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( Matthew Sharp ),( Jacob Wilson ),( Matthew Stefan ),( Raad Gheith ),( Ryan Lowery ),( Charlie Ottinger ),( Dallen Reber ),( Cemal Orhan ),( Nurhan Sahin ),( Mehmet Tuzcu ),( Shane Durkee ),( Zainula 한국운동영양학회 2021 Physical Activity and Nutrition (Phys Act Nutr) Vol.25 No.1
[Purpose] This study investigated the effects of marine phytoplankton supplementation (Oceanix®, Tetraselmis chuii ) on 1) maximal isometric strength and immune function in healthy humans following a one-week high-intensity resistance-training program and 2) the proinflammatory cytokine response to exercise in a rat model. [Methods] In the human trial, 22 healthy male and female participants were randomly divided into marine phytoplankton and placebo groups. Following baseline testing, participants underwent a 14-day supplement loading phase before completing five consecutive days of intense resistance training. In the rat model, rats were randomly divided into four groups (n=7 per condition): (i) control, (ii) exercise, (iii) exercise + marine phytoplankton (2.55 mg/kg/day), or (iv) exercise + marine phytoplankton (5.1 mg/kg/day). Rats in the exercising groups performed treadmill exercise 5 days per week for 6 weeks. [Results] In the human model, marine phytoplankton prevented significant declines in the isometric peak rate of force development compared to placebo. Additionally, salivary immunoglobulin A concentration was significantly lower following the resistance training protocol in the placebo group but not in the marine phytoplankton group. Marine phytoplankton in exercising rats decreased intramuscular levels and serum concentrations of tumor necrosis factor-alpha (TNF-α) and interleukin-1 beta (IL-1β) and intramuscular concentrations of malondialdehyde. [Conclusion] Marine phytoplankton prevented decrements in indices of functional exercise recovery and immune function. Mechanistically, these outcomes could be prompted by modulating the oxidative stress and proinflammatory cytokine response to exercise.
Stirling Sharpe 글로벌지식마케팅경영학회 2018 Journal of Global Sport Management Vol. No.
The increasing commercialism of sport has been accompanied by pressure for sport organizations to become (more) professional. The kitchen table or boardroom approaches that may be ingrained in accepted values within organizations are being challenged by contemporary business principles of sport organization governance. While considerable work has been conducted under the banner of the professionalization of sport, there has been limited research addressing the ongoing professionalization of organizations which have already moved away from being volunteer based and are operating in a business-like manner. This research provides a case study of the ACT Brumbies rugby union club in Australia addressing this issue with interviews conducted within three key stakeholder groups of this organization: Board members, operations staff, and players. Semi-structured interviews were conducted with a purposive sample of twelve stakeholders. Results indicated that the ongoing professionalization process had differing impacts on operations for various employees.
Neural network-based build time estimation for additive manufacturing: a performance comparison
Oh Yosep,Sharp Michael,Sprock Timothy,권순조 한국CDE학회 2021 Journal of computational design and engineering Vol.8 No.5
Additive manufacturing (AM) has brought positive opportunities with phenomenal changes to traditional manufacturing. Consistent efforts and novel studies into AM use have resolved critical issues in manufacturing and broadened technical boundaries. Build time estimation is one of the critical issues in AM that still needs attention. Accurate build time estimation is key for feasibility studies, preliminary design, and process/production planning. Recent studies have provided the possibility of neural network (NN)-based build time estimation. In particular, traditional artificial NN (ANN)- and convolutional NN (CNN)-based methods have been demonstrated. However, very little has been done on the performance comparison for build time estimation among the different types of NNs. This study is aimed at filling this gap by designing various NNs for build time estimation and comparing them. Two types of features are prepared as inputs for the NNs by processing three-dimensional (3D) models: (1) representative features (RFs) including dimensions, part volume, and support volume; and (2) the set of voxels generated from designating the cells occupied by the workpiece in a mesh grid. With the combination of NN types and input feature types, we design three NNs: (1) ANN with RFs; (2) ANN with voxels; and (3) CNN with voxels. To obtain large enough label data for reliable training, we consider simulation build time from commercial slicing applications rather than actual build time. The simulation build time is calculated based on a material extrusion process. To address various cases for input models, two design factors (scale and rotation) are considered by controlling the size and build orientation of 3D models. In computational experiments, we reveal that the CNN-based estimation is often more accurate than others. Furthermore, the design factors affect the performance of build time estimation. In particular, the CNN-based estimation is strongly influenced by changing the size of 3D models.
Fabrication and mechanical characterization of 3D woven Cu lattice materials
Zhang, Y.,Ha, S.,Sharp, K.,Guest, J.K.,Weihs, T.P.,Hemker, K.J. Elsevier Ltd 2015 Materials & Design Vol.85 No.-
3D metallic lattices designed to have two distinctly different material architectures have been woven with metallic Cu wires. A vacuum soldering technique was employed to metallurgically bond the wire nodes and form stiff 3D lattice materials. The structures and mechanical properties of the as-woven and soldered lattices were characterized by optical microscopy and micro-scale mechanical property experiments. The measured in-plane shear stiffness shows good agreement with predictions from finite element (FE) models that account for variations in the manufacturing and solder bonding. The study indicates that stiffness is influenced by the percentage of bonded nodes and the location of bonding. The 3D woven lattice materials manufactured in this study exhibited a very high percentage (80%) of bonded nodes and a unique combination of stiffness and density as compared to that typically reported for ultra lightweight lattice materials.