Real-time gait assessment utilizing a new way of accelerometry

Real-time registration of body segment angles is essential in artificial body position control. A new method is presented for the real-time calculation of the lower extremity angles using data obtained from pairs of two one-dimensional accelerometers. It is shown that, assuming rigid-body dynamics and simple hinge joints, relative angles (i.e. angles between segments) can be calculated without integration, thereby solving the problem of integration drift normally associated with accelerometry. During the stance phase of walking, the relative angles can be transformed to absolute angles (i.e. relative to the gravitational field direction) for the different leg segments. The feasibility of relative angle calculation is demonstrated by calculation of the knee angle of a healthy subject. Stability and resolution were demonstrated with measurements during standing. Measurements during standing up, sitting down and walking showed that shock (heel-strike) and skin movements, due to movements of the underlying muscle tissue, are the main error sources. Additional signal processing, e.g. low-pass filtering, can be used to diminish this error. The accuracy of the knee angle found is shown to be high enough to be used in a feedback controller for functional electrostimulation of the lower extremities

Semantics-driven event clustering in Twitter feeds

Detecting events using social media such as Twitter has many useful applications in real-life situations. Many algorithms which all use different information sources - either textual, temporal, geographic or community features - have been developed to achieve this task. Semantic information is often added at the end of the event detection to classify events into semantic topics. But semantic information can also be used to drive the actual event detection, which is less covered by academic research. We therefore supplemented an existing baseline event clustering algorithm with semantic information about the tweets in order to improve its performance. This paper lays out the details of the semantics-driven event clustering algorithms developed, discusses a novel method to aid in the creation of a ground truth for event detection purposes, and analyses how well the algorithms improve over baseline. We find that assigning semantic information to every individual tweet results in just a worse performance in F1 measure compared to baseline. If however semantics are assigned on a coarser, hashtag level the improvement over baseline is substantial and significant in both precision and recall

Mass transfer and thermodynamics during immersion precipitation for a two-polymer system: Evaluation with the system PES-PVP-NMP-water

An extended version of the mass transfer model by Reuvers et al. for a four-component system is evaluated, which is shown to be generally valid for short times. The thermodynamics under these circumstances are evaluated, together with the kinetics. Initial composition paths (concentration profiles) are calculated. It appears that delay of demixing is not possible when a polymeric additive is used, which is soluble in the nonsolvent, while the velocity of demixing decreases. The calculations are evaluated for the system poly(ether sulfone)-poly(vinylpyrrolidone)-N-methylpyrrolidone-water by means of light transmission measurements during immersion precipitation, for a wide range of compositions of the polymer solution and coagulation bath

Control vector parameterization with sensitivity based refinement applied to baking optimization

In bakery production, product quality attributes as crispness, brownness, crumb and water content are developed by the transformations that occur during baking and which are initiated by heating. A quality driven procedure requires process optimization to improve bakery production and to find operational procedures for new products. Control vector parameterization (CVP) is an effective method for the optimization procedure. However, for accurate optimization with a large number of parameters CVP optimization takes a long computation time. In this work, an improved method for direct dynamic optimization using CVP is presented. The method uses a sensitivity based step size refinement for the selection of control input parameters. The optimization starts with a coarse discretization level for the control input in time. In successive iterations the step size was refined for the parameters for which the performance index has a sensitivity value above a threshold value.With this selection, optimization is continued for a selected group of input parameters while the other nonsensitive parameters (below threshold) are kept constant. Increasing the threshold value lowers the computation time, however the obtained performance index becomes less. A threshold value in the range of 10–20% of the mean sensitivity satisfies well. The method gives a better solution for a lower computation effort than single run optimization with a large number of parameters or refinement procedures without selection

Linearized cloudpoint curve correlation for ternary systems consisting of one polymer, one solvent and one non-solvent

A linear correlation function is found for cloudpoint composition curves of ternary systems consisting of one polymer, one solvent and one non-solvent. The conditions for validity of this correlation function appear to be that the polymer is strongly incompatible with the non-solvent, and that only liquid-liquid demixing occurs. The linearized cloudpoint (LCP) curve is interpreted in terms of the various parameters occurring in the Flory-Huggins theory. The slope of the LCP line appears to be only dependent on the molar volumes of the components. Information about the binary Flory-Huggins interaction parameters and their concentration dependence can be obtained from the intercept of the linearized curve. Cloudpoints induced by crystallization do not follow the correlation. This gives an opportunity to distinguish between crystallization and liquid-liquid demixing without any additional experiments

Skeletal muscle composition in various breeds of domestic dogs: (A comparative study)

The rising rate of insulin resistance and type 2 diabetes in humans over the past two decades have been linked to increasing rates of obesity, aging and urbanisation. A similar pattern is occurring in domestic animals, specifically cats and dogs. Skeletal muscle is a vital organ in the regulation of blood glucose. Its composition in terms of muscle fibre type, metabolism and contractility can differ substantially between species, but is poorly studied in the domestic dog, in particular the various breeds. It was hypothesised that insulin resistance and type 2 diabetes may be associated with muscle fibre type, in particular, muscle with a low type I fibre content being a predisposing factor. Therefore, the aims of this study were to investigate the skeletal muscle fibre composition and metabolic profile in the Triceps brachii (TB) and Vastus lateralis (VL) of 16 breeds of domestic dogs (Canis lupus familiaris). A secondary aim was to correlate the skeletal muscle composition with breeds reported as having a high incidence of diabetes. Skeletal muscle samples were collected post mortem from the TB and VL of 38 dogs from different breeds, age and sex, and analysed for fibre type composition, fibre size, oxidative and glycolytic metabolic capacity (citrate synthase (CS), 3-hydroxyacetyl co A dehydrogenase (3-HAD), creatine kinase (CK) and lactate dehydrogenase (LDH) enzyme activities). There was no significant difference between the TB and VL in any of the measurements. Type IIA was the predominant fibre type for both muscle groups (TB: 43%; VL: 44%) followed by type I (TB: 33%; VL: 38%) and type IIX (TB: 24%; VL: 18%). The cross sectional area (CSA) of the fibres were all smaller compared to humans and other wild animals. Surprisingly, there was no difference in the CSA between the fibres types and muscle groups: Type I: TB: 1740 µm2 ; VL: 1712 µm2 , Type IIA: TB: 1690 µm2 ; VL: 1720 µm2 , Type IIX TB: 1726 µm2 ; VL: 1791 µm2 ). Metabolically, the muscle of the dog displayed a high oxidative capacity with high activities (all activities in µmol/min/g protein) for CS (TB: 61; VL: 49) and 3-HAD (TB: 53; VL: 46). Lower CK (TB: 6115; VL: 6279) and higher LDH (TB: 1550; VL: 1478) activities than humans indicated a lower and higher flux through the high energy phosphate and glycolytic pathway, respectively. These results indicate that the dog has a predominance of type IIA fibres along with a higher oxidative capacity. There appears to be no pattern in fibre type profile that could be associated with a predisposition of a specific breed to insulin resistance and diabetes, although many of the breeds with a known risk did not form part of the study sample. This is the first study to characterise the skeletal muscle composition of a large population of dogs (16 breeds), but the association of breed to diabetes was not found. Future studies should include younger and more animals, as well as a diabetic population of dogs

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Microstructures in phase inversion membranes. Part II. The role of a polymeric additive

Membranes were prepared from a casting solution of a water-soluble polymer, poly (vinyl pyrrolidone) (PVP), and a membrane forming polymer, poly (ether sulfone), in 1-methyl-2-pyrrolidone (NMP) as solvent by immersing them in mixtures of water and NMP. It was found that the addition of PVP to the ternary system suppresses the formation of macrovoids in the sub-layer, while the ultrafiltration-type top-layer consists of a closely packed layer of nodules. Using a model for pass transfer in this quaternary system, it is possible to explain the effects of the additive on macrovoid formation. Strong indications are found that the appearance of a nodular structure in the top-layer follows a mechanism of spinodal decomposition during the very early stages of the immersion step