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The worldwide population is undergoing a fundamental change in its age structure, which challenges the health- and social-services system. The need to migrate towards a more person-centered and coordinated model of care that supports the optimization of abilities and capacities for older people has to be matched. In this sense, eHealth technologies can play a fundamental role. In this paper, through a questionnaire-based data collection using 30 primary (older people) and 32 secondary (informal caregivers) end-users, we share our vision on how to sustainably develop a product by optimizing the user experience and ensuring adoption. We hypothesized that a technology-based intervention can promote healthy ageing through informed and active user involvement at all stages of the care process. Both older adults and caregivers consider the use of a smartphone and smartwatch to be very important; in addition, the use of digital devices for healthcare can be helpful. Seniors care about self-monitoring health parameters through the use of wearable devices, regardless of their health status, and would like to be included in the process of making good health decisions, because they need to feel in control of their healthcare process. Digital solutions in health and care can support the well-being of older adults in many areas of their daily lives, both at home and in their communities, but only if such innovation is designed around the natural voice of the intended target.

The aim of this work is to highlight the influence of blends based on TiO2 nanoparticles and reduced graphene oxide (RGO) on the photodegradation of acetaminophen (AC). To this end, the catalysts of TiO2/RGO blends with RGO sheet concentrations equal 5, 10, and 20 wt. % were prepared by the solid-state interaction of the two constituents. The preferential adsorption of TiO2 particles onto the RGO sheets’ surfaces via the water molecules on the TiO2 particle surface was demonstrated by FTIR spectroscopy. This adsorption process induced an increase in the disordered state of the RGO sheets in the presence of the TiO2 particles, as highlighted by Raman scattering and scanning electron microscopy (SEM). The novelty of this work lies in the demonstration that TiO2/RGO mixtures, obtained by the solid-phase interaction of the two constituents, allow an acetaminophen removal of up to 95.18% after 100 min of UV irradiation. This TiO2/RGO catalyst induced a higher photodegradation efficiency of AC than TiO2 due to the presence of RGO sheets, which acted as a capture agent for the photogenerated electrons of TiO2, hindering the electron–hole recombination. The reaction kinetics of AC aqueous solutions containing TiO2/RGO blends followed a complex first-order kinetic model. Another novelty of this work is the demonstration of the ability of PVC membranes modified with Au nanoparticles to act both as filters for the removal of TiO2/RGO blends after AC photodegradation and as potential SERS supports, which illustrate the vibrational properties of the reused catalyst. The reuse of the TiO2/RGO blends after the first cycle of AC photodegradation indicated their suitable stability during the five cycles of pharmaceutical compound photodegradation.

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In this work, synthesis and optical properties of a new composite based on poly(o-phenylenediamine) (POPD) fiber like structures, poly(vinylidene fluoride) (PVDF) spheres and double-walled carbon nanotubes (DWNTs) are reported. As increasing the PVDF weight in the mixture of the chemical polymerization reaction of o-phenylenediamine, the presence of the PVDF spheres onto the POPD fibers surface is highlighted by scanning electron microscopy (SEM). The down-shift of the Raman line from 1421 cm−1 to 1415 cm−1 proves the covalent functionalization of DWNTs with the POPD-PVDF blends. The changes in the absorbance of the IR bands peaked around 840, 881, 1240 and 1402 cm−1 indicate hindrance steric effects induced of DWNTs to the POPD fiber like structures and the PVDF spheres, as a consequence of the functionalization process of carbon nanotubes with macromolecular compounds. The presence of the PVDF spheres onto the POPD fiber like structures surface induces a POPD photoluminescence (PL) quenching process. An additional PL quenching process of the POPD-PVDF blends is reported to be induced in the presence of DWNTs. The studies of anisotropic PL highlight a change of the angle of the binding of the PVDF spheres onto the POPD fiber like structures surface from 50.2° to 38° when the carbon nanotubes concentration increases in the POPD-PVDF/DWNTs composites mass up to 2 wt.%.

The paper proposes a method for human robot interaction through gestures. Even if there are different methods that perform gesture recognition, many of them are tested in ideal conditions. This paper proposes a convolutional neural network that is used for gesture recognition applied for human-robot interaction in different environmental conditions: such as: blurring, low or high illumination, low quality image or losing part of frames. We started from a pre-trained ResNeXt 101 model and we increased the accuracy by adding a preprocessing stage for improving the quality of image, applying data augmentation, using different optimisers and learning rate scheduler. The proposed model obtained an improvement of 0.9% compared to the baseline model. Online evaluation of gesture recognition was performed using the Turtlebot robot.

Sleep represents a main factor for a healthy lifestyle. It improves health and quality of life in many ways: 1) it is vital for physical health; 2) it is essential for mental health; 3) improves memory and focus and 4) promotes personal and public safety. Sleep is a basic biological function that undergoes changes along with ageing and many pathological conditions. Some changes due to age are so deep that it is hard to distinguish between ageing and disease. Each person is different, considering the activities they perform that influence the sleep during the night, but also their metabolism, age etc. Different methods are therefore needed to explain the variation in sleep patterns for many people. Also, physical activity and sleep are highly interrelated health behaviours. The physical activity during the day influences the quality of sleep, and vice versa. The purpose of this paper is to present a system for creating a user profile based on his sleep behaviour. Based on the learnt profile, the system will automatically detect changes in the user's sleep pattern. If there are changes, the system will automatically check other medical parameters: heart rate, respiratory rate, physical activity during day (eg. number of steps, number of stairs). In case of existing abnormal values, an alarm message will be sent to the user with some suggestions regarding his daily programme. Data analysed is collected using two sensors: Emfit QS sensor for sleep monitoring and Fitbit for physical activity monitoring. In case of sleep, different machine learning methods were applied through pairs of sleep parameters (eg duration in rem versus total sleep duration, duration in light versus total sleep duration, duration awake versus total sleep duration, activity versus toss and turns count) in order to learn the profile of the user. The learning method is based on regression models. The regression is performed on a variable number of days in order to find a model that will learn the data set. For each number of days used for training, the model score will be calculated on the following days, and in the end, the model that has managed to obtain the highest score will be chosen. The models used are simple linear regression, polynomial regression, regression trees and regression support vectors. The models were evaluated on data collected from three users. The data sets used for the evaluation of each user was collected over a period of six months. The following models have proven to be common to all users: the model that learns the correlation between the variation of sleep duration in the light stage versus the total sleep duration. Thus, the proposed system will be able to generate alerts or recommendations using his sleep pattern. In case of differences between his history, the user will receive information that will help him to correct his lifestyle. Through the learning profile of the user, the system will proactive supervise him, making possible to reduce the possibility of illness.

Introduction Recent statistics show an increase in the prevalence of the elderly population. The year 2012 was declared European Year for Active Ageing and Solidarity between Generations, and the European Commission launched campaigns like The Active and Assisted Living Joint Program (AAL JP). Rehabilitation in the elderly is a desideratum, but the problems of rehabilitation in the elderly are numerous. The aim of the study was to evaluate degree of acceptance/implementation of different technologies in Romania, of monitoring in the rehabilitation activity conducted at home. Material and methods the study comprised 154 persons with a mean age of 73.37 ± 7.33 years, of which 64 (41.6%) male and 90 (58.4%) female. All subjects completed a questionnaire regarding the living conditions and health status, about the degree of acceptance of intelligent technologies for monitoring current health status/reporting acute events. Results 18.2% used the Internet frequently, and the rest used it almost never or rarely. 71.9 % of patients agreed to wear a portable sensor (p=0.07 between men and women), 33.1% accepted videocam, 47.4% accepted a screen, 41.3% accepted living room monitoring, 68% sensor in the room on the wall and 69.1% accepted fall detection sensor. No significant differences were found regarding the acceptance vs rejection of personal sensors, living room monitoring, sensors in the room, fall detection sensors depending on the gender, income level, type of caregiving. Using of videocam and screen was influenced by type of care giving and income (p=0.002, p

Electronic coupling between adjacent molecules is one of the key parameters determining the charge transfer (CT) rates in bulk heterojunction (BHJ) polymer solar cells (PSCs). We calculate theoretically electronic couplings for exciton dissociation (ED) and charge recombination (CR) processes at local poly(thiophene-co-quinoxaline) (TQ)-PC71BM interfaces. We use eigenstate-based coupling schemes, i.e. the generalized Mulliken-Hush (GMH) and fragment charge difference (FCD) schemes, including 2 to multiple (3-11) states. Moreover, we study the effects of functionals, excited state methods, basis sets, surrounding media, and relative placements of TQ and PC71BM on the coupling values. Generally, both schemes provide consistent couplings with the global hybrid functionals, which yield more charge-localized diabatic states and constant coupling values regardless of the number of states, and so the 2-state schemes may be sufficient. The (non-tuned and optimally tuned) long-range corrected (LRC) functionals result in more notable mixing of the local components with the CT states. Employing multiple states reduces the mixing and thus improves the LRC results, although the method still affects the GMH CR couplings. As the FCD scheme is less sensitive, we recommend combining it with the multi-state treatment for polymer-fullerene systems when using the LRC functionals. Finally, we employ the 11-state FCD couplings to calculate the ED and CR rates, which are consistent with the experimental rates of the polymer-fullerene systems. Our results provide more insight into choosing a suitable eigenstate-based coupling scheme for predicting the electronic couplings and CT rates in photoactive systems.

Electronic coupling between adjacent molecules is one of the key parameters determining the charge transfer (CT) rates in bulk heterojunction (BHJ) polymer solar cells (PSCs). We calculate theoretically electronic couplings for exciton dissociation (ED) and charge recombination (CR) processes at local poly(thiophene-co-quinoxaline) (TQ)-PC71BM interfaces. We use eigenstate-based coupling schemes, i.e. the generalized Mulliken-Hush (GMH) and fragment charge difference (FCD) schemes, including 2 to multiple (3-11) states. Moreover, we study the effects of functionals, excited state methods, basis sets, surrounding media, and relative placements of TQ and PC71BM on the coupling values. Generally, both schemes provide consistent couplings with the global hybrid functionals, which yield more charge-localized diabatic states and constant coupling values regardless of the number of states, and so the 2-state schemes may be sufficient. The (non-tuned and optimally tuned) long-range corrected (LRC) functionals result in more notable mixing of the local components with the CT states. Employing multiple states reduces the mixing and thus improves the LRC results, although the method still affects the GMH CR couplings. As the FCD scheme is less sensitive, we recommend combining it with the multi-state treatment for polymer-fullerene systems when using the LRC functionals. Finally, we employ the 11-state FCD couplings to calculate the ED and CR rates, which are consistent with the experimental rates of the polymer-fullerene systems. Our results provide more insight into choosing a suitable eigenstate-based coupling scheme for predicting the electronic couplings and CT rates in photoactive systems. Funding Agencies|Academy of FinlandAcademy of Finland [251823, 298182, 310489]; Graduate School of Tampere University of Technology (TUT); Finnish Cultural FoundationFinnish Cultural Foundation; Faculty of Engineering and Natural Sciences of Tampere University; Swedish e-Science Research Center (SeRC)

In this paper, we present the outcomes and conclusions obtained by involving seniors from three countries (Denmark, Poland and Romania) in an innovative project funded under the European Ambient As ...