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Ontology for Personalized Recipe Recommendations Supporting Sustainability, Personal Preferences, and Health Restrictions
No full textMany people consume food without having enough information about its nutritional value, environmental impact, or how it aligns with their personal preferences, health, and sustainability goals. With increasing concerns about human health and sustainability, there is a growing need for tools that help individuals make better-informed food choices. This paper introduces the SustainHealthyFood ontology to be used as a reference model for sustainable and healthy food consumption. The ontology serves two key purposes: (1) helping users make informed decisions by providing insights into food nutrients and Eco-Scores, enabling them to assess both health and environmental impact; and (2) facilitating personalized food recommendations, such as recipe suggestions, tailored to individual preferences, personal attributes, dietary needs, health conditions, and goals. The SustainHealthyFood ontology consists of four OntoUML conceptual models focusing on: (1) Food Nutrition, (2) Health Status and Diet, (3) Environmental Sustainability, and (4) Explainable Recommendations. The operational ontology is implemented in OWL, with instances populated from existing datasets in the domains of food and environmental sustainability. For ontology testing, SPARQL queries are used to assess whether the ontology meets the competency questions. This paper describes and evaluates the SustainHealthyFood ontology, presents related work, and discusses benefits, limitations, and future work
Concurrent multi-scale modeling of granular materials:Benchmarking volume-coupled DEM-FEM models across elastic and elasto-plastic regimes
No full textWe develop and benchmark a concurrent DEM–FEM scheme that couples particle and continuum physics via an overlapping region with penalty-enforced kinematic compatibility, implemented in Kratos Multiphysics. Analysis spans three levels: (i) a mono-disperse elastic column with an exact reference, (ii) an elastic polydisperse assembly, and (iii) an elasto-plastic polydisperse assembly whose continuum follows a Drucker–Prager law calibrated to DEM data through Bayesian inference. We quantify how penalty magnitude, spatial weighting, and mesh-to-particle size ratio govern stress/strain transfer, lateral stress ratio , and the emergence of local overlap artefacts, and show that smooth weights and sufficient Gauss-point sampling suppress spikes without degrading accuracy. Across friction levels, the hybrid model closely reproduces DEM axial hysteresis and lateral–vertical stress paths, and macroscopic discrepancies align with contact-scale slip statistics, highlighting the limitations of an elastic–plastic (Drucker Prager) FEM model in capturing dilatancy evolution and path dependence. The results provide practical guidance on parameter selection and hybrid-zone design, demonstrate scalability to large granular systems, and indicate the specific flow regimes in which a more advanced continuum model (e.g. with non-associated plasticity, strain hardening/softening, or fabric evolution) would be needed to fully match DEM
Comparative Analysis of Operation and Maintenance Practices in Community-Based Solar Microgrids
Get PDFCommunity-based solar microgrids face significant sustainability challenges, particularly in the context of remote islands where resources and infrastructure are limited. Effective operation and maintenance (O&M) are crucial to address these challenges. This study presents empirical evidence from four solar microgrids on an Indonesian island, focusing on their O&M practices and electricity service levels based on the Multi-Tier Framework. It also examines the influence of design, management structure, and geographical characteristics on microgrid sustainability. Data was collected through direct observation and stakeholder interviews, allowing for a comparative analysis of the four microgrids. The findings reveal notable disparities, with two microgrids located near the district capital showing early abandonment and signs of deterioration
Influence of varied assistance levels provided by a dual-joint active back-support exoskeleton on spinal musculoskeletal loading and kinematics during lifting
Get PDFAn active dual-joint back-support exoskeleton with motors at both lumbar and hip level was designed to reduce spinal musculoskeletal loading and preserve lumbar flexibility during lifting. A subject-specific controller estimated the moment actively generated by back muscles to counteract gravitational forces on the upper body, minimising a counter-productive abdominal muscle contraction. Eight subjects lifted a 15 kg load using free technique with four assistance levels, i.e. 0%, 30%, 50%, and 70% of the active moment. Time-averaged L5S1 compressive force and back muscle active moment estimated by an EMG-driven biomechanical model, decreased by 5.5–9.3% and 14.9–28.6%, respectively, with non-zero assistance. Higher assistance did not yield larger L5S1 compression reduction but did gain further reduction in the time-averaged back muscles active moment. No significant changes in abdominal muscle activity and minor changes in lumbar flexion were observed suggesting the controller and dual-joint design achieved their objectives
Surgical Skills training with PRIDE - Pre-clinical Redesign with Inclusiveness, Diversity and Equity
No full textIntroductie: Chirurgie staat niet bekend als een inclusief en divers werkveld. Normen, waarden en gebruiken die tijdens chirurgisch simulatieonderwijs worden besproken hebben rote impact op studenten. Helaas hebben scenario’s onbewuste vooringenomenheid richting mainstream groepen en individuen en zijn daardoor minder toegankelijk voor personen met een beperking of andere minderheden. Er is behoefte aan betere toegankelijkheid voor fysiek, visueel of auditief beperkte mensen en personen met neurodiverse kenmerken. Het is van belang om binnen medisch simulatieonderwijs, gender- en afkomst gerelateerde gelijkheid te bevorderen. Middels DE&I-evaluatie en herontwerp van het vak Surgical Skills (Technische Geneeskunde, Universiteit Twente) nemen we deze ongelijkheden weg en biedt het inzicht in de impact hiervan op studenten.Methoden: Surgical Skills studenten van vorig jaar vullen als controlegroep een DE&I-vragenlijst in als kwantitatieve nulmeting. Het vak wordt via de SIM-EDI tool geanalyseerd, gevolgd door een DE&I focusgroep met stakeholders, waarbij de SIM-EDI resultaten als input gelden. Op basis van deze uitslagen en inzichten wordt het vak aangepast naar een toegankelijker, inclusiever en diverser vak voor de huidige lichting studenten (24/25). Zij vullen dezelfde vragenlijst in als kwantitatieve beoordeling van de aanpassingen. Verwachte resultaten: De SIM-EDI tool geeft inzicht in de DE&I-domeinen ‘EDI in learning situations’, ‘Missed Opportunities’, ‘Harms’, Potential Biases’ en ‘Action Items’. Verwachte resultaten van de studentenenquête zijn: inclusievere simulatiecasussen, neurodiversvriendelijke colleges, samenstelling van het Surgical Skills team en toegankelijkheid van(diverse) oefenmaterialen.Discussie & Conclusie: Doordat in chirurgisch simulatieonderwijs studenten een breder beeld aan patiënten of collegae leren kennen, bereiden we studenten beter voor op de praktijk. Mogelijkerwijs leidden DE&I elementen uit één domein tot verminderde diversiteit of toegankelijkheid op een ander domein, waardoor balans tussen aanpassingen cruciaal is om stereotypering en uitsluiting te voorkomen
Advancing groundwater hydrology in a data-scarce mountainous catchment on the Tibetan plateau:challenges and innovations
Get PDFClimate warming is altering the water cycle on the Tibetan Plateau (TP). Groundwater is a crucial component for human use within this cycle. However, studying groundwater on the TP faces significant challenges due to data scarcity, complex topography, and intricate geology. This thesis aims to understand the groundwater in the Maqu catchment, a data-scarce area on the TP, and to explore the importance of groundwater modeling in mountainous regions. In Chapter 2, intensive fieldwork was carried out to obtain a comprehensive dataset, including borehole core lithology, soil thickness, altitude, hydrogeological data (groundwater level and aquifer test data), and hydrogeophysical data (MRS, ERT, and TEM). The hydrogeological surveys reveal that groundwater flows from the west to the east, recharging the Yellow River. The hydraulic conductivity ranges from 0.2 m d-1 to 12.4 m d-1. The MRS soundings results, i.e., water content and hydraulic conductivity, confirmed the presence of an unconfined aquifer in the flat eastern area. Based on TEM results, the depth of the Yellow River deposits was derived at several places in the flat eastern area, ranging from 50 m to 208 m. Most soil thicknesses, except on the valley floor, are within 1.2 m in the western mountainous area of the catchment, and the soil thickness decreases as the slope increases. In Chapter 3, the hydrogeochemical composition and stable isotopes (δD and δ18O) of surface water and groundwater samples collected in the Maqu catchment were analyzed to characterize the surface water and groundwater, investigate the contributions of different sources, and determine CO2 consumptions. Different techniques were used, including inverse modeling, end-member mixing analysis (EMMA), and a forward mass balance model. The results indicated that all water samples are of the HCO3-Ca type. Both the surface water and groundwater are of meteoric origin and there is close contact between them (except wetlands). Water in the wetlands is substantially evaporated (0-45%). Calcite and illite generally precipitate, whereas chlorite and CO2 generally dissolve along groundwater flow paths in the east. The mean contributions of fresh surface waters, mountain-front groundwaters, and anthropogenic inputs to the surface water samples are 56%, 16%, and 28%, respectively. Carbonate and silicate weathering are the dominant sources of major cations. Moreover, high CO2 consumption rates in both the surface runoff and groundwater make the Maqu catchment an important carbon sink in the Yellow River Basin. In Chapter 4, a systematic methodology for integrating diverse datasets from various sources to develop a comprehensive conceptual model for the Maqu catchment is proposed. The approach incorporates a wide range of data including hydrogeological and hydrogeophysical data, bedrock depth information, reanalysis datasets, and satellite-derived gravimetry and altimetry data. Within the framework of the Maqu catchment's hydrogeological conceptual model, the driving forces and state variables are presented; a hydrostratigraphic unit and system parameters are determined; the flow system, hydrogeological boundary conditions, preliminary water balance, and water storage are analyzed. Finally, a one-layer numerical model, with a shallow, unconfined layer is recommended. Based on the numerical model by Yu (2022), the time-varying stages of the Yellow River and reanalysis precipitation data are incorporated into the integrated hydrological model STEMMUS-MODFLOW. The proposed method for developing hydrogeological conceptual models is expected to be readily extended to other data-scarce catchments on the Tibetan Plateau. In Chapter 5, compared to the previous groundwater model, notable enhancements to the hydraulic conductivity, specific yield, and recharge have been made. These improvements are attributed to the inclusion of additional groundwater level data and MRS-estimated hydraulic conductivities during the calibration process. Simulating only the downstream flat region may result in severe underestimation of groundwater recharge. The groundwater level in upstream mountainous regions exhibits greater sensitivity to recharge compared to the downstream flat regions. This implies that a more accurate representation of recharge dynamics can be achieved through the calibration process using time-series groundwater level data from the upstream mountainous regions. Consequently, the inclusion of upstream mountainous regions is essential in groundwater modeling. To extend parameters from points to the entire Maqu catchment, both inverse distance weighting (IDW) and Ordinary cokriging (OCK) are implemented. The performances of simulated results using interpolated hydraulic conductivity, specific yield, and recharge derived from IDW and OCK are generally similar. However, each interpolation method exhibits distinct strengths and limitations. IDW produces smooth interpolated results, leading to good simulations of groundwater levels in data-sparse areas. However, it struggles to adequately capture spatial variabilities in parameters. In contrast, OCK, which integrates diverse spatial information, effectively represents parameter spatial variabilities. Consequently, it yields good simulations in data-sufficient areas but exhibits weaker performance in data-sparse areas. This thesis contributes to the understanding of groundwater in the data-scarce Maqu catchment on the Tibetan Plateau, and highlights the importance of groundwater modeling in mountainous regions. Both relevant observations and numerical modeling tools are required to advance the understanding of the groundwater system at different temporal and spatial scales under current and future climate conditions in future studies
Role of Mass Transfer Phenomena in Electrochemical Nitrate Reduction:A Case Study Using Ti and Ag-Modified Ti-Hollow Fiber Electrodes
Get PDFDecentralized electrochemical reduction of nitrate into ammonium is explored as a viable approach to mitigate nitrate accumulation in groundwater. In this study, tubular porous electrodes made of titanium (termed hollow fiber electrodes or HFEs) were successfully modified with silver (Ag) nanoparticles through electrodeposition. Under galvanostatic control and in acidic electrolyte, Ag deposition on Ti HFE resulted in an increase in the Faradaic efficiency for ammonium formation from low concentrations of nitrate (50 mM), but only under reaction conditions of restricted mass transport. For conditions of favorable transport, facilitated by an inert gas flow (Ar) exiting the pores, a higher nitrate conversion but an increase in hydroxylamine selectivity at the expense of the ammonium selectivity are observed for Ti/Ag hollow fiber electrodes. For Ti/Ag electrodes, it is concluded that ammonium formation is prevented by effective removal of surface intermediates. Remarkably, for unmodified Ti hollow fiber electrodes, the Faradaic efficiency to ammonium is significantly improved when operated at high current densities and in conditions of high mass transport. The selectivity to liquid products even surpasses the selectivity of Ti/Ag electrodes. These findings indicate that nitrate reduction to ammonium at Ti and Ti/Ag hollow fiber electrodes can be achieved at comparable rates but under distinctly different process conditions. In fact, for Ti electrodes, operation at a lower applied potential compared to Ti/Ag electrodes is feasible, ultimately resulting in reduced energy consumption. This study thus highlights the importance of controlling the interfacial electrode environment, particularly when comparing and evaluating the effectiveness of electrode materials in electrochemical nitrate reduction. The study also reveals that transport phenomena affect electrode material-dependent activity–selectivity correlations and must be considered in ongoing material development efforts
Every Shot Counts:Using Exemplars for Repetition Counting in Videos
Get PDFVideo repetition counting infers the number of repetitions of recurring actions or motion within a video. We propose an exemplar-based approach that discovers visual correspondence of video exemplars across repetitions within target videos. Our proposed Every Shot Counts (ESCounts) model is an attention-based encoder-decoder that encodes videos of varying lengths alongside exemplars from the same and different videos. In training, ESCounts regresses locations of high correspondence to the exemplars within the video. In tandem, our method learns a latent that encodes representations of general repetitive motions, which we use for exemplar-free, zero-shot inference. Extensive experiments over commonly used datasets (RepCount, Countix, and UCFRep) showcase ESCounts obtaining state-of-the-art performance across all three datasets. Detailed ablations further demonstrate the effectiveness of our method
An updated version of the SZ-plugin:from space to space-time data-driven modeling in QGIS
Get PDFThe geospatial community usually makes use of GIS environments to handle databases and pre-process their information. Actual analyses, especially data-driven ones, are performed outside GIS platforms. This interrupts the flow of information and the processing chain in a number of I/O operations that inevitably slow down the overall analytical protocols. The first version of the SZ-plugin attempted to mitigate this issue by offering a modeling solution from within QGIS. However, the available models in the SZ-plugin essentially boiled down to binary classifiers, whose dimensionality was constrained to address pure spatial problems. In this updated version, we focused on two major aspects: 1) a space-time extension and 2) the inclusion of a regression option in addition to the already existing classification one. These two aspects have been introduced as part of two new models, namely, a Generalized Additive Modeling and a Multi-Layer Perceptron. In short, these would allow users to obtain susceptibility and intensity estimates in space and time. An improved graphical reporting tool has also been implemented. This makes it possible to produce relevant statistical summaries as well as cartographic outputs for users to directly integrate into their technical reports or scientific documents. The problem of landslide prediction is taken as a reference in Taiwan, but the same plugin can be used to perform regressions or classifications for any other phenomenon associated with (e.g.) digital soil mapping, wildfire and gully erosion modeling, land-use or tree species detection, etc
