An experimental study on a motion sensing system for sports training

In sports science, motion data collected from athletes is used to derive key performance characteristics, such as stride length and stride frequency, that are vital coaching support information. The sensors for use must be more accurate, must capture more vigorous events, and have strict weight and size requirements, since they must not themselves affect performance. These requirements mean each wireless sensor device is necessarily resource poor and yet must be capable of communicating a considerable amount of data, contending for the bandwidth with other sensors on the body. This paper analyses the results of a set of network traffic experiments that were designed to investigate the suitability of conventional wireless motion sensing system design � which generally assumes in-network processing - as an efficient and scalable design for use in sports training

Compressing Inertial Motion Data in Wireless Sensing Systems – An Initial Experiment

The use of wireless inertial motion sensors, such as accelerometers, for supporting medical care and sport’s training, has been under investigation in recent years. As the number of sensors (or their sampling rates) increases, compressing data at source(s) (i.e. at the sensors), i.e. reducing the quantity of data that needs to be transmitted between the on-body sensors and the remote repository, would be essential especially in a bandwidth-limited wireless environment. This paper presents a set of compression experiment results on a set of inertial motion data collected during running exercises. As a starting point, we selected a set of common compression algorithms to experiment with. Our results show that, conventional lossy compression algorithms would achieve a desirable compression ratio with an acceptable time delay. The results also show that the quality of the decompressed data is within acceptable range

Classification of finite irreducible modules over the Lie conformal superalgebra CK6

We classify all continuous degenerate irreducible modules over the exceptional linearly compact Lie superalgebra E(1, 6), and all finite degenerate irreducible modules over the exceptional Lie conformal superalgebra CK6, for which E(1, 6) is the annihilation algebra

Haar expectations of ratios of random characteristic polynomials

We compute Haar ensemble averages of ratios of random characteristic polynomials for the classical Lie groups K = O(N), SO(N), and USp(N). To that end, we start from the Clifford-Weyl algebera in its canonical realization on the complex of holomorphic differential forms for a C-vector space V. From it we construct the Fock representation of an orthosymplectic Lie superalgebra osp associated to V. Particular attention is paid to defining Howe's oscillator semigroup and the representation that partially exponentiates the Lie algebra representation of sp in osp. In the process, by pushing the semigroup representation to its boundary and arguing by continuity, we provide a construction of the Shale-Weil-Segal representation of the metaplectic group. To deal with a product of n ratios of characteristic polynomials, we let V = C^n \otimes C^N where C^N is equipped with its standard K-representation, and focus on the subspace of K-equivariant forms. By Howe duality, this is a highest-weight irreducible representation of the centralizer g of Lie(K) in osp. We identify the K-Haar expectation of n ratios with the character of this g-representation, which we show to be uniquely determined by analyticity, Weyl group invariance, certain weight constraints and a system of differential equations coming from the Laplace-Casimir invariants of g. We find an explicit solution to the problem posed by all these conditions. In this way we prove that the said Haar expectations are expressed by a Weyl-type character formula for all integers N \ge 1. This completes earlier work by Conrey, Farmer, and Zirnbauer for the case of U(N).Comment: LaTeX, 70 pages, Complex Analysis and its Synergies (2016) 2:

Spectral dimensions of hierarchical scale-free networks with shortcuts

The spectral dimension has been widely used to understand transport properties on regular and fractal lattices. Nevertheless, it has been little studied for complex networks such as scale-free and small world networks. Here we study the spectral dimension and the return-to-origin probability of random walks on hierarchical scale-free networks, which can be either fractals or non-fractals depending on the weight of shortcuts. Applying the renormalization group (RG) approach to the Gaussian model, we obtain the spectral dimension exactly. While the spectral dimension varies between $1$ and $2$ for the fractal case, it remains at $2$, independent of the variation of network structure for the non-fractal case. The crossover behavior between the two cases is studied through the RG flow analysis. The analytic results are confirmed by simulation results and their implications for the architecture of complex systems are discussed.Comment: 10 pages, 3 figure

Combining Genome Wide Association Studies and Differential Gene Expression Data Analyses Identifies Candidate Genes Affecting Mastitis Caused by Two Different Pathogens in the Dairy Cow

Mastitis is a costly disease which hampers the dairy industry. Inflammation of the mammary gland is commonly caused by bacterial infection, mainly Escherichia coli, Streptococcus uberis and Staphylococcus aureus. As more bacteria become multi-drug resistant, one potential approach to reduce the disease incidence rate is to breed selectively for the most appropriate and potentially protective innate immune response. The genetic contribution to effective disease resistance is, however, difficult to identify due to the complex interactions that occur. In the present study two published datasets were searched for common differentially expressed genes (DEGs) with similar changes in expression in mammary tissue following intra-mammary challenge with either E. coli or S. uberis. Additionally, the results of seven published genome-wide association studies (GWAS) on different dairy cow populations were used to compile a list of SNPs associated with somatic cell count. All genes located within 2 Mbp of significant SNPs were retrieved from the Ensembl database, based on the UMD3.1 assembly. A final list of 48 candidate genes with a role in the innate immune response identified from both the DEG and GWAS studies was further analyzed using Ingenuity Pathway Analysis. The main signalling pathways highlighted in the response of the bovine mammary gland to both bacterial infections were 1) granulocyte adhesion and diapedesis, 2) ephrin receptor signalling, 3) RhoA signalling and 4) LPS/IL1 mediated inhibition of RXR function. These pathways comprised a network regulating the activity of leukocytes, especially neutrophils, during mammary gland inflammation. The timely and properly controlled movement of leukocytes to infection loci seems particularly important in achieving a good balance between pathogen elimination and excessive tissue damage. These results suggest that polymorphisms in key genes in these pathways such as SELP, SELL, BCAR1, ACTR3, CXCL2, CXCL6, CXCL8 and FABP may influence the ability of dairy cows to resist mastitis

Formation and kinetics of transient metastable states in mixtures under coupled phase ordering and chemical demixing

We present theory and simulation of simultaneous chemical demixing and phase ordering in a polymer-liquid crystal mixture in conditions where isotropic- isotropic phase separation is metastable with respect to isotropic-nematic phase transition. It is found that mesophase formation proceeds by a transient metastable phase that surround the ordered phase, and whose lifetime is a function of the ratio of diffusional to orientational mobilities. It is shown that kinetic phase ordering in polymer-mesogen mixtures is analogous to kinetic crystallization in polymer solutions.Comment: 17 pages, 5 figures accepted for publication in EP

Diverse Temporal Properties of GRB Afterglow

The detection of delayed X-ray, optical and radio emission, "afterglow", associated with $\gamma$-ray bursts (GRBs) is consistent with fireball models, where the emission are produced by relativistic expanding blast wave, driven by expanding fireball at cosmogical distances. The emission mechanisms of GRB afterglow have been discussed by many authors and synchrotron radiation is believed to be the main mechanism. The observations show that the optical light curves of two observed gamma-ray bursts, GRB970228 and GRB GRB970508, can be described by a simple power law, which seems to support the synchrotron radiation explanation. However, here we shall show that under some circumstances, the inverse Compton scattering (ICS) may play an important role in emission spectrum and this may influence the temporal properties of GRB afterglow. We expect that the light curves of GRB afterglow may consist of multi-components, which depends on the fireball parameters.Comment: Latex, no figures, minor correctio

Is GRO J1744-28 a Strange Star?

The unusal hard x-ray burster GRO J1744-28 recently discovered by the Compton Gamma-ray Observatory (GRO) can be modeled as a strange star with a dipolar magnetic field $\le 10^{11}$Gauss. When the accreted mass of the star exceeds some critical mass, its crust may break, resulting in conversion of the accreted matter into strange matter and release of energy. Subsequently, a fireball may form and expand relativistically outward. The expanding fireball may interact with the surrounding interstellar medium, causing its kinetic energy to be radiated in shock waves, producing a burst of x-ray radiation. The burst energy, duration, interval and spectrum derived from such a model are consistent with the observations of GRO J1744-28.Comment: Latex, has been published in SCIENCE, Vol. 280, 40