatal care, post natal care including skilled birth attendance and institutional deliveries instead of usual care. Methods The study is quasi-experimental in design. We aim to recruit 576 pregnant women (288 interventions and 288 comparisons) less than 20 weeks of gestational age. The intervention will be delivered over around 6 months. The outcome measure is the difference in maternal service coverage including ANC and PNC coverage, skilled birth attendance and institutional deliveries between the intervention and comparison group. Discussion Findings from the research will contribute to improve maternal and newborn outcome in our existing health system. Findings of the research can be used for planning a new strategy and improving the health outcome for Bangladeshi women. Finally addressing the maternal health goal, this study is able to contribute to strengthening health system

Prevalence, antibiotic susceptibility profiles and ESBL production in Klebsiella pneumoniae and Klebsiella oxytoca among hospitalized patients

Background and Purpose: Klebsiella pneumoniae and Klebsiella oxytoca are the two most common pathogens causing nosocomial infections in humans and are of great concern for developing multidrug resistance. In the present study, K. pneumoniae and K. oxytoca from clinical samples were evaluated for their antibiotic sensitivity patterns against commonly used antibiotics and production of extended-spectrum beta-lactamase (ESBL). Materials and Methods: The isolates were obtained from tracheal swabs, sputum, wound swabs, pus, blood and urine samples of hospitalized patients. Klebsiella pneumoniae and Klebsiella oxytoca were identified by cultural and biochemical methods. Antibiotic sensitivity test was performed by modified Kirby-Bauer disc diffusion technique. ESBL production in Klebsiella spp. was confirmed by double disc synergy test. Results and Conclusion: Out of 500 clinical isolates, 120 were found positive for Klebsiella among which 108 were K. pneumoniae and 12 were K. oxytoca based on indole test. Prevalence rate of Klebsiella was found more prominent in males aged over 50 years, mostly in urine samples. Overall resistance pattern of Klebsiella isolates to Ampicillin, Amoxicillin, Ceftriaxone, Ciprofloxacin, Co-trimoxazole, Gentamicin, Nalidixic acid, Tetracycline was 100%, 90%, 45%, 40%, 45%, 25%, 50%, 35% respectively. Multidrug resistance was found more common in K. pneumoniae (56%) than in K. oxytoca (50%). Prevalence rate of ESBL producing Klebsiella was found 45% among which K. pneumoniae (50%) were found more prominent than K. oxytoca (25%). All the ESBL producing Klebsiella isolates were found to be multidrug resistant, showing 100% resistance to Ampicillin, Amoxicillin, Ceftriaxone and Ciprofloxacin

Economic power dispatch solutions incorporating stochastic wind power generators by moth flow optimizer

Optimization encourages the economical and efficient operation of the electrical system. Most power system problems are nonlinear and nonconvex, and they frequently ask for the optimization of two or more diametrically opposed objectives. The numerical optimization revolution led to the introduction of numerous evolutionary algorithms (EAs). Most of these methods sidestep the problems of early convergence by searching the universe for the ideal. Because the field of EA is evolving, it may be necessary to reevaluate the usage of new algorithms to solve optimization problems involving power systems. The introduction of renewable energy sources into the smart grid of the present enables the emergence of novel optimization problems with an abundance of new variables. This study's primary purpose is to apply state-of-the-art variations of the differential evolution (DE) algorithm for single-objective optimization and selected evolutionary algorithms for multi-objective optimization issues in power systems. In this investigation, we employ the recently created metaheuristic algorithm known as the moth flow optimizer (MFO), which allows us to answer all five of the optimal power flow (OPF) difficulty objective functions: (1) reducing the cost of power generation (including stochastic solar and thermal power generation), (2) diminished power, (3) voltage variation, (4) emissions, and (5) reducing both the cost of power generating and emissions. Compared to the lowest figures provided by comparable approaches, MFO's cost of power production for IEEE-30 and IEEE-57 bus architectures is $888.7248 per hour and$ 31121.85 per hour, respectively. This results in hourly cost savings between 1.23 % and 1.92%. According to the facts, MFO is superior to the other algorithms and might be utilized to address the OPF problem

Trends, determinants and inequities of 4+ ANC utilisation in Bangladesh

Background: The objectives of this study are to document the trend on utilisation of four or more (4+) antenatal care (ANC) over the last 22 years period and to explore the determinants and inequity of 4+ ANC utilisation as reported by the last two Bangladesh Demographic and Health surveys (BDHS) (2011 and 2014). Methods: The data related to ANC have been extracted from the BDHS data set which is available online as an open source. STATA 13 software was used for organising and analysing the data. The outcome variable considered for this study was utilisation of 4+ ANC. Trends of 4+ ANC were measured in percentage and predictors for 4+ ANC were measured through bivariate and multivariable analysis. The concentration index was estimated for assessing inequity in 4+ ANC utilisation. Results: Utilisation of 4+ ANC has increased by about 26% between the year 1994 and 2014. Higher level of education, residing in urban region and richest wealth quintile were found to be significant predictors. The utilisation of 4+ ANC has decreased with increasing parity and maternal age. The inequity indices showed consistent inequities in 4+ ANC utilisation, and such inequities were increased between 2011 and 2014. Conclusions: In Bangladesh, the utilisation of any ANC rose steadily between 1994 and 2014, but progress in terms of 4+ ANC utilisation was much slower as the expectation was to achieve the national set target (50%: 4+ ANC utilisation) by 2016. Socio-economic inequities were observed in groups that failed to attend a 4+ ANC visit. Policymakers should pay special attention to increase the 4+ ANC coverage where this study can facilitate to identify the target groups whom need to be intervened on priority basis

Moth Flame Optimization Algorithm including Renewable Energy for Minimization of Generation & Emission Costs in Optimal Power Flow

Optimal power flow is an approach for enhancing power system performance, scheduling, and energy management. Because of its adaptability in a variety of settings, optimum power flow is becoming increasingly vital. The demand for optimization is driven by the need for cost-effective, efficient, and optimum solutions. Optimization is useful in a variety of fields, including science, economics, and engineering. This problem must be overcome to achieve the goals while keeping the system stable. Moth Flame Optimization (MFO), a recently developed metaheuristic algorithm, will be used to solve objective functions of the OPF issue for combined cost and emission reduction in IEEE 57-bus systems with thermal and stochastic wind-solar-small hydropower producing systems. According to the data, the MFO generated the best results across all simulated research conditions. MFO, for example, offers a total cost and emission of power generation of 248.4547 $/h for IEEE 57-bus systems, providing a 1.5 percent cost savings per hour above the worst values obtained when comparing approaches. According to the statistics, MFO beats the other algorithms and is a viable solution to the OPF proble

Success history moth flow optimization for multi-goal generation dispatching with nonlinear cost functions

Combined Economic Emission Dispatch (CEED) is resolved by combining Success History Moth Flow Optimization (SHMFO) and valve-point loading of thermal generators. This SHMFO the valve-point loading problem is a multi-objective nonlinear optimization problem including generator capacity limits and power balance. The valve-point loading causes oscillations in the input-output characteristics of generating units, hence rendering the CEED problem an imperfect optimization problem. As a benchmark test system for validating the efficacy of SHMFO, IEEE 30-bus systems are studied. Comparing the SHMFO method to other optimization strategies revealed its superiority and proved its capacity to resolve the CEED issue. The OPF is framed as a single or multiobjective problem with restrictions on generator capability, line capacity, bus voltage, and power flow balance to minimize fuel cost, emission, transmission loss, voltage deviation, etc. The numerical findings indicate that the SHMFO algorithm can provide cost-efficiency, diversity, and convergence in a single run. SHMFO performs better than the other algorithms and is an excellent choice for addressing the OPF problem, as shown by the results. On non-dominated solutions, a method adapted from the Technique for Ordering Preferences by Similarity to Ideal Solution (TOPSIS) is used to establish the Best Compromise Solution (BCS)