DOT-LINE — Furniture for Inspired Living

Design as a functional outlet results from research that revolves around the user experience. It is a fair definition that seems to acknowledge today\u27s standards of designing for the masses, prioritizing market-driven factors that include utility, manufacturability, and market demand. This approach aligns with contemporary design, but does it take ontological design out of the equation? Given that consumer consciousness determines what exists in the market, a design\u27s nonvisual and deeply conceptual aspects may go unnoticed. While market research allows designers to anticipate and shape consumer desires, it is also an opportunity to delve deeper into the user\u27s psyche, not for commercial gain, but to enhance well-being through emotional design. What emotions contribute to user welfare? And how can such a study be transmuted into a tangible user experience? This research explores how Art and Design interplay can materialize a product that carries more meaning beyond mere utility. The research about potential relational dynamics of art integration, interactivity, modularity, and intuitive design choices provides an in-depth look at how a product can be both a functional object and a signifier for creativity and self-expression in a living environment

Mapping Accessibility in Dubai: Evaluating Al Wasl and Mirdif Against 20-Minute City Principles and the Dubai 2040 Urban Master Plan

The 15-minute city is a planning concept that aims to give people easy access to daily services such as schools, shops, healthcare, and recreation within a short walk or bike ride. Dubai has adapted this concept into a 20-minute city model under the Dubai 2040 Urban Master Plan. The goal is to reduce car use, improve quality of life, and create connected and sustainable neighborhoods. This study evaluates how well two neighborhoods in Dubai, Al Wasl and Mirdif, match the 20-minute city model. It analyzes three main goals from the Urban Master Plan: having 55% of residents within 800 meters of public transport, making 80% of essential services reachable within 20 minutes, and supporting walking and cycling through better transport networks. The study uses spatial analysis tools, travel time maps, and access scores to measure how easy it is to reach services and transit in each area. The results show that Al Wasl meets the 20-minute city goals across walking, cycling, and public transport because of its compact layout, metro access, and mix of land uses. Mirdif does not meet the same targets, mainly due to car dependence, spread-out housing, and no metro station nearby. Even with the planned Blue Line metro station, only 38% of residents will live within 800 meters of transit, which is still below the 55% target. The research explores how Dubai’s urban form, transportation systems, and land use patterns influence accessibility within the 20-minute city framework. It also suggests directions for future research, including applying this method to other districts across Dubai and tracking changes after planned infrastructure investments. This research shows that good public transport alone is not enough. To support the 20-minute city model, urban plans must also include closer service locations, better walking conditions, and more balanced land use. The findings give helpful ideas for planners and policy makers in Dubai and other growing cities

Development of a Miniaturized Extracorporeal Membrane Oxygenation (ECMO) Device on a Microfluidic Platform

This research investigates the design, performance, and optimization of blood-contacting microfluidic medical devices, with each aim contributing to a broader understanding of how engineering choices influence hemocompatibility and oxygen transfer. Collectively, the findings from Aims 1A–2B offer integrated strategies to develop safer, more effective microfluidic systems for ECMO and dialysis. Aim 1A assessed hemolysis across device geometries using computational and experimental methods. All designs showed low device-induced hemolysis (\u3c 2 ppm), validating their hemocompatibility. However, Power-Law models frequently overpredicted hemolysis, indicating a need for refined parameters tailored to microfluidic flow conditions. Aim 1B demonstrated the effectiveness of thrombosis assay techniques in evaluating clot formation in microfluidic device geometries. Results showed that geometry and local shear patterns strongly influence thrombogenesis. While hemolysis remained minimal even in high-shear devices, thrombus formation was more geometry-sensitive—underscoring the need to account for both factors in design. Modifying surface properties and accounting for blood composition could further reduce thrombotic risk. In Aim 2A, we compared PDMS, polypropylene (PP), and nanoporous silicon nitride (NPSiN) membranes for oxygen transport. Findings showed that in ECMO devices, blood-side resistance, not membrane permeability, often dominates oxygen transfer. Thus, membrane choice must be paired with optimized blood-side flow for full performance gains. Aim 2B directly addressed these limitations by integrating staggered herringbone mixers (SHBs), which introduced secondary flows and enhanced mixing. The Single Channel Herringbone design yielded the highest oxygen transfer, confirming the synergy between flow geometry and oxygen transport performance. Altogether, Aims 1A and 1B establish a strong framework for hemocompatibility evaluation, while Aims 2A and 2B provide complementary insights into optimizing oxygen transfer. Their interconnections highlight the value of a systems-level approach to designing microfluidic blood-contacting devices

Energy-Efficient Distributed Algorithms: A Survey, Visualizations, and New Results in Radio Networks

Distributed algorithms have been studied for decades, with a particular focus on round and message complexities. Recent works have presented energy-efficient distributed algorithms, where nodes are allowed to sleep, sacrificing the ability to communicate, and the goal is to minimize the amount of time nodes spend in an awake state. This thesis further explores the area and can broadly be divided into three parts. In the first part of this thesis, we provide a literature survey of existing works. Several fundamental graph problems have been studied in this context. Our survey compares the known results from different models, highlights the use of similar techniques, and explores the extent to which the energy complexity of these various problems is understood. In the second part, we study the problem of initialization in single-hop radio networks, which aims to assign unique, consecutive identifiers to all nodes. Previous results on initialization assumed a stronger variant of the radio model, where nodes have sender-side feedback. We introduce an energy-efficient algorithm for partial initialization, which assigns identifiers to a constant fraction of the nodes in the more challenging setting without sender-side feedback. As a consequence, we can simulate existing initialization protocols while maintaining the same energy bound and dropping the reliance on sender-side feedback. Finally, we present visualizations of energy-efficient radio network algorithms for generic simulation, maximal matching, and partial initialization. These visualizations highlight when and where energy is being saved throughout the execution of the algorithms. They also serve as a helpful tool for understanding the algorithms, which may otherwise be difficult to grasp because of the parallel nature of distributed computing

Study of an Evolutionary Sequence of Nearby, High-excitation Bipolar Planetary Nebulae with ALMA and HST

Planetary nebulae (PNe) reveal the near-final stages of the evolution of intermediate-mass (1-8 solar mass) stars, immediately after such stars shed their envelopes through copious asymptotic giant branch (AGB) mass loss. PNe reveal products of intermediate-mass stellar nucleosynthesis just before they enrich the interstellar medium, and their central stars provide subjects for studying the origins of white dwarfs and interacting binary systems involving compact objects. The processes that shape planetary nebulae and determine their chemistries can be unveiled through multiwavelength observational studies of molecule-rich PNe ranging from young and rapidly evolving nebulae, such as NGC 7027, NGC 6302, and NGC 6537, to more mature bi-lobed nebulae, such as NGC 2899 and NGC 2818. In this dissertation, I present analysis of Hubble Space Telescope Wide-Field Camera 3 (HST/WFC3) panchromatic images of NGC 7027 revealing the spatial distributions of emission lines covering low-ionization species such as singly-ionized Fe, N, and Si, through H recombination lines, to more highly ionized O and Ne. I use these HST/WFC3 imaging results to describe the recent, rapid evolution of NGC 7027 in terms of a series of shaping events. I then present results from a program of Atacama Large Millimeter Array (ALMA) Band 6 and Band 3 molecular line mapping of a sample of nearby, bipolar/pinched-waist, molecule-rich PNe (NGC 6302, NGC 6537, Hubble 5, NGC 2440, NGC 6445, NGC 2899, and NGC 2818). The resulting velocity-resolved, high-resolution radio interferometric images of these bipolar PNe afford unparalleled opportunities to study their structures, kinematics, and molecular content. Isotopologues of CO as well as various molecular line tracers of high-energy irradiation including HCN, HNC, HCO$^+$, SO, and CS -- many of these detected in these PNe for the first time -- are mapped to reveal key details concerning the compositions and the velocity fields of the equatorial tori and (in some cases) polar regions of the sample PNe. All of our ALMA sample objects show evidence of having descending from progenitor AGB stars of $\geq4$ M$\odot$, with post-AGB ages ranging from $1000-19000$ years. Our survey reveals the morphological evolution of the molecular tori of bipolar PNe over this timescale, and expands on previously studied trends in HCN/HNC ratio and HCO$^+$ emission. Molecular diagnostic diagrams are utilized to further analyze $^{12}$C/$^{13}$C and CN hyperfine ratios to probe progenitor mass ranges and emission-line optical depths. Collectively, these ALMA survey results provide insight into the rapid structural evolution as well as the zones of UV- and X-ray-irradiated molecular gas that characterize dusty, molecule-rich, bipolar PNe

From Sim to 6DOF: Deep Learning for Real-Time Satellite Pose Estimation from Resolved Ground-Based Imagery

This dissertation presents the first practical system for automated six degrees of freedom (6DOF) satellite pose estimation from resolved ground-based adaptive optics (AO) imagery. Addressing a key challenge in Space Domain Awareness (SDA), the proposed approach eliminates the need for human labeling by directly regressing satellite orientation and position from blurry, noisy, and deeply-shadowed imagery. The architecture consists of a multi-stage deep neural network pipeline that localizes the satellite, predicts pose, and optionally smooths predictions over time. Networks are trained exclusively on fully synthetic imagery generated from a 3D CAD model. Despite this, the model generalizes effectively, bridging the Sim2Real domain gap and overcoming the nonexistence of real labeled data. On 137 real, human-labeled test images of Seasat, it achieved a mean rotation error of 5° and a mean image-plane translation error of 21 cm. Independent evaluation of additional real Seasat images rated 178 of 199 predicted poses as “ground truth equivalent” or “high confidence match,” with zero catastrophic failures. The approach was extended to seven degrees of freedom (7DOF) to handle articulating components and demonstrated on the Hubble Space Telescope (HST). On a 249-frame real, labeled pass of HST, applying temporal processing yielded a mean rotation error of 5.9°, a mean image-plane translation error of 48 cm, and a mean symmetry-adjusted solar array rotation error of 6°. The combined 586 real test images of Seasat and HST span multiple decades and were captured under diverse pose, illumination, and atmospheric conditions from separate ground sites. On a high-fidelity wave optics (HFWO) synthetic test set featuring Seasat in varied poses and illumination conditions, the model achieved 8.4° mean rotation error, 34 cm image-plane translation error, and 1.4% range error for a typical atmosphere (r₀ = 6 cm) and mean target range of 1,031 km. The system outperformed a human labeler in both accuracy (48% reduction in rotation error) and speed (800× faster, 7.1 Hz inference), running on consumer-grade hardware. End-to-end data generation and training required less than 40 hours on a single A100 GPU to produce a model suitable for long-term deployment. The approach was also demonstrated on a smaller satellite (ARGOS) with strong geometric symmetry using HFWO synthetic test data. A General Image-Quality Equation (GIQE)-based image quality metric was introduced to forecast pose accuracy, marking the first comprehensive study of directly regressed pose performance as a function of image quality. Key factors affecting pose accuracy were systematically analyzed, including object pose, illumination direction, Sun azimuth and zenith angles, CAD model fidelity, and training set size. Additionally, generalist models such as GPT-4o and Depth Anything V2 failed across most SDA pose estimation tasks. However, vision language models showed rapid improvement, warranting ongoing evaluation by the pose estimation and SDA communities. These results establish a new operational baseline and demonstrate, for the first time, reliable satellite pose estimation from AO SDA imagery in real time

Enhancement of Firefighter Mental Performance: A Review

Background: The life-or-death nature of firefighting exposes those who respond to calls to an increased number of stressors that can impact performance and overall well-being. To combat this, the mental element of firefighting can be optimized through psychological skills training programs and mindfulness training. Other tactical populations, such as the police force, military, and emergency medicine units have found success in implementing these interventions, Literature suggests a similar effect may be observed in firefighters because of their similar demands; although, little research exists regarding the effects of mental performance programs on firefighter populations specifically. Methods: A review of existing literature was conducted using the search words: “mental performance,” “tactical,” “attention,” “firefighter,” and “mindfulness”. The results were narrowed by excluding articles that were not peer reviewed, scholarly, or published between 2000-2022. The sources used in this review were extracted from the remaining results based on relevancy. Summary: The demands of firefighting require both physical and psychological proficiency; however, most training programs have neglected the mental aspect. To enhance overall performance, mindfulness training, psychological skills training, relaxation training, and mindfulness-based attention training programs can be implemented to better prepare firefighters for the stress endured during calls. Interventions focused on adaptability and resilience rather than automaticity by strengthening core executive functions, filtering through cues and departing from previous mental frameworks. To measure the impact of programs on performance, studies have mostly utilized questionnaires following the intervention. Results showed that greater emotional control and improved focus can be achieved through training the cognitive mind and thus enhancing overall performance. Recommendations: Future studies should investigate methods to measure values prior to intervention to further gauge the efficacy of various mental trainings. Additionally, other firefighter specific physical assessments under the presence of stress should be introduced

Chinese Creative Writing Studies

Review of Rebecca Leung Mo-Ling, editor. Chinese Creative Writing Studies. Springer Nature, 2023. 175 pages