Introducing dental students to e-learning at a South African University

This article serves to report on the introduction of an innovative ‘blended learning’ approach in the Paediatric Dentistry Department at the University of the Western Cape (UWC) in Cape Town, South Africa. This intervention was the first of its kind to be introduced at UWC’s dentistry faculty. Methods Educational resources were placed online to supplement didactic and clinical teaching and in so-doing, compensate for the lack of chair side teaching. An online learning platform was thus provided for students to engage with. Results Forty-seven percent of students accessed the site. The evaluation of the course by these 4th and 5th year students was mostly positive. Students who did not access the site provided a variety of reasons for not doing so, with the main reasons being the ‘lack of time’ (40%) and ‘lack of IT resources’ (41%). Conclusion This intervention highlighted the fact that ‘blended learning’ definitely has its place in the dentistry curriculum, especially if minor issues like access to resources can be addressed. The Paediatric Dentistry department at the University of Western Cape is continually pursuing current trends in teaching to provide an education that is on par with global standards

The identification and remote detection of alien invasive plants in commercial forests: An Overview

Invasive alien plants are responsible for extensive economic and ecological damage in forest plantations. They have the ability to aggressively manipulate essential ecosystem structural and functional processes. Alterations in these processes can have detrimental effects on the growth and productivity of forest species and ultimately impact on the quality and quantity of forest wood material. Using direct sampling field-based methods or visual estimations have generally expressed moderate success owing to the logistical and timely impracticalities. Alternatively, remote sensing techniques offer a synoptic rapid approach for detecting and mapping weeds affecting plantation forest environments. This paper reviews remote sensing techniques that have been used in detecting the occurrence of weeds and the implications for detecting S. mauritianum (bugweed); one of the most notorious alien plant invaders to affect southern Africa. Gaining early control of these alien plant invasions would reduce the impacts that may permanently alter our forested ecosystems, contributing to its successful eradication and promoting sustainable forest management practices. Furthermore, the review highlights the difficulties and opportunities that are associated with weed identification using remote sensing and future directions of research are also proposed

Private sector intensive care physiotherapists profile and current practices in South Africa

Magister Scientiae (Physiotherapy) - MSc(Physio)Variability of profile and practices (roles) of the ICU physiotherapists exists globally. The profile and current practices (roles) of the private practice physiotherapist in the private ICU has been minimally explored especially in South Africa (SA). A dearth of survey data and in-depth exploration of the latter exists in the current literature. The aim of this study was to determine and explore the profile and current practices (roles) of the ICU physiotherapists in private ICUs in SA

Dental treatment of pre-school paediatric patients under general anaesthesia in the Western Cape

Magister Scientiae Dentium - MSc(Dent)AIM:The aim of this study was to review the data available from the Department of Health(DOH), on pre-school paediatric patients treated under Dental General Anaesthesia(DGA), at public health facilities in the Western Cape (WC) in order to ascertain the type and nature of treatment provided.METHODOLOGY:This retrospective descriptive study reviewed the records on the Department of Health(DoH) Database of 16 732 pre-school patients treated under dental general anaesthesia in the period 1 January 2005 until 31 December 2007. A questionnaire was also completed telephonically with 22 dentists from the district dental health clinics.Summary descriptive statistics were calculated from data collected and comparisons were drawn between services available at the health districts and academic hospitals.RESULTS:Of the 58 255 procedures recorded for pre-school patients in the district health clinics in the Western Cape, 99.94% were for extractions provided and 0.5% for restorations.The average number of teeth extracted was 10.4 (SD ±3.9).The average rate of DGA per 1000 of the population was 1.06. Only 9% (2) of dentists at district clinics reported that pre-DGA prevention was provided and 5% (1) reported including post-DGA prevention. The Academic Hospital at Tygerberg Oral Health Centre was the only facility in the Western Cape that provided comprehensive dental treatment for pre-school patients which included restorations, extractions, pre and post DGA prevention. Red Cross Children’s Hospital provided treatment for pre-school patients under DGA that included extractions, pre- and post DGA, but no restorative treatment. CONCLUSION:The demand for DGA in pre-school patients in the WC was high. The lack of prevention associated with DGA in the public health service is the most likely reason the retreatment rate under DGA was reported by dentists as being 77%. There was an absence of protocol regarding DGA for pre-school patients in the public health service.RECOMMENDATIONS:Guidelines formulated were recommended for use in the public service for pre-school patients being treated under DGA and includes the provision of preventive interventions such as regular topical fluoride applications, oral hygiene instruction and dietary advice

Forest canopy gaps offer a window into the future: The case of subtropical coastal forests within an urban matrix in South Africa

Alien and indigenous species emergence patterns within canopy gaps in urban subtropical forests are poorly understood. This study compared canopy gap floristics in relation to abiotic and physical characteristics across three subtropical urban forests differing in disturbance history. : Three Northern Coastal Forests of varying disturbance histories located in coastal subtropical urban KwaZulu-Natal (KZN), South Africa (SA). Closed canopy (n = 15 quadrats per forest ) and four gaps (n = 12 quadrats per forest) from three size classes (‘small’ < 25 m2 , ‘medium’ 25 - 45 m2 ; ‘large’ > 45 m2 ) were surveyed for the primary least disturbed (PLD), primary highly disturbed (PHD) and transitional highly disturbed (THD) forests using classical vegetation sampling techniques. Soil moisture content and air temperature were measured within each gap

Unsupervised extremely randomized trees

International audienceIn this paper we present a method to compute dissimilarities on unlabeled data, based on extremely randomized trees. This method, Unsupervised Extremely Randomized Trees, is used jointly with a novel randomized labeling scheme we describe here, and that we call AddCl3. Unlike existing methods such as AddCl1 and AddCl2, no synthetic instances are generated, thus avoiding an increase in the size of the dataset. The empirical study of this method shows that Unsupervised Extremely Randomized Trees with AddCl3 provides competitive results regarding the quality of resulting clusterings, while clearly outperforming previous similar methods in terms of running time

Assessing the surface material quality of unpaved rural roads to understand susceptibility to surface deterioration. A case study of four rural areas in KwaZulu-Natal, South Africa

Road surface deterioration is one of the most common problems of unpaved road networks worldwide. It is areduction in the performance of a road due to a decline in road surface material quality. Accumulated damagefrom vehicles, environmental and physical effects may contribute to a decline in the surface material quality andhence deterioration on an unpaved road surface. This study assesses the surface material quality of unpaved ruralroads in four rural areas in the KwaZulu-Natal Province, South Africa in order to understand susceptibility tosurface deterioration. The study further establishes other possible factors such as slope gradient and rainfall, thatcould determine the surface material quality. Soil samples were collected from R3, R4, and R5 road classes infour rural areas which are: Emazabekweni, Dukuza, Mkhunya and Mhlwazini Area. Laboratory analyses wereconducted in order to determine the performance of the material as potential wearing course. Material per-formance was then determined using the Standard Methods of Testing Road Construction Materials (TMH1:1976) classification method. The results obtained imply that there is a need for better material selection duringthe construction of unpaved road networks. All road classes in Mkhunya, Emazabekweni and Mhlwazini areasexhibited grading coefficient (Gc) values less than 16 and some of the shrinkage product (Sp) values in excess of365, corresponding to a classification of Class D, A and B. These results indicate material that is susceptible toslippery conditions, easily erodible and prone to the formation of ravels and corrugations. Correlation analysisresults conducted to assess the individual relationship between measured rainfall and slope with field shrinkageproduct and grading coefficient values in each area indicated that variation in slope better explains shrinkageproduct values in each area with an R2of 0.62 when compared to rainfall producing a lower R2of 0.57. Forgrading coefficient, slope and rainfall produced similar R2of 0.65 and 0.67, respectively

Introducing dental students to e-learning at a South African university

Background. This article reports on the introduction of an innovative ‘blended learning’ approach in the Paediatric Dentistry Department at theUniversity of the Western Cape (UWC) in Cape Town, South Africa. This intervention was the first of its kind to be introduced at UWC’s dentistryfaculty.Methods. Educational resources were placed online to supplement didactic and clinical teaching and thus compensate for the lack of chair-sideteaching. An online learning platform was therefore provided for students to engage with.Results. Forty-seven per cent of students accessed the site. The evaluation of the course by these 4th- and 5th-year students was mostly positive. Students who did not access the site provided a variety of reasons for not doing so, the main reasons being ‘lack of time’ (40%) and ‘lack of IT resources’ (41%).Conclusion. This intervention highlighted the fact that ‘blended learning’ definitely has its place in the dentistry curriculum, especially if minorissues such as access to resources can be addressed. The Paediatric Dentistry Department at UWC is continually pursuing current trends in teaching to provide an education that is on par with global standards

Detecting and mapping levels of Gonipterus scutellatus-induced vegetation defoliation and leaf area index using spatially optimized vegetation indices

Gonipterus scutellatus outbreaks may severely defoliate Eucalyptus plantations growing in South Africa. Therefore, detecting and mapping the severity and extent of G. scutellatus defoliation is essential for the deployment of suppressive measures. In this study, we tested the utility of spatially optimized vegetation indices and an artificial neural network in detecting and mapping G. scutellatus-induced vegetation defoliation, using both visual estimates of percentage defoliation and optical leaf area index (LAI) measures. We tested both field methods to determine which of the two were more superior in detecting vegetation defoliation using optimized vegetation indices. These indices were computed from a WorldView-2 pan-sharpened image, which is characterized with a 0.5-m spatial resolution and eight spectral bands. The indices were resampled to spatial resolutions that best represented levels of G. scutellatus-induced defoliation. The results showed that levels of defoliation, using visual percentage estimates, were detected with an R2 of 0.83 and an RMSE of 1.55 (2.97% of the mean measured defoliation), based on an independent test data-set. Similarly, LAI subjected to defoliation was detected with an R2 of 0.80 and an RMSE of 0.03 (0.06% of the mean measured LAI), based on an independent test data-set. Therefore, the results indicate that the cheaper less-complicated visual percentage estimates of defoliation was the more superior model of the two. A sensitivity analysis revealed that NDRE, MCARI2 and ARI ranked as the top three most influential indices in developing both percentage defoliation and LAI models. Furthermore, we compared the optimized model with a model developed using the original image spatial resolution. The results indicated that the optimized model performed better than the original 0.5-m spatial resolution model. Overall, the study showed that vegetation indices optimized to specific spatial resolutions can effectively detect and map levels of G. scutellatus-induced defoliation and LAI subjected to defoliation

Burned Area Mapping over the Southern Cape Forestry Region, South Africa Using Sentinel Data within GEE Cloud Platform

Planted forests in South Africa have been affected by an increasing number of economically damaging fires over the past four decades. They constitute a major threat to the forestry industry and account for over 80% of the country’s commercial timber losses. Forest fires are more frequent and severe during the drier drought conditions that are typical in South Africa. For proper forest management, accurate detection and mapping of burned areas are required, yet the exercise is difficult to perform in the field because of time and expense. Now that ready-to-use satellite data are freely accessible in the cloud-based Google Earth Engine (GEE), in this study, we exploit the Sentinel-2-derived differenced normalized burned ratio (dNBR) to characterize burn severity areas, and also track carbon monoxide (CO) plumes using Sentinel-5 following a wildfire that broke over the southeastern coast of the Western Cape province in late October 2018. The results showed that 37.4% of the area was severely burned, and much of it occurred in forested land in the studied area. This was followed by 24.7% of the area that was burned at a moderate-high level. About 15.9% had moderate-low burned severity, whereas 21.9% was slightly burned. Random forests classifier was adopted to separate burned class from unburned and achieved an overall accuracy of over 97%. The most important variables in the classification included texture, NBR, and the NIR bands. The CO signal sharply increased during fire outbreaks and marked the intensity of black carbon over the affected area. Our study contributes to the understanding of forest fire in the dynamics over the Southern Cape forestry landscape. Furthermore, it also demonstrates the usefulness of Sentinel-5 for monitoring CO. Taken together, the Sentinel satellites and GEE offer an effective tool for mapping fires, even in data-poor countries