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Alkali-Activated Foams Coated with Colloidal Ag for Point-of-Use Water Disinfection
No full textAlkali-activated foams are ceramic-like materials prepared at near-ambient temperature. This study investigates them for point-of-use water disinfection, thus providing an alternative to ceramic filters fired at a high temperature. Alkali-activated foams with different compositions were characterized for the porosity, mechanical strength, shrinkage, and microstructure. The optimized foam, employing metakaolin as the raw material, was coated with a colloidal Ag solution. The disinfection performance and leaching behavior of the foams was followed in a continuous 10 week experiment, where clean water with a weekly pulse of contaminated water was distributed through the foam. The average inactivation of Escherichia coli with the Ag-coated foam was 2.84 log10, which was 1.27 units higher compared to foam without Ag. A quantitative polymerase chain reaction analysis and metagenomic sequencing verified that foams with and without Ag were both capable of reducing the microbial load. Furthermore, the changes induced by the foam with Ag on the microbial community composition, antibiotic resistome, and metal and biocide resistomes were significant. The leached concentrations of Ag, Na, Si, and Al were in accordance with the drinking water guidelines. Finally, a life cycle assessment indicated the possibility of reducing the global warming potential and the total embodied energy in comparison with a conventional ceramic filter.Materials and Environmen
Projects as a speciation and aggregation mechanism in transitions: Bridging project management and transitions research in the digitalization of UK architecture, engineering, and construction industry
No full textSociotechnical transitions are mostly seen in the literature as processes where actors and technologies in small niches peripheral to an organizational field, accumulate momentum, scale up, aggregate, and eventually bring about large-scale regime change. Foundational examples include the British transition from sailing ships to steamships and the American transition from traditional factories to mass production. Herein lies a paradox, transitions concern large scale system change for example transition to electric cars or renewable energy, but large-scale options for technological change driven by incumbents have received less attention in transitions research. This is an important opportunity for transition research to draw on the literature of project management research on large-scale projects. We bridge transitions research and project management research by exploring speciation and aggregation from both perspectives. We illustrate how this bridge may be instantiated drawing on published research and interviews on six megaprojects that have been instrumental in the digital transformation of UK construction: (i) the Channel Tunnel Rail Link, (ii) Heathrow Terminal 5, (iii) London Olympics, (iv) Crossrail, (v) Thames Tideway and (vi) High Speed Two. The speciation of digital technology seeds the process of aggregation and UK industry transition which is driven by incumbents at the organizational field core and ripples outward to its periphery. This is a reverse process to the one mostly considered in transition research where change initiates in small niches peripheral to an organizational field and propagates until it eventually brings about large-scale change to its core.Integral Design & Managemen
Homeostasis in intestinal organoids at the single cell level
No full textHow does the small intestine maintain itself? What mechanism does it use to achievehomeostasis, and how optimal is this mechanism? We approached these questionsmainly using cell tracking in organoids, for which we developed new cell trackers.We found that the intestinal crypt uses a surprisingly simple and effective strategy.Finally, we showed that cell segmentation and tracking is possible in organoids without fluorescent markers.BN/Sander Tans La
Flow partitioning between branches of the Karnali river in Nepal
No full textThe dynamics of the bifurcating Karnali river in the western plains of Nepal and India is governed by the geomorphological processes in an alluvial fan. The dynamic branches showcase a notable degree of braiding, dominant channel switching and unequal discharge partitioning. Since recent switching of the dominant channel of Karnali system occurred after an intense monsoon in 2009, the eastern Geruwa branch of the system, which used to be dominant channel passing through the Bardiya National Park, is now receiving a lower share of discharge. This situation exacerbates in the low flow periods when there is very small flow in the Geruwa branch. This decreasing discharge has been associated with depleting diversity of wildlife habitat in Bardiya National Park (Bijlmakers et al., 2023). For sustainable habitat management in the Bardiya National Park, there is a necessity to study the dynamic Karnali river and its two branches, the eastern Geruwa branch and the western Kauriala branch. Activities such as sediment mining, construction of irrigation and hydropower and inter-basin water transfer projects will potentially influence the system dynamics. Our objective is to understand the switching behaviour of the Karnali system to the natural dynamics such as bend sorting (Baar et al., 2020; Parker & Andrews, 1985) of sediments at the location where water from the main Karnali enters the Geruwa branch, and offer understanding of system response to human interventions especially with regards to the distribution of discharge between the Geruwa and Kauriala branches. We combine the technique of field observations and numerical modelling to study the system.Rivers, Ports, Waterways and Dredging EngineeringCivil Engineering & GeosciencesWater Resource
Laying the experimental foundation for corrosion inhibitor discovery through machine learning
No full textCreating durable, eco-friendly coatings for long-term corrosion protection requires innovative strategies to streamline design and development processes, conserve resources, and decrease maintenance costs. In this pursuit, machine learning emerges as a promising catalyst, despite the challenges presented by the scarcity of high-quality datasets in the field of corrosion inhibition research. To address this obstacle, we have created an extensive electrochemical library of around 80 inhibitor candidates. The electrochemical behaviour of inhibitor-exposed AA2024-T3 substrates was captured using linear polarisation resistance, electrochemical impedance spectroscopy, and potentiodynamic polarisation techniques at different exposure times to obtain the most comprehensive electrochemical picture of the corrosion inhibition over a 24-h period. The experimental results yield target parameters and additional input features that can be combined with computational descriptors to develop quantitative structure–property relationship (QSPR) models augmented by mechanistic input features.Team Arjan MolTeam Peyman Taher
Exceptional mechanical performance by spatial printing with continuous fiber: Curved slicing, toolpath generation and physical verification
No full textThis work explores a spatial printing method to fabricate continuous fiber-reinforced thermoplastic composites (CFRTPCs), which can achieve exceptional mechanical performance. For models giving complex 3D stress distribution under loads, typical planar-layer based fiber placement usually fails to provide sufficient reinforcement due to their orientations being constrained to planes. The effectiveness of fiber reinforcement could be maximized by using multi-axis additive manufacturing (MAAM) to better control the orientation of continuous fibers in 3D-printed composites. Here, we propose a computational approach to generate 3D toolpaths that satisfy two major reinforcement objectives: (1) following the maximal stress directions in critical regions and (2) connecting multiple load-bearing regions by continuous fibers. Principal stress lines are first extracted in an input solid model to identify critical regions. Curved layers aligned with maximal stresses in these critical regions are generated by computing an optimized scalar field and extracting its iso-surfaces. Then, topological analysis and operations are applied to each curved layer to generate a computational domain that preserves fiber continuity between load-bearing regions. Lastly, continuous fiber toolpaths aligned with maximal stresses are generated on each surface layer by computing an optimized scalar field and extracting its iso-curves. A hardware system with dual robotic arms is employed to conduct the physical MAAM tasks depositing polymer or fiber reinforced polymer composite materials by applying a force normal to the extrusion plane to aid consolidation. When comparing to planar-layer based printing results in tension, up to 644% failure load and 240% stiffness are observed on shapes fabricated by our spatial printing method. We demonstrate the versatility of our approach through various complex load cases which demonstrate their successful implementation of continuous fiber printing in 3D.Emerging MaterialsGroup Masani
Particle filter-based fatigue damage prognosis by fusing multiple degradation models
No full textFatigue damage prognosis always requires a degradation model describing the damage evolution with time; thus, the prognostic performance highly depends on the selection of such a model. The best model should probably be case specific, calling for the fusion of multiple degradation models for a robust prognosis. In this context, this paper proposes a scheme of online fusing multiple models in a particle filter (PF)-based damage prognosis framework. First, each prognostic model has its process equation built through a physics-based or data-driven degradation model and has its measurement equation linking the damage state and the measurement. Second, each model is independently processed through one PF to provide one group of particles. Then, the particles from all models are adopted for remaining useful life prediction. Finally, the particles from each PF are fused with those from all the other PFs to improve their particle diversity, and consequently, to provide better estimation and prognostic performance. The feasibility and robustness of the proposed method are validated by an experimental study, where an aluminum lug structure subject to fatigue crack growth is monitored by a guided wave measurement system.Group Zaroucha
Predicting cell population-specific gene expression from genomic sequence
No full textMost regulatory elements, especially enhancer sequences, are cell population-specific. One could even argue that a distinct set of regulatory elements is what defines a cell population. However, discovering which non-coding regions of the DNA are essential in which context, and as a result, which genes are expressed, is a difficult task. Some computational models tackle this problem by predicting gene expression directly from the genomic sequence. These models are currently limited to predicting bulk measurements and mainly make tissue-specific predictions. Here, we present a model that leverages single-cell RNA-sequencing data to predict gene expression. We show that cell population-specific models outperform tissue-specific models, especially when the expression profile of a cell population and the corresponding tissue are dissimilar. Further, we show that our model can prioritize GWAS variants and learn motifs of transcription factor binding sites. We envision that our model can be useful for delineating cell population-specific regulatory elements.Pattern Recognition and Bioinformatic
Design for behaviour change of consumers around furniture repair and upgrading
No full textThis Design for Interaction master thesis is focussed on the development of a design intervention to encourage consumer behaviour towards DIY repair and upgrading of furniture. The project was carried out in collaboration with the Behaviour Insights Team of the Ministry of Infrastructure and Water Management and Het Groene Brein.Problem background:Furniture is a product category which causes a large environmental impact due to the materials they contain and consumers’ current replacement behaviour. In the Netherlands, over half of the large amount of disposed furniture pieces have not reaching the end of their lifespan (Koch & Vringer, 2023). Increasing repair and upgrading behaviour can extend the life of damaged or undesired furniture pieces and thereby reduce environmental impact.Research & design goal:Literature research, generative sessions, a survey and expert interviews were used to determine how a design intervention can most effectively contribute to the desired behaviour change. It was concluded that the design should support 18-35 aged, high income, high education consumers, living in the big cities, to ...1. … make a plan with a desired outcome for ...2. … together perform ...... DIY repair and/or upgrade activities for furniture from the low/medium priced segment made from wood and/or textile and foam in 2024. Design proposal:The outcome of this master thesis is a design intervention named ‘Opknappers,’ a proposal for Intergamma (the umbrella organization of Karwei and Gamma). The proposal includes DIY cards and an exposition showcasing and explaining repair/upgrade possibilities in the physical shops. Additionally, a concept for the Opknappers app has been developed, which allows consumers to visualise upgrade options for their own furniture. Finally, a plan was made for using Intergamma’s websites and social media to support consumers in the DIY process. The final design was evaluated with customers and employees of Intergamma, and final improvements and recommendations were made.Design for Interactio
Context-specific value inference via hybrid intelligence
No full textHuman values are the abstract motivations that drive our opinions and actions. AI agents ought to align their behavior with our value preferences (the relative importance we ascribe to different values) to co-exist with us in our society. However, value preferences differ across individuals and are dependent on context. To reflect diversity in society and to align with contextual value preferences, AI agents must be able to discern the value preferences of the relevant individuals by interacting with them. We refer to this as the value inference challenge, which is the focus of this thesis. Value inference entails several challenges and the related work on value inference is scattered across different AI subfields. We present a comprehensive overview of the value inference challenge by breaking it down into three distinct steps and showing the interconnections among these steps.Interactive Intelligenc