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Products 8.168

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Integrating in vitro data and physiologically based kinetic modeling-facilitated reverse dosimetry to predict human cardiotoxicity of methadone

Development of novel testing strategies to detect adverse human health effects is of interest to replace in vivo-based drug and chemical safety testing. The aim of the present study was to investigate whether physiologically based kinetic (PBK) modeling-facilitated conversion of in vitro toxicity data is an adequate approach to predict in vivo cardiotoxicity in humans. To enable evaluation of predictions made, methadone was selected as the model compound, being a compound for which data on both kinetics and cardiotoxicity in humans are available. A PBK model for methadone in humans was developed and evaluated against available kinetic data presenting an adequate match. Use of the developed PBK model to convert concentration–response curves for the effect of methadone on human-induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CM) in the so-called multi electrode array (MEA) assay resulted in predictions for in vivo dose–response curves for methadone-induced cardiotoxicity that matched the available in vivo data. The results also revealed differences in protein plasma binding of methadone to be a potential factor underlying variation between individuals with respect to sensitivity towards the cardiotoxic effects of methadone. The present study provides a proof-of-principle of using PBK modeling-based reverse dosimetry of in vitro data for the prediction of cardiotoxicity in humans, providing a novel testing strategy in cardiac safety studies.

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Integrating in vitro data and physiologically based kinetic modeling-facilitated reverse dosimetry to predict human cardiotoxicity of methadone

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Combining ecosystem modeling with serious gaming in support of transboundary maritime spatial planning

The Maritime Spatial Planning (MSP) Challenge simulation platform helps planners and stakeholders understand and manage the complexity of MSP. In the interactive simulation, different data layers covering an entire sea region can be viewed to make an assessment of the current status. Users can create scenarios for future uses of the marine space over a period of several decades. Changes in energy infrastructure, shipping, and the marine environment are then simulated, and the effects are visualized using indicators and heat maps. The platform is built with advanced game technology and uses aspects of role-play to create interactive sessions; it can thus be referred to as serious gaming. To calculate and visualize the effects of planning decisions on the marine ecology, we integrated the Ecopath with Ecosim (EwE) food web modeling approach into the platform. We demonstrate how EwE was connected to MSP, considering the range of constraints imposed by running scientific software in interactive serious gaming sessions while still providing cascading ecological feedback in response to planning actions. We explored the connection by adapting two published ecological models for use in MSP sessions. We conclude with lessons learned and identify future developments of the simulation platform.

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Modeling scientific research articles

We review over 10 years of research at Elsevier and various Dutch academic institutions on establishing a new format for the scientific research article. Our work rests on two main theoretical principles: the concept of modular documents, consisting of content elements that can exist and be published independently and are linked by meaningful relations, and the use of semantic data standards allowing access to heterogeneous data. We discuss the application of these concepts in five different projects: a modular format for physics articles, an XML encyclopedia in pharmacology, a semantic data integration project, a modular format for computer science proceedings papers, and our current work on research articles in cell biology.

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Projects 18

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Aaltjes: automatisch classificeren en tellen

Aaltjes: automatisch classificeren en tellen. Agrariërs laten bodemmonsters analyseren op onder meer aanwezigheid van aaltjes. Deze bodemanalyse is voor agrariërs cruciaal om de bodemgezondheid- en vruchtbaarheid vast te stellen maar behelst een grote kostenpost. Het identificeren, analyseren en tellen van aaltjes (nematoden) in een bodemmonster geschiedt in een gespecialiseerd laboratorium. Dit is tijdrovend, specialistisch en seizoensgebonden werk. Het tellen- en analyseren van aaltjes is mensenwerk en vergt training en ervaring van de laborant. Daarnaast hebben de laboratoria te maken met personeelstekort en de laboranten met sterk fluctuerende werkdruk. Derhalve is het speciaal voor dit project opgerichte samenwerkingsverband tussen Fontys GreenTechLab, ROBA Laboratorium en CytoSMART voornemens om een oplossing te ontwikkelen voor het automatisch classificeren en tellen van aaltjes. Dit project richt zich op de ontwikkeling van een proof of concept van een analysescanner. Het werk van de laboranten wordt grotendeels geautomatiseerd waarbij door de scanner de bodemmonsters middels toepassing van deep learning en virtual modeling kan worden geanalyseerd. Daarmee wordt beoogd een oplossing te bieden waarmee het personeelstekort wordt tegengegaan, de werkdruk kan worden verlaagd, mensenwerk wordt geautomatiseerd (waardoor de kans op fouten wordt verkleind) en de kosten voor agrariërs worden verlaagd.

Finished

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Application of wastewater treatment systems to minimize the water consumption of a pulp mill located in the Rio Doce basin (WatMin).

Due to the existing pressure for a more rational use of the water, many public managers and industries have to re-think/adapt their processes towards a more circular approach. Such pressure is even more critical in the Rio Doce region, Minas Gerais, due to the large environmental accident occurred in 2015. Cenibra (pulp mill) is an example of such industries due to the fact that it is situated in the river basin and that it has a water demanding process. The current proposal is meant as an academic and engineering study to propose possible solutions to decrease the total water consumption of the mill and, thus, decrease the total stress on the Rio Doce basin. The work will be divided in three working packages, namely: (i) evaluation (modelling) of the mill process and water balance (ii) application and operation of a pilot scale wastewater treatment plant (iii) analysis of the impacts caused by the improvement of the process. The second work package will also be conducted (in parallel) with a lab scale setup in The Netherlands to allow fast adjustments and broaden evaluation of the setup/process performance. The actions will focus on reducing the mill total water consumption in 20%.

Finished

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Biglide

FDM, Fused Deposition Modeling, is de meest toegepaste techniek voor 3D printers. Het printen duurt echter lang, wat FDM minder geschikt maakt voor massaproductie. Door inzet van een slim constructieprincipe slagen we erin om de snelheid op te voeren waardoor commerciële inzet mogelijk wordt.Doel De printkop van de 3D-printer legt al snel meerdere kilometers in afstand af voor het printen van een product. Hierdoor is het FDM printen een traag proces. Het doel is dan ook om een supersnelle mechanische oplossing voor het FDM printen te ontwikkelen. Resultaten De snelheid van het FDM-printproces kon een factor twee opgevoerd worden. Door de uitvoering van de printer nam ook de footprint af, waardoor in een matrix van printers de output onbeperkt verhoogd kon worden. Looptijd 01 september 2015 - 01 juli 2020 Aanpak Een slimme samenvoeging van een cartesiaans en een delta aandrijvings-principe. Met deze ontwikkeling kunnen snelheid en precisie optimaal worden gecombineerd voor het FDM 3D print proces.

Finished

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Collaborative Networks for Sustainability (CONESU)

Collaborative networks for sustainability are emerging rapidly to address urgent societal challenges. By bringing together organizations with different knowledge bases, resources and capabilities, collaborative networks enhance information exchange, knowledge sharing and learning opportunities to address these complex problems that cannot be solved by organizations individually. Nowhere is this more apparent than in the apparel sector, where examples of collaborative networks for sustainability are plenty, for example Sustainable Apparel Coalition, Zero Discharge Hazardous Chemicals, and the Fair Wear Foundation. Companies like C&A and H&M but also smaller players join these networks to take their social responsibility. Collaborative networks are unlike traditional forms of organizations; they are loosely structured collectives of different, often competing organizations, with dynamic membership and usually lack legal status. However, they do not emerge or organize on their own; they need network orchestrators who manage the network in terms of activities and participants. But network orchestrators face many challenges. They have to balance the interests of diverse companies and deal with tensions that often arise between them, like sharing their innovative knowledge. Orchestrators also have to “sell” the value of the network to potential new participants, who make decisions about which networks to join based on the benefits they expect to get from participating. Network orchestrators often do not know the best way to maintain engagement, commitment and enthusiasm or how to ensure knowledge and resource sharing, especially when competitors are involved. Furthermore, collaborative networks receive funding from grants or subsidies, creating financial uncertainty about its continuity. Raising financing from the private sector is difficult and network orchestrators compete more and more for resources. When networks dissolve or dysfunction (due to a lack of value creation and capture for participants, a lack of financing or a non-functioning business model), the collective value that has been created and accrued over time may be lost. This is problematic given that industrial transformations towards sustainability take many years and durable organizational forms are required to ensure ongoing support for this change. Network orchestration is a new profession. There are no guidelines, handbooks or good practices for how to perform this role, nor is there professional education or a professional association that represents network orchestrators. This is urgently needed as network orchestrators struggle with their role in governing networks so that they create and capture value for participants and ultimately ensure better network performance and survival. This project aims to foster the professionalization of the network orchestrator role by: (a) generating knowledge, developing and testing collaborative network governance models, facilitation tools and collaborative business modeling tools to enable network orchestrators to improve the performance of collaborative networks in terms of collective value creation (network level) and private value capture (network participant level) (b) organizing platform activities for network orchestrators to exchange ideas, best practices and learn from each other, thereby facilitating the formation of a professional identity, standards and community of network orchestrators.

Finished

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Crossing borders at the Grensmaas

The Dutch main water systems face pressing environmental, economic and societal challenges due to climatic changes and increased human pressure. There is a growing awareness that nature-based solutions (NBS) provide cost-effective solutions that simultaneously provide environmental, social and economic benefits and help building resilience. In spite of being carefully designed and tested, many projects tend to fail along the way or never get implemented in the first place, wasting resources and undermining trust and confidence of practitioners in NBS. Why do so many projects lose momentum even after a proof of concept is delivered? Usually, failure can be attributed to a combination of eroding political will, societal opposition and economic uncertainties. While ecological and geological processes are often well understood, there is almost no understanding around societal and economic processes related to NBS. Therefore, there is an urgent need to carefully evaluate the societal, economic, and ecological impacts and to identify design principles fostering societal support and economic viability of NBS. We address these critical knowledge gaps in this research proposal, using the largest river restoration project of the Netherlands, the Border Meuse (Grensmaas), as a Living Lab. With a transdisciplinary consortium, stakeholders have a key role a recipient and provider of information, where the broader public is involved through citizen science. Our research is scientifically innovative by using mixed methods, combining novel qualitative methods (e.g. continuous participatory narrative inquiry) and quantitative methods (e.g. economic choice experiments to elicit tradeoffs and risk preferences, agent-based modeling). The ultimate aim is to create an integral learning environment (workbench) as a decision support tool for NBS. The workbench gathers data, prepares and verifies data sets, to help stakeholders (companies, government agencies, NGOs) to quantify impacts and visualize tradeoffs of decisions regarding NBS.

Ongoing

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CW.Code – Circular Wood Computational Design Tools

Hoogwaardig afvalhout van bewoners, bouwbedrijven en meubelmakers blijft momenteel ongebruikt omdat het te arbeidsintensief is om grote hoeveelheden ongelijke stukken hout van verschillende afmetingen en soorten te verwerken. Waardevol hout wordt waardeloos afval, tegen de principes van de circulaire economie in. In CW.Code werken Powerhouse Company, Bureau HUNC en Vrijpaleis samen met de HvA om te onderzoeken hoe een toegankelijke ontwerptool te ontwikkelen om upcycling en waardecreatie van afvalhout te faciliteren. In andere projecten hebben HvA en partners verschillende objecten gemaakt van afvalhout: een stoel, een receptiebalie, kleine meubels en objecten voor de openbare ruimte, vervaardigd met industriële robots. Deze objecten zijn 3D gemodelleerd met behulp van specifieke algoritmen, in de algemeen gebruikte ontwerpsoftware Rhino en Grasshopper. De projectpartners willen nu onderzoeken hoe deze algoritmen via een toegankelijke tool bruikbaar te maken voor creatieve praktijken. Deze tool integreert generatieve ontwerpalgoritmen en regelsets die rekening houden met beschikbaar afvalhout, en de ecologische, financiële en sociale impact van resulterende ontwerpen evalueren. De belangrijkste ontwerpparameters kunnen worden gemanipuleerd door ontwerpers en/of eindgebruikers, waardoor het een waardevol hulpmiddel wordt voor het co-creëren van circulaire toepassingen voor afvalhout. Dit onderzoek wordt uitgevoerd door HvA Digital Production Research Group, met bovengenoemde partners. HUNC heeft ervaring met stadsontwikkeling waarbij gebruik wordt gemaakt van lokaal gekapt afvalhout. Vrijpaleis biedt toegang tot een actieve, lokale community van makers met een sterke band met buurtbewoners. Powerhouse Company heeft ervaring in het ontwerpen met hout in de bouw. Alle drie kunnen profiteren van slimmere circulaire ontwerptools, waarbij beschikbaar materiaal, productiebeperkingen en impactevaluatie worden geïntegreerd. De tool wordt ontwikkeld en getest voor twee designcases: een binnenmeubelobject en een buitengevelelement. Bevindingen hiervan zullen leidend zijn bij de ontwikkeling van de tool. Na afronding van het project is een bètaversie gereed voor validatie door ontwerpers, bewonerscollectieven en onderzoek/onderwijs van de HvA.

Finished

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Data Engineering and Management in Dataketens | DEMAND

Digitalisering en dataficering zijn belangrijke ontwikkelingen die zich in ons dagelijkse leven voltrekken. Bedrijven worden steeds afhankelijker van data waarop ze hun bedrijfsprocessen en verdienmodellen baseren. Maar in hoeverre is die data volledig en betrouwbaar? Dataketens vormen het digitale fundament voor datagedreven organisaties om optimale bedrijfsprocessen, producten of diensten (servitization) te kunnen realiseren. De praktijk laat echter zien dat nog veel organisaties vaak te snel stappen zetten naar het ontwikkelen en implementeren van op data gebaseerde digitale oplossingen, zonder dat het ‘datafundament’ daarvoor op orde is. Dat leidt tot onbetrouwbare data en suboptimale besluitvorming. Data-engineering en -management in dataketens (DEMAND) realiseert een onderzoeksinfrastructuur die nieuwe oplossingen ontwikkelt voor geïntegreerde en gevalideerde dataketens van overheden en bedrijven. Het consortium heeft de overall ambitie om een toolbox te ontwikkelen met nieuwe toepasbare digitale technologieën en methodologieën die bijdragen aan optimalisatie van dataketens in private en publieke organisaties. Hierbij staan datagerichte activiteiten in dataketens van organisaties centraal, met inbegrip van data-acquisitie en data-opslag, data-(pre)processing, data-exploratie, data-modeling en data-benutting. Deze zogenaamde Key Enabling Methodologies verbinden mens en maatschappij langs de lat van Technical Readiness Levels en Societal Readiness Levels, zij vegroten het (toekomstig) verdienvermogen van Nederland en dragen bij aan maatschappelijke opgaven. Het DEMAND-programma wordt uitgevoerd door HAN University of Applied Sciences (HAN), Saxion Hogeschool en Fontys Hogeschool en dertien consortiumpartners met bewezen technische en organisatorische kennis van dataketens. DEMAND fungeert als bruggenbouwer tussen enerzijds de onderzoekspraktijk met de onderwijspraktijk en anderzijds de onderzoekspraktijk met het werkveld. Een set van casussen, de learning communities, vormen de basis van de onderzoeksinfrastructuur waarin de SPRONG-groep in co-creatie en interdisciplinair samenwerkt. Het consortium intensiveert de bestaande casussen én ontwikkelt daarnaast nieuwe casussen in data-intensieve omgevingen in het private als ook het publieke domein. Dit leidt tot meervoudige waardecreatie en systemische veranderingen (impact).

Ongoing

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Dieren in de Dijk

‘Dieren in de dijk’ aims to address the issue of animal burrows in earthen levees, which compromise the integrity of flood protection systems in low-lying areas. Earthen levees attract animals that dig tunnels and cause damages, yet there is limited scientific knowledge on the extent of the problem and effective approaches to mitigate the risk. Recent experimental research has demonstrated the severe impact of animal burrows on levee safety, raising concerns among levee management authorities. The consortium's ambition is to provide levee managers with validated action perspectives for managing animal burrows, transitioning from a reactive to a proactive risk-based management approach. The objectives of the project include improving failure probability estimation in levee sections with animal burrows and enhancing risk mitigation capacity. This involves understanding animal behavior and failure processes, reviewing existing and testing new deterrence, detection, and monitoring approaches, and offering action perspectives for levee managers. Results will be integrated into an open-access wiki-platform for guidance of professionals and in education of the next generation. The project's methodology involves focus groups to review the state-of-the-art and set the scene for subsequent steps, fact-finding fieldwork to develop and evaluate risk reduction measures, modeling failure processes, and processing diverse quantitative and qualitative data. Progress workshops and collaboration with stakeholders will ensure relevant and supported solutions. By addressing the knowledge gaps and providing practical guidance, the project aims to enable levee managers to effectively manage animal burrows in levees, both during routine maintenance and high-water emergencies. With the increasing frequency of high river discharges and storm surges due to climate change, early detection and repair of animal burrows become even more crucial. The project's outcomes will contribute to a long-term vision of proactive risk-based management for levees, safeguarding the Netherlands and Belgium against flood risks.

Ongoing

Products 8.168

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Integrating in vitro data and physiologically based kinetic modeling-facilitated reverse dosimetry to predict human cardiotoxicity of methadone

MULTIFILE

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