Mobile Underwater Backscatter Networking

Underwater backscatter is a recently introduced technology for ultra-low-power underwater networking. Despite advances in this technology, existing systems are limited to static environments and cannot operate reliably under mobility. This thesis presents EchoRider, the first system that enables reliable underwater backscatter networking under mobility. EchoRider’s design introduces three new components. The first is a robust, chirp-based downlink protocol that brings the benefits of LoRa wireless networks to underwater backscatter, while accounting for the ultra-low-power nature of the backscatter sensor nodes. The second is a novel NACK-based backscatter retransmission algorithm, which enables reliable and efficient underwater backscatter. The third is a Doppler-resilient backscatter decoding pipeline on the uplink that features adaptive equalization, polar coding, and an equalizer retraining mechanism. We implemented an end-to-end prototype of EchoRider and compared it to a state-of-the-art baseline. Our evaluation across more than 1,200 real-world experimental trials in real-world environments demonstrates that EchoRider outperforms the state-of-the-art baseline by more than 160× in BER under mobility, and that it can sustain typical underwater goodput (around 0.5kbps) in scenarios where the baseline’s goodput drops to zero at speeds as low as 0.1m/s. Finally, we demonstrate EchoRider in an example application involving an underwater mobile drone and a backscatter sensor node.S.M

A Tactile-enabled Hybrid Rigid-Soft Continuum Manipulator for Forceful Enveloping Grasps via Scale Invariant Design

2023 IEEE International Conference on Robotics and Automation (ICRA 2023) May 29 - June 2, 2023. London, UKThis work presents a novel hybrid rigid-soft continuum manipulator, which integrates high-resolution tactile sensing in a form factor that is forceful, compliant, inherently safe, and easily controllable. We utilize a hybrid approach motivated by scale-invariant principles to fuse the rigid and soft design domains while addressing their respective challenges. We use Euler-Bernoulli beam theory and geometric inference to design and develop a novel variant of folded flexure hinge (FFH) compliant mechanism, the variable area moment of inertia folded flexure hinge (VAFFH), which deforms logarithmically along its length and thus yields first-order scale-invariant grasp behavior. Finally, we characterize the forcefulness of the manipulator and demonstrate its compliance, adaptability, and tactile sensing capabilities in selected task

Shifting Paradigms: Data-Centric Approach for Marine Statics Correction using Symmetric Autoencoding

Deep learning has demonstrated remarkable performance in a wide variety of domains and is often leveraged for making high-stakes decisions. Parallel to its growing and beneficial presence in other domains, deep learning is gaining a notable reputation for solving challenging problems in geophysics. A key problem - given the escalating energy and geosequestration demands in present times - is marine statics correction. The traditional workflow for correcting marine statics has been based on a model-centric paradigm. This paradigm involves a series of transformations between non-commensurate spaces: first, inversion from seismic data space to velocity model space and second, forward modeling from velocity model space to seismic data space. Statics correction within this paradigm has severe drawbacks, mainly the high compute, time and labor cost, and inaccuracies stemming from errors in velocity model inversion or from unmet assumptions about subsurface structure. Overcoming these drawbacks was thus, the prime motivation for our study - where we chose to leverage deep learning as the core algorithmic tool to understand the limits of the model-centric paradigm and explore the performance horizons of a different, data-centric, paradigm to statics correction. The main feature of the data-centric paradigm is the direct mapping between commensurate data spaces, eliminating the need for intermediary transformations to and from velocity model space. Initial benchmark tests on the model-centric approach revealed the impact of inaccuracies in velocity model inversion as substantial nonzero timeshifts - exceeding 0.01s, and reaching values as large as 0.04s - for most arrivals in seismic data. These arrival time precision levels are unacceptable for good seismic imaging and time-lapse analysis; underscoring the need for an improved approach to marine statics correction. Consequently, we began our investigations into the data-centric paradigm. With the focus of disentangling the effects of varying seawater velocity from coherent subsurface geology in seismic records, we implemented an autoencoder algorithm, named SymAE. Notably, SymAE leverages the permutation symmetry of coherent subsurface information to perform the separation of information from nuisance variations. Once trained, SymAE is able to redatum selected subsurface and water velocity information in its latent space to produce statics-corrected seismic records. Our results show that for training datasets of increasing subsurface complexity, SymAE strongly converges all dynamic timeshifts to zero, aligning perturbed traces to reference traces. Crucially, SymAE delivers the required timeshift precision of 0.01 seconds for all arrivals - an achievement that the model-centric approach falls short of. This notable precision improvement using SymAE highlights how a streamlined data-centric paradigm outperforms the traditional model-centric paradigm of marine statics correction. This finding is pivotal as it is the foundation that lays the groundwork and opens the path towards the real-world deployment of SymAE for statics correction in challenging deepwater environments.Ph.D

From Waste to Structure: A Deep Reinforcement Learning Approach to Circular Design

The design-to-construction process of buildings predominantly follows a top-down linear workflow, where a design is drawn and subsequently refined to determine the required materials and components. This approach assumes an infinite material supply or the capability to manufacture what is needed for the design. Constructing in this manner is resource-intensive and wasteful, making it incompatible with our global climate goals. One way to significantly reduce our material and environmental footprint is by extending the lifespan of building materials through circular design practices. In this approach, the available materials define the architecture, inverting the process from top-down to bottom-up. This method, known as Inventory-Constrained Design, enables the creation of new buildings using materials sourced from construction and demolition waste streams. These inventories, characterized by their non-standard and uniquely varied elements, are hard to design with due to the enormous quantity of possible combinations of even a few discrete elements. Identifying a feasible design that aligns with the designer's intent and meets functional requirements becomes an overwhelmingly time-consuming task, heavily reliant on manual trial and error. Computational optimization has been implemented to automate the process, but state-of-the-art algorithms still require manually pre-defining a parametric target design-space or take too long to compute when applied to larger problems. This thesis proposes a new method for circular design utilizing Deep Reinforcement Learning (RL) to design structures, requiring only a design gesture and the inventory as input. It works by training an artificial neural network to sequentially assemble a structure from inventory elements, following the gesture while meeting a structural goal. Hence, the design layout directly arises from available inventory. After training, the neural net can be employed instantaneously to design new structures with new inventories without any significant computational expense. To evaluate the effectiveness of the RL method, it is applied to the specific problem of inventory-constrained design of planar roof trusses and demonstrated in a realistic example of assembling a long-span roof from a disassembled transmission tower.S.M.S.M

Report to the President for year ended June 30, 2024, Department of Urban Studies and Planning

This report contains the following sections: Promotions and Faculty Appointments; New & Emerging Initiatives; Comings, Goings, Changing Roles; Committees & Leadership; Other Noteworthy News; New Faculty Books; Student-led Publications; Education/Degree Programs; Education; and Commencement/Awards

Co-Design of Resource Limited Genetic Networks Tuning System Parameters to Satisfy Specifications

Modular composition is a very powerful and widely used tool in engineering disciplines, as it aids in maintaining the system complexity tractable. Its main idea is that parts of the systems can be encapsulated into black box models characterized only by its input to output behavior, which eliminates the need to consider the complex dynamics inside the black box. Moreover, this process can be done iteratively, allowing the design of highly complex systems, such as computer chips. But this powerful tool is not always available, like in synthetic biology, where engineered systems in cells have very complex and intricate interconnections between subsystems, which makes encapsulating parts of theses systems a very challenging endeavor. There are many reasons for this failure in modularity in biological systems, such as load effects (retroactivity), unknown interactions and resource competition, which is our focus for this work. Recent efforts to achieve modular design in systems with resource competition, have focused in adding additional machinery to the cell to either try to isolate the subsystems or control the availability of the shared resource. In this work we explore a co-design approach, where instead of adding additional machinery to the cell, we aim to tune some systems parameters to satisfy some specification. To this end we provide conditions on the systems parameters for a network of subsystems to meet a given specification, which are derived using mathematical logic and ideas on how to tackle similar problems. With this, this work lays the foundations for further development of co-design techniques for genetic networks with production and/or degradation resources, where one may be able to mitigate the effects of one type of resource sharing by tuning the other.S.M

Properties and Processing of Chalcogenide Perovskites

There is an unmet need for thin film photovoltaic (PV) technology that features low materials cost, high performance and reliability, and compatibility with low-cost manufacturing. Chalcogenide perovskite materials show promise to meet these criteria but are at an early stage of development. Other promising optoelectronic materials, such as lead halides perovskites, have shown remarkable strides in optoelectronic performance, but they are plagued with issues of toxicity and stability. Chalcogenide perovskites have been proposed as potential replacements for these lead halide perovskites, but there is a dearth of information on their fundamental material properties. Recent theoretical studies have demonstrated that chalcogenide perovskite materials have suitable band gaps for a single-junction solar cell, and these results are backed by experimental studies on bulk sample morphologies. In order to determine the technological potential of this material class, it is important to understand their structure-property correlations, as well as study it in thin-film form. In this thesis, we focus on materials in the Ba-Zr-S system, particularly BaZrS3 and Ba3Zr2S7 . Although the band gap of these materials have been experimentally determined, there are still many unknown material properties, including absorption coefficients, carrier mobilities, and carrier diffusion lengths. High-quality thin film samples of chalcogenide perovskites will enable measurements of these properties. This thesis has two main goals: 1) to further investigate and characterize bulk properties of these materials for optoelectronic applications and 2) realize the synthesis of thin films, enabling further measurements and paving the way for device fabrication. We connect optoelectronic performance to both intrinsic and extrinsic material properties, using a suite of characterization techniques. We also demonstrate the first-of-a-kind synthesis of epitaxial chalcogenide perovskite thin films using molecular beam epitaxy (MBE), and show encouraging results on alloying and defect control. This thesis advances the current knowledge of chalcogenide perovskites both in terms of properties and processing, and sets the stage for realizing chalcogenide perovskite optoelectronics.Ph.D

The role of Orc6 in ORC binding-site switching during helicase loading

DNA replication is a fundamental cellular process that enables proper maintenance of genomic integrity and cellular identity as cells divide. Initiation of bidirectional DNA replication is a key requirement for complete duplication of the genome. The first step in eukaryotic DNA replication is origin licensing, during which the origin recognition complex (ORC) coordinates loading of two Mcm2-7 hexameric helicases in opposite orientations to form the Mcm2-7 double hexamer. These Mcm2-7 double hexamers mark sites of eventual bidirectional replication initiation upon entering S-phase, when activation of these helicases and recruitment of DNA polymerases leads to new DNA synthesis. In. S. cerevisiae, ORC initially binds to a high affinity site at origins of replication to load the first Mcm2-7 complex. ORC is then able to bind a secondary inverted binding site at origins to load a second Mcm2-7 in the opposite orientation to coordinate formation of the Mcm2-7 double hexamer. Previous single-molecule studies show that one ORC can recruit and load both Mcm2-7 helicases at origins. This one-ORC helicase-loading model requires a dramatic change in ORC location to transition between its primary and secondary binding site. Importantly, this must occur without release of ORC from the site of helicase loading. How this binding-site switch is mediated is currently unknown. In this thesis, we used single-molecule Förster resonance energy transfer (smFRET) assays to study interactions between ORC and Mcm2-7 during helicase loading. We found that upon recruitment of Mcm2-7 to origin DNA, in addition to the previously described ORC C-terminal tier interaction with Mcm2-7 C-terminal tier, Orc6N forms an interaction with the N-terminal tier of Mcm2-7 (Mcm2-7N). We identified elements of Orc6 required to mediate this interaction, as well as potential mechanisms of inhibition of this interaction by the regulatory kinase CDK. The kinetics of this interaction indicate that Orc6N interacts with Mcm2-7N well before ORC undergoes its binding site switch, consistent with a role of this interaction in retaining ORC at the site of helicase loading during this transition. Additionally, we demonstrate a role for Orc6 in mediating stable second Mcm2-7 recruitment. These findings emphasize the role of protein-protein interactions in enabling ORC to coordinate loading of oppositely-oriented Mcm2-7 helicases to enable bidirectional replication and identify new functions for Orc6 during this process.Ph.D

Distributed Sensors, Data Analysis, and Non-Intrusive Load Monitoring: Foundations for Reliability-Centered Maintenance on Ships

Advances in computing and sensing technology have brought powerful new tools within reach of shipboard engineers. With the right setup, operators can leverage statistics and digital signal processing tools to gain physical insight previously obscured by the sheer amount of work and specialized knowledge it once took to do the same. This thesis explores several applications of non-intrusive load monitoring (NILM) tools aboard a U.S. Coast Guard Fast-Response Cutter (FRC) patrol boat, novel analysis methods of the corrosion protection systems on the FRC, and practical ways of making smart data approachable. Once implemented, these methods will reduce the effort needed to safely operate a modern, high-tech ship by giving operators greater insight into how their systems perform in real-time.S.M

Calculation of Zakat on Financial Assets for American Muslims: A Financial and Jurisprudential Approach

This thesis presents a comprehensive framework for calculating Zakat on modern financial assets specifically tailored for American Muslims. As one of the five pillars of Islam, Zakat is an obligatory form of charity for those who meet specific wealth criteria. However, applying traditional Zakat principles to contemporary financial instruments poses significant challenges, particularly within the context of the U.S. financial system. The research addresses these complexities by developing methodologies that consider diverse financial instruments, valuation challenges, tax implications, accessibility issues, and Shariah compliance. The framework covers a wide range of assets, including cash and bank accounts, stocks, mutual funds, bonds, cryptocurrencies, retirement accounts (401(k)s, Traditional and Roth IRAs), Health Savings Accounts (HSAs), employee stock options, precious metals and jewelry, and real estate investments. Bridging classical Islamic jurisprudence with modern financial realities, this thesis provides detailed calculation methodologies for each asset class, incorporating U.S.-specific considerations such as tax-deferred accounts and capital gains implications. The framework is designed to be adaptable to evolving financial markets and balances various scholarly opinions on contentious issues. To enhance accessibility, both comprehensive and simplified calculation methods are offered, catering to users with different levels of financial literacy. In conclusion, this thesis makes a significant contribution to Islamic finance by offering a structured, principle-based approach to Zakat calculation that is both Shariah-compliant and applicable in the modern American financial context. It provides a valuable resource for American Muslims striving to fulfill their religious obligations amidst the complexities of the U.S. financial system and lays the groundwork for future research in Islamic finance in Western contexts.S.M