Aniek, Lentferink, Louis, Polstra, Labour Participation, Austin, D'Souza, New Business & ICT, Hilbrand, Oldenhuis, Personalized Digital Health, Hugo, Velthuijsen, New Business & ICT, Lisette, van Gemert-Pijnen, New Business & ICT, Labour Participation, and Personalized Digital Health
BMC Medical Informatics and Decision Making.
ehealth ontwikkeling, stress management, waardebepaling, medical information, Computer Science(all), Entrepreneurship and Healthy Ageing, Entrepreneurship, and Science
Background: For a stress-management app to be persuasive and impactful, designers and developers should obtain a clear perspective of the value proposition according to key stakeholders before development. However, this is often not the case. In order to increase the chance of creating an impact by means of the Resilience Navigator app, this study aims to identify key stakeholders and work with them to gain an in-depth understanding of the value proposition of this stress-management app. Methods: The approach used in this study builds on the approaches taken by Van Limburg et al. and Van Woezik et al. An initial list of stakeholders was identified by means of a literature scan. Stakeholders on this initial list took an online survey to identify key stakeholders with a ranking system. Semi-structured interviews were conducted with a subset of key stakeholders to identify the value proposition using the value proposition canvas as a framework for data collection. Finally, the value proposition was validated by key stakeholders during focus groups. Results: The key stakeholders identified included employees, employers, participation councils within organisations, HR advisors, product owners, company doctors, and business analysts. The interviews produced a list of approximately one hundred values from which fifteen core values were distilled. One example is to take into account time constraints experienced by users during stress periods. In general, the Resilience Navigator app’s main goal is to increase awareness of personal stress levels and causes of stress. In addition, the sub-goal is to increase skills for effective stress management. The focus groups validated the idea that the most important values were reflected in the value proposition and had been appropriately translated into design elements, according to key stakeholders. Conclusions: A thorough, bottom-up identification and validation of the value proposition for the Resilience Navigator app was obtained, reflecting key stakeholders’ varying ideas on this piece of eHealth technology. The results will facilitate the continued development of the Resilience Navigator app from the value specification phase to the design phase. In the design phase, the remaining assumptions regarding the app’s value proposition should be tested using rapid prototyping.
Usó, Vanessa Ghiraldeli, Sandnes, Frode Eika, and Medola, Fausto Orsi
Usó, V.G., Sandnes, F.E. & Medola, F.O. (2020). Using virtual reality and rapid prototyping to co-create together with hospitalized children. In: M. Di Nicolantonio, E. Rossi & T. Alexander (Eds.). Advances in additive manufacturing, modeling systems and 3D prototyping: Proceedings of the AHFE 2019 International Conference on Additive Manufacturing, Modeling Systems and 3D Prototyping, 2020 (pp. 279-288) Cham: Springer
Despite the last 60 years have seen major advances in many scientific and technological inputs of drug Research and Development, the number of new molecules hitting the market per billion US dollars of R&D spending has been declined steadily during the same period. The current scenario highlights the need for new research tools to enable reduce costly animal and clinical trials while providing a better prediction about drug efficacy and security in humans A recent emerging approach to improve the current models is emerging from the field of microfluidics, which studies systems that process or manipulate tiny amounts of fluids using channels with dimensions of tens to hundreds of micrometers. Combining microfluidics with cell culture, scientists gave rise to a new field named “Organ-on-chip” (OOC). Microfluidic OOCs are advanced platforms designed to mimic physiological structures and continuous flow conditions, thus allowing the culture of cells in a friendlier microenvironment. This thesis, titled “Cell culture interfaces for different organ-on-chip applications: from photolithography to rapid-prototyping techniques with sensor embedding”, aims to design, simulate and test new OOC devices to reproduce cell culture interface under flow conditions. The work has a focus on the exploration of novel fabrication techniques which enable rapid prototyping of OOC devices, reducing costs, time and human labor associated to the fabrication process. The final objective is to demonstrate the viability of the devices as research tools for biological problems, applying them to the tubular kidney and the blood brain barrier (BBB). To achieve the objective, at least three device version have been developed: 1) OOCv1, fabricated by multilayer PDMS soft lithography; 2) OOCv2, fabricated in thermoplastic by layered object manufacturing using both a vinyl cutter and a laser cutter, integrating standard fluidic connectors alone (OOCv2.1) or together with embedded electrodes (OOCv2.2); 3) OOCv3 using a mixed technique of laser cut and 3D printing by stereolithography. All devices are fabricated using biocompatible materials with high optical quality and an embedded commercial membrane. The biological experiments with renal tubular epithelial cells, realized on OOCv1 and OOCv2.1 devices, demonstrated the viability of the device for culturing cells under flow conditions. The study realized on fatty acid oxidation and accumulation in cells exposed to physiological and diabetogenic oscillating levels of glucose suggest a possible positive role of shear stress in activation of fatty acid metabolism. The studies were performed using a compact experimental unit with embedded flow control which reduce significatively the complexity and cost of the fluidic experimental setup. The biological experiments on the BBB confirmed viability of OOCv2.1 and OOCv2.2 for compartmentalized co-culturing of endothelial cells and pericytes. The formation and recovery of the barrier after disruptive treatment has been assessed using different techniques, including immunostaining, fluorescence and live phase contrast imaging, and electrical impedance spectroscopy. The repeatability of measurements using electrodes was verified. A model to classify measurements from different timepoints has been developed, resulting in accuracy of 100% in learning and 90% in testing case. Results are confirmed by imaging data, which also suggest a critical role of pericytes in the development, maintenance, and regulation of BBB, in accordance with the literature.
Strukton Rail wants to try new training methods for their employees by creating a virtual reality simulation where the workers can practice in a safe environment. Strukton employees have to do maintenance work in heights in the rail track. Besides the risks related to the actual job of working in heights, external factors like the weather changes play a big role in the increase of risks in the worksite. In the VR simulation that will be created to solve the client’s problem, a weather system will be created to produce hazardous weather conditions, so the employees can practice in those conditions as well and learn about the conditions that they should stop working. In this research literature review is conducted to better understand what makes the different weather components look real and how to achieve better visual realism for a weather system in VR. Afterwards different approaches are tried in Unity engine to create a multi-layered weather system for a VR simulation. The focus of the prototyping was to create a realistic transition from a clear sky to a thunderstorm. During the experimental design, besides the realistic looking weather system, two more scenes were created. One where the complexity of the weather system was reduced, and the illumination of the environment wasn’t changing accordingly to the changes in the weather, and one where the weather system was rendered using cartoony shading and textures, rather than realistic looking ones. The three scenes were tested out with the safety officer of Strukton Rail and 9 other participants. During the tests it was found out that an increase in visual realism of the weather system had a significant role on the feeling of presence of the participants. It was noticed that what had the biggest impact in the effectiveness of the weather system was the change of lighting and illumination of the environment depending on the weather changes, and the increase in complexity/detail of the weather components. The rendering technique didn’t have a big impact as the cartoony rendered weather system was as clear as the realistic looking one, and according to the safety officer the thunderstorm felt hazardous in both scenarios.
Conducció autònoma, Conducción autónoma, Autonomous driving, Visió per computador, Visión por computador, Computer vision, Aprenentatge màquina, Aprendizaje máquina, Machine learning, and Ciències Experimentals
Els vehicles autònoms es consideren ara com a actius assegurats en el futur. Literalment, tots els marcadors d’automòbils rellevants es troben en una cursa per produir vehicles totalment autònoms. Aquests fabricants de cotxes solen fer ús de canonades modulars per al disseny de vehicles autònoms. Aquesta estratègia descompon el problema en diverses tasques com la detecció i el reconeixement d’objectes, la segmentació semàntica i la instància, l’estimació de profunditat, el reconeixement de llocs i SLAM, així com la planificació i el control. Cada mòdul requereix un conjunt separat d’algoritmes experts, que són costosos especialment quant al treball humà i la necessitat d’etiquetatge de dades. Una alternativa que recentment té un interès significatiu és la conducció integral. En el paradigma de conducció de extrem a extrem, la percepció i el control s’obtenen simultàniament mitjançant una xarxa profunda. Els models de tesisensorotor s’obtenen normalment mitjançant l’aprenentatge de imitacions de les demostracions de humà. L’avantatge principal és que aquest enfocament pot aprendre directament de les grans flotes de vehicles dirigits per humans sense necessitat d’un ontologia fixa i d’una àmplia quantitat d’etiquetatge. No obstant això, els mètodes de extrem a extrem es van utilitzar habitualment per aprendre conductes simples com ara manteniment de carrils i el vehicle principal. En aquesta tesi, per tal d’aconseguir comportaments més complexos, abordemalguns problemes quan es crea un sistema de conducció de extrem a extrem mitjançant l’aprenentatge de la imitació. El primer d’aquests és la necessitat d’un entorn per a l’avaluació d’algorismes i la recopilació de demostracions d’administració. En aquest sentit, hem participat en la creació del simulador de Carla, una plataforma de codi obert construïda des de la base per a la validació i el prototipatge d’autònoms. Atès que l’enfocament de extrem a extrem és purament re-actiu, també hi ha la necessitat de proporcionar una interfície amb un sistema de planificació global. Amb això, proposem l’aprenentatge d’imitació condicional que condiciona les accions produïdes en algun comandament d’alt nivell. L’avaluació és també una qüestió i normalment es fa mitjançant la comparació de la sortida de la xarxa de cap a cap a un conjunt de dades de conducció que es recull. Demostrem que això és correlacionat sorprenentment debilitat amb la conducció real i proposa estratègies sobre com adquirir millor les dades i una estratègia de comparació millor. Finalment, confirmem problemes de generalització ben coneguts (deguts a biaixos i sobraccessos actuals), de nous (a causa d’objectes dinàmics i la manca de model acausal) i la inestabilitat de la formació; Els problemes que requereixen més investigacions abans de finalitzar la conducció a través de la imitació poden escalar a la conducció del món real.
Large-scale simulation and visualization are essential topics in areas as different as sociology, physics, urbanism, training, entertainment among others. This kind of systems requires a vast computational power and memory resources commonly available in High Performance Computing HPC platforms. Currently, the most potent clusters have heterogeneous architectures with hundreds of thousands and even millions of cores. The industry trends inferred that exascale clusters would have thousands of millions. The technical challenges for simulation and visualization process in the exascale era are intertwined with difficulties in other areas of research, including storage, communication, programming models and hardware. For this reason, it is necessary prototyping, testing, and deployment a variety of approaches to address the technical challenges identified and evaluate the advantages and disadvantages of each proposed solution. The focus of this research is interactive large-scale crowd simulation and visualization. To exploit to the maximum the capacity of the current HPC infrastructure and be prepared to take advantage of the next generation. The project develops a new approach to scale crowd simulation and visualization on heterogeneous computing cluster using a task-based technique. Its main characteristic is hardware agnostic. It abstracts the difficulties that imply the use of heterogeneous architectures like memory management, scheduling, communications, and synchronization — facilitating development, maintenance, and scalability. With the goal of flexibility and take advantage of computing resources as best as possible, the project explores different configurations to connect the simulation with the visualization engine. This kind of system has an essential use in emergencies. Therefore, urban scenes were implemented as realistic as possible; in this way, users will be ready to face real events. Path planning for large-scale crowds is a challenge to solve, due to the inherent dynamism in the scenes and vast search space. A new path-finding algorithm was developed. It has a hierarchical approach which offers different advantages: it divides the search space reducing the problem complexity, it can obtain a partial path instead of wait for the complete one, which allows a character to start moving and compute the rest asynchronously. It can reprocess only a part if necessary with different levels of abstraction. A case study is presented for a crowd simulation in urban scenarios. Geolocated data are used, they were produced by mobile devices to predict individual and crowd behavior and detect abnormal situations in the presence of specific events. It was also address the challenge of combining all these individual’s location with a 3D rendering of the urban environment. The data processing and simulation approach are computationally expensive and time-critical, it relies thus on a hybrid Cloud-HPC architecture to produce an efficient solution. Within the project, new models of behavior based on data analytics were developed. It was developed the infrastructure to be able to consult various data sources such as social networks, government agencies or transport companies such as Uber. Every time there is more geolocation data available and better computation resources which allow performing analysis of greater depth, this lays the foundations to improve the simulation models of current crowds. The use of simulations and their visualization allows to observe and organize the crowds in real time. The analysis before, during and after daily mass events can reduce the risks and associated logistics costs.