Predictors of Performance during a 161 km Mountain Footrace

Training volume and cardiovascular dynamics influence endurance performance. However, there is limited information on the interplay between training volume, cardiovascular dynamics, and performance in ultra-marathon athletes. PURPOSE: We aimed to determine predictors of performance in finishers of the 2023 Western States Endurance Run (WSER). METHODS: Sixty participants who finished the race (49 males/11 females; mean age: 44.7 ± 9.6 y, range: 26–66 y; BMI: 22.7 ± 2.2 kg/m2) completed pre-race surveys including average training volume (AV) and peak training volume (PV), as well as resting cardiovascular measures including resting heart rate (RHR) and augmentation index (AIx), a measure of wave reflection characteristics. Based on WSER completion time, we calculated average running velocity (RV). We assessed associations among 22 variables using bivariate correlation analysis (Pearson’s Correlation for normally distributed data and Spearman’s Rank Correlation if normality was not met). Within our listed variables, normality was met in age and AV. Additionally, we completed multiple regression analyses for predictors. We present descriptive data as mean ± SD. RESULTS: Participants had an average RV of 6.33 ± 0.97 km/h (3.93 ± 0.6 mph), and reported an AV of 91.9 ± 24.5 km/wk (57.1 ± 15.2 miles/wk) and a PV of 141.0 ± 47.2 km/wk (87.6 ± 29.3 miles/wk). We observed significant associations between RV and age (r(58) = -0.57, p r(58) = 0.41, p r(58) = 0.34, p R2 = 0.37; F(3,56) = 12.4, pb1 = 0.013; t(56) = 2.57, p = 0.013), resulting in a 0.33 km/h increase in RV for every 25-km increase in AV. Last, significant relations existed between RV and AIx (r(58) = -0.30, p = 0.022); and RHR (r(58) = -0.26, p = 0.046). CONCLUSION: We found that (1) average weekly training volume is a significant predictor of performance in elite ultra-marathon athletes and (2) race performance was inversely associated with resting arterial wave reflection characteristics and heart rate

3-D Volumetric Evaluation of Human Mandibular Growth

Bone growth is a complex process that is controlled by a multitude of mechanisms that are not fully understood.Most of the current methods employed to measure the growth of bones focus on either studying cadaveric bones from different individuals of different ages, or successive two-dimensional (2D) radiographs. Both techniques have their known limitations. The purpose of this study was to explore a technique for quantifying the three dimensional (3D) growth of an adolescent human mandible over the period of one year utilizing cone beam computed tomography (CBCT) scans taken for regular orthodontic records. Three -dimensional virtual models were created from the CBCT data using mainstream medical imaging software. A comparison between computer-generated surface meshes of successive 3-D virtual models illustrates the magnitude of relative mandible growth. The results of this work are in agreement with previously reported data from human cadaveric studies and implantable marker studies. The presented method provides a new relatively simple basis (utilizing commercially available software) to visualize and evaluate individualized 3D (mandibular) growth in vivo

The effect of low level laser on condylar growth during mandibular advancement in rabbits

<p>Abstract</p> <p>Introduction</p> <p>It has been shown that Low Level Laser (LLL) has a positive effect on bone formation. The aim of this study was to evaluate the effect of low level laser on condylar growth during mandibular advancement in rabbits.</p> <p>Materials and methods</p> <p>Continuous forward mandibular advancement was performed in fourteen male Albino rabbits with the mean age of 8 weeks and the mean weight of 1.5 ± 0.5 kg, with acrylic inclined planes. The rabbits were randomly assigned into two groups after 4 weeks. LLL (KLO3: wave length 630 nm) was irradiated at 3 points around the TMJ, through the skin in the first group. The exposure was performed for 3 minutes at each point (a total of 9 minutes) once a day for 3 weeks. The control group was not exposed to any irradiation. The rabbits in both groups were sacrificed after two months and the histological evaluation of TMJ was performed to compare fibrous tissue, cartilage, and new bone formation in condylar region in both groups. Disc displacement was also detected in both groups. Student's t-test, Exact Fisher and Chi square tests were used for the statistical analysis.</p> <p>Results</p> <p>The formation of fibrous tissue was significantly lower, while bone formation was significantly greater in lased group as compared with control group. The thickness of cartilage did not differ significantly between two groups.</p> <p>Conclusion</p> <p>Irradiation of LLL (KLO3) during mandibular advancement in rabbits, increases bone formation in condylar region, while neither increase in the cartilage thickness nor fibrous tissues was observed.</p

Modelling semantic transparency

We present models of semantic transparency in which the perceived trans- parency of English noun–noun compounds, and of their constituent words, is pre- dicted on the basis of the expectedness of their semantic structure. We show that such compounds are perceived as more transparent when the first noun is more frequent, hence more expected, in the language generally; when the compound semantic rela- tion is more frequent, hence more expected, in association with the first noun; and when the second noun is more productive, hence more expected, as the second ele- ment of a noun–noun compound. Taken together, our models of compound and con- stituent transparency lead us to two conclusions. Firstly, although compound trans- parency is a function of the transparencies of the constituents, the two constituents differ in the nature of their contribution. Secondly, since all the significant predictors in our models of compound transparency are also known predictors of processing speed, perceived transparency may itself be a reflex of ease of processing

Social media in undergraduate medical education: A systematic review.

INTRODUCTION: There are over 3.81 billion worldwide active social media (SoMe) users. SoMe are ubiquitous in medical education, with roles across undergraduate programmes, including professionalism, blended learning, well being and mentoring. Previous systematic reviews took place before recent explosions in SoMe popularity and revealed a paucity of high-quality empirical studies assessing its effectiveness in medical education. This review aimed to synthesise evidence regarding SoMe interventions in undergraduate medical education, to identify features associated with positive and negative outcomes. METHODS: Authors searched 31 key terms through seven databases, in addition to references, citation and hand searching, between 16 June and 16 July 2020. Studies describing SoMe interventions and research on exposure to existing SoMe were included. Title, abstract and full paper screening were undertaken independently by two reviewers. Included papers were assessed for methodological quality using the Medical Education Research Study Quality Instrument (MERSQI) and/or the Standards for Reporting Qualitative Research (SRQR) instrument. Extracted data were synthesised using narrative synthesis. RESULTS: 112 studies from 26 countries met inclusion criteria. Methodological quality of included studies had not significantly improved since 2013. Engagement and satisfaction with SoMe platforms in medical education are described. Students felt SoMe flattened hierarchies and improved communication with educators. SoMe use was associated with improvement in objective knowledge assessment scores and self-reported clinical and professional performance, however evidence for long term knowledge retention was limited. SoMe use was occasionally linked to adverse impacts upon mental and physical health. Professionalism was heavily investigated and considered important, though generally negative correlations between SoMe use and medical professionalism may exist. CONCLUSIONS: Social media is enjoyable for students who may improve short term knowledge retention and can aid communication between learners and educators. However, higher-quality study is required to identify longer-term impact upon knowledge and skills, provide clarification on professionalism standards and protect against harms

Developing Phoneme-based Lip-reading Sentences System for Silent Speech Recognition

Lip-reading is a process of interpreting speech by visually analyzing lip movements. Recent research in this area has shifted from simple word recognition to lip-reading sentences in the wild. This paper attempts to use phonemes as a classification schema for lip-reading sentences to explore an alternative schema and to enhance systems performance. Different classification schemas have been investigated, including character-based and visemes-based schemas. In this presented work, the visual front-end model of the system consists of a Spatial-Temporal (3D) convolution followed by a 2D ResNet. Transformers utilize multi-headed attention for the phoneme recognition models. For the language model, a Recurrent Neural Network is used. The performance of the proposed system has been testified with the BBC Lip Reading Sentences 2 (LRS2) benchmark dataset. Compared with the state-of-the-art approaches in lip reading sentences the proposed system has demonstrated an improved performance by a 10% lower word error rate on average under varying illumination ratios