Barriers and enablers to healthcare access and use among Arabic-speaking and Caucasian English-speaking patients with type 2 diabetes mellitus: a qualitative comparative study

OBJECTIVE: The objective of this study was to explore the decision-making processes and associated barriers and enablers that determine access and use of healthcare services in Arabic-speaking and English-speaking Caucasian patients with diabetes in Australia. STUDY SETTING AND DESIGN: Face-to-face semistructured individual interviews and group interviews were conducted at various healthcare settings-diabetes outpatient clinics in 2 tertiary referral hospitals, 6 primary care practices and 10 community centres in Melbourne, Australia. PARTICIPANTS: A total of 100 participants with type 2 diabetes mellitus were recruited into 2 groups: 60 Arabic-speaking and 40 English-speaking Caucasian. DATA COLLECTION: Interviews were audio-taped, translated into English when necessary, transcribed and coded thematically. Sociodemographic and clinical information was gathered using a self-completed questionnaire and medical records. PRINCIPAL FINDINGS: Only Arabic-speaking migrants intentionally delayed access to healthcare services when obvious signs of diabetes were experienced, missing opportunities to detect diabetes at an early stage. Four major barriers and enablers to healthcare access and use were identified: influence of significant other(s), unique sociocultural and religious beliefs, experiences with healthcare providers and lack of knowledge about healthcare services. Compared with Arabic-speaking migrants, English-speaking participants had no reluctance to access and use medical services when signs of ill-health appeared; their treatment-seeking behaviours were straightforward. CONCLUSIONS: Arabic-speaking migrants appear to intentionally delay access to medical services even when symptomatic. Four barriers to health services access have been identified. Tailored interventions must be developed for Arabic-speaking migrants to improve access to available health services, facilitate timely diagnosis of diabetes and ultimately to improve glycaemic control.

A comparative study on procedure and state of the art of conventional maximum power point tracking techniques for photovoltaic system

Due to the increasing world energy demand, renewable energy systems have been significantly applied in the power generation sector. Among the renewable energy options, photovoltaic system is one of the most popular resources which has been experiencing a huge attention during recent decades. The remarkable advantages, such as static and movement free characteristics, low maintenance costs, and longevity are the primary factors for the popularity of solar generation in the late years. Nevertheless, the low PV conversion efficiency in one side and high PV material cost in the other side have made PV generation comparably expensive system. Consequently, a capable maximum power point tracking (MPPT) is all important to elicit the maximum energy from the production of PV systems. Different researches have been conducted to design a fast, simple and robust MPPT technique under uniform conditions. However, due to the series and parallel connection of PV modules and according to the use of bypass diodes, in the structure of PV modules, a conventional techniques are unable to track a true MPP. Recently, several studies have been undertaken to modify these conventional methods and enable them to track the global MPP under rapidly changing environments and partial shading (PS) conditions. This report concentrates on the state of the art of these methods and their evolution to apply under PS conditions. The recent developments and modifications are analyzed through a comparison based on design complexity, cost, speed and the ability to track the MPP under rapid environmental variations and PS conditions.

A comparative study of different power system stabilizers for dynamic stability analysis

Power system stabilizers (PSSs) are extensively used to ensure the dynamic stability of power systems through the modulation of excitation signals supplied to synchronous generators. This paper presents a comparative study of two different PSSs: STAB1 and IEEEST. The stabilizers are designed for the linearized model of a single machine infinite bus (SMIB) system with different loads. Both time-and frequency-domain simulations are carried out to investigate the performance of these stabilizers. For all PSSs, the time-domain simulations are performed by applying a three-phase short-circuit fault at the terminal of the synchronous generator. These simulation results are compared against the open-loop characteristics of the SMIB system where no PSS is implemented. Simulation results demonstrate that the speed-fed PSS provides more damping as compared to frequency- and power-fed stabilizers.

Integration of renewable generation uncertainties into stochastic unit commitment considering reserve and risk: a comparative study

The uncertainties of renewable energy have brought great challenges to power system commitment, dispatches and reserve requirement. This paper presents a comparative study on integration of renewable generation uncertainties into SCUC (stochastic security-constrained unit commitment) considering reserve and risk. Renewable forecast uncertainties are captured by a list of PIs (prediction intervals). A new scenario generation method is proposed to generate scenarios from these PIs. Different system uncertainties are considered as scenarios in the stochastic SCUC problem formulation. Two comparative simulations with single (E1: wind only) and multiple sources of uncertainty (E2: load, wind, solar and generation outages) are investigated. Five deterministic and four stochastic case studies are performed. Different generation costs, reserve strategies and associated risks are compared under various scenarios. Demonstrated results indicate the overall costs of E2 is lower than E1 due to penetration of solar power and the associated risk in deterministic cases of E2 is higher than E1. It implies the superimposed effect of uncertainties during uncertainty integration. The results also demonstrate that power systems run a higher level of risk during peak load hours, and that stochastic models are more robust than deterministic ones.