High dietary diversity is associated with obesity in Sri Lankan adults : an evaluation of three dietary scores

Background Dietary diversity is recognized as a key element of a high quality diet. However, diets that offer a greater variety of energy-dense foods could increase food intake and body weight. The aim of this study was to explore association of diet diversity with obesity in Sri Lankan adults. Methods Six hundred adults aged > 18 years were randomly selected by using multi-stage stratified sample. Dietary intake assessment was undertaken by a 24 hour dietary recall. Three dietary scores, Dietary Diversity Score (DDS), Dietary Diversity Score with Portions (DDSP) and Food Variety Score (FVS) were calculated. Body mass index (BMI) ≥ 25 kg.m-2 is defined as obese and Asian waist circumference cut-offs were used diagnosed abdominal obesity. Results Mean of DDS for men and women were 6.23 and 6.50 (p=0.06), while DDSP was 3.26 and 3.17 respectively (p=0.24). FVS values were significantly different between men and women 9.55 and 10.24 (p=0.002). Dietary diversity among Sri Lankan adults was significantly associated with gender, residency, ethnicity, education level but not with diabetes status. As dietary scores increased, the percentage consumption was increased in most of food groups except starches. Obese and abdominal obese adults had the highest DDS compared to non obese groups (p<0.05). With increased dietary diversity the level of BMI, waist circumference and energy consumption was significantly increased in this population. Conclusion Our data suggests that dietary diversity is positively associated with several socio-demographic characteristics and obesity among Sri Lankan adults. Although high dietary diversity is widely recommended, public health messages should emphasize to improve dietary diversity in selective food items.

Diabetes mellitus in South Asia : scientific evaluation of the research output

BACKGROUND: Diabetes in South Asia represents a different disease entity in terms of its onset, progression, and complications. In the present study, we systematically analyzed the medical research output on diabetes in South Asia. METHODS: The online SciVerse Scopus database was searched using the search terms "diabetes" and "diabetes mellitus" in the article Title, Abstract or Keywords fields, in conjunction with the names of each regional country in the Author Affiliation field. RESULTS: In total, 8478 research articles were identified. Most were from India (85.1%) and Pakistan (9.6%) and the contribution to the global diabetes research output was 2.1%. Publications from South Asia increased markedly after 2007, with 58.7% of papers published between 2000 and 2010 being published after 2007. Most papers were Research Articles (75.9%) and Reviews (12.9%), with only 90 (1.1%) clinical trials. Publications predominantly appeared in local national journals. Indian authors and institutions had the most number of articles and the highest h-index. There were 136 (1.6%) intraregional collaborative studies. Only 39 articles (0.46%) had >100 citations. CONCLUSIONS: Regional research output on diabetes mellitus is unsatisfactory, with only a minimal contribution to global diabetes research. Publications are not highly cited and only a few randomized controlled trials have been performed. In the coming decades, scientists in the region must collaborate and focus on practical and culturally acceptable interventional studies on diabetes mellitus.

The impact on clinical practice of a postgraduate clinical pharmacy programme, incorporating competency-based performance evaluation

Background A goal of the postgraduate clinical pharmacy programme (PGCPP) at the University of Queensland is to enhance clinical practice. Aims To evaluate student perceptions of the impact of the PGCPP on practice and the inclusion of a competency-based performance evaluation as a formative component of the curriculum. Method In 2010, students completed a questionnaire to evaluate the impact of the PGCPP. In 2011, formative competency-based performance evaluations were conducted as a component of the course and the questionnaire was repeated. Responses, competency ratings and evaluation feedback were collated. Data were analysed using descriptive statistics. Results 51/57 (89%) of students completed the questionnaire in 2010 and 2011. Over 90% of students agreed or strongly agreed that the PGCPP enhanced practice, knowledge, confidence and contribution to patient care. Responses were similarly positive after the inclusion of the performance evaluation. Conclusion This study demonstrated that the PGCPP is achieving the goal of enhancing the practice of pharmacists.

A hybrid genetic algorithm for the energy-efficient virtual machine placement problem in data centers

Server consolidation using virtualization technology has become an important technology to improve the energy efficiency of data centers. Virtual machine placement is the key in the server consolidation technology. In the past few years, many approaches to the virtual machine placement have been proposed. However, existing virtual machine placement approaches consider the energy consumption by physical machines only, but do not consider the energy consumption in communication network, in a data center. However, the energy consumption in the communication network in a data center is not trivial, and therefore should be considered in the virtual machine placement. In our preliminary research, we have proposed a genetic algorithm for a new virtual machine placement problem that considers the energy consumption in both physical machines and the communication network in a data center. Aiming at improving the performance and efficiency of the genetic algorithm, this paper presents a hybrid genetic algorithm for the energy-efficient virtual machine placement problem. Experimental results show that the hybrid genetic algorithm significantly outperforms the original genetic algorithm, and that the hybrid genetic algorithm is scalable.

An evaluation of medication review reports across different settings

Background There is a growing body of evidence which supports that a pharmacist conducted medication review increases the health outcomes for patients. A pharmacist integrated into a primary care medical centre may offer many potential advantages in conducting medication reviews in this setting however research describing this is presently limited. Objective To compare medication review reports conducted by pharmacists practicing externally to a medical centre to those medication review reports conducted by an integrated practice pharmacist. The secondary objective was to compare medication review reports conducted by pharmacists in the patient’s home to those conducted in the medical centre. Setting A primary care medical centre, Brisbane, Australia Method A retrospective analysis of pharmacist conducted medication reviews prior to and after the integration of a pharmacist into a medical centre. Main outcome measures Types of drug related problems identified by the Pharma cists, recommended intervention for drug related problems made by the pharmacist, and the extent of implementation of pharmacist recommendations by the general practitioner. Results The primary drug related problem reported in the practice pharmacist phase was Additional therapy required as compared to Precautions in the external pharmacist phase. The practice pharmacist most frequently recommended to add drug with Additional monitoring recommended most often in the external pharmacists. During the practice pharmacist phase 71 % of recommendations were implemented and was significantly higher than the external pharmacist phase with 53 % of recommendations implemented (p\0.0001). Two of the 23 drug related problem domains differed significantly when comparing medication reviews conducted in the patient’s home to those conducted in the medical centre.

Evaluation of MegaVoltage Cone Beam CT image quality with an unmodified Elekta Precise Linac and EPID : a feasibility study

In order to increase the accuracy of patient positioning for complex radiotherapy treatments various 3D imaging techniques have been developed. MegaVoltage Cone Beam CT (MVCBCT) can utilise existing hardware to implement a 3D imaging modality to aid patient positioning. MVCBCT has been investigated using an unmodified Elekta Precise linac and 15 iView amorphous silicon electronic portal imaging device (EPID). Two methods of delivery and acquisition have been investigated for imaging an anthropomorphic head phantom and quality assurance phantom. Phantom projections were successfully acquired and CT datasets reconstructed using both acquisition methods. Bone, tissue and air were 20 clearly resolvable in both phantoms even with low dose (22 MU) scans. The feasibility of MegaVoltage Cone beam CT was investigated using a standard linac, amorphous silicon EPID and a combination of a free open source reconstruction toolkit as well as custom in-house software written in Matlab. The resultant image quality has 25 been assessed and presented. Although bone, tissue and air were resolvable 2 in all scans, artifacts are present and scan doses are increased when compared with standard portal imaging. The feasibility of MVCBCT with unmodified Elekta Precise linac and EPID has been considered as well as the identification of possible areas for future development in artifact correction techniques to 30 further improve image quality.

An efficient hybrid evolutionary optimization algorithm based on PSO and SA for clustering

The K-means algorithm is one of the most popular techniques in clustering. Nevertheless, the performance of the K-means algorithm depends highly on initial cluster centers and converges to local minima. This paper proposes a hybrid evolutionary programming based clustering algorithm, called PSO-SA, by combining particle swarm optimization (PSO) and simulated annealing (SA). The basic idea is to search around the global solution by SA and to increase the information exchange among particles using a mutation operator to escape local optima. Three datasets, Iris, Wisconsin Breast Cancer, and Ripley’s Glass, have been considered to show the effectiveness of the proposed clustering algorithm in providing optimal clusters. The simulation results show that the PSO-SA clustering algorithm not only has a better response but also converges more quickly than the K-means, PSO, and SA algorithms.

An efficient hybrid evolutionary optimization algorithm for daily volt/var control at distribution system including DGs

This paper presents a new hybrid evolutionary algorithm based on Particle Swarm Optimization (PSO) and Ant Colony Optimization (ACO) for daily Volt/Var control in distribution system including Distributed Generators (DGs). Due to the small X/R ratio and radial configuration of distribution systems, DGs have much impact on this problem. Since DGs are independent power producers or private ownership, a price based methodology is proposed as a proper signal to encourage owners of DGs in active power generation. Generally, the daily Volt/Var control is a nonlinear optimization problem. Therefore, an efficient hybrid evolutionary method based on Particle Swarm Optimization and Ant Colony Optimization (ACO), called HPSO, is proposed to determine the active power values of DGs, reactive power values of capacitors and tap positions of transformers for the next day. The feasibility of the proposed algorithm is demonstrated and compared with methods based on the original PSO, ACO and GA algorithms on IEEE 34-bus distribution feeder.

A novel algorithm based on honey bee mating optimization for distribution harmonic state estimation including distributed generators

This paper presents a new algorithm based on honey-bee mating optimization (HBMO) to estimate harmonic state variables in distribution networks including distributed generators (DGs). The proposed algorithm performs estimation for both amplitude and phase of each harmonics by minimizing the error between the measured values from phasor measurement units (PMUs) and the values computed from the estimated parameters during the estimation process. Simulation results on two distribution test system are presented to demonstrate that the speed and accuracy of proposed distribution harmonic state estimation (DHSE) algorithm is extremely effective and efficient in comparison with the conventional algorithms such as weight least square (WLS), genetic algorithm (GA) and tabu search (TS).

A novel hybrid evolutionary algorithm based on ACO and SA for distribution feeder reconfiguration with regard to DGs

This paper presents an efficient hybrid evolutionary optimization algorithm based on combining Ant Colony Optimization (ACO) and Simulated Annealing (SA), called ACO-SA, for distribution feeder reconfiguration (DFR) considering Distributed Generators (DGs). Due to private ownership of DGs, a cost based compensation method is used to encourage DGs in active and reactive power generation. The objective function is summation of electrical energy generated by DGs and substation bus (main bus) in the next day. The approach is tested on a real distribution feeder. The simulation results show that the proposed evolutionary optimization algorithm is robust and suitable for solving DFR problem.

Distribution feeder reconfiguration for loss minimization based on modified honey bee mating optimization algorithm

This paper presents an efficient algorithm for multi-objective distribution feeder reconfiguration based on Modified Honey Bee Mating Optimization (MHBMO) approach. The main objective of the Distribution feeder reconfiguration (DFR) is to minimize the real power loss, deviation of the nodes’ voltage. Because of the fact that the objectives are different and no commensurable, it is difficult to solve the problem by conventional approaches that may optimize a single objective. So the metahuristic algorithm has been applied to this problem. This paper describes the full algorithm to Objective functions paid, The results of simulations on a 32 bus distribution system is given and shown high accuracy and optimize the proposed algorithm in power loss minimization.

A hybrid evolutionary algorithm based on ACO and SA for distribution feeder reconfiguration

This paper deals with an efficient hybrid evolutionary optimization algorithm in accordance with combining the ant colony optimization (ACO) and the simulated annealing (SA), so called ACO-SA. The distribution feeder reconfiguration (DFR) is known as one of the most important control schemes in the distribution networks, which can be affected by distributed generations (DGs) for the multi-objective DFR. In such a case, DGs is used to minimize the real power loss, the deviation of nodes voltage and the number of switching operations. The approach is carried out on a real distribution feeder, where the simulation results show that the proposed evolutionary optimization algorithm is robust and suitable for solving the DFR problem.

Experimental evaluation of an autonomous surface vehicle for water quality and greenhouse gas emission monitoring

This paper describes the experimental evaluation of a novel Autonomous Surface Vehicle capable of navigating complex inland water reservoirs and measuring a range of water quality properties and greenhouse gas emissions. The 16 ft long solar powered catamaran is capable of collecting water column profiles whilst in motion. It is also directly integrated with a reservoir scale floating sensor network to allow remote mission uploads, data download and adaptive sampling strategies. This paper describes the onboard vehicle navigation and control algorithms as well as obstacle avoidance strategies. Experimental results are shown demonstrating its ability to maintain track and avoid obstacles on a variety of large-scale missions and under differing weather conditions, as well as its ability to continuously collect various water quality parameters complimenting traditional manual monitoring campaigns.

Distribution harmonic state estimation based on a hybrid PSO and SA algorithm considering parameters uncertainty

This paper presents a new algorithm based on a Hybrid Particle Swarm Optimization (PSO) and Simulated Annealing (SA) called PSO-SA to estimate harmonic state variables in distribution networks. The proposed algorithm performs estimation for both amplitude and phase of each harmonic currents injection by minimizing the error between the measured values from Phasor Measurement Units (PMUs) and the values computed from the estimated parameters during the estimation process. The proposed algorithm can take into account the uncertainty of the harmonic pseudo measurement and the tolerance in the line impedances of the network as well as uncertainty of the Distributed Generators (DGs) such as Wind Turbines (WT). The main feature of proposed PSO-SA algorithm is to reach quickly around the global optimum by PSO with enabling a mutation function and then to find that optimum by SA searching algorithm. Simulation results on IEEE 34 bus radial and a realistic 70-bus radial test networks are presented to demonstrate the speed and accuracy of proposed Distribution Harmonic State Estimation (DHSE) algorithm is extremely effective and efficient in comparison with the conventional algorithms such as Weight Least Square (WLS), Genetic Algorithm (GA), original PSO and Honey Bees Mating Optimization (HBMO) algorithm.

Retrospective evaluation of dosimetric quality for prostate carcinomas treated with 3D conformal, intensity-modulated and volumetric-modulated arc radiotherapy

Introduction This study examines and compares the dosimetric quality of radiotherapy treatment plans for prostate carcinoma across a cohort of 163 patients treated across 5 centres: 83 treated with three-dimensional conformal radiotherapy (3DCRT), 33 treated with intensity-modulated radiotherapy (IMRT) and 47 treated with volumetric-modulated arc therapy (VMAT). Methods Treatment plan quality was evaluated in terms of target dose homogeneity and organ-at-risk sparing, through the use of a set of dose metrics. These included the mean, maximum and minimum doses; the homogeneity and conformity indices for the target volumes; and a selection of dose coverage values that were relevant to each organ-at-risk. Statistical significance was evaluated using two-tailed Welch’s T-tests. The Monte Carlo DICOM ToolKit software was adapted to permit the evaluation of dose metrics from DICOM data exported from a commercial radiotherapy treatment planning system. Results The 3DCRT treatment plans offered greater planning target volume dose homogeneity than the other two treatment modalities. The IMRT and VMAT plans offered greater dose reduction in the organs-at-risk: with increased compliance with recommended organ-at-risk dose constraints, compared to conventional 3DCRT treatments. When compared to each other, IMRT and VMAT did not provide significantly different treatment plan quality for like-sized tumour volumes. Conclusions This study indicates that IMRT and VMAT have provided similar dosimetric quality, which is superior to the dosimetric quality achieved with 3DCRT.