Building family/general practice research capacity

To promote the range of interventions for building family/general practice (family medicine) research capacity, we describe successful international examples. Such examples of interventions that build research capacity focus on diseases and illness research, as well as process research; monitor the output of research in family/general practice (family medicine); increase the number of family medicine research journals; encourage and enable research skills acquisition (including making it part of professional training); strengthen the academic base; and promote research networks and collaborations. The responsibility for these interventions lies with the government, colleges and academies, and universities. There are exciting and varied methods of building research capacity in family medicine.

Research on the BET surface area and packing of molecules on the activated carbon

Adsorption of different aromatic compounds (two of them are electrolytes) onto an untreated activated carbon (F100) is investigated. The experimental isotherms are fitted into Langmuir homogenous and heterogeneous Model. Theoretical maximum adsorption capacities that are based on the BET surface area of the adsorbent cannot be close to the real value. The affinity and the heterogeneity of the adsorption system observed to be related to the pK(a) of the solutes. The maximum adsorption capacity (Q(max)) of activated carbon for each solute dependent on the molecular area as well as the type of functional group attached on the aromatic compound and also pH of solution. The arrangement of the molecules on the carbon surface is not face down. Furthermore, it is illustrated that the packing arrangement is most likely edge to face (sorbate-sorbent) with various tilt angles. For characterization of the carbon, the N-2 and CO2 adsorption were used. X-ray Photoelectron Spectroscopy (XPS) measurement was used to surface elemental analysis of activated carbon.

Determinants of exercise capacity in patients with type 2 diabetes

OBJECTIVE - Type 2 diabetes is associated with reduced exercise capacity, but the cause of this association is unclear. We sought the associations of impaired exercise capacity in type 2 diabetes. RESEARCH DESIGN AND METHODS - Subclinical left ventricular (LV) dysfunction was sought from myocardial strain rate and the basal segmental diastolic velocity (Em) of each wall in 170 patients with type 2 diabetes (aged 56 +/- 10 years, 91 men), good quality echocardiographic images, and negative exercise echocardiograms. The same measurements were made in 56 control subjects (aged 53 +/- 10 years, 29 men). Exercise capacity was calculated in metabolic equivalents, and heart rate recovery (HRR) was measured as the heart rate difference between peak and 1 min after exercise. In subjects with type 2 diabetes, exercise capacity was correlated with clinical, therapeutic, biochemical, and echocardiographic variables, and significant independent associations were sought using a multiple linear regression model. RESULTS - Exercise capacity, strain rate, Em, and HRR were significantly reduced in type 2 diabetes. Exercise capacity was associated with age (r- = -0.37, P < 0.001), male sex (r = 0.26, P = 0.001), BMI (r = -0.19, P = 0.012), HbA(1c) (AlC; r = -0.22, P = 0.009), Em (r = 0.43, P < 0.001), HRR (r = 0.42, P < 0.001), diabetes duration (r = -0.18, P = 0.021), and hypertension history (r = -0.28, P < 0.001). Age (P < 0.001), male sex (P = 0.007), BMI (P = 0.001), Em (P = 0.032), HRR (P = 0.013), and AlC (P = 0.0007) were independent predictors of exercise capacity. CONCLUSIONS - Reduced exercise capacity in patients with type 2 diabetes is associated with diabetes control, subclinical LV dysfunction, and impaired HRR.

Functional capacity evaluation as a performance measure - Evidence for a new approach for clients with chronic back pain

Objectives: To report the research and development of a new approach to Functional Capacity Evaluation, the Gibson Approach to Functional Capacity Evaluation (GAPP FCE) for chronic back pain clients. Methods: Four Studies, including pilot and feasibility testing, expert review, and preliminary interrater reliability examination, are described here. Participants included 7 healthy young adults and 19 rehabilitation clients with back pain who underwent assessment using the GAPP FCE. Thirteen therapists were trained in the approach and were silently observed administering the Functional Capacity Evalutions by at least 1 other trained therapists or the first investigator Or both. An expert review using 5 expert occupational therapists was also conducted. Results: Study 1, the pilot with healthy individuals, indicated that the GAPP FCE was a feasible approach with good utility. Study 2, a pilot using 2 trained therapists assessing 5 back pain clients, supported the clinical feasibility of the approach. The expert review in Study 3 found support for GAPP FCE. Study 4, a trial of the approach with 14 rehabilitation clients, found support for the interrater reliability of recommendations for return to work based on performance in the GAPP FCE. Discussion: The evidence thus far available supports the GAPP FCE as ail approach that provides a Sound method for evaluating the performance of the physical demands of work with clients with chronic back pain. The tool has been shown to have good face and content validity, to meet acceptable test standards, and to have reasonable interrater reliability. Further research is occurring to look at a larger interrater reliability study, to further examine content validity, and to examine predictive validity.

Validating the functional capacity index: A comparison of predicted versus observed total body scores

Background: The Functional Capacity Index (FCI) was designed to predict physical function 12 months after injury. We report a validation study of the FCI. Methods: This was a consecutive case series registered in the Queensland Trauma Registry who consented to the prospective 12-month telephone-administered follow-up study. FCI scores measured at 12 months were compared with those originally predicted. Results: Complete Abbreviated Injury Scale score information was available for 617 individuals, of whom 587 (95%) could be assigned at least one FCI score (range, 1-17). Agreement between the largest predicted FCI and observed FCI score was poor (kappa = 0.05; 95% confidence interval, 0.00-0.10) and explained only 1% of the variability in observed FCI. Using an encompassing model that included all FCI assignments, agreement remained poor (kappa = 0.05; 95% confidence interval, -0.02-0.12), and the model explained only 9% of the variability in observed FCI. Conclusion: The predicted functional capacity poorly agrees with actual functional outcomes. Further research should consider including other (noninjury) explanatory factors in predicting FCI at 12 months.

Predicting functional capacity outcome 12 months after hospitalized injury

Background: There is a recognized need to move from mortality to morbidity outcome predictions following traumatic injury. However, there are few morbidity outcome prediction scoring methods and these fail to incorporate important comorbidities or cofactors. This study aims to develop and evaluate a method that includes such variables. Methods: This was a consecutive case series registered in the Queensland Trauma Registry that consented to a prospective 12-month telephone conducted follow-up study. A multivariable statistical model was developed relating Trauma Registry data to trichotomized 12-month post-injury outcome (categories: no limitations, minor limitations and major limitations). Cross-validation techniques using successive single hold-out samples were then conducted to evaluate the model's predictive capabilities. Results: In total, 619 participated, with 337 (54%) experiencing no limitations, 101 (16%) experiencing minor limitations and 181 (29%) experiencing major limitations 12 months after injury. The final parsimonious multivariable statistical model included whether the injury was in the lower extremity body region, injury severity, age, length of hospital stay, pulse at admission and whether the participant was admitted to an intensive care unit. This model explained 21% of the variability in post-injury outcome. Predictively, 64% of those with no limitations, 18% of those with minor limitations and 37% of those with major limitations were correctly identified. Conclusion: Although carefully developed, this statistical model lacks the predictive power necessary for its use as a basis of a useful prognostic tool. Further research is required to identify variables other than those routinely used in the Trauma Registry to develop a model with the necessary predictive utility.

Specific heat capacity of Australian honeys from 35 to 165C as a function of composition using differential scanning calorimetry

Modulated temperature differential scanning calorimetry was used to investigate the specific heat capacity (C-p) of 10 Australian honeys within the processing and handling temperatures. The values obtained were found to be different from the literature values at certain temperatures, and are not predictable by the additive model. The C-p of each honey exhibited a cubic relationship (P < 0.001) with the temperature (T, C). In addition, the moisture (M, %), fructose (F, %) and glucose (G, %) contents of the honeys influenced their C-p. The following equation (r(2) = 0.92) was proposed for estimating C-p of honey, and is recommended for use in the honey industry and in research: C = 996.7 + 1.4 x 10(-3)T + 5.6 x 10(-5)T(2) - 2.4 x 10(-7)T(3) - 56.5M - 25.8F - 31.0G + 1.5(M * F) + 1.8(M * G) + 0.8(F * G) - 4.6 x 10(-2) (M * F * G).

Strengthening cardiac rehabilitation and secondary prevention for Aboriginal and Torres Strait Islander peoples

This article summarises the findings of a project funded and supported by a principal committee of the National Health and Medical Research Council, the Health Advisory Committee, chaired by Professor Adele Green.

Evaluation of parameters effective in FRP shear strengthening of RC beams using FE method

Shear strengthening is required when an RC beam is found deficient in shear, or when its shear capacity falls below its flexural capacity after flexural strengthening. A recent technique for the shear strengthening of RC beams is to provide additional FRP web reinforcement, commonly in the form of bonded external FRP strips/sheets. Over the last few years, several experimental studies have been conducted on this new strengthening technique, which has established its effectiveness. While experimental methods of investigation are extremely useful in obtaining information about the composite behaviour of FRP and reinforced concrete, the use of numerical models such as the one presented in this paper helps in developing a good understanding of the behaviour at lower costs. In the study presented in this paper, ANSYS finite element program is used to examine the response of beams strengthened in shear by FRPs. The FE model is calibrated against test results performed at the University of Kentucky. Once validated, the model is used to examine the influence of fibre orientation, compressive strength of concrete, area of tensile and compressive reinforcements, and amount and distance between stirrups on the strength and ductility of FRP strengthened beam.

Investigations into the effect of LOS signal blocking on capacity of an indoor MIMO system

In indoor environments the properties of communication channel are affected by the presence of various objects which block the Line Of Sight signal propagation. For example, this occurs because of presence of movement of humans and furniture. In this paper, the effect of reflection and scattering due to the presence of such objects is studied with respect to the capacity of a multiple input multiple output (MIMO) wireless system. The carried out investigations are performed by applying a simple electromagnetic model, in which transmitting and receiving antennas of MIMO system, as well as signal blocking objects, are represented by wire dipoles. In order to provide a fair assessment, calculations of MIMO capacity are performed under both fixed transmitted power and fixed received power conditions.