DETERMINATION OF OPTIMAL FILTER PARAMETERS FOR FILTERING KINEMATIC WALKING DATA USING BUTTERWORTH LOW PASS FILTER

INTRODUCTION: Noise in biomechanical displacement data are often reduced by digital filter routines. In literature the cross-validated quintic spline from Woltring (1986) and the Butterworth low pass filter are commonly used. Challis (1999) recently suggested a method for determining the optimal cut-off frequency of Butterworth low pass filters. This method is based on a combination of residual analysis and autocorrelation. The optimization of the filter order, however, is not discussed by Challis. Thus the purpose of this study was to determine optimal filter parameters (frequency and order) of a Butterworth low-pass filter using the approach of Challis applied to a kinematic data set in walking

MEASURING DEVICE FOR ON-LINE CALCULATING AND SCREENING OF KNEE JOINT FORCES

INTRODUCTION: For calculating knee joint forces quasi-static and dynamic 2D knee models have been developed (Moeinzadeh et al., 1983, Nisell, 1985, Yamaguchi/ Zajac, 1989). From the preventive point of view the on-line calculation and screening of knee joint forces could give us important simultaneous feedback on the loads on the different structures during training and performance exercises in several sports. Based on these considerations an existing 2D knee model should be adapted for on-line calculating and screening of knee joint forces. METHODS: The purpose is to determine the kinematics of the knee joint as function of the knee angle. Therefore data from Yamaguchi/Zajac (1989), Nisell (1985) and ourselves were combined to the 2D model called 'Plakmos'. All relevant parameters needed for determining the kinematics of the knee were calculated for knee angles between 0° and 96° in steps of 2°. In a further procedure these data were calculated as polynomial functions of the knee angle up to order 10 using non-linear regression technique. These functions in combination with the direction, the magnitude and the point of application of the ground reaction force (GRF) are sufficient to obtain the main compression, shear and tendon forces. A special measuring device consisting of a force platform (for determining the direction, magnitude and application point of the GRF) and two goniometers (to obtain the ankle and knee angles) yields the input data for calculating the knee joint forces. The data collection and the calculation procedure is carried out using the measuring software Dasylab. RESULTS: The kinematics of Plakmos coincides with the knee models reported very closely, so the validity of the model is given with sufficient accuracy to investigate at least relative comparisons in different situations. The utility and simplicity of the measuring device including Plakmos has been demonstrated in comparative studies of knee bending with and without additional weights and different knee bending techniques. REFERENCES: Moeinzadeh, M., Engin, A., Akkas, N. (1983). Two-Dimensional Dynamic Modeling of Human Knee Joint. J. Biomechanics 16, 253-264. Nisell, R. (1985). Mechanics of the Knee. A. Orth. Scand, Suppl. 216, 56, 4-42. Yamaguchi, G., Zajac, F. (1989). A Planar Model of the Knee Joint to Characterize the Knee Extensor Mechanism. J. Biomechanics 22, 1-10

A study on shape-dependent settling of single particles with equal volume using surface resolved simulations

A detailed knowledge of the influence of a particle’s shape on its settling behavior is useful for the prediction and design of separation processes. Models in the available literature usually fit a given function to experimental data. In this work, a constructive and data-driven approach is presented to obtain new drag correlations. To date, the only considered shape parameters are derivatives of the axis lengths and the sphericity. This does not cover all relevant effects, since the process of settling for arbitrarily shaped particles is highly complex. This work extends the list of considered parameters by, e.g., convexity and roundness and evaluates the relevance of each. The aim is to find models describing the drag coefficient and settling velocity, based on this extended set of shape parameters. The data for the investigations are obtained by surface resolved simulations of superellipsoids, applying the homogenized lattice Boltzmann method. To closely study the influence of shape, the particles considered are equal in volume, and therefore cover a range of Reynolds numbers, limited to [9.64, 22.86]. Logistic and polynomial regressions are performed and the quality of the models is investigated with further statistical methods. In addition to the usually studied relation between drag coefficient and Reynolds number, the dependency of the terminal settling velocity on the shape parameters is also investigated. The found models are, with an adjusted coefficient of determination of 0.96 and 0.86, in good agreement with the data, yielding a mean deviation below 5.5% on the training and test dataset

Promoting the high-quality recycling of plastics from demolition waste and enhancing the use of recycled materials in construction products in accordance with the European plastics strategy : final report

This study presents in detail: the use of plastic products and the opportunities for recyclate use in the construction sector, quantities of plastic used, take-back systems, recycling techniques, current recyclate use and plastic construction product packaging.Potentials for increasing high-quality recyclate use were identified. Existing hurdles and options for action for industry and politics are presented. Current recyclate use as well as its potential use are strongly dependent on the application area of plastics. The biggest hurdles for the use of recycled materials are product life time, dismantling and technical requirements

Distributional regression for demand forecasting in e-grocery

Ulrich M, Jahnke H, Langrock R, Pesch R, Senge R. Distributional regression for demand forecasting in e-grocery. Universität Bielefeld Working Papers in Economics and Management. Vol 09-2018. Bielefeld: Bielefeld University, Department of Business Administration and Economics; 2019.E-grocery offers customers an alternative to traditional brick-and-mortar grocery retailing. Customers select e-grocery for convenience, making use of the home delivery at a selected time slot. In contrast to brick-and-mortar retailing, in e-grocery on-stock information for stock keeping units (SKUs) becomes transparent to the customer before substantial shopping effort has been invested, thus reducing the personal cost of switching to another supplier. As a consequence, compared to brick-and-mortar retailing, on-stock availability of SKUs has a strong impact on the customer’s order decision, resulting in higher strategic service level targets for the e-grocery retailer. To account for these high service level targets, we propose a suitable model for accurately predicting the extreme right tail of the demand distribution, rather than providing point forecasts of its mean. Specifically, we propose the application of distributional regression methods— so-called Generalised Additive Models for Location, Scale and Shape (GAMLSS)—to arrive at the cost-minimising solution according to the newsvendor model. As benchmark models we consider linear regression, quantile regression, and some popular methods from machine learning. The models are evaluated in a case study, where we compare their out-of-sample predictive performance with regard to the service level selected by the e-grocery retailer considered

TAPBPR bridges UDP-glucose : glycoprotein glucosyltransferase 1 onto MHC class I to provide quality control in the antigen presentation pathway

Funding Wellcome: Senior Research Fellowship 104647, Andreas Neerincx, Louise H Boyle Royal Society: University Research Fellowship, UF100371, Janet E Deane Cancer Research UK: Programme Grant, C7056A, Andy van Hateren, Tim Elliott Deutsche Forschungsgemeinschaft: SFB 685, Nico Trautwein, Stefan Stevanović Wellcome: PhD studentship, 089563, Clemens Hermann Wellcome: Strategic Award 100140, Robin Antrobus Wellcome: Programme grant, WT094847MA, Huan Cao Acknowledgements We are extremely grateful to Peter Cresswell and Najla Arshad (Yale University School of Medicine, New Haven, CT) for valuable advice, tapasin and TAP-specific antibody reagents, and the recombinant calreticulin proteins. We thank John Trowsdale (University of Cambridge, UK) for his mentorship and critical reading of this manuscript, and Jim Kaufman (University of Cambridge, UK) for useful discussions. We also thank Yi Cao (Cranfield University, UK) for MATLAB programming for densitometry analysis, and Mark Vickers and Sadie Henderson (Scottish National Blood Transfusion Services, UK) for permitting the use of and assistance with the Amersham WB system. The reagent ARP7099 FEC peptide pool was obtained from the Centre for AIDS Reagents, National Institute for Biological Standards and Control (NIBSC), and was donated by the NIH AIDS Reagent Program, Division of AIDS, NIAID, NIH.Peer reviewedPublisher PD

Impact of Engineered Nanomaterials on Health: Considerations for Benefit-Risk Assessment

Nanotechnology encompasses the design, characterisation, production and application of materials and systems by controlling shape and size at the nanoscale (nanometres). Nanomaterials may differ from other materials because of their relatively large specific surface area, such that surface properties become particularly important. There has been rapid growth in investment in nanotechnology by both the public and private sectors worldwide. In the EU, nanotechnology is expected to become an important strategic contributor to achieving economic gain and societal and individual benefits. At the same time there is continuing scientific uncertainty and controversy about the safety of nanomaterials. It is important to ensure that timely policy development takes this into consideration. Uncertainty about safety may lead to polarised public debate and to business unwillingness to invest further. A clear regulatory framework to address potential health and environmental impacts, within the wider context of evaluating and communicating the benefit-risk balance, must be a core part of Europe's integrated efforts for nanotechnology innovation. While a number of studies have been carried out on the effect of environmental nanoparticles, e.g. from combustion processes, on human health, there is yet no generally acceptable paradigm for safety assessment of nanomaterials in consumer and other products. Therefore, a working group was established to consider issues for the possible impact of nanomaterials on human health focussing specifically on engineered nanomaterials. This represents the first joint initiative between EASAC and the Joint Research Centre of the European Commission. The working group was given the remit to describe the state of the art of benefits and potential risks, current methods for safety assessment, and to evaluate their relevance, identify knowledge gaps in studying the safety of current nanomaterials, and recommend on priorities for nanomaterial research and the regulatory framework. This report focuses on key principles and issues, cross-referencing other sources for detailed information, rather than attempting a comprehensive account of the science. The focus is on human health although environmental effects are also discussed when directly relevant to healt