Forming norms: informing diagnosis and management in sports medicine

Clinicians aim to identify abnormalities, and distinguish harmful from harmless abnormalities. In sports medicine, measures of physical function such as strength, balance and joint flexibility are used as diagnostic tools to identify causes of pain and disability and monitor progression in response to an intervention. Comparing results from clinical measures against ‘normal’ values guides decision-making regarding health outcomes. Understanding ‘normal’ is therefore central to appropriate management of disease and disability. However, ‘normal’ is difficult to clarify and definitions are dependent on context. ‘Normal’ in the clinical setting is best understood as an appropriate state of physical function. Particularly as disease, pain and sickness are expected occurrences of being human, understanding ‘normal’ at each stage of the lifespan is essential to avoid the medicalisation of usual life processes. Clinicians use physical measures to assess physical function and identify disability. Accurate diagnosis hinges on access to ‘normal’ reference values for such measures. However our knowledge of ‘normal’ for many clinical measures in sports medicine is limited. Improved knowledge of normal physical function across the lifespan will assist greatly in the diagnosis and management of pain, disease and disability

Relating CP-violating decays to the neutron EDM

We use the present upper bound on the neutron electric dipole moment to give an estimate for the upper limit of the CP-violating couplings of the $\eta(\eta')$ meson to the neutron. Using this result, we derive constraints on the CP-violating two-pion decays of the $\eta(\eta')$. Our results are relevant for the running and planned GlueX and LHCb measurements of rare meson decays.Comment: NSTAR 2017 conference proceeding

Viral RNA at two stages of reovirus infection is required for the induction of necroptosis

Necroptosis, a regulated form of necrotic cell death, requires the activation of the RIP3 kinase. Here, we identify that infection of host cells with reovirus can result in necroptosis. We find that necroptosis requires sensing of the genomic RNA within incoming virus particles via cytoplasmic RNA sensors to produce type I interferon (IFN). While these events that occur prior to the de novo synthesis of viral RNA are required for the induction of necroptosis, they are not sufficient. The induction of necroptosis also requires late stages of reovirus infection. Specifically, efficient synthesis of double-stranded RNA (dsRNA) within infected cells is required for necroptosis. These data indicate that viral RNA interfaces with host components at two different stages of infection to induce necroptosis. This work provides new molecular details about events in the viral replication cycle that contribute to the induction of necroptosis following infection with an RNA virus. IMPORTANCE An appreciation of how cell death pathways are regulated following viral infection may reveal strategies to limit tissue destruction and prevent the onset of disease. Cell death following virus infection can occur by apoptosis or a regulated form of necrosis known as necroptosis. Apoptotic cells are typically disposed of without activating the immune system. In contrast, necroptotic cells alert the immune system, resulting in inflammation and tissue damage. While apoptosis following virus infection has been extensively investigated, how necroptosis is unleashed following virus infection is understood for only a small group of viruses. Here, using mammalian reovirus, we highlight the molecular mechanism by which infection with a dsRNA virus results in necroptosis

Experimental investigation of a transonic potential flow around a symmetric airfoil

Experimental flow investigations on smooth airfoils were done using numerical solutions for transonic airfoil streaming with shockless supersonic range. The experimental flow reproduced essential sections of the theoretically computed frictionless solution. Agreement is better in the expansion part of the of the flow than in the compression part. The flow was nearly stationary in the entire velocity range investigated

Undergraduate public health education: a workforce perspective

Objective: To describe the career paths of students who majored in public health at the undergraduate level and to assess the skills and knowledge these g raduates believed were most useful to them in the public health workforce. Method: A telephone survey was conducted of all graduates from Adelaide University\u27s Bachelor of Health Sciences degree from 1992-99 who had majored in public health (124 graduates). Results: The response rate to the graduate survey was 71 %. Using the definition of public health functions from the National Delphi Study on Public Health Functions to delineate the public health workforce, 59% of respondents were employed in public health. Graduates working in public health valued generic skills such as communication and collaboration more highly than more specific public health skills and knowledge areas. However, they also believed their undergraduate course would have been improved by a more practical orientation. Conclusions: A high proportion of graduates from this generalist degree who major in public health find employment in the public health workforce. They greatly value the generic skills associated with their undergraduate public health education and believe their entry into the workforce would have been further facilitated by stronger links between their academic program and the working environment of public health professionals. Implications: Studies of workforce training programs in public health must differentiate between the educational needs of undergraduate and postgraduate students. In particular, strategies need to be developed to provide stronger links between undergraduate students and the public health workforce

Simulation of Dimensionally Reduced SYM-Chern-Simons Theory

A supersymmetric formulation of a three-dimensional SYM-Chern-Simons theory using light-cone quantization is presented, and the supercharges are calculated in light-cone gauge. The theory is dimensionally reduced by requiring all fields to be independent of the transverse dimension. The result is a non-trivial two-dimensional supersymmetric theory with an adjoint scalar and an adjoint fermion. We perform a numerical simulation of this SYM-Chern-Simons theory in 1+1 dimensions using SDLCQ (Supersymmetric Discrete Light-Cone Quantization). We find that the character of the bound states of this theory is very different from previously considered two-dimensional supersymmetric gauge theories. The low-energy bound states of this theory are very ``QCD-like.'' The wave functions of some of the low mass states have a striking valence structure. We present the valence and sea parton structure functions of these states. In addition, we identify BPS-like states which are almost independent of the coupling. Their masses are proportional to their parton number in the large-coupling limit.Comment: 18pp. 7 figures, uses REVTe

Biosorption of arsenic and cadmium from aqueous solutions

The biosorption of cadmium and arsenic from aqueous solutions onto the unmodified compact biomass of microscopic filamentous fungus Aspergillus clavatus DESM. was studied in the concentrationrange of 0.25 – 100 mg.l-1. The experimental biosorption results for arsenic and cadmium followed well the Freundlich equilibrium sorption model

The L3Pilot Common Data Format - Enabling Efficient Automated Driving Data Analysis

Analyzing road-test data is important for developing automated vehicles. L3Pilot is a European pilot project on level 3 automation, including 34 partners among manufacturers, suppliers and research institutions. Targeting around 100 cars and 1000 test subjects, the project will generate large amounts of data. We present a data format, allowing efficient data collection, handling and analysis by multiple organizations. A project of the scope of L3Pilot involves various challenges. Data come from a multitude of heterogeneous sources and are processed by a variety of tools. Recorded data span all data types generated in various vehicular sensors/systems and are enriched with external data sources. Videos supplement time-series data as external files. Derived measures and performance indicators \u2013 required to answer research questions about effectiveness of automated driving \u2013 are processed by analysis partners and included for each test session. As a file format, we chose HDF5, which offers a data model and software libraries for storing and managing data. HDF5 is designed for flexible and efficient I/O and for high volume and complex data. The usage of different computing environments for specific tasks is facilitated by the portability that comes with the format. Portability is also important for exploiting the rising potential within artificial intelligence (e.g. automatic scene detection and video annotation). Based on lessons learned from past field tests, we defined a general frame for the common data format that is aligned with the data processing steps of FESTA \u201cV\u201d evaluation methodology. The definitions include representation of the source signals and a hierarchical structure for including multiple datasets that are gradually supplemented (post-processed or annotated) during the various analysis steps. By using the HDF5 format, analysis partners have the freedom to exploit their familiar tools: MATLAB, Java, Python, R, etc. First comparisons between time-series data in previous projects (e.g. AdaptIVe) and the proposed data format show a reduction in storage size of around 80 %, without losses in performance. Much of that is due to efficient internal compression and structuring of data. Considering the amount of objective data involved in automated driving, this leads to a great benefit, in terms of usability. This paper presents a compact, portable, and extensible format aimed at handling extremely large amounts of field test data collected in automated driving pilots. As a harmonized format between tens of organizations performing tests in the L3Pilot project, the proposed format has the potential to promote data sharing as well as development of common tools and gain popularity for use in other projects. The format is designed to allow efficient storing of data and its iterative processing with analysis and evaluation tools. The format also considers the requirements of AI tools supporting neural network training and use