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Therapeutic Analysis of a Ligament Regeneration System
No full textUlnar collateral ligament (UCL) injuries have become a major concern for athletes, particularly overhead throwing athletes, and are especially concerning in youth athletics. Surgical intervention options include UCL Reconstruction, commonly referred to as Tommy John surgery, and Arthrex™ InternalBrace™ Ligament Augmentation. The goal of this project was to analyze a scaffold that promotes biological healing to a grade two tear of the UCL and works in conjunction with an Arthrex™ InternalBrace™ surgical repair. This goal was met using Platelet Derived Growth Factor Isomer BB (PDGF-BB) as the growth factor of choice due to its proliferative qualities, and a fetal engineered biological matrix (f-EBM) as the scaffold material due to its innate biological compatibility. Experiment 1 investigated the loading and release kinetics of the f-EBM with different loading concentrations of bovine serum albumin (BSA), which was used as an analog for PDGF-BB. Results showed the BSA was successfully loaded onto f-EBM patches at varying amounts for varying soaking concentrations. Further results showed the release kinetics of patches loaded in the 100 µg/mL soaking solution produced the most promising results with sustained release of BSA from patches. Experiment 2 focused on analyzing tissue outgrowth; however, due to limited experimental outcomes, results were presented as recommendations for future protocols rather than definitive findings. Ultimately, this device is expected to significantly improve the treatment of partial UCL tears in athletes who perform overhead throwing
Incorporating Sustainability Into Moroccan Engineering Higher Education
No full textEngineering projects are often entwined into critical aspects of infrastructure, directly impacting the lives of the public. Higher education institutions (HEIs) play a critical role in preparing future engineers to address the social, economic, and environmental issues encapsulated by sustainable development (SD). The purpose of this research was to examine opportunities for Moroccan HEIs looking to incorporate SD. We conducted interviews with administrators, faculty, and students at three technical universities in Rabat. We noted disparities between the capacities of private and public universities, with accreditation systems emerging as a major influence. Based on these findings, we made recommendations for how Moroccan HEIs can further adopt SD principles into their engineering programs
Simultaneous Task Scheduling and Coalition Formation in Multi-robot Systems Using Centralized and Decentralized Methods
No full textMulti-robot systems offer tremendous potential for complex missions through their parallelism, redundancy, and diverse capabilities. However, coordinating heterogeneous robots to work together and schedule tasks efficiently remains challenging. This dissertation introduces and solves the Simultaneous Task Scheduling and Coalition Formation (STSCF) problem, where robots with diverse skills must collaborate to complete tasks requiring multiple complementary capabilities. We present four approaches that span the spectrum from optimal to practical solutions. First, we develop an Integer Linear Programming (ILP) formulation that provides optimal solutions but struggles with scalability. Second, we design a heuristic method that achieves near-optimal solutions, typically within 1.3-2x of optimal, while being orders of magnitude faster in computation. Third, we introduce \emph{HeteroSync Scheduler (HeSS)}, a decentralized algorithm that eliminates single points of failure introduced by centralized scheduling, but requires careful parameter tuning. Finally, we present \emph{Greedy HeSS (G-HeSS)}, which employs a task-by-task allocation strategy that consistently produces high-quality solutions without careful parameter adjustment. Through extensive evaluation across general scenarios, challenging edge-case, and large-scale scenarios, we demonstrate that G-HeSS strikes the best balance between solution quality and computational efficiency while maintaining the advantages of decentralized operation. Our work reveals a counterintuitive insight: in highly interdependent multi-robot systems, simpler incremental decision-making processes can outperform sophisticated optimization approaches that attempt to solve the entire problem simultaneously. This research provides practical solutions for real-world applications in space exploration, warehouse automation, and disaster response, where efficient heterogeneous multi-robot coordination is essential. The contributions advance our understanding of distributed algorithms for complex scheduling problems and establish a foundation for future work in resilient, adaptive multi-robot systems
Replacing Large Language Models For Personalized Robot Behavior
No full textUnderstanding semantics of the environment can allow robots to personalize for their users, and help them in everyday life. Popular machine learning tools such as Large Language Models (LLMs) have proven to be extremely useful for extracting and understanding semantic information from language. Yet they suffer from problems such as hallucinations, jailbreaking, and the physical sizes of the models make them unable to be run on the edge. In this research I compare methods that are not reliant on predefined information of the environment to replace the complexity of LLMs to learn contextual information. I adapt statistical methods such as the moving average, Bayesian inference, and a simple Neural Network (NN), to ground objects based on the users preferences in their environment. This allows the robots to become more predictable, safe, and accurate, while maintaining the ability to personalize to their users. All of these models exist under one generalised package that can be deployed on any robot under any environment that has the room and object information. These methods are then evaluated based on how well they do against an LLM in a task that requires understanding of the environment. Finally, I built the WorldGenerator and WorldActions software architecture around the PyRoboSim simulator to enable fast world building, and robot method testing
Serious Game Workshops: Exploring A Tool for Science-Policy
No full textThe Engage program, a joint initiative of the ETH domain, has developed a serious game to allow participants to utilize competencies and improve dialogue. Our goal was to evaluate the potential of serious games in improving different competencies in scientists when participating in science policy dialogue. We accomplished this by co-developing an evaluation procedure with Engage, holding a workshop session with scientists, interviewing them using Q-Methodology, and analyzing the subjective opinions of participants on how competencies were utilized. The results we found were inconclusive in how participants utilized competencies, but we found that there were certain skills that the game excelled in improving
Engineering Catalytic Transients in Microreactors for Tunable Surface Oxidation
No full textConventional chemical manufacturing has efficiently matched fast-growing global demand for energy and downstream chemicals by leveraging economies of scales; but next generation manufacturing needs to accommodate low volume/geographically distributed resources, changes in production volume, supply chain disruptions, and fast implementation of new products, all without introducing diseconomies of scale. These urgent needs and technical hurdles have given rise to a new strategy for small-scale, modular chemical systems designed for distributed chemical manufacturing (DCheM). Modularization has successfully worked for lab-on-chip reactors, 3D printers and even steam methane reformers, but bulk and commodity chemicals need more advanced small-scale systems: microreactors. Fast heat and mass transfer in microreactors gives substantive advantages for energy and material savings but also the use of otherwise unachievable modes of operation like forced periodic operation (FPO). While catalytic systems are known to be dynamic, they are often considered at their thermodynamically equilibrated state, which is subject to the Sabatier optimum, the maximum activity reached by the ideal catalyst that balances surface interactions just right. FPO relaxes that assumption by forcing changes to the microenvironment of a catalyst, through modulation of process inputs like temperature, feed composition, etc., and has already shown enhancement in performance beyond thermodynamic limits. Catalytic surfaces respond to a perturbation with initial coverage changes that can enhance reaction rates during the transient before the system re-equilibrates to a new state. Over the past 50 years, the field has made strides in establishing theoretical frameworks and more sparsely experimental approaches to probe the role of periodic operation in achieving higher reaction rate and selectivity, lower light-off temperature for oxidation chemistries, among others. Recently, innovative reactor designs have been developed to push the boundaries of experimental advances in FPO. The present thesis supports that undertaking with the development of a microreactor and feed modulation systems to investigate non-equilibrium coverage control for methane oxidation reactions. It comprises three key contributions to the field as well as other on-going and proposed work. The first direction outlines the design of a feed modulated microreactor capable of millisecond gas pulsing, the fastest reported thus far, and sets the framework for engineering waveforms under such complex transient conditions. The second direction provides mechanistic insights on surface transients during partial cycles and extends the study to uncover limits set by modulation frequency, as well as surface inhibition effects. Lastly, oxygen pulsing is applied as a regeneration strategy to minimize catalyst deactivation during co-synthesis of turquoise hydrogen and carbon nanotubes from methane pyrolysis, a key bottleneck to growth of long carbon nanotubes. Altogether, the body of work provides hopeful perspectives on the use of reaction engineering to tune catalytic activity through non-equilibrium forced periodic operation of microreactors, while highlighting critical needs that must be addressed to fully tap into the potential of induced catalytic transients
A25 Zurich Optimization of the Middle Ear Model
No full textThis project explored the improvement of a physical model of the middle ear for instructional purposes in the Department of Otorhinolaryngology at Univerisitätsspital Zürich. Current models of the middle ear are only static, failing to demonstrate how sound travels through the ear. The goal of this project is to increase the accessibility and organization of the dynamic model of the middle ear. This was accomplished by developing a new support structure and suspension system for the model, improving the organizational system, and creating a support document. Vibrational testing indicated that the new dynamic model demonstrated consistently improved biological trends compared to past iterations of the model. The following report outlines the tasks taken to accomplish these results
2518 IQP Stock Market Simulation - Joshua Kashambala
No full textThis project consisted of background research on the stock market followed by a six-week stock market simulation. The simulation contained two different portfolios that were identical except for the trading strategies used to run them which were the Buy and Hold strategy and the Swing Trading strategy. The simulations started with an initial 100,980.56 which was a 0.98% gain. The Swing Trading had a final account value of $105,548.45 which was a gain of 5.55% and thus was the superior trading strategy. The experience gained about the history of the stock market and its terminology as well as practical application of knowledge gained was enlightening and will be helpful in the future
Detecting ESG Rating Anomalies
No full textThis project strengthens Green Future Wealth Management’s ESG portfolio tool by transforming last year’s prototype into a stable, optimized Markowitz system. The team rebuilt the mathematical engine with improved data cleaning, Ledoit–Wolf shrinkage, eigenvalue clipping, Michaud resampling, and volatility-based weight bounds to produce consistent frontiers. A new anomaly detection framework using PCA, Isolation Forest, and an Autoencoder highlights unreliable ESG reporters. A Monte Carlo simulator adds forward-looking, SEC-aligned projections. Together, these upgrades create a more transparent, reliable, and advisor-ready ESG platform
Revitalization Plan and Business Model for Open Co Hub
No full textThis report outlines the development of a business model for Accountability Lab Nepal’s (ALN) in-house coworking space, Open Co Hub (OCH). We evaluated company administrative goals, user preferences, market rates, and successful practices surrounding coworking space operation in and around Kathmandu, Nepal. To acquire this data, we conducted interviews with ALN administration, OCH clients, Nepal coworking space administrations, and potential users of the space. We then created a business model guided by market rates, successful practices, and user preferences of Nepal coworking spaces