Dental attendance in undocumented immigrants before and after the implementation of a personal assistance program : a cross-sectional observational study

Undocumented immigrants are a high-risk social group with low access to care. The present study aims to increase awareness and dental attendance in this subgroup, assisted by community health workers (CHW). Starting from 2015, two trained dentists volunteered to perform free oral health examinations and further dental care referral in a welfare organisation in Ghent, Belgium. In 2016 and 2017, a two-day oral health training was added, enabling social workers to operate as community oral health workers and to provide personal oral health advice and assistance. Over the three years, an oral health examination was performed on 204 clients from 1 to 69 years old, with a mean age of 36.7 (SD = 15.9), showing high levels of untreated caries (71.6%; n = 146) and a Dutch Periodontal Screening Index (DPSI) score of 3 or 4 in 62.2% of the sample (n = 97). Regarding dental attendance, the total number of missed appointments decreased significantly, with 40.9% in 2015, 11.9% in 2016 and 8.0% in 2017 (p < 0.001). Undocumented immigrants can be integrated into professional oral health care. Personal assistance by community health workers might be an effective method, although this requires further investigation

Python bindings for the open source electromagnetic simulator Meep

Meep is a broadly used open source package for finite-difference time-domain electromagnetic simulations. Python bindings for Meep make it easier to use for researchers and open promising opportunities for integration with other packages in the Python ecosystem. As this project shows, implementing Python-Meep offers benefits for specific disciplines and for the wider research community

Socioeconomic inequalities in caries experience, care level and dental attendance in primary school children in Belgium : a cross-sectional survey

Objectives: Oral health inequality in children is a widespread and well-documented problem in oral healthcare. However, objective and reliable methods to determine these inequalities in all oral health aspects, including both dental attendance and oral health, are rather scarce. Aims: To explore oral health inequalities and to assess the impact of socioeconomic factors on oral health, oral health behaviour and dental compliance of primary school children. Methods: Data collection was executed in 2014 within a sample of 2216 children in 105 primary schools in Flanders, by means of an oral examination and a validated questionnaire. Intermutual Agency database was consulted to objectively determine individuals' social state and frequency of utilisation of oral healthcare services. Underprivileged children were compared with more fortunate children for their mean DMFt, DMFs, plaque index, care index (C, restorative index (RI), treatment index (TI), knowledge and attitude. Differences in proportions for dichotomous variables (RI100%, TI100% and being a regular dental attender) were analysed. The present study was approved by the Ethics Committee of the University Hospital Ghent (2010/061). All parents signed an informed consent form prior to data collection. All schools received information about the study protocol and agreed to participate. Children requiring dental treatment or periodic recall were referred to the local dentist. Results: Underprivileged children had higher D1MFT (95% CI 0.87 to 1.36), D3MT (95% CI 0.30 to 0.64), plaque scores (95% CI 0.12 to 0.23) and lower care level (p< 0.02). In the low- income group, 78.4% was caries-free, compared with 88.4% for the other children. Half of the low- income children could be considered as regular dental attenders, while 12.6% did not have any dental visit during a 5-year period. Conclusion: Oral health, oral hygiene, oral healthcare level and dental attendance patterns are negatively affected by children's social class, leading to oral health inequalities in Belgian primary school children

Promoting inclusion oral-health:social interventions to reduce oral health inequities

The aim of this collection of papers is to provide the reader with a cogent understanding of the role of evidence in the development of social or community-based interventions to promote inclusion oral-health and reduce oral health, health, and psychosocial inequities. In addition, this material will include various methods used for their implementation and evaluation. At the outset, the reader will be offered a working definition of inclusion oral-health, which will be modelled on the work of Luchenski et al. [1]. The interventions described are theoretically underpinned by a pluralistic definition of evidence-based practice [2] and the radical discourse of health promotion as postulated by Laverack and Labonte [3] and others [4,5]. This Special Issue will consist of eight papers, including an introduction. The first three papers will examine the various sources of evidence used to transform top-down into bottom-up community-based interventions for people experiencing homelessness; people in custody and for families residing in areas of high social deprivation. The final four papers will report on the implementation and evaluation of social or community-based interventions. This collection of research papers will highlight the importance of focusing on prevention and the adoption of a common risk factor agenda to tackle oral health, health and psychosocial inequities felt by those most excluded in our societies

Progressive modeling of steered mixture-of-experts for light field video approximation

Steered Mixture-of-Experts (SMoE) is a novel framework for the approximation, coding, and description of image modalities. The future goal is to arrive at a representation for Six Degrees-of-Freedom (6DoF) image data. The goal of this paper is to introduce SMoE for 4D light field videos by including the temporal dimension. However, these videos contain vast amounts of samples due to the large number of views per frame. Previous work on static light field images mitigated the problem by hard subdividing the modeling problem. However, such a hard subdivision introduces visually disturbing block artifacts on moving objects in dynamic image data. We propose a novel modeling method that does not result in block artifacts while minimizing the computational complexity and which allows for a varying spread of kernels in the spatio-temporal domain. Experiments validate that we can progressively model light field videos with increasing objective quality up to 0.97 SSIM

Accessibility to oral health care for people on social assistance : a survey of social service providers from Public Welfare Centers in Flanders

Objectives: The goals of the present study were as follows: (i) to explore the characteristics of the Flemish Public Centers for Social Welfare (PCSW) concerning oral health care; (ii) to explore possible barriers experienced by people on social assistance and oral health-care providers; and (iii) to explore the accessibility of general and oral health care for people on social assistance. Methods: The data of this cross-sectional study were obtained by a survey of social service providers working in a PCSW. For this purpose, a new questionnaire was developed. The survey was validated by means of a pilot study. All 306 PCSWs in Flanders were invited to participate in this survey, of which 192 (62.7%) responded. Results: The findings demonstrate that for people on social assistance, financial limitations and low prioritisation of oral health are the main barriers to good oral health care. The study reveals that such individuals experience greater financial barriers and poorer access to a dentist than to a general medical practitioner. The study also reveals that dentists report financial concerns and administrative burdens as the main barriers in treating this subgroup. The responses of PCSWs demonstrate that local dentists are reluctant to treat this subgroup. Conclusion: Additional efforts are needed to improve the accessibility of oral health care for people on social assistance. Recommended improvements at the organisational level could improve increased education to target the population on the importance of oral health care. Administrative burden and financial concerns of the providers also need to be addressed to decrease their reluctance to work with those on social assistance

SILVR: A Synthetic Immersive Large-Volume Plenoptic Dataset

In six-degrees-of-freedom light-field (LF) experiences, the viewer's freedom is limited by the extent to which the plenoptic function was sampled. Existing LF datasets represent only small portions of the plenoptic function, such that they either cover a small volume, or they have limited field of view. Therefore, we propose a new LF image dataset "SILVR" that allows for six-degrees-of-freedom navigation in much larger volumes while maintaining full panoramic field of view. We rendered three different virtual scenes in various configurations, where the number of views ranges from 642 to 2226. One of these scenes (called Zen Garden) is a novel scene, and is made publicly available. We chose to position the virtual cameras closely together in large cuboid and spherical organisations ($2.2m^3$ to $48m^3$), equipped with 180{\deg} fish-eye lenses. Every view is rendered to a color image and depth map of 2048px $\times$ 2048px. Additionally, we present the software used to automate the multi-view rendering process, as well as a lens-reprojection tool that converts between images with panoramic or fish-eye projection to a standard rectilinear (i.e., perspective) projection. Finally, we demonstrate how the proposed dataset and software can be used to evaluate LF coding/rendering techniques(in this case for training NeRFs with instant-ngp). As such, we provide the first publicly-available LF dataset for large volumes of light with full panoramic field of viewComment: In 13th ACM Multimedia Systems Conference (MMSys '22), June 14-17, 2022, Athlone, Ireland. ACM, New York, NY, USA, 6 page