Many individuals do not participate in resistance exercise, with perceived lack of time being a key barrier. Minimal dose strategies, which generally reduce weekly exercise volumes to less than ...recommended guidelines, might improve muscle strength with minimal time investment. However, minimal dose strategies and their effects on muscle strength are still unclear. Here our aims are to define and characterize minimal dose resistance exercise strategies and summarize their effects on muscle strength in individuals who are not currently engaged in resistance exercise. The minimal dose strategies overviewed were: “Weekend Warrior,” single-set resistance exercise, resistance exercise “snacking,” practicing the strength test, and eccentric minimal doses. “Weekend Warrior,” which minimizes training frequency, is resistance exercise performed in one weekly session. Single-set resistance exercise, which minimizes set number and session duration, is one set of multiple exercises performed multiple times per week. “Snacks,” which minimize exercise number and session duration, are brief bouts (few minutes) of resistance exercise performed once or more daily. Practicing the strength test, which minimizes repetition number and session duration, is one maximal repetition performed in one or more sets, multiple days per week. Eccentric minimal doses, which eliminate or minimize concentric phase muscle actions, are low weekly volumes of submaximal or maximal eccentric-only repetitions. All approaches increase muscle strength, and some approaches improve other outcomes of health and fitness. “Weekend Warrior” and single-set resistance exercise are the approaches most strongly supported by current research, while snacking and eccentric minimal doses are emerging concepts with promising results. Public health programs can promote small volumes of resistance exercise as being better for muscle strength than no resistance exercise at all.
Purpose
The aim of the present study was to determine whether depression of maximal muscular force and neural drive subsequent to prolonged ( ≥ 60 s) passive muscle stretching is associated with ...altered corticospinal excitability or intracortical (GABA
B
-mediated) inhibition.
Methods
Fourteen healthy adult males were tested before and after 5 min (5 × 60-s stretches) of intense, passive static stretching of the plantar flexor muscles. Two protocols (A and B) were conducted in a randomized order. Transcranial magnetic stimulation was delivered to the contralateral motor cortex at rest (Protocol A) and during maximal voluntary contractions (Protocol B). Changes in maximal voluntary isometric torque, voluntary surface electromyographic activity of triceps surae muscles (normalized to M-wave; EMG/
M
), motor-evoked potentials (MEP), and cortical silent period (cSP; Protocol B) in soleus elicited by transcranial magnetic stimulation were examined 10 min after stretch.
Results
In both protocols A and B, significant decreases were observed immediately after stretching in maximal voluntary plantar flexion torque ( − 20.1 ± 15.9%,
P
= 0.004; and − 17.2 ± 13.5%,
P
= 0.006) and EMG/
M
( − 18.0 ± 18.2%,
P
= 0.023; and − 13.0 ± 9.3%,
P
= 0.003). Decreases in torque and EMG/
M
were highly correlated (
r
= 0.67–0.85,
P
< 0.05). However, no changes were observed in MEP amplitudes during rest ( + 29.3 ± 50.0%) or maximum voluntary contraction ( + 1.9 ± 16.8%), or in cSP ( + 2.1 ± 15.1%).
Conclusions
Impaired neural drive contributed to the stretch-induced force loss; however, changes in corticospinal excitability and intracortical inhibition could not explain the phenomenon.
The purpose of this study was to investigate changes in muscle spindle sensitivity with early and late soleus reflex responses via tendon taps and transcranial magnetic stimulation, respectively, ...after an acute bout of prolonged static plantar flexor muscle stretching. Seventeen healthy males were tested before and after 5 min (5 × 60‐s stretches) of passive static stretching of the plantar flexor muscles. Maximal voluntary isometric torque and M wave‐normalized triceps surae muscle surface electromyographic activity were recorded. Both soleus tendon reflexes, evoked by percussion of the Achilles tendon during rest and transcranial magnetic stimulation‐evoked soleus late responses during submaximal isometric dorsiflexion were also quantified. Significant decreases in maximal voluntary isometric plantar flexion torque (−19.2 ± 13.6%, p = .002) and soleus electromyographic activity (−20.1 ± 11.4%, p < .001) were observed immediately after stretching, and these changes were highly correlated (r = 0.76, p < .001). No changes were observed in tendon reflex amplitude or latency or peak muscle twitch torque (p > .05). Significant reductions in soleus late response amplitudes (−46.9 ± 36.0%, p = .002) were detected, although these changes were not correlated with changes in maximal electromyographic activity, torque or tendon reflex amplitudes. No changes in soleus late response latency were detected. In conclusion, impaired neural drive was implicated in the stretch‐induced force loss; however, no evidence was found that this loss was related to changes in muscle spindle sensitivity. We hypothesize that the decrease in soleus late response indicates a stretch‐induced reduction in a polysynaptic postural reflex rather than spindle reflex sensitivity.
Passive muscle stretching causes reductions in neural drive and force output during subsequent voluntary muscle contractions. It appears that muscle spindle desensitization, which may weaken facilitatory Ia afferent input to motoneurons, does not contribute to the impairment in voluntary contraction strength. Rather muscle stretching may interfere with postural reflexes that support upright balance.
Multiple neuromuscular processes contribute to the loss of force production following repeated, high-intensity muscular efforts; however, the relative contribution of each process is unclear. In ...Experiment 1, 16 resistance trained men performed six sets of unilateral isometric plantar flexor contractions of the right leg (3 s contraction/2 s rest; 85% maximal voluntary contraction torque; 90-s inter-set rest) until failure with and without caffeine ingestion (3 mg kg
) on two separate days. Corticospinal excitability and cortical silent period (cSP) were assessed before and immediately, 10 and 20 min after the exercise. In Experiment 2, electrically evoked tetanic force and persistent inward current (PIC)-mediated facilitation of the motor neuron pool (estimated using neuromuscular electrical stimulation with tendon vibration) were assessed before and after the same exercise intervention in 17 resistance trained men. Results showed decreases in peak plantar flexion torque (Experiment 1: -12.2%, Experiment 2: -16.9%), electrically evoked torque (20 Hz -15.3%, 80 Hz -15.3%, variable-frequency train -17.9%), and cSP (-3.8%; i.e., reduced inhibition) post-exercise which did not recover by 20 min. Electromyographic activity (EMG; -6%), corticospinal excitability (-9%), and PIC facilitation (-24.8%) were also reduced post-exercise but recovered by 10 min. Caffeine ingestion increased torque and EMG but did not notably affect corticospinal excitability, PIC amplification, or electrically evoked torque. The data indicate that a decrease in muscle function largely underpins the loss of force after repeated, high-intensity muscular efforts, but that the loss is exacerbated immediately after the exercise by simultaneous decreases in corticospinal excitability and PIC amplitudes at the motor neurons.
The concept of metacognition has been proposed and applied to radar system analysis to enhance the classical cognitive radar paradigm. Metacognition allows a cognitive radar to have self-awareness ...about its cognitive processes. To accurately compare various cognitive processes and select the best under the operational scenario, a performability metric capable of comparing system performance over various scales and units is proposed and analyzed. This correspondence expands previous work on radar operational reliability to provide a metareliability metric for a metacognitive tracking radar. The approach is tested and validated on a radar that tracks a target performing a composite maneuver involving constant velocity, constant turn, and constant acceleration.
A network of distributed radar nodes can significantly improve detection, parameter estimation, and tracking capabilities of a single platform-based radar systems. Optimum allocation of bandwidths ...and carrier frequencies to these nodes is an important non-trivial research problem. A simple way of equally dividing the available bandwidth among radar nodes can become highly suboptimal. In this paper, we propose both model- and deep learning-based joint bandwidth and carrier frequency allocation algorithms for a network consisting of a central coordinator and distributed radar nodes, each operating in a monostatic mode. With an objective of enabling poor performing radar nodes, that observe low target signal-to-noise-interference ratio (SINR) values, benefit from distributed collaboration, we propose model-based max-min approach, in which we maximize the minimum of the SINRs observed by all nodes, under total bandwidth and individual node's range resolution (RR) constraints. This optimization is non-convex, but we solve it efficiently utilizing an explicit relationship between bandwidth and carrier frequencies, and the fact that each node's SINR is a monotonically decreasing function of bandwidth and carrier frequency allocated to the node. We propose two iterative optimization methods that employ successive convex approximation with a) semidefinite programming (SDP) and b) geometric programming (GP) problem formulations. Computer simulations show the performance of the proposed methods under different RR requirements, which significantly outperform the equal bandwidth allocation (EBWA) method and enable poor performing nodes to enhance their individual SINRs significantly. The solutions of this model-based optimization and target locations are then used, respectively, as labels and input, to train a bidirectional long short-term memory (LSTM) network. The trained network can significantly reduce the online run-time complexity of the bandwidth and carrier frequency allocation in distributed radar networks.
Congestion in the RF spectrum is rapidly increasing, which has motivated the need for efficient spectrum sharing techniques. A cognitive radar system has been developed to implement a perception ...action cycle, for spectrum sharing, in which the RF spectrum is sensed, other RF signals are identified, and the radar frequency band of operation is adapted to avoid interfering signals in the spectrum. The system operates in real time and is capable of coexisting with common communications signals. A system with this capability requires efficient programming that pushes the limits of the technology available. In order to properly test the performance of a radar system designed for this kind of reactive spectrum sharing, a rigorous set of synthetic interference signals is generated and several informative evaluation metrics are defined. Additionally, the system's performance is evaluated with common communications signals such as LTE and GSM. The performance of the system is found to be adequate for avoiding signals that are either varying in frequency or turning on and off at rates on the order of 10 ms.
In this paper we describe the libMesh (http://libmesh.sourceforge.net) framework for parallel adaptive finite element applications. libMesh is an open-source software library that has been developed ...to facilitate serial and parallel simulation of multiscale, multiphysics applications using adaptive mesh refinement and coarsening strategies. The main software development is being carried out in the CFDLab (http://cfdlab.ae.utexas.edu) at the University of Texas, but as with other open-source software projects; contributions are being made elsewhere in the US and abroad. The main goals of this article are: (1) to provide a basic reference source that describes libMesh and the underlying philosophy and software design approach; (2) to give sufficient detail and references on the adaptive mesh refinement and coarsening (AMR/C) scheme for applications analysts and developers; and (3) to describe the parallel implementation and data structures with supporting discussion of domain decomposition, message passing, and details related to dynamic repartitioning for parallel AMR/C. Other aspects related to C++ programming paradigms, reusability for diverse applications, adaptive modeling, physics-independent error indicators, and similar concepts are briefly discussed. Finally, results from some applications using the library are presented and areas of future research are discussed.
The growing demand for radio frequency (RF) spectrum access poses new challenges for next-generation radar systems. To operate in a crowded electromagnetic environment, radars must coexist with other ...RF emitters while maintaining system performance. This work evaluates the performance of a spectrum sharing cognitive radar system, which predicts and avoids RF interference (RFI) in real time. The system applies a cognitive perception-action cycle that senses RFI, learns RFI behavior over time, and adapts the radar's frequency band of operation. Through cognition, the system learns a stochastic model describing RF activity. This model allows the cognitive radar to predict RF activity in real time and share the spectrum with emitters, such as communication systems. A set of synthetic and measured interference signals are used to evaluate the performance of this predictive spectrum sharing scheme. This work assesses the impact of RFI on the cognitive radar's range profile with respect to variation in RF environment. The system demonstrates accurate avoidance of deterministic RFI with a degradation in spectrum sharing efficiency as variability over time increases.
A spectrum sharing radar can be guided by a cognitive decision process to determine the optimal radar operating frequency as the spectral environment changes. This decision process utilizes spectrum ...sensing or spectral prediction to determine the optimal radar transmission for a given situation. The radar transmitter power amplifier performance varies with frequency and bandwidth of the applied waveform, thus adaptive impedance tuners are useful in maximizing the transmitted power and radar range as the transmission frequency range is varied. Since high power handling is required in radar transmissions, and mechanically actuated impedance tuners presently demonstrate the best power handling, the time required to tune is often orders of magnitude greater than the pulse repetition interval. As such, the relatively lengthy impedance tuning operations should be guided to maximize the average output power as the system transitions between different center frequencies, bandwidths, and waveforms over time. This article presents an algorithm that performs impedance tuning with an evanescent-mode cavity tuner based on an average performance gradient computed for multiple transmit pulses. Comparison of test results with traditionally measured amplifier load-pull data shows that the transmitter is effectively optimized for maximum average output power.
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