Extraction and Classification of Diving Clips from Continuous Video Footage

Due to recent advances in technology, the recording and analysis of video data has become an increasingly common component of athlete training programmes. Today it is incredibly easy and affordable to set up a fixed camera and record athletes in a wide range of sports, such as diving, gymnastics, golf, tennis, etc. However, the manual analysis of the obtained footage is a time-consuming task which involves isolating actions of interest and categorizing them using domain-specific knowledge. In order to automate this kind of task, three challenging sub-problems are often encountered: 1) temporally cropping events/actions of interest from continuous video; 2) tracking the object of interest; and 3) classifying the events/actions of interest. Most previous work has focused on solving just one of the above sub-problems in isolation. In contrast, this paper provides a complete solution to the overall action monitoring task in the context of a challenging real-world exemplar. Specifically, we address the problem of diving classification. This is a challenging problem since the person (diver) of interest typically occupies fewer than 1% of the pixels in each frame. The model is required to learn the temporal boundaries of a dive, even though other divers and bystanders may be in view. Finally, the model must be sensitive to subtle changes in body pose over a large number of frames to determine the classification code. We provide effective solutions to each of the sub-problems which combine to provide a highly functional solution to the task as a whole. The techniques proposed can be easily generalized to video footage recorded from other sports.Comment: To appear at CVsports 201

Using Enamel Matrix Derivative to Improve Treatment Efficacy in Periodontal Furcation Defects

Purpose Furcations are complicated periodontal defects. Untreated furcations lead to loss of the involved teeth and supporting tissues. It has been demonstrated that regenerative biomaterials are beneficial in reconstruction of the bone surrounding furcation‐affected teeth. These biomaterials range from bone grafts and nonresorbable/resorbable barrier membranes to biologics that are able to trigger inactive regenerative processes in periodontal tissues. Selection of appropriate material(s) to treat furcations is challenging. The aim of this article is to provide a comparative outlook on different biomaterials applicable in regeneration of furcations with a focus on enamel matrix derivative (EMD). Methods Scientific databases including PubMed/MEDLINE, ScienceDirect, and EMBASE were searched, and 28 articles were found primarily for this specific study. Full texts were studied to identify relevant studies; 17 studies were excluded because of irrelevancy, while 11 main studies were ultimately selected. Other references have been used for general statements. Results EMD is a protein complex widely used in the regeneration of different periodontal defects. To assess the effects of EMD for treatment of root furcations, clinical studies involving EMD with and without barrier membranes and bone grafts were selected and compared. Briefly, this study reveals that when EMD is combined with open flap debridement (OFD), guided tissue regeneration (GTR), or bone grafting (BG), the amount of class II furcations converted to class I increases significantly. EMD also reduces tissue swelling and patient discomfort after treatment. Conclusions This study provides evidence to find the best combination of biomaterials to treat furcation defects. The best results are obtained if EMD is combined with β‐TCP/HA alloplastic bone grafts

A systematic review of the use of Deep Learning in Satellite Imagery for Agriculture

Agricultural research is essential for increasing food production to meet the requirements of an increasing population in the coming decades. Recently, satellite technology has been improving rapidly and deep learning has seen much success in generic computer vision tasks and many application areas which presents an important opportunity to improve analysis of agricultural land. Here we present a systematic review of 150 studies to find the current uses of deep learning on satellite imagery for agricultural research. Although we identify 5 categories of agricultural monitoring tasks, the majority of the research interest is in crop segmentation and yield prediction. We found that, when used, modern deep learning methods consistently outperformed traditional machine learning across most tasks; the only exception was that Long Short-Term Memory (LSTM) Recurrent Neural Networks did not consistently outperform Random Forests (RF) for yield prediction. The reviewed studies have largely adopted methodologies from generic computer vision, except for one major omission: benchmark datasets are not utilised to evaluate models across studies, making it difficult to compare results. Additionally, some studies have specifically utilised the extra spectral resolution available in satellite imagery, but other divergent properties of satellite images - such as the hugely different scales of spatial patterns - are not being taken advantage of in the reviewed studies.Comment: 25 pages, 2 figures and lots of large tables. Supplementary materials section included here in main pd

Is subclinical cardiovascular disease linked with periodontal disease in diabetic and non-diabetic subjects?

: Periodontal disease leads to a systemic hyper-inflammatory state that might impair other co-morbidities including cardiovascular disease. Evidence-based findings showed that periodontitis may be linked with subclinical signs of cardiovascular diseases such as arterial stiffness. Nevertheless, some contrasting results have been reported over the years. A cross-sectional study regarding the relationship between periodontal disease and subclinical cardiovascular diseases, in non-diabetic and diabetic individuals, has been recently published. Therefore, the aim of this commentary is to give an in-depth on this topic

Analysis of genetic polymorphisms as risk factors for Aggressive Periodontitis.

This PhD consisted of a series of studies aiming at detecting genetic risk factors for Aggressive Periodontitis (AgP). AgP is a destructive disease of the periodontium affecting around 1% of the population and leading to early tooth loss. Microbiological and environmental factors are thought to act on a genetically susceptible host to determine AgP. We conducted a case-control association study on 224 AgP patients (both Generalised AgP and Localised AgP) and 231 healthy controls to detect differences in genotype distributions of 13 single nucleotide polymorphisms (SNPs). The selected SNPs included FcR and FPR, NADPH oxidase, IL-6, TNF-a and VDR polymorphisms. Further studies on subsets of patients were conducted to detect associations between these SNPs and classical features of AgP: disease severity, familial aggregation, presence of periodontopathogenic bacteria and neutrophil hyperactivity. The NADPH p22phox 242 polymorphism was associated with the AgP trait and with disease severity. The IL-6 -174 SNP was associated with LAgP and with increased detection of periodontopathogenic bacteria. The FcyRIIIb NA polymorphism was associated with GAgP, while FcyR haplotypes were linked with AgP in Blacks and FcyRIIa was associated with familial aggregation of the AgP phenotype. The VDR Taq-I polymorphism showed a trend for association with AgP in smokers. The overall results of the study provide two possible pathogenic pathways leading to AgP: one is mediated through an excessive inflammatory response triggered by the presence of specific bacteria in individuals with hyper-responsive genotypes (NADPH p22phox 242 T allele, FcyRIIIb NA1 homozygosity, IL-6 -174 G homozygosity) the second is initiated by an increased susceptibility to bacterial colonization (FcyRIIa R homozygosity). In conclusion, this study supports the importance of genetic factors in Aggressive Periodontitis and hypothesizes possible pathogenic mechanisms

Expression of gingival crevicular fluid markers during early and late healing of intrabony defects after surgical treatment: a systematic review

Background: Surgical treatments such as guided tissue regeneration (GTR) and access flap surgery are widely employed for the treatment of intrabony defects. However, little is known regarding the postoperative expression of gingival crevicular fluid (GCF) markers. Objective: The aim of this systematic review was to compare the expression of GCF markers following treatment of periodontal intrabony defects with guided tissue regeneration or access surgery. The association of the markers’ expression with the clinical outcome was also assessed. Methods: An electronic literature search was conducted in MEDLINE, EMBASE, OpenGrey, LILACS and Cochrane Library up to December 2018 complemented by a manual search. Human, prospective clinical studies were identified. The changes from baseline up to 30 days (early healing) and 3 months (late healing) were assessed. Results: A total of 164 publications were identified and reviewed for eligibility. Of these, 10 publications fulfilled the inclusion criteria. The included studies evaluated 15 different GCF markers with a follow-up time between 21 and 360 days postoperatively. PDGF, VEGF and TIMP-1 changes were often investigated in the included studies; however, contrasting results were reported. Two studies agreed that both GTR and OFD lead to similar OPG level changes. TGF-β1 is increased early postoperatively, irrespective of the surgical technique employed. Conclusión: There is limited evidence available on the expression of GCF markers after surgical interventions of intrabony periodontal defects. However, OPG and TGF-β1 tend to increase early post-operatively, irrespective of the surgical technique employed, irrespective of the surgical technique employed. Clinical relevance: More well-designed, powered studies with sampling periods reflecting the regenerative process are needed, and future research should focus on employing standardised protocols for collecting, storing and analysing GCF markersS

The effect of a behavioural management tool in adults with mild to moderate periodontitis. A single‐blind, randomized controlled trial

OBJECTIVE: To compare a behavioural management program (test) to a standard communication approach (control) to reduce plaque, improve clinical outcomes and patient's compliance with oral self-care. BACKGROUND: Since psychological factors affect oral health-related behaviours, approaches directed at changing behaviours and improving compliance might improve the effect of oral health education. MATERIALS AND METHODS: This was a randomized, single-blind, parallel-design trial involving 71 patients with mild to moderate periodontitis. During a run-in period, all participants began using a power toothbrush. Two sessions of non-surgical periodontal therapy were performed post-baseline, along with one of the two oral healthcare communication approaches. Plaque and bleeding scores, probing pocket depth (PPD) and clinical attachment level (CAL) were recorded at the screening visit, baseline visit and at 8 and 14 weeks post-baseline. Patients were asked to fill in oral self-care diaries. Experience questionnaires were administered to both clinicians and patients to assess subjective experience of the clinician-patient interactions during the visits. RESULTS: In both groups, a significant reduction in plaque and bleeding scores was observed from baseline to 8 weeks after baseline, which then remained stable at week 14, but no differences between the groups were noted. An improvement in CAL and PPD was recorded at week 8 post-baseline in the test compared to the control group. No inter-group differences in the clinician's and subject's experience questionnaires were observed. CONCLUSION: Both approaches significantly promoted periodontal health. However, changing lifestyle requires repeated communication/engagement over time and a behavioural management program based upon two visits did not provide additional benefit compared to a standard approach