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Estimating 3D Ground Reaction Forces During Daily Activities:A Reduced Sensor Setup and Virtual Pivot Point Approach
Get PDFGround reaction forces (GRF) during daily activities are critical for assessing joint loading, particularly in individuals with osteoarthritis (OA). Traditional GRF measurements rely on force plates, which restrict their use to laboratory environments. This study presents a novel method for estimating 3D GRF using a minimal sensor setup comprising three inertial measurement units (IMUs) and pressure insoles (PI), and exploiting the biomechanical concept of Virtual Pivot Point (VPP) to distribute the total GRF between the feet. Data were collected during various activities of daily living (ADL), including walking tasks, stair ascent/descent, and sit-to-stand movements. The proposed system demonstrates high accuracy, achieving relative root mean squared errors (rRMSE) below 15% and correlation coefficients exceeding 0.7 for all tasks, except sit-to-stand movements during Timed Up and Go test (TUG). This approach significantly reduces the sensor burden while maintaining performance comparable to more extensive setups. By combining the estimated 3D GRF with kinematics, joint loading can be estimated, enabling a portable setup for monitoring healthy subjects during ADL in real-world settings. The open-source MATLAB code and dataset are available in the 4TU Research Data repository
From MODIS to Sentinel-2:A regional comparative analysis of crop-yield prediction with matched spatiotemporal data
No full textLarge-scale crop yield mapping has long relied on the Moderate Resolution Imaging Spectrometer (MODIS) due to its high temporal resolution and consistent atmospheric correction. The Sentinel-2 constellation, with its finer spatial resolution and vegetation-sensitive spectral bands, now offers new opportunities for regional- and field-scale yield prediction—especially as MODIS nears the end of its operational life. However, it remains unclear whether Sentinel-2 can ensure continuity of MODIS-based estimates across diverse agricultural regions. We present a regional sensor-to-sensor comparison of MODIS and Sentinel-2 for crop yield prediction using matched spatiotemporal inputs across two agro-ecological zones. Using reproducible regression workflows, we demonstrate that Sentinel-2 captures finer spatial variation in crop phenology and consistently outperforms MODIS in terms of predictive accuracy. For cotton, Sentinel-2 achieved an RMSE of 123.52 lb/acre and R 2 of 0.76, versus MODIS with 129.20 lb/acre and R 2 of 0.74. For corn, Sentinel-2 achieved 8.40 Bu/acre and 0.79, outperforming MODIS at 8.69 and 0.66, respectively. SHAP analysis identifies Enhanced Vegetation Index (EVI), Fraction of Photosynthetically Active Radiation, and Leaf Area Index as key predictors across both sensors. Despite its lower temporal frequency, Sentinel-2 delivers robust, regionally consistent estimates, supporting its suitability as a successor to MODIS for operational crop monitoring.</p
Pathways to Planetary Health:Integrating Systems Thinking and Futures Approaches in Engineering Education to Address the Health-Environment Nexus.
No full textAs scholars and professionals expand their understanding of anthropogenic environmental changes threatening human and planetary well-being, they must engage with interconnected social, economic, and environmental issues. This requires acquiring new knowledge and skills to deepen their understanding of the complex and reciprocal relationship between human well-being and the health of the natural systems upon which it relies. Designers and engineers play a critical role as change agents by their capacity to design systemic interventions that drive climate action. Given the ongoing environmental and health crises, it is crucial for them to develop competencies in systems-based, future-oriented, and integrative approaches to health. Nevertheless, the existing literature reflects a limited number of attempts to explore the implementation of such holistic and integrative approaches, aiming at preparing design and engineering students to contribute to pathways toward planetary health futures. A narrative review was conducted on systems thinking, strategic foresight and integrative approaches to planetary health education and practice, with the aim of supporting the development and implementation of a systemic design methodology within engineering education. In addition, critical analyses of pedagogical practices and the student learning process are presented, informed by observations of design activities and outcomes, which reflect on the challenges and opportunities encountered in a graduate course delivered by the authors. Moreover, we correlate these experiences with existing literature in the field, thereby establishing connections that underscore best practices and identify areas for improvement. The results demonstrate how students address planetary health challenges using a project-based pedagogical approach, emphasising interdisciplinary collaboration within small groups as they engage with complex real-world problems. The findings reveal the implications of adopting the methodology Systemic Design for Planetary Health, exploring various challenges encountered, and providing recommendations for improving course design, content and future iterations. The findings of the study hold significant value for educators who are integrating planetary health, systems thinking, and futures thinking into design and engineering curricula, as well as for professionals aiming to implement systems practice to address challenges within the health-environmental nexus. From a broader perspective, these findings contribute to advancing future research and educational practices within the realm of planetary health education.<br/
Subsurface sediment properties and potential impacts of marine sand extraction on sand wave occurrence on the Netherlands Continental Shelf
No full textBedform existence in shallow shelf seas is predominantly controlled by the surface sediment characteristics. However, the sediment characteristics might change following sediment extraction, as this exposes a currently burried layer. This study presents a method to use existing sediment data to map the median grain size and mud content in the current surface layer and the deeper layer, to quantify the change between the layers and to analyse how this change might affect sand wave occurrence. When applied to the Netherlands Continental Shelf, this reveals that, on average, the deeper layer contains finer (230 versus 219 μm) and muddier (1.7 versus 1.3%), although local variations can be considerable. Furthermore, our results suggest that the potential exposure of the deeper layer might reduce the sand wave area by 300 km2
Exploring the AI electricity crisis scenario:A case study of Texas-ERCOT
Get PDFThis article explores artificial intelligence (AI) effects on data center electricity consumption by answering the question if and when AI growth may cause an electricity crisis. We study this through combining 3 AI demand electricity and 3 electricity supply scenarios to 9 scenarios and simulating these for estimating their longer-term outcomes on anticipated reserve margins (ARM). These scenarios contain multiple theoretical constructs for explaining AI impact on data centers via a system dynamics narrative, i.e. non-linear predictions with feedbackmechanisms through time. We apply our system dynamics simulation model to a specific region because possible conflicts between data center electricity demand and electricity supply capacity manifest themselves only at a regional level. As a case for our simulations, we selected Texas-Electric Reliability Council of Texas (ERCOT): an electricity region covering most of the state of Texas. Being a very energy rich area, we see only a few conditions in which an AI electricity crisis, i.e., an ARM below the reference margin level (RML), may happen in Texas-ERCOT, but a decline of the ARM from 31.2% in 2025 to between 7 (which is below the needed 13.75% RML) and 25% in 2030 with data centers taking about 21–26% of all electricity available may likely happen around 2030. The application of our method in other regions may give very different outcomes, but also the Texas-ERCOT region is not free of risks. While this paper focuses on direct AI impacts, it also suggests the need for future studies exploring the indirect effects of increased data center usage on the economy, society, and ecology
The Effect of Salt and Monomer Distribution on the Electroresponse of Partially Charged Polyelectrolyte Brushes
Get PDFPolyelectrolyte brushes reorganize when they are placed in electric fields, which allows for a field-induced collapse or swelling. While these systems have been studied theoretically in detail under salt-free conditions, the effect of salt on the electroresponse has been less systematically explored. Yet, in potential applications, for example, for anti-fouling, in biomedical systems or in the food industry, polyelectrolyte brushes are almost always in contact with solutions that contain salt. We use coarse-grained molecular dynamic simulations and Scheutjens-Fleer self-consistent field theory to study the effect of salt on the electroresponse of two different polyelectrolyte brushes: a random copolymer of neutral and charged monomers and a gradient copolymer where the composition gradually changes from neutral at the grafting plane to charged at the free end. We find that salt only has a limited effect of the electroresponse when the brush is in the osmotic regime at low salt concentrations, while it stifles the response in the salted regime at high salt concentrations. Additionally, we find that the electroresponse in the transition between these regimes is significantly affected by chain architecture. Our results show that the electroresponse of polyelectrolyte brushes can still be used at salt concentrations as they occur in practical applications.</p
K−factor Emulation in Different OTA Chambers
Get PDFThis paper discusses over-the-air testing chambers and the principles behind emulating Rician-distributed channel fading envelopes of the propagation channel.The discussed chambers are the classical reverberation chamber, the vibrating intrinsic reverberation chamber, the multi-probe anechoic chamber, the resonating cavity hybrid anechoic-reverberation chamber, and the aveguide hybrid anechoic-reverberation chamber.</p
Friend, Foe, or Target? Domain Models as Risk Deterrents, Risk Sources, and Assets at Risk
No full textModelers and organizations often struggle to assess the benefits and drawbacks of modeling activities. This paper proposes addressing this challenge through a risk-oriented lens, leveraging the Common Ontology of ValuE and Risk (COVER) and the Reference Ontology for Security Engineering (ROSE). The proposal focuses on identifying assets at risk throughout the modeling process to clarify: when models mitigate risks and contribute to cost savings (models as risk deterrents), when models introduce risk to other assets (models as risk sources), or when they are vulnerable to risk events themselves (models as assets at risk), potentially generating additional costs. This perspective enables modelers and organizations to evaluate the benefits and costs of modeling practices, aligning investments with organizational goals, while helping researchers identify gaps for enhancing modeling languages, methods, and tools. The proposal is evaluated by analyzing case studies from the literature and interviews with nine professionals and researchers.</p
Teacher in the Loop:Customizing Educational Games Using Natural Language
Get PDFDespite significant advances in educational technology and design methodologies, current educational games demonstrate a fundamental limitation: educators are unable to modify content after the games are deployed, limiting curriculum alignment and pedagogical customization. This paper introduces Imikathen-VR, a solution built upon a text-to-animation system, supporting K-1 and K-2 teachers to create minigames for their students to practice basic writing skills. Our implementation extends an existing animation pipeline by integrating a fine-tuned T5 model for sentence simplification, achieving 95% F1 BERT score and 76% ROUGE-L score in maintaining semantic and lexical fidelity. We improve visual reasoning by transforming the task of identifying missing visual details into a Masked Language Modeling problem. Preliminary results demonstrate the system's effectiveness in generating curriculum-aligned VR exercises, though comprehensive classroom testing remains pending. This work advances the integration of customizable VR technology in early education, providing teachers with enhanced control over educational content.</p
Development of Models to Quantify Training Load in Outdoor Running Using Inertial Sensors
No full textRunning is a popular sport that offers health benefits but also poses a high risk of overuse injuries, often leading to a temporary or permanent cessation of running. These injuries are often caused by repetitive mechanical loading, emphasizing the need to quantify training loads to understand injury development. While such quantification is feasible in controlled settings like gait labs, capturing accurate data in natural outdoor conditions is challenging. This requires a practical sensor setup that is feasible for daily use and robust modelling approaches to relate sensor-derived data to mechanical load. We address these challenges by quantifying biomechanical loads during outdoor running using a minimal sensor setup. A key achievement is a model that uses inertial sensors to estimate vertical ground reaction forces (GRFs) used to estimate load. Moreover, we show that runners’ perceived exertion is often misaligned with sensor-derived load measurements, highlighting the importance of combining subjective and objective metrics for a holistic view of training loads. The discrepancy also underscores the need to quantify structure-specific loads, such as forces on the lower legs, to better understand their potential role in mechanical fatigue and injury risk. We present a neural network model to estimate 3D GRFs needed to quantify these structure-specific loads accurately. These results advance biomechanics with novel data methods for quantifying training loads in outdoor environments with a feasible setup for many runners, enabling large future studies to better understand injury mechanisms. The study highlights the difficulty of data analysis when moving from a controlled situation in the laboratory to a large study outside the laboratory.</p