Adsorption of Cu, Ag, and Au atoms on graphene including van der Waals interactions

We performed a systematic density functional study of the adsorption of copper, silver, and gold adatoms on graphene, especially accounting for van der Waals interactions by the vdW-DF and the PBE+D2 methods. In particular, we analyze the preferred adsorption site (among top, bridge, and hollow positions) together with the corresponding distortion of the graphene sheet and identify diffusion paths. Both vdW schemes show that the coinage metal atoms do bind to the graphene sheet and that in some cases the buckling of the graphene can be significant. The results for silver are at variance with those obtained with GGA, which gives no binding in this case. However, we observe some quantitative differences between the vdW-DF and the PBE+D2 methods. For instance the adsorption energies calculated with the PBE+D2 method are systematically higher than the ones obtained with vdW-DF. Moreover, the equilibrium distances computed with PBE+D2 are shorter than those calculated with the vdW-DF method

Physico-chemical properties of extrudates and their relation to lipid incorporation and lipid oxidation

Extrusion cooking is a key technology in food processing used to produce a wide range of products and extrudates such as cereals, cornflakes and snacks. In addition, extrusion plays a central role in the production of animal food. The oxidation of lipids in extrudates is problematic as this is associated with considerable quality deteriorations. Most conspicuous is the rancid off-flavour. Lipids can interact differently with the matrix in an extrudate and be incorporated into the matrix to different degrees. The aim of this thesis is to understand the relationship between lipid oxidation and the structural properties of the extrudate and the interaction of lipids with the matrix in order to create a basis for reducing oxidation processes in extrudates. A fractionated lipid extraction was developed, which enabled the characterization and investigation of oxidation processes in different regions of an extrudate. Three fractions were obtained which can be assigned to surface lipids, lipids adsorbing on the inner lamellas of the extrudate and matrix-incorporated lipids. Matrix-incorporated lipids are finely dispersed in the amylose-amylopectin matrix and can only be extracted after an amylase treatment which causes a degradation of the starch matrix. It was shown that the water content of the extrusion mass influences the microstructure and the expansion. The higher the proportion of lipids incorporated in the matrix, the higher is the oxidative stability of the extrudate. Furthermore, the effects of a lipid-based coating on lipid oxidation in extrudates with different microstructures were investigated. Coating with MCT oil inhibited lipid oxidation in corn extrudates beyond the effects of dilution. This effect was particularly pronounced in porous extrudates, as it could be shown that the coating adheres mainly to the surface, migrates only slightly into the core and closes micro cracks. The formation of radicals in model systems and extrudates was investigated by electron paramagnetic resonance spectroscopy. The extrusion process formed stable protein radicals and lipid radical concentration increased simultaneously with the formation of hydroperoxides in the model system. In addition, it was demonstrated that the reaction rate of lipid oxidation is influenced by the matrix. However, the logarithmic plot of the reaction rate, based on the increase of hydroperoxide formation after the lag phase, led to an overestimation of lipid oxidation at room temperature and requires the application of more complex models. Within this thesis, different mechanisms and matrix effects could be identified that influence lipid oxidation during extrusion and storage. They provide a basis for the derivation of factors to increase the oxidative stability of extrudates

Evaluation of MS kinect for elderly meal intake monitoring

Any form of eating disorder is detrimental for health. Having an eating disorder increases the risks for chronic diseases and general morbidity, leading to several health problems such as obesity, hypertension and cardio-vascular diseases. The risk is greater for elderly people, as ageing submits the body to several functional changes that affect health and nutrition conditions. Automatic monitoring systems can help to prevent these risks by supporting people to maintain appropriate eating behaviours. Ageing services based on ICT assistive services are increasing as a result of the awareness of the growing socio-economic relevance of this issue, especially when we consider the rural and very sparsely-populated areas. In order to assess these requirements, systems should be automatic, non-intrusive and low cost. This paper presents an evaluation test of the Microsoft Kinect sensor for monitoring older people's meal intake, with the aim of contributing to the development of an automatic diet monitoring system.The authors thank the FEUP – Faculdade de Engenharia da Universidade do Porto through the Project I-City for Future Mobility: NORTE-07-0124-FEDER-000064, and European Project FP7 - Future Cities: FP7-REGPOT-2012-2013-1

Physical Activity Comparison Between Body Sides in Hemiparetic Patients Using Wearable Motion Sensors in Free-Living and Therapy: A Case Series

Background: Physical activity (PA) is essential in stroke rehabilitation of hemiparetic patients to avoid health risks, and moderate to vigorous PA could promote patients' recovery. However, PA assessments are limited to clinical environments. Little is known about PA in unguided free-living. Wearable sensors could reveal patients' PA during rehabilitation, and day-long long-term measurements over several weeks might reveal recovery trends of affected and less-affected body sides.Methods: We investigated PA in an observation study during outpatient rehabilitation in a day-care center. PA of affected and less-affected body sides, including upper and lower limbs were derived using wearable motion sensors. In this analysis we focused on PA during free-living and clinician guided therapies, and investigated differences between body-sides. Linear regressions were used to estimate metabolic equivalents for each limb at comparable scale. Non-parametric statistics were derived to quantify PA differences between body sides.Results: We analyzed 102 full-day movement data recordings from eleven hemiparetic patients during individual rehabilitation periods up to 79 days. The comparison between free-living and clinician guided therapy showed on average 16.1 % higher PA in the affected arm during therapy and 5.3 % higher PA in the affected leg during therapy. Average differences between free-living and therapy in the less-affected side were below 4.5 %.Conclusion: We analyzed PA of patients with a hemiparesis in two distinct rehabilitation settings, including free-living and clinician guided therapies over several weeks and compared MET values of affected and less-affected body sides. In particular, we investigated PA using individual regression models for each limb. We demonstrated that wearable motion sensors provide insights in patient's PA during rehabilitation. Although, no clear PA trends were found, our analysis showed patients' tendency to sedentary behavior, confirming previous lab study results. Our PA analysis approach could be used beyond clinical rehabilitation to devise personalized patient and limb-specific exercise recommendations in future remote rehabilitation

Estimating posture-recognition performance in sensing garments using geometric wrinkle modeling

A fundamental challenge limiting information quality obtained from smart sensing garments is the influence of textile movement relative to limbs. We present and validate a comprehensive modeling and simulation framework to predict recognition performance in casual loose-fitting garments. A statistical posture and wrinkle-modeling approach is introduced to simulate sensor orientation errors pertained to local garment wrinkles. A metric was derived to assess fitting, the body-garment mobility. We validated our approach by analyzing simulations of shoulder and elbow rehabilitation postures with respect to experimental data using actual casual garments. Results confirmed congruent performance trends with estimation errors below 4% for all study participants. Our approach allows to estimate the impact of fitting before implementing a garment and performing evaluation studies with it. These simulations revealed critical design parameters for garment prototyping, related to performed body posture, utilized sensing modalities, and garment fitting. We concluded that our modeling approach can substantially expedite design and development of smart garments through early-stage performance analysis

Collaborative personal speaker identification: A generalized approach

n/

Psychophysiological body activation characteristics in daily routines

We present a novel approach to analyse and model psychophysiological body activation patterns that emerge from physical and mental activity during daily routines. We analyse our approach on a 62h dataset of daily routine recordings using acceleration and heart rate sensors. We present a descriptive analysis of psychophysiological activations during the routines using a novel visualisation technique. Our results show that daily routines exhibit different psychophysiological body activation characteristics. While physically-related routines are correlated with heart activity, mentally-related routines show activation patterns without physical activity. © 2009 IEEE

Early indication of decompensated heart failure in patients on home-telemonitoring: a comparison of prediction algorithms based on daily weight and noninvasive transthoracic bio-impedance

Background: Heart Failure (HF) is a common reason for hospitalization. Admissions might be prevented by early detection of and intervention for decompensation. Conventionally, changes in weight, a possible measure of fluid accumulation, have been used to detect deterioration. Transthoracic impedance may be a more sensitive and accurate measure of fluid accumulation. Objective: In this study, we review previously proposed predictive algorithms using body weight and noninvasive transthoracic bio-impedance (NITTI) to predict HF decompensations. Methods: We monitored 91 patients with chronic HF for an average of 10 months using a weight scale and a wearable bio-impedance vest. Three algorithms were tested using either simple rule-of-thumb differences (RoT), moving averages (MACD), or cumulative sums (CUSUM). Results: Algorithms using NITTI in the 2 weeks preceding decompensation predicted events (P<.001); however, using weight alone did not. Cross-validation showed that NITTI improved sensitivity of all algorithms tested and that trend algorithms provided the best performance for either measurement (Weight-MACD: 33%, NITTI-CUSUM: 60%) in contrast to the simpler rules-of-thumb (Weight-RoT: 20%, NITTI-RoT: 33%) as proposed in HF guidelines. Conclusions: NITTI measurements decrease before decompensations, and combined with trend algorithms, improve the detection of HF decompensation over current guideline rules; however, many alerts are not associated with clinically overt decompensation