AN EXAMINATION OF RETURN TO PLAY CRITERIA FOR KNEE STRENGTH 1Nl EXPERIENCED SOCCER PLAYERS

Clinicians often use isokinetic strength exercises in the rehabilitation of lower extremity injuries. Isokinetic testing scores are often used as criterion to determine the progression within a rehabilitation protocol as well as the suitability of the patient to return to sport participation. For example, Shelbourne, Klootwyk, and De Carlo (1995) suggested that once the anterior cruciate ligament (ACL) reconstructed extremity achieves 70% of the strength of the uninjured leg, the patient is allowed to engage in sport-specific activities and begin the progression toward competitive participation. A criterion like this would be a valid standard assuming no strength differences exist between limbs. Few bilateral differences in lower extremity strength exist in most sedentary individuals or athletes participating in bilaterally symmetrical lower extremity activities. However, soccer players usually have tendencies to use one leg more than the other for dribbling, shooting and performing long kicks. As a result, soccer can be characterized as an asymmetrical lower extremity activity. If bilateral strength differences exist, then appropriate adjustments should be made for return to activity standards. This study examined whether differences existed in isokinetic knee f1exion and extension strength between the dominant and non-dominant legs in experienced soccer players

EFFECTS OF ANKLE STABILlZATION ON PUSH-OFF MECHANICS FROM A THREE-POINT STANCE IN FOOTBALL

The purpose of this investigation was to examine the effects of taping and bracing on push-off mechanics from a three-point football stance. Nineteen males were tested under three ankle stabilization conditions: braced, taped, and control. Participants performed five trials in each condition. Two 250Hz video cameras and a forceplate were used to collect data. A MANOVA with repeated measures revealed a significant main effect for condition. Post hoc analysis indicated that bracing and taping resulted in reduced minimum and maximum ankle angles and maximum angular velocity compared to the control. The horizontal velocity of the center of mass at takeofffor the tape condition was significantly lower than the control. Bracing and taping can have a negative effect on push-off mechanics

A simple all-microwave entangling gate for fixed-frequency superconducting qubits

We demonstrate an all-microwave two-qubit gate on superconducting qubits which are fixed in frequency at optimal bias points. The gate requires no additional subcircuitry and is tunable via the amplitude of microwave irradiation on one qubit at the transition frequency of the other. We use the gate to generate entangled states with a maximal extracted concurrence of 0.88 and quantum process tomography reveals a gate fidelity of 81%

Estimating the feasibility of transition paths in extended finite state machines

There has been significant interest in automating testing on the basis of an extended finite state machine (EFSM) model of the required behaviour of the implementation under test (IUT). Many test criteria require that certain parts of the EFSM are executed. For example, we may want to execute every transition of the EFSM. In order to find a test suite (set of input sequences) that achieves this we might first derive a set of paths through the EFSM that satisfy the criterion using, for example, algorithms from graph theory. We then attempt to produce input sequences that trigger these paths. Unfortunately, however, the EFSM might have infeasible paths and the problem of determining whether a path is feasible is generally undecidable. This paper describes an approach in which a fitness function is used to estimate how easy it is to find an input sequence to trigger a given path through an EFSM. Such a fitness function could be used in a search-based approach in which we search for a path with good fitness that achieves a test objective, such as executing a particular transition, and then search for an input sequence that triggers the path. If this second search fails then we search for another path with good fitness and repeat the process. We give a computationally inexpensive approach (fitness function) that estimates the feasibility of a path. In order to evaluate this fitness function we compared the fitness of a path with the ease with which an input sequence can be produced using search to trigger the path and we used random sampling in order to estimate this. The empirical evidence suggests that a reasonably good correlation (0.72 and 0.62) exists between the fitness of a path, produced using the proposed fitness function, and an estimate of the ease with which we can randomly generate an input sequence to trigger the path

Efficient measurement of quantum gate error by interleaved randomized benchmarking

We describe a scalable experimental protocol for obtaining estimates of the error rate of individual quantum computational gates. This protocol, in which random Clifford gates are interleaved between a gate of interest, provides a bounded estimate of the average error of the gate under test so long as the average variation of the noise affecting the full set of Clifford gates is small. This technique takes into account both state preparation and measurement errors and is scalable in the number of qubits. We apply this protocol to a superconducting qubit system and find gate errors that compare favorably with the gate errors extracted via quantum process tomography.Comment: 5 pages, 2 figures, published versio

Applications of artificial intelligence to prostate multiparametric MRI (mpMRI): Current and emerging trends

Prostate carcinoma is one of the most prevalent cancers worldwide. Multiparametric magnetic resonance imaging (mpMRI) is a non-invasive tool that can improve prostate lesion detection, classification, and volume quantification. Machine learning (ML), a branch of artificial intelligence, can rapidly and accurately analyze mpMRI images. ML could provide better standardization and consistency in identifying prostate lesions and enhance prostate carcinoma management. This review summarizes ML applications to prostate mpMRI and focuses on prostate organ segmentation, lesion detection and segmentation, and lesion characterization. A literature search was conducted to find studies that have applied ML methods to prostate mpMRI. To date, prostate organ segmentation and volume approximation have been well executed using various ML techniques. Prostate lesion detection and segmentation are much more challenging tasks for ML and were attempted in several studies. They largely remain unsolved problems due to data scarcity and the limitations of current ML algorithms. By contrast, prostate lesion characterization has been successfully completed in several studies because of better data availability. Overall, ML is well situated to become a tool that enhances radiologists\u27 accuracy and speed