CHANGES IN SPLIT VELOCITIES DURING SPRINT PERFORMANCE DEVELOPMENT

Sprint times and split velocities are invaluable measures for coaches and athletes monitoring sprint training and performance development. This study analysed sprint times and 10 m split velocities as performance of three developing athletes developed over a five week training period. All significantly improved their 60 m sprint times over the training period (p < 0.05). Sprint performance developed individually with a tendency for maximal velocities to increase early in the training period and start and acceleration velocities later. All athletes’ performances fluctuated between weeks, possibly due to a period of experimental learning in their process of skill development. This study will inform further analysis of the kinematic and kinetic parameters determining velocity, with the aim of identifying the key variables responsible for these changes

Distributed Optimization via Gradient Descent with Event-Triggered Zooming over Quantized Communication

In this paper, we study unconstrained distributed optimization strongly convex problems, in which the exchange of information in the network is captured by a directed graph topology over digital channels that have limited capacity (and hence information should be quantized). Distributed methods in which nodes use quantized communication yield a solution at the proximity of the optimal solution, hence reaching an error floor that depends on the quantization level used; the finer the quantization the lower the error floor. However, it is not possible to determine in advance the optimal quantization level that ensures specific performance guarantees (such as achieving an error floor below a predefined threshold). Choosing a very small quantization level that would guarantee the desired performance, requires {information} packets of very large size, which is not desirable (could increase the probability of packet losses, increase delays, etc) and often not feasible due to the limited capacity of the channels available. In order to obtain a communication-efficient distributed solution and a sufficiently close proximity to the optimal solution, we propose a quantized distributed optimization algorithm that converges in a finite number of steps and is able to adjust the quantization level accordingly. The proposed solution uses a finite-time distributed optimization protocol to find a solution to the problem for a given quantization level in a finite number of steps and keeps refining the quantization level until the difference in the solution between two successive solutions with different quantization levels is below a certain pre-specified threshold

LOWER LIMB JOINT KINETICS IN THE SPRINT START PUSH-OFF

Previous studies have analysed lower limb joint kinetics during sprint performance, but not addressed the earliest contact out of the blocks. The aim of this study was to report lower limb joint moments and powers during the first stance phase of the sprint push-off. One competitive male sprinter performed 10 maximal sprint starts. An automatic motion analysis system (CODA, 200 Hz) with synchronised force plate data (1000 Hz) were used to collect kinematic profiles at the hip, knee and ankle and ground reaction forces for the first stance phase. Cluster markers defined the orientation of the lower limb segments in 3D. Knee and hip kinetics differed to the later phases of sprint, whereas similarities were found at the ankle. This study highlights the need for the push-off phase to be considered separately from both research and practical perspectives

Finite-Time Distributed Optimization with Quantized Gradient Descent

In this paper, we consider the unconstrained distributed optimization problem, in which the exchange of information in the network is captured by a directed graph topology, and thus nodes can send information to their out-neighbors only. Additionally, the communication channels among the nodes have limited bandwidth, to alleviate the limitation, quantized messages should be exchanged among the nodes. For solving the distributed optimization problem, we combine a distributed quantized consensus algorithm (which requires the nodes to exchange quantized messages and converges in a finite number of steps) with a gradient descent method. Specifically, at every optimization step, each node performs a gradient descent step (i.e., subtracts the scaled gradient from its current estimate), and then performs a finite-time calculation of the quantized average of every node's estimate in the network. As a consequence, this algorithm approximately mimics the centralized gradient descent algorithm. The performance of the proposed algorithm is demonstrated via simple illustrative examples

Asynchronous Distributed Optimization via ADMM with Efficient Communication

In this paper, we focus on an asynchronous distributed optimization problem. In our problem, each node is endowed with a convex local cost function, and is able to communicate with its neighbors over a directed communication network. Furthermore, we assume that the communication channels between nodes have limited bandwidth, and each node suffers from processing delays. We present a distributed algorithm which combines the Alternating Direction Method of Multipliers (ADMM) strategy with a finite time quantized averaging algorithm. In our proposed algorithm, nodes exchange quantized valued messages and operate in an asynchronous fashion. More specifically, during every iteration of our algorithm each node (i) solves a local convex optimization problem (for the one of its primal variables), and (ii) utilizes a finite-time quantized averaging algorithm to obtain the value of the second primal variable (since the cost function for the second primal variable is not decomposable). We show that our algorithm converges to the optimal solution at a rate of $O(1/k)$ (where $k$ is the number of time steps) for the case where the local cost function of every node is convex and not-necessarily differentiable. Finally, we demonstrate the operational advantages of our algorithm against other algorithms from the literature

The effects of dietary hesperidin and naringin supplementation on lamb performance and meat characteristics

An experiment was conducted to examine the effects of supplementing feed with hesperidin or naringin, bioflavonoids that are abundant and inexpensive by-products of citrus cultivation, on lambs’ growth performance, carcass and meat characteristics. Fourty-four male Chios lambs were randomly assigned to 4 groups. One of the groups served as control (C) and was given a basal diet, whereas the other 3 groups were given the same diet further supplemented with hesperidin at 2500 mg (H), or naringin at 2500 mg (N), or α-tocopheryl acetate at 200 mg (E) per kg feed. At the end of the experiment (35th day), lambs were fasted, weighed and slaughtered. After overnight chilling, samples of longissimus thoracis muscle were taken and were used for meat quality evaluation. No significant differences were observed in final body weight, body weight gain and edible organ weights among the four experimental groups. pH, colour parameters (L, a*, b*), water holding capacity and shear force value of longissimus thoracis muscle were also not significantly influenced by the dietary treatments. Measurement of lipid oxidation values showed that hesperidin or naringin supplementation positively influenced meat antioxidant properties during the refrigerated storage at 4°C for up to 8 days, however to a lesser extent compared to α-tocopheryl acetate. Nowadays, there is a strong interest in isolating antioxidants from natural sources and using them in animal nutrition with the intention to minimize lipid oxidation in meat products. According to the findings of the present study, flavonoids appeared as a great alternative, since they resulted in an improvement of meat antioxidant capacity leading to a prolongation of its shelf-life and an increase of its acceptability in the market

Direct observation of the flux-line vortex glass phase in a type II superconductor

The order of the vortex state in La_{1.9} Sr_{0.1} CuO_{4} is probed using muon spin rotation and small-angle neutron scattering. A transition from a Bragg glass to a vortex glass is observed, where the latter is composed of disordered vortex lines. In the vicinity of the transition the microscopic behavior reflects a delicate interplay of thermally-induced and pinning-induced disorder.Comment: 14 pages, 4 colour figures include

Muons as Local Probes of Three-body Correlations in the Mixed State of Type-II Superconductors

The vortex glass state formed by magnetic flux lines in a type-II superconductor is shown to possess non-trivial three-body correlations. While such correlations are usually difficult to measure in glassy systems, the magnetic fields associated with the flux vortices allow us to probe these via muon-spin rotation measurements of the local field distribution. We show via numerical simulations and analytic calculations that these observations provide detailed microscopic insight into the local order of the vortex glass and more generally validate a theoretical framework for correlations in glassy systems.Comment: 4+ pages, high-quality figures available on reques

Translating Biomarkers of Cholangiocarcinoma for Theranosis: A Systematic Review

Cholangiocarcinoma (CCA) is a rare disease with poor outcomes and limited research efforts into novel treatment options. A systematic review of CCA biomarkers was undertaken to identify promising biomarkers that may be used for theranosis (therapy and diagnosis). MEDLINE/EMBASE databases (1996–2019) were systematically searched using two strategies to identify biomarker studies of CCA. The PANTHER Go-Slim classification system and STRING network version 11.0 were used to interrogate the identified biomarkers. The TArget Selection Criteria for Theranosis (TASC-T) score was used to rank identified proteins as potential targetable biomarkers for theranosis. The following proteins scored the highest, CA9, CLDN18, TNC, MMP9, and EGFR, and they were evaluated in detail. None of these biomarkers had high sensitivity or specificity for CCA but have potential for theranosis. This review is unique in that it describes the process of selecting suitable markers for theranosis, which is also applicable to other diseases. This has highlighted existing validated markers of CCA that can be used for active tumor targeting for the future development of targeted theranostic delivery systems. It also emphasizes the relevance of bioinformatics in aiding the search for validated biomarkers that could be repurposed for theranosis