95 research outputs found

    Improving the Efficiency of Electrical Stimulation Activities After Spinal Cord Injury

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    In order to enhance spinal cord injury (SCI) rehabilitation programs using neuromuscular electrical stimulation (NMES) and functional electrical stimulation (FES) it is important to examine the manner in which muscle fibers are recruited and the dose–response relationship. A review of the literature suggests that premature force decline and early fatigue with NMES and FES activities may be alleviated with decreased current frequency and increased current intensity. Dose–response relationships with NMES and FES are dependent on the goals of interest as reversing muscle atrophy can be achieved with activities 2–3 times per week for 6 or more weeks while increasing bone mass is more limited and requires more intense activity with greater exercise frequency and duration, e.g., 3–5 days per week for at least 6–12 months. The best known protocol to elicit neurological improvement is massed practice activities-based restorative therapies (ABRT) (3–5 h per day for several weeks)

    Effects of Multipath and Conventional NMES on Maximum Comfortable Stimulus and Torque Production

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    A novel multipath NMES (m-NMES) device has shown improved outcomes relative to conventional NMES (c-NMES) during recent basic and training studies. However, the mechanisms by which m-NMES outperformed c-NMES remain unclear. This study aimed to better understand these mechanisms by comparing the effects of m-NMES and c-NMES on maximum comfortable stimulus intensity and the subsequent NMES-induced torque, as these variables ultimately impact NMES training intensity; which is considered to be the primary determinant of NMES effectiveness. We measured maximum comfortable stimulus intensity and the subsequent NMES-induced torque while participants performed NMES-induced contractions under two conditions (m-NMES and c-NMES). Maximum comfortable stimulus intensity was significantly greater under the m-NMES condition, but the subsequent NMES-induced torque was not significantly different across conditions. m-NMES does not appear to influence the outcomes in a clinically meaningful manner, since it performed similarly to c-NMES with respect to peak NMES-induced torque

    The Effects of High Volume Aquatic Plyometric Training on Vertical Jump, Muscle Power, and Torque

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    The purpose of this study was to examine the effects of high volume aquatic-based plyometrics versus lower volume land and aquatic plyometric training on vertical jump (VJ), muscular peak power and torque in the dominant knee. Thirty-nine adult participants were randomly assigned to 1 of 4 groups: aquatic group 1 (APT1), aquatic group 2 (APT2), land group (LPT1), and control group (CON). All groups performed a 6-week plyometric training program. The APT1 and LPT performed the same volume of training where, APT2 doubled the volume. All participants were pre- and post-tested on performance variables. A 4 (group) X 2 (time) ANOVA with repeated measures was used to determine differences between the performance variables. We found no significant differences between groups for all tested variables. However, APT2 showed the greatest increased average in the performance variables. The high volume aquatic plyometric protocol is useful to help increase performance and minimize muscle soreness

    Pre-Conceptual Design of a Fluoride-Salt-Cooled Small Modular Advanced High Temperature Reactor (SmAHTR)

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    This document presents the results of a study conducted at Oak Ridge National Laboratory during 2010 to explore the feasibility of small modular fluoride salt-cooled high temperature reactors (FHRs). A preliminary reactor system concept, SmATHR (for Small modular Advanced High Temperature Reactor) is described, along with an integrated high-temperature thermal energy storage or salt vault system. The SmAHTR is a 125 MWt, integral primary, liquid salt cooled, coated particle-graphite fueled, low-pressure system operating at 700 C. The system employs passive decay heat removal and two-out-of-three , 50% capacity, subsystem redundancy for critical functions. The reactor vessel is sufficiently small to be transportable on standard commercial tractor-trailer transport vehicles. Initial transient analyses indicated the transition from normal reactor operations to passive decay heat removal is accomplished in a manner that preserves robust safety margins at all times during the transient. Numerous trade studies and trade-space considerations are discussed, along with the resultant initial system concept. The current concept is not optimized. Work remains to more completely define the overall system with particular emphasis on refining the final fuel/core configuration, salt vault configuration, and integrated system dynamics and safety behavior

    TOI-2015b: A Warm Neptune with Transit Timing Variations Orbiting an Active mid M Dwarf

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    We report the discovery of a close-in (Porb=3.349daysP_{\mathrm{orb}} = 3.349\:\mathrm{days}) warm Neptune with clear transit timing variations (TTVs) orbiting the nearby (d=47.3pcd=47.3\:\mathrm{pc}) active M4 star, TOI-2015. We characterize the planet's properties using TESS photometry, precise near-infrared radial velocities (RV) with the Habitable-zone Planet Finder (HP) Spectrograph, ground-based photometry, and high-contrast imaging. A joint photometry and RV fit yields a radius Rp = 3.370.20+0.15RR_p~=~3.37_{-0.20}^{+0.15} \:\mathrm{R_\oplus}, mass mp = 16.44.1+4.1Mm_p~=~16.4_{-4.1}^{+4.1}\:\mathrm{M_\oplus}, and density ρp = 2.320.37+0.38gcm3\rho_p~=~2.32_{-0.37}^{+0.38} \:\mathrm{g cm^{-3}} for TOI-2015b, suggesting a likely volatile-rich planet. The young, active host star has a rotation period of Prot = 8.7± 0.9 daysP_{\mathrm{rot}}~=~8.7 \pm~0.9~\mathrm{days} and associated rotation-based age estimate of 1.1 ± 0.1Gyr1.1~\pm~0.1\:\mathrm{Gyr}. Though no other transiting planets are seen in the TESS data, the system shows clear TTVs of super period Psup  430daysP_{\mathrm{sup}}~\approx~430\:\mathrm{days} and amplitude \sim100minutes100\:\mathrm{minutes}. After considering multiple likely period ratio models, we show an outer planet candidate near a 2:1 resonance can explain the observed TTVs while offering a dynamically stable solution. However, other possible two-planet solutions -- including 3:2 and 4:3 resonance -- cannot be conclusively excluded without further observations. Assuming a 2:1 resonance in the joint TTV-RV modeling suggests a mass of mb = 13.34.5+4.7Mm_b~=~13.3_{-4.5}^{+4.7}\:\mathrm{M_\oplus} for TOI-2015b and mc = 6.82.3+3.5Mm_c~=~6.8_{-2.3}^{+3.5}\:\mathrm{M_\oplus} for the outer candidate. Additional transit and RV observations will be beneficial to explicitly identify the resonance and further characterize the properties of the system.Comment: 28 pages, 15 figures, 6 tables. As submitted to AAS Journal

    Structural changes in commercial agriculture

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    The basic idea of the conference on Structural Changes in Commercial Agriculture was planted in the spring of 1964 by Earl 0. Heady. He outlined for the North Central Farm Management Research Committee his concern about the kind and amount of response to both current and prospective structural changes in the commercial farm firm. Many changes represent adjustments to technological and other innovations originating in marketing, research, and educational agencies serving farmers.https://lib.dr.iastate.edu/card_reports/1025/thumbnail.jp

    Federated learning enables big data for rare cancer boundary detection.

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    Although machine learning (ML) has shown promise across disciplines, out-of-sample generalizability is concerning. This is currently addressed by sharing multi-site data, but such centralization is challenging/infeasible to scale due to various limitations. Federated ML (FL) provides an alternative paradigm for accurate and generalizable ML, by only sharing numerical model updates. Here we present the largest FL study to-date, involving data from 71 sites across 6 continents, to generate an automatic tumor boundary detector for the rare disease of glioblastoma, reporting the largest such dataset in the literature (n = 6, 314). We demonstrate a 33% delineation improvement for the surgically targetable tumor, and 23% for the complete tumor extent, over a publicly trained model. We anticipate our study to: 1) enable more healthcare studies informed by large diverse data, ensuring meaningful results for rare diseases and underrepresented populations, 2) facilitate further analyses for glioblastoma by releasing our consensus model, and 3) demonstrate the FL effectiveness at such scale and task-complexity as a paradigm shift for multi-site collaborations, alleviating the need for data-sharing

    Author Correction: Federated learning enables big data for rare cancer boundary detection.

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    10.1038/s41467-023-36188-7NATURE COMMUNICATIONS14
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