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[EN] The European Green Deal policy ambitions set out in the Chemicals Strategy for Sustainability and the Zero Pollution Action Plan identify the transition to a Safe and Sustainable by Design (SSbD) approach to chemicals and materials. The H2020 SUNSHINE project has developed an approach to operationalize SSbD, specifically addressing multi-component nanomaterials (MCNMs), and applied it to two case studies. This approach enables assessment of safety and sustainability aspects at each stage of product development from a lifecycle perspective. This is achieved via a tiered approach that uses qualitative (Tier 1), semi-quantitative (Tier 2) and quantitative (Tier 3) assessment methods. The present work focuses on the Tier 1 (self-assessment) methodology designed to evaluate the safety, functionality and sustainability in the early R&D stages of the lifecycle of chemicals and materials. This approach was developed to be implementable by industries in a straightforward manner as often there is lack of time and/or expertise to engage in resource-intensive safety and sustainability evaluations. The approach was tested using two real industrial case studies, namely nano-enabled PFAS (Polyfluoroalkyl substances)-free anti-sticking coating for bakery molds, and nano-drops of essential oil anchored to the surface of nano clays and encapsulated in a polymeric film. The results indicate that these innovative materials have a high probability to have better safety, functionality and sustainability performance compared to conventional benchmark materials.

The article evaluates the development of the Internet of Things (I₀T), digital technologies, various types of biological and biometric sensors and blockchain technologies in dairy and beef cattle breeding. The peculiarities, tendencies and perspectives for digital transformation and digitalization of the cattle farms and complexes have been studied. Precise technologies (PFL) make it possible to collect a sufficient cloud of data in accordance with the physiological and technological requirements of the various categories of animals of the species Bos taurus and the welfare of cattle. Biological and biometric sensors help farmers to increase the quantity and improve the quality of their products. Blockchain technologies present cattle breeding in detail, as transparent, stable and predictable in the eyes of the consumer. Cattle breeding is a sub-sector of animal husbandry in which there is no integration, but flexible digital management is applied.

Natural Capital Accounting (NCA) has evolved rapidly in recent years through substantial efforts of both international organizations and the scientific community. Water regulation ecosystem services (ES) are key elements of regulating services in ecosystem accounting, with most relevant studies strongly relying on models for ES quantification up to now. In this paper, we provide a review of modeling efforts for water regulation ES based on 148 scientific papers, properly systematized, analyzed and interpreted by using a detailed and structured original template. We examined emerging trends and gaps in model applications and the readiness to integrate them into the NCA and SEEA-EA frameworks. We propose a classification scheme which organizes the 92 different models and modeling approaches identified in the review process into eight model categories so that this scheme can be efficiently used in the water ES assessment of and for further integration into the accounting framework. Among the models, the hydrologic model SWAT and the modeling tool InVEST are by far the most popular. The results of the review revealed differences between the general ES literature and the accounting-related papers. Moreover, our analysis sets the basis for useful recommendations of which model categories are the most appropriate for the water regulation ES, included in the SEEA-EA reference list. Based on the number of relevant papers, the reliability and the confidence level of the recommendations for the use of models have been incorporated in our analysis. We highlight as model category with the highest confidence the ones relative to quantification water flow and flood control service aiming at ES accounting. Models for erosion control ES can only be recommended with a lower confidence, while for water purification the results lack clear evidence for using a particular group of models. Based on the research findings we identified the main research priorities on model integration in th

La herramienta de cálculo FRAX determina la probabilidad a 10 años de que un individuo entre 40 y 90 años sufra una fractura osteoporótica mayor o de cadera computando los factores de riesgo del individuo y, opcionalmente, la densidad mineral ósea determinada por absorciometría de fotón dual (DEXA), en comparación con los de una cohorte de la que se conoce la prevalencia de fractura. Por otra parte, hay datos que sugieren que la medida de la densidad radiológica mediante la técnica Earth Mover’s Distance (EMD) puede mejorar la precisión diagnostica en mamografías y radiología osteoarticular, entre otras.

Natural Capital Accounting (NCA) has evolved rapidly in recent years through substantial efforts of both international organizations and the scientific community. Water regulation ecosystem services (ES) are key elements of regulating services in ecosystem accounting, with most relevant studies strongly relying on models for ES quantification up to now. In this paper, we provide a review of modeling efforts for water regulation ES based on 148 scientific papers, properly systematized, analyzed and interpreted by using a detailed and structured original template. We examined emerging trends and gaps in model applications and the readiness to integrate them into the NCA and SEEA-EA frameworks. We propose a classification scheme which organizes the 92 different models and modeling approaches identified in the review process into eight model categories so that this scheme can be efficiently used in the water ES assessment of and for further integration into the accounting framework. Among the models, the hydrologic model SWAT and the modeling tool InVEST are by far the most popular. The results of the review revealed differences between the general ES literature and the accounting-related papers. Moreover, our analysis sets the basis for useful recommendations of which model categories are the most appropriate for the water regulation ES, included in the SEEA-EA reference list. Based on the number of relevant papers, the reliability and the confidence level of the recommendations for the use of models have been incorporated in our analysis. We highlight as model category with the highest confidence the ones relative to quantification water flow and flood control service aiming at ES accounting. Models for erosion control ES can only be recommended with a lower confidence, while for water purification the results lack clear evidence for using a particular group of models. Based on the research findings we identified the main research priorities on model integration in th

El campo de las matemáticas para ciencias de la salud hace referencia a los métodos y herramientas matemáticas que se aplican en la solución de problemas que pertenecen al área de las ciencias de la salud y de la medicina. Se trata de un campo muy amplio y el presente Trabajo de Fin de Grado centra la atención en el riesgo que presenta un individuo de sufrir una fractura. Se estudia y testea el algoritmo de la herramienta Fracture Risk Assesment Tool (FRAX) en una base de datos sintética. Esta aplicación calcula la probabilidad a 10 años que presenta un individuo entre 40 y 90 años de sufrir fractura de cadera o cualquier otra fractura osteoporótica a partir de una serie de factores clínicos de riesgo. Con la intención de mejorar la precisión del algoritmo, se añade a la información inicial un factor de riesgo específico: una serie de radiografías del paciente. Se realiza una comparación entre las imágenes con rayos X de manera automatizada. Así, la probabilidad de fractura puede aumentar con el empeoramiento de un hueso en concreto o de manera análoga podría disminuir con la mejora de ese hueso., The field of mathematics for health sciences refers to the mathematical methods that are applied in the solution of problems that belong to the area of health sciences and medicine. It is a very broad field, and this Final Degree Project focuses on the risk of an individual suffering a fracture. The algorithm of the Fracture Risk Assessment Tool (FRAX) is studied and tested on a synthetic database. This application calculates the 10-year probability of an individual between 40 and 90 years of suffering a hip fracture or any other osteoportic fracture based on a series of clinical risk factors. In order to improve the accuracy of the algorithm, a specific risk factor is added to the initial information: a series of radiographs of the patient. A comparison between the X-ray images is performed in an automated way. Thus, the probability of fracture may increase with the worsening of a particular bone, or similarly it may decrease with the improvement of that bone.

PURPOSE: It has been established that the infection with SARS-CoV-2 may cause an impairment of chemosensory function. However, there is little data on the long-term effects of SARS-CoV-2 infection on chemosensory function. METHODS: Twenty three SARS-CoV-2-positive patients diagnosed in spring 2020 with subjective hyposmia (out of 57 positive patients, 40.3%) were compared to SARS-CoV-2-positive patients without hyposmia (n = 19) and SARS-CoV-2-negative patients (n = 14). Chemosensory function was assessed by the Brief Smell Identification Test (BSIT), Taste Strips (TS), Visual Analogue Scales (VAS), and the SNOT-22. The initial cohort with hyposmia were also examined at 8 weeks and 6 months after initial examination. RESULTS: There were no differences between the SARS-CoV-2-positive cohort without hyposmia and negative controls in terms of BSIT (8.5 ± 2.6 vs. 10.2 ± 1.8), TS (3.4 ± 0.6 vs. 3.9 ± 0.3) or VAS (2.1 ± 1.3 vs. 1.1 ± 0.5); yet the SNOT-22 was significantly elevated (27.7 ± 11.2 vs. 16.4 ± 10.8). The SARS-CoV-2-positive group with hyposmia performed significantly poorer in BSIT (4.0 ± 1.7 vs. 8.5 ± 2.6/10.2 ± 1.8), TS (2.6 ± 1.3 vs. 3.4 ± 0.6/3.9 ± 0.3), and VAS (7.9 ± 2.2 vs. 2.1 ± 1.3/1.1 ± 0.5) compared to both control groups. At week 8 and month 6 control, six and five patients, respectively, still suffered from subjectively and objectively impaired chemosensory function. The other patients had recovered in both respects. CONCLUSION: SARS-CoV-2 patients with subjectively impaired chemosensory function regularly perform poorly in objective measurements. About 70% of patients suffering from olfactory dysfunction in SARS-CoV-2 quickly recover-the rest still suffers from considerable impairment 6 months after infection.

One of the most challenging problems in autonomous driving, and in computer vision in general, is the task of object detection. Recently, the advances of deep learning in the domain of computer vision have led the research community to apply ideas from deep learning to the problem of object detection. Such frameworks have shown promising results by outperforming all of the traditional approaches based on hand-crafted features. However, deep neural networks fail to provide reliability measurement for their predictions, which is a crucial requirement for critical systems. Moreover, it has been shown that deep neural networks tend to give more overconfident predictions compared to their shallow counterpart. Our objective with the current degree project is to review popular deep neural object detection frameworks and to investigate methods for uncertainty estimation in deep convolutional neural networks. Additionally, we would like to find out if applying a method of uncertainty estimation could improve the performance of a deep neural object detector in terms of standard object detection metrics such as average precision and log average miss rate. Moreover, we aim at discovering if an approach for measuring reliability improves the calibration quality of an object detector. Finally, we focus on investigating if uncertainty estimates could be utilised for detecting misclassified examples or highly occluded/truncated objects within an image. In order to answer these questions, we construct a variety of experiments that investigate different setups and conditions. Overall, we found that uncertainty estimation is a promising approach for alleviating overconfidence in deep neural networks as well as for providing a reliability measurement for all predictions., Ett av de mest utmanande problemen i autonom körning och i datorsyn i allmänhet är uppgiften att upptäcka objekt. Nyligen har framstegen med djup inlärning inom datorsynsområdet ledt till att forskarsamhället tillämpar idéer från djup inlärning till problemet med att upptäcka objekt. Sådana ramverk har visat lovande resultat genom att överträffa alla traditionella tillvägagångssätt baserade på handgjorda funktioner. Djupa nervnätverk kan emellertid inte tillhandahålla tillförlitlighetsmätning för sina förutsägelser, vilket är ett avgörande krav för kritiska system. Dessutom har det visats att djupa neurala nätverk tenderar att ge mer överviktiga förutsägelser jämfört med deras grunt motsvarighet. Vårt mål med det aktuella examensprojektet är att granska populära ramar för upptäckt av neurala objekt och undersöka metoder för osäkerhetsberäkning i invandrade neurala nätverk. Dessutom vill vi ta reda på om tillämpning av en metod för osäkerhetsberäkning kan förbättra prestandan för en djup neural objektdetektor när det gäller standardobjektdetekteringsmetriser som genomsnittlig precision och loggenomsnittlig missfrekvens. Dessutom syftar vi till att upptäcka om en metod för att mäta tillförlitlighet förbättrar kalibreringskvaliteten för en objektdetektor. Slutligen fokuserar vi på att undersöka om osäkerhetsberäkningar kan användas för att upptäcka felklassificerade exempel eller starkt ockluderade/trunkerade objekt i en bild. För att svara på dessa frågor konstruerar vi olika experiment som undersöker olika inställningar och villkor. Sammantaget konstaterade vi att osäkerhetsberäkningen är en lovande strategi för att lindra överförtroende i djupa nervnätverk och för att tillhandahålla tillförlitlighetsmått för alla förutsägelser.

El campo de las matemáticas para ciencias de la salud hace referencia a los métodos y herramientas matemáticas que se aplican en la solución de problemas que pertenecen al área de las ciencias de la salud y de la medicina. Se trata de un campo muy amplio y el presente Trabajo de Fin de Grado centra la atención en el riesgo que presenta un individuo de sufrir una fractura. Se estudia y testea el algoritmo de la herramienta Fracture Risk Assesment Tool (FRAX) en una base de datos sintética. Esta aplicación calcula la probabilidad a 10 años que presenta un individuo entre 40 y 90 años de sufrir fractura de cadera o cualquier otra fractura osteoporótica a partir de una serie de factores clínicos de riesgo. Con la intención de mejorar la precisión del algoritmo, se añade a la información inicial un factor de riesgo específico: una serie de radiografías del paciente. Se realiza una comparación entre las imágenes con rayos X de manera automatizada. Así, la probabilidad de fractura puede aumentar con el empeoramiento de un hueso en concreto o de manera análoga podría disminuir con la mejora de ese hueso., The field of mathematics for health sciences refers to the mathematical methods that are applied in the solution of problems that belong to the area of health sciences and medicine. It is a very broad field, and this Final Degree Project focuses on the risk of an individual suffering a fracture. The algorithm of the Fracture Risk Assessment Tool (FRAX) is studied and tested on a synthetic database. This application calculates the 10-year probability of an individual between 40 and 90 years of suffering a hip fracture or any other osteoportic fracture based on a series of clinical risk factors. In order to improve the accuracy of the algorithm, a specific risk factor is added to the initial information: a series of radiographs of the patient. A comparison between the X-ray images is performed in an automated way. Thus, the probability of fracture may increase with the worsening of a particular bone, or similarly it may decrease with the improvement of that bone.

One of the most challenging problems in autonomous driving, and in computer vision in general, is the task of object detection. Recently, the advances of deep learning in the domain of computer vision have led the research community to apply ideas from deep learning to the problem of object detection. Such frameworks have shown promising results by outperforming all of the traditional approaches based on hand-crafted features. However, deep neural networks fail to provide reliability measurement for their predictions, which is a crucial requirement for critical systems. Moreover, it has been shown that deep neural networks tend to give more overconfident predictions compared to their shallow counterpart. Our objective with the current degree project is to review popular deep neural object detection frameworks and to investigate methods for uncertainty estimation in deep convolutional neural networks. Additionally, we would like to find out if applying a method of uncertainty estimation could improve the performance of a deep neural object detector in terms of standard object detection metrics such as average precision and log average miss rate. Moreover, we aim at discovering if an approach for measuring reliability improves the calibration quality of an object detector. Finally, we focus on investigating if uncertainty estimates could be utilised for detecting misclassified examples or highly occluded/truncated objects within an image. In order to answer these questions, we construct a variety of experiments that investigate different setups and conditions. Overall, we found that uncertainty estimation is a promising approach for alleviating overconfidence in deep neural networks as well as for providing a reliability measurement for all predictions., Ett av de mest utmanande problemen i autonom körning och i datorsyn i allmänhet är uppgiften att upptäcka objekt. Nyligen har framstegen med djup inlärning inom datorsynsområdet ledt till att forskarsamhället tillämpar idéer från djup inlärning till problemet med att upptäcka objekt. Sådana ramverk har visat lovande resultat genom att överträffa alla traditionella tillvägagångssätt baserade på handgjorda funktioner. Djupa nervnätverk kan emellertid inte tillhandahålla tillförlitlighetsmätning för sina förutsägelser, vilket är ett avgörande krav för kritiska system. Dessutom har det visats att djupa neurala nätverk tenderar att ge mer överviktiga förutsägelser jämfört med deras grunt motsvarighet. Vårt mål med det aktuella examensprojektet är att granska populära ramar för upptäckt av neurala objekt och undersöka metoder för osäkerhetsberäkning i invandrade neurala nätverk. Dessutom vill vi ta reda på om tillämpning av en metod för osäkerhetsberäkning kan förbättra prestandan för en djup neural objektdetektor när det gäller standardobjektdetekteringsmetriser som genomsnittlig precision och loggenomsnittlig missfrekvens. Dessutom syftar vi till att upptäcka om en metod för att mäta tillförlitlighet förbättrar kalibreringskvaliteten för en objektdetektor. Slutligen fokuserar vi på att undersöka om osäkerhetsberäkningar kan användas för att upptäcka felklassificerade exempel eller starkt ockluderade/trunkerade objekt i en bild. För att svara på dessa frågor konstruerar vi olika experiment som undersöker olika inställningar och villkor. Sammantaget konstaterade vi att osäkerhetsberäkningen är en lovande strategi för att lindra överförtroende i djupa nervnätverk och för att tillhandahålla tillförlitlighetsmått för alla förutsägelser.

Antibodies play an important role in host defense against microorganisms. Besides direct microbicidal activities, antibodies can also provide indirect protection via crosstalk to constituents of the adaptive immune system. Similar to many human chronic viral infections, persistence of Lymphocytic choriomeningitis virus (LCMV) is associated with compromised T- and B-cell responses. The administration of virus-specific non-neutralizing antibodies (nnAbs) prior to LCMV infection protects against the establishment of chronic infection. Here, we show that LCMV-specific nnAbs bind preferentially Ly6C$^{hi}$ inflammatory monocytes (IMs), promote their infection in an Fc-receptor independent way, and support acquisition of APC properties. By constituting additional T-cell priming opportunities, IMs promote early activation of virus-specific CD8 T cells, eventually tipping the balance between T-cell exhaustion and effector cell differentiation, preventing establishment of viral persistence without causing lethal immunopathology. These results document a beneficial role of IMs in avoiding T-cell exhaustion and an Fc-receptor independent protective mechanism provided by LCMV-specific nnAbs against the establishment of chronic infection.

Fibroblast growth factors (FGFs) play key roles in the pathogenesis of different human diseases, but the cross-talk between FGFs and other cytokines remains largely unexplored. We identified an unexpected antagonistic effect of FGFs on the interferon (IFN) signaling pathway. Genetic or pharmacological inhibition of FGF receptor signaling in keratinocytes promoted the expression of interferon-stimulated genes (ISG) and proteins in vitro and in vivo. Conversely, FGF7 or FGF10 treatment of keratinocytes suppressed ISG expression under homeostatic conditions and in response to IFN or poly(I:C) treatment. FGF-mediated ISG suppression was independent of IFN receptors, occurred at the transcriptional level, and required FGF receptor kinase and proteasomal activity. It is not restricted to keratinocytes and functionally relevant, since FGFs promoted the replication of herpes simplex virus I (HSV-1), lymphocytic choriomeningitis virus, and Zika virus. Most importantly, inhibition of FGFR signaling blocked HSV-1 replication in cultured human keratinocytes and in mice. These results suggest the use of FGFR kinase inhibitors for the treatment of viral infections.

оформление гармоничной композиции древесно-кустарниковой группы требует разрисовку с нескольких точек зрения. Помещение более высоких деревьев в центр композиции в плане еще недостаточно выражает возможности художественных внушений ландшафтного архитектора. Мы предлагаем несколько простых действий: разрисовывать композицию с нескольких сторон, пользуясь перспективной системой, чтобы оформить хороший вид композиции с двух точек наблюдения, находящихся под углом 180° относительно друг друга., the process of designing a harmonious tree and shrub composition requires multi-perspective painting. Not all the landscape designer’s artistic conceptions might be expressed by placing the tallest trees to the center of a room. We suggest a few simple steps, such as using a spatial method of painting and the multi-perspective system, in order to design a good looking composition from two perspectives at an angle 180° relative to each other.

оформление гармоничной композиции древесно-кустарниковой группы требует разрисовку с нескольких точек зрения. Помещение более высоких деревьев в центр композиции в плане еще недостаточно выражает возможности художественных внушений ландшафтного архитектора. Мы предлагаем несколько простых действий: разрисовывать композицию с нескольких сторон, пользуясь перспективной системой, чтобы оформить хороший вид композиции с двух точек наблюдения, находящихся под углом 180° относительно друг друга., the process of designing a harmonious tree and shrub composition requires multi-perspective painting. Not all the landscape designer’s artistic conceptions might be expressed by placing the tallest trees to the center of a room. We suggest a few simple steps, such as using a spatial method of painting and the multi-perspective system, in order to design a good looking composition from two perspectives at an angle 180° relative to each other.

We report in this paper on a multiyear endeavour within the EIT (European Institute of Innovation and Technology) Digital community, during which EIT Digital built an international community of Innovation and Entrepreneurship (“I&E”) teachers at Master level by implementing a blended learning strategy. We see this challenge as a case in change management, which could offer relevant insight to run similar initiatives of blending learning adoption as an enabler to developing pedagogical cooperation in networks of universities with real impact on practices. Through the lenses of change management theory, we describe and analyse the methods that allowed EIT Digital to create and enhance a community of “teacher-producers” in order to develop and deploy blended education from scratch. EIT Digital, a Knowledge and Innovation Community of the European Institute of Innovation and Technology (EIT), provides IT education at Master’s level since 2013 and in association with its around 20 member universities, including a strong “Innovation & Entrepreneurship” (“I&E”) education component. EIT Digital developed a blended learning strategy whose originality came from the fact that some of the teachers are also producers on behalf of the entire community, receiving associated co-funding and technical support from EIT Digital. More specifically, teachers actively took part to the production agenda, according to which producers were chosen within the community to create and deliver the agreed online contents. EIT Digital library now encompasses more than 500 basic online contents (“nuggets”) covering most topics relevant for I&E education at the graduate level, from basic business model introductions to complex technology transfer strategies. This amounts to more than 45 hours’ worth of videos along with dozens of written cases, quizzes and other forms of online/offline assignments. Depending on the various universities’ contexts, different blending strategies were dep, QC 20181105

This paper evaluates the budget transparency of international organizations. Building on IMF, OECD, IPSAS, and Open Budget Survey standards for sovereign-state budget transparency, we create a 93-item budget transparency measure reflective of international organization characteristics. International organizations are important global dispensers of accumulated knowledge. This includes the purveying of advice on member state budget transparency. Despite this role, we find only partial budget transparency among our surveyed international organizations. Nonetheless, the international organization financial management and accountability practices were more transparent than their budget process or budget disclosures

Models based on Artificial Neural Networks (ANN) in recent years are increasingly being used in environmental studies. Among the many types of ANN, the network type Multilayer Perceptron (MLP) has become most widespread. Such networks are universal, simple, and suitable for most tasks. The main problem when modelling using MLP is the choice of the learning algorithm. In this paper, we compared several learning algorithms: Levenberg-Marquart (LM), LM with Bayes regularization (BR), gradient descent (GD), and GD with the speed parameter setting (GDA). The data for modelling were taken from the results of the soil screening of an urbanized area. The spatial distribution of the chemical element Chromium (Cr) in the surface layer of the soil was simulated. The structure of the MLP network was chosen using computer simulations based on minimization of the root mean squared error (RMSE). The model using the LM training algorithm showed the best accuracy. © 2018 Author(s).

This paper evaluates the budget transparency of international organizations. Building on IMF, OECD, IPSAS, and Open Budget Survey standards for sovereign-state budget transparency, we create a 93-item budget transparency measure reflective of international organization characteristics. International organizations are important global dispensers of accumulated knowledge. This includes the purveying of advice on member state budget transparency. Despite this role, we find only partial budget transparency among our surveyed international organizations. Nonetheless, the international organization financial management and accountability practices were more transparent than their budget process or budget disclosures

This article provides an overview of current European Commission effort in term of educational innovation to reduce the gap between research and industry which still is a barrier to the economic development. Entrepreneurial innovation & education driving Europe's digital transformation (EIT Digital for short) is an European-based initiative fostering I&E (innovation and entrepreneurship) by integrating education, research and business at different educational levels. For instance in EIT master programmes, students work together with industries and academics to have a faster go-to-market of research results. Summer schools are part of the master programs; three of them have been organised related to CPS (cyber-physical systems), critical infrastructure and, more recently, Industry 4.0. Past and present events are discussed and the experience from these events is reported. It is further analysed how the general setup of the summer school program is affecting the educational aspects and achievement of the intended learning outcomes., QC 20170217

This article provides an overview of current European Commission effort in term of educational innovation to reduce the gap between research and industry which still is a barrier to the economic development. Entrepreneurial innovation & education driving Europe's digital transformation (EIT Digital for short) is an European-based initiative fostering I&E (innovation and entrepreneurship) by integrating education, research and business at different educational levels. For instance in EIT master programmes, students work together with industries and academics to have a faster go-to-market of research results. Summer schools are part of the master programs; three of them have been organised related to CPS (cyber-physical systems), critical infrastructure and, more recently, Industry 4.0. Past and present events are discussed and the experience from these events is reported. It is further analysed how the general setup of the summer school program is affecting the educational aspects and achievement of the intended learning outcomes.

This article provides an overview of current European Commission effort in term of educational innovation to reduce the gap between research and industry which still is a barrier to the economic development. Entrepreneurial innovation & education driving Europe's digital transformation (EIT Digital for short) is an European-based initiative fostering I&E (innovation and entrepreneurship) by integrating education, research and business at different educational levels. For instance in EIT master programmes, students work together with industries and academics to have a faster go-to-market of research results. Summer schools are part of the master programs; three of them have been organised related to CPS (cyber-physical systems), critical infrastructure and, more recently, Industry 4.0. Past and present events are discussed and the experience from these events is reported. It is further analysed how the general setup of the summer school program is affecting the educational aspects and achievement of the intended learning outcomes.

The ‘Smart Mirror’ project introduces non-contact based technological innovations at our homes where its usage can be as ubiquitous as ‘looking at a mirror’ while providing critical actionable insights thereby leading to improved care and outcomes. The key objectives is to detect key physiological markers like Heart Rate (HR), Respiration Rate (RR), Inter-beat-interval (IBI) and Blood Pressure (BP) and also drowsiness using the video input of the individual standing in front of the mirror and display the results in real-time. A satisfactory level of accuracy has been attained with respect to the reference sensors signal., SafeDriver: A Real Time Driver's State Monitoring and Prediction System

Activated carbons with different textural and chemical surface characteristics were synthesized from waste biomass and low rank coals, and furthermore used as a host matrix for cobalt species, varying the preparation and modification methods. The obtained activated carbons and modified samples were characterized by complex of various physicochemical methods, such as: low temperature physisorption of nitrogen, XRD, EPR, XPS, UV–Vis and TPR with hydrogen. Boehm method was applied for qualitative and quantitative determination of oxygen-containing groups on the carbon surface before and after cobalt deposition. The catalytic properties of cobalt modifications were tested in methanol decomposition. The dominant effect of activated carbon texture over the surface chemistry on the state and catalytic behavior of cobalt species was discussed.

Tungsten oxide nanostructures functionalized with gold or platinum NPs are synthesized and integrated, using a single-step method via aerosol-assisted chemical vapour deposition, onto micro-electromechanical system (MEMS)-based gas-sensor platforms. This co-deposition method is demonstrated to be an effective route to incorporate metal nanoparticles (NP) or combinations of metal NPs into nanostructured materials, resulting in an attractive way of tuning functionality in metal oxides (MOX). The results show variations in electronic and sensing properties of tungsten oxide according to the metal NPs introduced, which are used to discriminate effectively analytes (C2H 5OH, H2, and CO) that are present in proton-exchange fuel cells. Improved sensing characteristics, in particular to H2, are observed at 250 °C with Pt-functionalized tungsten oxide films, whereas non-functionalized tungsten oxide films show responses to low concentrations of CO at low temperatures. Differences in the sensing characteristics of these films are attributed to the different reactivities of metal NPs (Au and Pt), and to the degree of electronic interaction at the MOX/metal NP interface. The method presented in this work has advantages over other methods of integrating nanomaterials and devices, of having fewer processing steps, relatively low processing temperature, and no requirement for substrate pre-treatment. Tungsten oxide nanoneedles functionalized with gold or platinum nanoparticles (NPs) are synthesized using a single-step aerosol-assisted chemical vapor deposition method. They are integrated into gas-sensor platforms, which are used to discriminate analytes present in proton-exchange fuel cells. This co-deposition method is demonstrated to be effective both for incorporating metal NPs into nanostructured materials, resulting in an attractive way of tuning functionality in metal oxides, and for directly integrating these materials with devices. Copyright © 2013 WILEY-VCH Verlag GmbH &

We have prepared tungsten oxide films decorated with gold particles on Si substrates by aerosol assisted chemical vapor deposition (AACVD) and characterized them using scanning electron microscopy (SEM), transmission electron microscopy (TEM) and X-ray photoelectron spectroscopy (XPS). SEM shows that the films are composed of needle-like structures and TEM shows that both the needles and the gold particles are crystalline. XPS indicates the presence of oxygen vacancies, i.e. the films are WO 3-x, and hence the deposited material is composed of semiconducting nanostructures and that the interaction between the gold particles and the WO 3 needles surface is weak. The synthesis of semiconducting tungsten oxide nanostructures decorated with metal particles represents an important step towards the development of sensing devices with optimal properties. © 2012 Elsevier B.V. All rights reserved.

A new method of synthesising nanoparticle-functionalised nanostructured materials via Aerosol Assisted Chemical Vapour Deposition (AACVD) has been developed. Co-deposition of Au nanoparticles with WO(3) nanoneedles has been used to deposit a sensing layer directly onto gas sensor substrates providing devices with a six-fold increase in response to low concentrations of a test analyte (ethanol).

In this article is a report of SnO2 deposition by aerosol-assisted (AA)CVD from tin complexes, [Sn(18-Cr-6)Cl4] and [Sn(H2O)2Cl4](18-Cr-6). The structure and properties of the precursors, used to synthesize SnO2 layers by AACVD for the first time, are characterized with the help of X-ray diffraction (XRD), infrared (IR), and thermogravimetric analysis (TGA). Each complex is deposited by AACVD at 250, 400, and 500°C in a flow of N2. The resulting films are studied by XRD and atomic force microscopy (AFM). Gas-sensing properties of the deposited layers are tested to 10ppm NO2 in air. The maximum sensor response to the analyte is measured at 300°C. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

In this doctoral thesis, it has been investigated and developed the Aerosol Assisted Chemical Vapour Deposition (AACVD) method for direct in-situ growth of intrinsic and Au-functionalised nanostructured WO3, as well as SnO2-based devices for gas sensing applications. The nanostructured material synthesis, device fabrication and their gas sensing properties have been studied. AACVD method was used for synthesis and direct deposition of sensing films onto classical alumina and microhotplate gas sensor substrates, demonstrating the compatibility between the microhotplate fabrication process and the sensing nanostructured layer deposition. The effect of Au nanoparticles on the gas sensor’s response was measured and presented in this thesis. The test results revealed that the addition of Au nanoparticles to the WO3 nanoneedles has increased the sensor’s response towards the tested gases (i.e. EtOH). It was therefore demonstrated that the Au-functionalisation has an enhancing effect on the gas sensing properties of WO3 nanoneedles, En esta tesis doctoral, se ha investigado y desarrollado un nuevo método de CVD asistido por aerosol (AACVD), que permite el crecimiento de nanoestructuras de WO3 intrínsecas y funcionalizadas con Au. Así mismo se han depositado capas policristalinas de SnO2 para aplicaciones de detección de gases. La síntesis de materiales nanoestructurados, la fabricación de dispositivos y sus propiedades de detección de gases, han sido estudiadas. El método AACVD fue utilizado para la síntesis y la deposición directa de capas activas encima de sustratos de alúmina y también sobre substratos micromecanizados (microhotplates), lo que demuestra la compatibilidad entre la tecnología de silicio y la deposición de la capas activas nanoestructuradas. En la tesis se ha demostrado que las capas nanoestructuradas de WO3 funcionalizadas con oro tienen una sensibilidad mejor que las intrínsecas frente a algunos gases relevantes y al mismo tiempo se ha producido un cambio de selectividad.

This brief explores the change in the distribution of income. FRC Brief 199

This paper reviews the existing literature on the property tax exemption for nonprofit organizations and identifies gaps to be addressed in future research. We start by examining justifications and existing eligibility criteria for the property tax exemption, followed by studies of the magnitude of the revenue loss from the exemption. We focus on theoretical and empirical studies of the economic effects of the exemption. We consider the effect of the tax advantage on nonprofit decisions about inputs, outputs and organizational form, decisions to rent or own, location decision, market share, and the effect of the exemption on neighboring property values. Finally, we evaluate research about the use of PILOTs and the implications of their possible expansion. We conclude that future studies need to examine further the magnitude of the revenues forgone, the advantages and disadvantages of PILOTs, and other solutions for distributing more evenly the burden of the exemption. Further studies are also needed to understand the economic effects of the property tax exemption, with opportunities for theoretical and empirical contributions. Working Paper 08-15

This paper reviews the existing literature on the property tax exemption for nonprofit organizations and identifies gaps to be addressed in future research. We start by examining justifications and existing eligibility criteria for the property tax exemption, followed by studies of the magnitude of the revenue loss from the exemption. We focus on theoretical and empirical studies of the economic effects of the exemption. We consider the effect of the tax advantage on nonprofit decisions about inputs, outputs and organizational form, decisions to rent or own, location decision, market share, and the effect of the exemption on neighboring property values. Finally, we evaluate research about the use of PILOTs and the implications of their possible expansion. We conclude that future studies need to examine further the magnitude of the revenues forgone, the advantages and disadvantages of PILOTs, and other solutions for distributing more evenly the burden of the exemption. Further studies are also needed to understand the economic effects of the property tax exemption, with opportunities for theoretical and empirical contributions. Working Paper 08-15

This paper reviews the existing literature on the property tax exemption for nonprofit organizations and identifies gaps to be addressed in future research. We start by examining justifications and existing eligibility criteria for the property tax exemption, followed by studies of the magnitude of the revenue loss from the exemption. We focus on theoretical and empirical studies of the economic effects of the exemption. We consider the effect of the tax advantage on nonprofit decisions about inputs, outputs and organizational form, decisions to rent or own, location decision, market share, and the effect of the exemption on neighboring property values. Finally, we evaluate research about the use of PILOTs and the implications of their possible expansion. We conclude that future studies need to examine further the magnitude of the revenues forgone, the advantages and disadvantages of PILOTs, and other solutions for distributing more evenly the burden of the exemption. Further studies are also needed to understand the economic effects of the property tax exemption, with opportunities for theoretical and empirical contributions. Working Paper 08-15

This paper reviews the existing literature on the property tax exemption for nonprofit organizations and identifies gaps to be addressed in future research. We start by examining justifications and existing eligibility criteria for the property tax exemption, followed by studies of the magnitude of the revenue loss from the exemption. We focus on theoretical and empirical studies of the economic effects of the exemption. We consider the effect of the tax advantage on nonprofit decisions about inputs, outputs and organizational form, decisions to rent or own, location decision, market share, and the effect of the exemption on neighboring property values. Finally, we evaluate research about the use of PILOTs and the implications of their possible expansion. We conclude that future studies need to examine further the magnitude of the revenues forgone, the advantages and disadvantages of PILOTs, and other solutions for distributing more evenly the burden of the exemption. Further studies are also needed to understand the economic effects of the property tax exemption, with opportunities for theoretical and empirical contributions. Working Paper 08-15

The theoretical background of optical holographic recording in very thin films is given. The interference fringes are stored by surface - propagating evanescent waves. Such waves are created by the total internal light reflection (TIR). The experimental verification of the theory is made. The holographic grating with 454nm period has been recorded in 29, 39 and 74 nm thick As2S3 films. The diffraction efficiency dependence on the time is investigated. The polarization behavior of TIR surface holograms is similar to that of the thick Bragg gratings. The possible applications of this holographic recording are also discussed., Published in Jnl. of Optoelectronics and Advanced Materials, v3 n2, Jun 2001. p395-398 This article is from ADA398590 International Workshop on Amorphous and Nanostructured Chalcogenides 1st, Fundamentals and Applications held in Bucharest, Romania, 25-28 Jun 2001. Part 1

Background and Objectives: In South Africa, the prevalence of human papillomavirus (HPV) and associated diseases, such as cervical cancer and genital warts, is among the highest in the world. This study evaluates the cost-effectiveness of bivalent, quadrivalent, and nonavalent HPV vaccination for 9- to 14-year-old girls from the South African healthcare system perspective. Methods: A Markov model portraying the natural HPV disease progression from high-risk infection to cervical intraepithelial neoplasia (CIN) I, CIN II/III, or cervical cancer and from low-risk infection to genital warts was built. Transition probability, utility, and efficacy data were sourced from peer-reviewed literature. Vaccination costs were calculated based on the World Health Organization (WHO) guidelines. The model was populated with a cohort of 520,000 9-year-old girls to calculate incremental cost-effectiveness ratios (ICER) in South African Rand (R) per quality-adjusted life-years (QALYs) gained for each vaccination strategy. Results: All HPV vaccination strategies dominate the no vaccine strategy. Compared with the bivalent vaccine, the nonavalent strategy increases QALYs by 0.14 and costs by R1793 (ICER: R13,013 per QALY) per person, while the quadrivalent vaccination provides −0.02 incremental QALYs and R1748 costs (ICER: −R116,397 per QALY). Consequently, at the South African willingness-to-pay threshold of R23,630 per QALY, nonavalent vaccination is the preferred strategy, with a probability of 90.2%. Scenario analysis demonstrated that results are influenced by vaccine coverage, efficacy, and duration of efficacy. Conclusions: The introduction of nonavalent for bivalent HPV vaccination is a cost-effective intervention in South Africa. HPV vaccination should be part of a multifaceted public health strategy entailing screening, condoms, and education of all stakeholders to reduce the significant burden of sexual transmitted diseases in South Africa. Sex-neutral and catch-up vaccinati