Rehabilitation of soft tissue injuries of the hip and pelvis

Soft tissue injuries of the hip and pelvis are common among athletes and can result in significant time loss from sports participation. Rehabilitation of athletes with injuries such as adductor strain, iliopsoas syndrome, and gluteal tendinopathy starts with identification of known risk factors for injury and comprehensive evaluation of the entire kinetic chain. Complex anatomy and overlapping pathologies often make it difficult to determine the primary cause of the pain and dysfunction. The purpose of this clinical commentary is to present an impairment-based, stepwise progression in evaluation and treatment of several common soft tissue injuries of the hip and pelvis. LEVEL OF EVIDENCE: 5

Robust multi-fidelity design of a micro re-entry unmanned space vehicle

This article addresses the preliminary robust design of a small-scale re-entry unmanned space vehicle by means of a hybrid optimization technique. The approach, developed in this article, closely couples an evolutionary multi-objective algorithm with a direct transcription method for optimal control problems. The evolutionary part handles the shape parameters of the vehicle and the uncertain objective functions, while the direct transcription method generates an optimal control profile for the re-entry trajectory. Uncertainties on the aerodynamic forces and characteristics of the thermal protection material are incorporated into the vehicle model, and a Monte-Carlo sampling procedure is used to compute relevant statistical characteristics of the maximum heat flux and internal temperature. Then, the hybrid algorithm searches for geometries that minimize the mean value of the maximum heat flux, the mean value of the maximum internal temperature, and the weighted sum of their variance: the evolutionary part handles the shape parameters of the vehicle and the uncertain functions, while the direct transcription method generates the optimal control profile for the re-entry trajectory of each individual of the population. During the optimization process, artificial neural networks are utilized to approximate the aerodynamic forces required by the optimal control solver. The artificial neural networks are trained and updated by means of a multi-fidelity approach: initially a low-fidelity analytical model, fitted on a waverider type of vehicle, is used to train the neural networks, and through the evolution a mix of analytical and computational fluid dynamic, high-fidelity computations are used to update it. The data obtained by the high-fidelity model progressively become the main source of updates for the neural networks till, near the end of the optimization process, the influence of the data obtained by the analytical model is practically nullified. On the basis of preliminary results, the adopted technique is able to predict achievable performance of the small spacecraft and the requirements in terms of thermal protection materials

Hemangioma related to Maffucci syndrome in a man: a case report

<p>Abstract</p> <p>Introduction</p> <p>Maffucci syndrome is a rare clinical entity (approximately 200 cases have been reported in the medical literature) with a combined occurrence of multiple enchondromas and vascular tumors.</p> <p>Case presentation</p> <p>The case of a 43-year-old Japanese man with multiple chondromas and hemangiomas (Maffucci syndrome) is reported. One of the hemangiomas was removed and examined pathologically. The morphological picture was an admixture of cavernous hemangioma and spindle cell hemangioma without cytological atypia or mitosis. Sheets of vacuolated endothelial cells were also observed.</p> <p>Conclusion</p> <p>A rare case of hemangioma associated with Maffucci syndrome, focusing on the pathologic nature of the submitted tissue, is reported.</p

Improving music genre classification using automatically induced harmony rules

We present a new genre classification framework using both low-level signal-based features and high-level harmony features. A state-of-the-art statistical genre classifier based on timbral features is extended using a first-order random forest containing for each genre rules derived from harmony or chord sequences. This random forest has been automatically induced, using the first-order logic induction algorithm TILDE, from a dataset, in which for each chord the degree and chord category are identified, and covering classical, jazz and pop genre classes. The audio descriptor-based genre classifier contains 206 features, covering spectral, temporal, energy, and pitch characteristics of the audio signal. The fusion of the harmony-based classifier with the extracted feature vectors is tested on three-genre subsets of the GTZAN and ISMIR04 datasets, which contain 300 and 448 recordings, respectively. Machine learning classifiers were tested using 5 × 5-fold cross-validation and feature selection. Results indicate that the proposed harmony-based rules combined with the timbral descriptor-based genre classification system lead to improved genre classification rates

Using Mixture Covariance Matrices to Improve Face and Facial Expression Recognitions

Abstract. In several pattern recognition problems, particularly in image recognition ones, there are often a large number of features available, but the number of training examples for each pattern is significantly less than the dimension of the feature space. This statement implies that the sample group covariance matrices often used in the Gaussian maximum probability classifier are singular. A common solution to this problem is to assume that all groups have equal covariance matrices and to use as their estimates the pooled covariance matrix calculated from the whole training set. This paper uses an alternative estimate for the sample group covariance matrices, here called the mixture covariance, given by an appropriate linear combination of the sample group and pooled covariance matrices. Experiments were carried out to evaluate the performance associated with this estimate in two biometric applications: face and facial expression. The average recognition rates obtained by using the mixture covariance matrices were higher than the usual estimates

Clustering data by inhomogeneous chaotic map lattices

A new approach to clustering, based on the physical properties of inhomogeneous coupled chaotic maps, is presented. A chaotic map is assigned to each data-point and short range couplings are introduced. The stationary regime of the system corresponds to a macroscopic attractor independent of the initial conditions. The mutual information between couples of maps serves to partition the data set in clusters, without prior assumptions about the structure of the underlying distribution of the data. Experiments on simulated and real data sets show the effectiveness of the proposed algorithm.Comment: 8 pages, 6 figures. Revised version accepted for publication on Physical Review Letter

Disorder Induced Ferromagnetism in CaRuO3

The magnetic ground state of perovskite structure CaRuO3 has been enigmatic for decades. Here we show that paramagnetic CaRuO3 can be made ferromagnetic by very small amounts of partial substitution of Ru by Ti. Magnetic hysteresis loops are observed at 5 K for as little as 2% Ti substitution. Ti is non-magnetic and isovalent with Ru, indicating that the primary effect of the substitution is the disruption of the magnetic ground state of CaRuO3 through disorder. The data suggest that CaRuO3 is poised at a critical point between ferromagnetic and paramagnetic ground states

Pentaquark baryons in SU(3) quark model

We study the SU(3) group structure of pentaquark baryons which are made of four quarks and one antiquark. The pentaquark baryons form {1}, {8}, {10}, {10}-bar, {27}, and {35} multiplets in SU(3) quark model. First, the flavor wave functions of all the pentaquark baryons are constructed in SU(3) quark model and then the flavor SU(3) symmetry relations for the interactions of the pentaquarks with three-quark baryons and pentaquark baryons are obtained.Comment: REVTeX, 36 pages, 8 figures, references added, section for mass sum rules is added, to appear in Phys. Rev.