Comparison of muscle strength and flexibility between the preferred and non-preferred leg in English soccer players

Most soccer players have a favoured foot for kicking the ball, and it is believed that this preference may lead to an asymmetry in the strength and flexibility of the lower extremities. This study was designed to determine whether asymmetry in strength and flexibility are present in the legs of soccer players.Forty-one elite and sub-elite soccer players (age 23.4 +/- 3.8 years; height 1.81 +/- 0.06 m; body mass 81.7 +/- 9.9 kg) were studied (data are presented as mean +/- SD). The dynamic strength of knee flexors (hamstrings) and knee extensors (quadriceps) was measured using an isokinetic dynamometer at angular velocities of 1.05, 2.09, 5.23 rad/s (in a concentric mode) and 2.09 rad/s (in an eccentric mode). The concentric strength ratio (hamstrings(conc)/quadriceps(conc)) and the dynamic control ratio (hamstrings(ecc)/quadriceps(conc)) were computed. Hip joint flexibility (in flexion) was measured using a goniometer.A significant difference between the preferred and non-preferred leg was found in the knee flexors at 2.09 rad/s (119 +/- 22 versus 126 +/- 24 Nm; P < 0.05) and for the dynamic control ratio (0.79 +/- 0.13 versus 0.84 +/- 0.16 Nm; P < 0.05). In both cases the knee flexors of the preferred leg were weaker than those of the non-preferred leg. A total of 28 of the 41 players (68%) had significant musculoskeletal abnormality (imbalance >10%) in one or more specific muscle groups. No significant differences were found in flexibility of the hip joint between the preferred and non-preferred leg (P > 0.05).It is concluded that the lower strength of the knee flexor muscles of the preferred leg may be associated with the differential use of these muscle during the kicking action and thus constitutes a unique training effect associated with soccer. This in turn can lead to muscular imbalance which is generally regarded as an injury risk factor.     

Nonlinear control techniques for an atomic force microscope system

Two nonlinear control techniques are proposed for an atomic force microscope system. Initially, a learning-based control algorithm is developed for the microcantilever-sample system that achieves asymptotic cantilever tip tracking for periodic trajectories. Specifically, the control approach utilizes a learning-based feedforward term to compensate for periodic dynamics and high-gain terms to account for non-periodic dynamics. An adaptive control algorithm is then developed to achieve asymptotic cantilever tip tracking for bounded tip trajectories despite uncertainty throughout the system parameters. Simulation results are provided to illttstrate the efficacy and performance of the control strategies.     

Adaptive multi‐scale analysis for point‐based surface editing

This paper presents a tool that enables the direct editing of surface features in large point‐clouds or meshes. This is made possible by a novel multi‐scale analysis of unstructured point‐clouds that automatically extracts the number of relevant features together with their respective scale all over the surface. Then, combining this ingredient with an adequate multi‐scale decomposition allows us to directly enhance or reduce each feature in an independent manner. Our feature extraction is based on the analysis of the scale‐variations of locally fitted surface primitives combined with unsupervised learning techniques. Our tool may be applied either globally or locally, and millions of points are handled in real‐time. The resulting system enables users to accurately edit complex geometries with minimal interaction.     

Dynamic modeling and CPG-based trajectory generation for a masticatory rehab robot

Human mastication is a complex and rhythmic biomechanical process which is regulated by a brain stem central pattern generator (CPG). Masticatory patterns, frequency and amplitude of mastication are different from person to person and significantly depend on food properties. The central nervous system controls the activity of muscles to produce smooth transitions between different movements. Therefore, to rehab human mandibular system, there is a real need to use the concept of CPG for development of a new methodology in jaw exercises and to help jaw movements recovery. This paper proposes a novel method for real-time trajectory generation of a mastication rehab robot. The proposed method combines several methods and concepts including kinematics, dynamics, trajectory generation and CPG. The purpose of this article is to provide a methodology to enable physiotherapists to perform the human jaw rehabilitation. In this paper, the robotic setup includes two Gough–Stewart platforms. The first platform is used as the rehab robot, while the second one is used to model the human jaw system. Once the modeling is completed, the second robot will be replaced by an actual patient for the selected physiotherapy. Gibbs–Appell’s formulation is used to obtain the dynamics equations of the rehab robot. Then, a method based on the Fourier series is employed to tune parameters of the CPG. It is shown that changes in leg lengths, due to the online changes of the mastication parameters, occur in a smooth and continuous manner. The key feature of the proposed method, when applied to human mastication, is its ability to adapt to the environment and change the chewing pattern in real-time parameters, such as amplitudes as well as jaw movements velocity during mastication.     

Three empirical evaluations of a software reuse reference model

The contribution of this paper is three empirical evaluations of a reference model for the practice of software reuse. Our research thesis is that software development based upon a software reuse reference model improves quality of products, productivity of processes and product time‐to‐market for many software development enterprises. The definition and investigation of such a model has been carried out using three steps. First, the reference model is developed based on existing software reuse concepts. Second, this reference model is empirically evaluated using three studies: one using a survey method, one using a case studies method, and one using a legacy studies method. Third, the impact of the reference model on software development productivity, quality, and time‐to‐market is empirically derived. This revised version was published online in June 2006 with corrections to the Cover Date.     

Enhancing encoding capacity of combinational test stimulus decompressors

While scan-based compression is widely utilized in order to alleviate the test time and data volume problems,the overall compression level is dictated not only by the chain to channel ratio but also the ratio of encodable patterns.Aggressively increasing the number of scan chains in an effort to raise the compression levels may reduce the ratio of encodable patterns,degrading the overall compression level.In this paper,we present various methods to improve the ratio of encodable patterns.These methods are b...     

A semi-parametric generalization of the Cox proportional hazards regression model: Inference and Applications

The assumption of proportional hazards (PH) fundamental to the Cox PH model sometimes may not hold in practice. In this paper, we propose a generalization of the Cox PH model in terms of the cumulative hazard function taking a form similar to the Cox PH model, with the extension that the baseline cumulative hazard function is raised to a power function. Our model allows for interaction between covariates and the baseline hazard and it also includes, for the two sample problem, the case of two Weibull distributions and two extreme value distributions differing in both scale and shape parameters. The partial likelihood approach can not be applied here to estimate the model parameters. We use the full likelihood approach via a cubic B-spline approximation for the baseline hazard to estimate the model parameters. A semi-automatic procedure for knot selection based on Akaike’s information criterion is developed. We illustrate the applicability of our approach using real-life data.     

A Model for Locating Park-and-Ride Facilities on Urban Networks Based on Maximizing Flow Capture: A Case Study of Isfahan, Iran

Traffic congestion is one of the main problems in large cities for which several approaches have been proposed. Park-and-ride is one of the best approaches that can remove traffic from the traffic network. Park-and-ride facilities are an important part of urban mass transit systems, effectively extending the service area and attracting commuters and other people who may not otherwise have used mass transit. However, its efficiency depends on its location in the urban network. In this research, we focus on travel time of shortest paths instead of the distance criterion for computing network traffic and develop a model for finding the best location(s) for siting park-and-ride systems so as to minimize the network traffic. The model is formulated based on population points, potential sites for park-and-ride establishment, and several Central Business District (CBDs). Then we present a Genetic algorithm that has been proved to be efficient in solving large size problems. Finally, the proposed model is used to locate park-and-ride facilities in the city of Isfahan, Iran.     

Context-aware saliency detection for image retargeting using convolutional neural networks

Multimedia Tools and Applications - Image retargeting is the task of making images capable of being displayed on screens with different sizes. This work should be done so that high-level visual...