Modeling the Expenditure and Recovery of Anaerobic Work Capacity in Cycling

The objective of this research is to model the expenditure and recovery of Anaerobic Work Capacity (AWC) as related to Critical Power (CP) during cycling. CP is a theoretical value at which a human can operate indefinitely and AWC is the energy that can be expended above CP. There are several models to predict AWC-depletion, however, only a few to model AWC recovery. A cycling study was conducted with nine recreationally active subjects. CP and AWC were determined by a 3-min all-out test. The subjects performed interval tests at three recovery intervals (15 s, 30 s, or 60 s) and three recovery powers (0.50CP, 0.75CP, and CP). It was determined that the rate of expenditure exceeds recovery and the amount of AWC recovered is influenced more by recovery power level than recovery duration. Moreover, recovery rate varies by individual and thus, a robust mathematical model for expenditure and recovery of AWC is needed

Experimental Modeling of Cyclists Fatigue and Recovery Dynamics Enabling Optimal Pacing in a Time Trial

Improving a cyclist performance during a time-trial effort has been a challenge for sport scientists for several decades. There has been a lot of work on understanding the physiological concepts behind it. The concepts of Critical Power (CP) and Anaerobic Work Capacity (AWC) have been discussed often in recent cycling performance related articles. CP is a power that can be maintained by a cyclist for a long time; meaning pedaling at or below this limit, theoretically, can be continued for infinite amount of time. However, there is a limited source of energy for generating power above CP. This limited energy source is AWC. After burning energy from this tank, a cyclist can recover some by pedaling below CP. In this paper we utilize the concepts of CP and AWC to mathematically model muscle fatigue and recovery of a cyclist. Then, the models are used to formulate an optimal control problem for a time trial effort on a 10.3 km course located in Greenville SC. The course is simulated in a laboratory environment using a CompuTrainer. At the end, the optimal simulation results are compared to the performance of one subject on CompuTrainer.Comment: 6 pages, 8 figure

Analytical solution of BVPs for fourth-order integrodifferential equations by using homotopy analysis method

Abstract:An analytic technique, the homotopy analysis method (HAM), is applied to obtain the approximate analytical solutions of fourth-order integro-differential equations. The homotopy analysis method (HAM) is one of the most effective method to obtain the exact and approximate solution and provides us with a new way to obtain series solutions of such problems. HAM contains the auxiliary parameter ℏ, which provides us with a simple way to adjust and control the convergence region of series solution. It is shown that the solutions obtained by the Adomian decomposition method (ADM) and the homotopy-perturbation method (HPM) are only special cases of the HAM solutions. we have shown that fourth-order boundary value problems can be transformed into a system of differential equations and integro-differential equation, which can be solved by using homotopy analysis method. Several examples are given to illustrate the efficiency and implementation of the method

Lithium Phthalocyanine: A Probe for Electron Paramagnetic Resonance Oximetry in Viable Biological Systems.

Lithium phthalocyanine (LiPc) is a prototype of another generation of synthetic, metallic-organic, paramagnetic crystallites that appear very useful for in vitro and in vivo electron paramagnetic resonance oximetry. The peak-to-peak line width of the electron paramagnetic resonance spectrum of LiPc is a linear function of the partial pressure of oxygen (pO2); this linear relation is independent of the medium surrounding the LiPc. It has an extremely exchange-narrowed spectrum (peak-to-peak line width = 14 mG in the absence of O2). Physicochemically LiPc is very stable; its response to pO2 does not change with conditions and environments (e.g., pH, temperature, redox conditions) likely to occur in viable biological systems. These characteristics provide the sensitivity, accuracy, and range to measure physiologically and pathologically pertinent O2 tensions (0.1-50 mmHg; 1 mmHg = 133 Pa). The application of LiPc in biological systems is demonstrated in measurements of pO2 in vivo in the heart, brain, and kidney of rats

Measuring the impact of virtual reality on a serious game for improving oral presentation skill

Background and Objectives: Oral presentation is a key competence for success in the diverse work environments that academics need. It is recommended as part of a higher education curriculum. The role of technology in improving oral presentation skills and especially facilitating feedback, is significant. In particular, the combination of serious game and virtual reality is a new area of ​​research that is a modern alternative to traditional skills training. The interactive digital environment, real-time feedback, the realism of the learning scenario, the direct experience, and the persistence of the knowledge gained are some of the virtual reality opportunities for skills training. It should not be overlooked that insufficient budget, negative attitude of users about their physical and psychological condition after experiencing virtual reality, and poor technological design of virtual reality environments are also among the limitations of this technology. However, recent meta-analyzes confirm the influence of virtual reality in learning environments. Accordingly, the purpose of this study was to measure the impact of virtual reality on a serious game with the serious purpose of oral presentation training. Methods: We designed and developed an SG and conducted a quasi-experimental study with a post-test on 32 graduate students. The research question we sought to answer was “to what extent can VR impact the effectiveness of SGs in oral presentation training?” The authors also analyzed the cost-effectiveness of incorporating VR elements. The game focused on three key skills, eye contact, walking around while presenting, and time management. The experimental group played the game with the HTC Vive VR system and the control group played the same game with an HD display, a keyboard, and a mouse. In addition to that, we collected in-game data while players were playing the game. Mann-Whitney U test and Student's t-test were used to compare the two groups. Findings: Results revealed that VR elements did not have a significant impact on the demonstration of the players' eye contact skills but they increased players' tendency to walk around the virtual environment. Analysis of players’ performance regarding time management skills showed no significant difference between the two groups. Conclusion: It is concluded that even though playing the serious game with an HD display, a keyboard, and a mouse can be effective, turning the game into a VR experience would result in further improvement in the demonstration of some of the presentation key skills (walking around while presenting). However, creating a VR experience requires developers to spend more time and resources into developing the game. According to researchers, creating a VR SG for improving oral presentation skills allows for training to be done in the context that it occurs within. Moreover, the VR SG can be effectively used to overcome public presentation nerves. Also, due to the challenging economic situations outside the university and the need to benefit from communication skills and oral presentation, a serious game based on virtual reality can improve the indicators of oral presentation. Achieving this requires higher education attention to interactive technologies such as virtual reality.   ===================================================================================== COPYRIGHTS  ©2020 The author(s). This is an open access article distributed under the terms of the Creative Commons Attribution (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, as long as the original authors and source are cited. No permission is required from the authors or the publishers.  ====================================================================================

A Novel Mutation in the OFD1 Gene in a Family with Oral-Facial-Digital Syndrome Type 1: A Case Report.

Oral-facial-digital syndrome as heterogeneous developmental conditions is characterized by abnormalities in the oral cavity, facial features and digits. Furthermore, central nervous system (CNS) abnormalities can also be part of this developmental disorder. At least 13 forms of OFDS based on their pattern of signs and symptoms have been identified so far. Type 1 which is now considered to be a ciliopathy accounts for the majority of cases. It is transmitted in an X-linked dominant pattern and caused by mutations in OFD1 gene, which can result in embryonic male lethality. In this study, we present a family suffering from orofaciodigital syndrome type I who referred to Medical Genetics Research Center, Shahid Sadoughi University of Medical Sciences in 2015. Two female siblings and their mother shared a novel 2-base pair deletion (c.1964-1965delGA) in exon 16 of OFD1 gene. Clinically, the sibling had oral, facial and brain abnormalities, whereas their mother is very mildly affected. She also had history of recurrent miscarriage of male fetus

Perceptual musical similarity metric learning with graph neural networks

Sound retrieval for assisted music composition depends on evaluating similarity between musical instrument sounds, which is partly influenced by playing techniques. Previous methods utilizing Euclidean nearest neighbours over acoustic features show some limitations in retrieving sounds sharing equivalent timbral properties, but potentially generated using a different instrument, playing technique, pitch or dynamic. In this paper, we present a metric learning system designed to approximate human similarity judgments between extended musical playing techniques using graph neural networks. Such structure is a natural candidate for solving similarity retrieval tasks, yet have seen little application in modelling perceptual music similarity. We optimize a Graph Convolutional Network (GCN) over acoustic features via a proxy metric learning loss to learn embeddings that reflect perceptual similarities. Specifically, we construct the graph's adjacency matrix from the acoustic data manifold with an example-wise adaptive k-nearest neighbourhood graph: Adaptive Neighbourhood Graph Neural Network (AN-GNN). Our approach achieves 96.4% retrieval accuracy compared to 38.5% with a Euclidean metric and 86.0% with a multilayer perceptron (MLP), while effectively considering retrievals from distinct playing techniques to the query example