Study protocol: SWING – social capital and well-being in neighborhoods in Ghent

Background: Investing in social capital has been put forth as a potential lever for policy action to tackle health inequity. Notwithstanding, empirical evidence that supports social capital's role in the existence of health inequity is limited and inconclusive. Furthermore, social capital literature experiences important challenges with regard to (1) the level on which social capital is measured and analyzed; (2) the measurement of the concept in line with its multidimensional nature; and (3) the cross-cultural validity of social capital measurements. The Social capital and Well-being In Neighborhoods in Ghent (SWING) study is designed to meet these challenges. The collected data can be used to investigate the distribution of health problems and the association between social capital, health and well-being, both at the individual and at the neighborhood level. The main goals of the SWING study are (1) to develop a coherent multilevel dataset of indicators on individual and neighborhood social capital and well-being that contains independent indicators of neighborhood social capital at a low level of aggregation and (2) to measure social capital as a multidimensional concept. The current article describes the background and design of the SWING study. Methods/Design: The SWING study started in 2011 and data were collected in three cross-sectional waves: the first in 2011, the second in 2012, and the third in 2013. Data collection took place in 142 neighborhoods (census tract level) in the city of Ghent (Flanders, Belgium). Multiple methods of data collection were used within each wave, including: (1) a standardized questionnaire, largely administered face-to-face interviews for neighborhood inhabitants (N = 2,730); (2) face-to-face interviews with key informants using a standardized questionnaire (N = 2,531); and (3) an observation checklist completed by the interviewers (N = 2,730 in total). The gathered data are complemented by data available within administrative data services. Discussion: The opportunities and ambitions of the SWING study are discussed, together with the limitations of the database

Development of a smart transformer to control the power exchange of a microgrid

A smart transformer enables to control the power exchange between a microgrid and the utility network by controlling the voltage at the microgrid side within certain limits. The distributed generation units in the microgrid are equipped with a voltage-based droop control strategy. This controller reacts on the voltage change, making the smart transformer an element that controls power exchange without the need for communication to other elements in the microgrid. To build a smart transformer, several concepts are possible. In a smart transformer with continuous turns ratio, hereafter referred to as continuous smart transformer, the transformer's microgrid-side voltage can be controlled without voltage steps and the accuracy of the voltage control can be very high. The voltage control of a smart transformer with discrete turns ratio, hereafter referred to as discrete smart transformer, is less accurate, as the output voltage is regulated between several discrete values. In this paper, the development of a continuous and discrete smart transformer will be elaborated. Their validity will be proven by implementing these smart transformers in an experimental test setup. Also, some concepts to improve the control accuracy will be proposed

Contribution of a smart transformer in the local primary control of a microgrid

In order to enable an easy participation of microgrids in the electricity markets, the smart transformer (ST) concept has been developed. The ST controls the power exchange between a microgrid and the utility network by only controlling its microgrid side voltage, instead of the conventional arrangement where new set points are communicated to all microgrid elements. When the voltage-based droop (VBD) control is implemented in the DG units, loads and storage elements, all microgrid units automatically respond to this change of microgrid voltage by altering their power output or consumption. However, this reference value of power exchange is dependent on (day-ahead) predictions of both consumption and (renewable) power generation. Hence, when these predictions prove to be inaccurate, the ST will still control the power exchange, but with consequently large variations of the microgrid voltage from its nominal value. It is suggested to take the real-time microgrid voltage into account when determining the reference power of the ST. This is presented in this paper by extending the ST's control strategy with a VBD control, such that the ST can contribute in the primary control. Simulations are included to analyze this primary control of the ST combined with VBD control of the other microgrid elements

Bacterial diversity assessment in Antarctic terrestrial and aquatic microbial mats : a comparison between bidirectional pyrosequencing and cultivation

The application of high-throughput sequencing of the 16S rRNA gene has increased the size of microbial diversity datasets by several orders of magnitude, providing improved access to the rare biosphere compared with cultivation-based approaches and more established cultivation-independent techniques. By contrast, cultivation-based approaches allow the retrieval of both common and uncommon bacteria that can grow in the conditions used and provide access to strains for biotechnological applications. We performed bidirectional pyrosequencing of the bacterial 16S rRNA gene diversity in two terrestrial and seven aquatic Antarctic microbial mat samples previously studied by heterotrophic cultivation. While, not unexpectedly, 77.5% of genera recovered by pyrosequencing were not among the isolates, 25.6% of the genera picked up by cultivation were not detected by pyrosequencing. To allow comparison between both techniques, we focused on the five phyla (Proteobacteria, Actinobacteria, Bacteroidetes, Firmicutes and Deinococcus-Thermus) recovered by heterotrophic cultivation. Four of these phyla were among the most abundantly recovered by pyrosequencing. Strikingly, there was relatively little overlap between cultivation and the forward and reverse pyrosequencing-based datasets at the genus (17.1–22.2%) and OTU (3.5–3.6%) level (defined on a 97% similarity cut-off level). Comparison of the V1–V2 and V3–V2 datasets of the 16S rRNA gene revealed remarkable differences in number of OTUs and genera recovered. The forward dataset missed 33% of the genera from the reverse dataset despite comprising 50% more OTUs, while the reverse dataset did not contain 40% of the genera of the forward dataset. Similar observations were evident when comparing the forward and reverse cultivation datasets. Our results indicate that the region under consideration can have a large impact on perceived diversity, and should be considered when comparing different datasets. Finally, a high number of OTUs could not be classified using the RDP reference database, suggesting the presence of a large amount of novel diversity

The impact of neighborhood deprivation on patients' unscheduled out-of-hours healthcare seeking behavior: a cross-sectional study

Background: The use of unscheduled out of hours medical care is related to the social status of the patient. However, the social variance in the patient's preference for a hospital based versus a primary care based facility, and the impact of specific patient characteristics such as the travel distance to both types of facilities is unclear. This study aims to determine the social gradient in emergency care seeking behavior (consulting the emergency department (ED) in a hospital or the community-based Primary Care Center (PCC)) taking into account patient characteristics including the geographical distance from the patient's home to both services. Methods: A cross-sectional study, including 7,723 patients seeking out-of-hours care during 16 weekends and 2 public holidays was set up in all EDs and PCCs in Ghent, Belgium. Information on the consulted type of service, and neighborhood deprivation level was collected, but also the exact geographical distance from the patient's home to both types of services, and if the patient has a regular GP. Results: Patients living in a socially deprived area have a higher propensity to choose a hospital-based ED than their counterparts living in more affluent neighborhoods. This social difference persists when taking into account distance to both services, having a regular GP, and being hospitalized or not. The impact of the distance between the patient's home address and the location of both types of services on the patient's choice of service is rather small. Conclusions: Initiatives aiming to lead patients more to PCC by penalizing inappropriate ED use might increase health inequity when they are not twinned with interventions improving the access to primary care services and tackling the underlying mechanisms of patients' emergency care seeking behavior. Further research exploring the impact of out-of-hours care organization (gatekeeping, payment systems, ...) and the patient's perspectives on out-of-hours care services is needed

Surface exclusion and molecular mobility may explain Vroman effects in protein adsorption

Data on protein adsorption usually show that for increasing surface coverage the adsorption velocity decreases much faster than linearly. This contrasts to the classical Langmuir model with an adsorption velocity proportional to the number of unoccupied binding sites. It has been shown that this non-linearity may explain phenomena like transient adsorption of different proteins from a protein mixture or dilution-dependent changes in binding properties, collectively called Vroman effects. However, the molecular mechanisms explaining this non-linear behavior remain to be established. A Monte Carlo simulation model is presented that incorporates steric hindrance, lateral mobility and mutual interactions of adsorbed molecules. Experimental data on the adsorption kinetics of prothrombin and annexin V, a recently discovered anticoagulant protein, at phospholipid bilayers are analyzed with this model. A major conclusion is that the steep decline in adsorption rates for increasing surface coverage can be explained, without assuming repulsive forces between adsorbed molecules, as a surface exclusion effect combined with lateral mobility of adsorbed molecules. The fact that annexin V shows this effect to a much lesser degree than prothrombin is tentatively explained by clustering of adsorbed annexin V molecules. A qualitative effect of lateral mobility on the adsorption characteristics, predicted by the model, is confirmed in experiments in which the fluidity of the bilayers was manipulated