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Multiscale topology optimization (TO) provides an inverse design computational framework for designing globally and locally optimized hierarchical structures. Triply periodic minimal surfaces (TPMS), a subclass of parametrically-driven lattice structures, exhibit unique properties such as large surface area, significant volume densities, and good strength-to-weight ratio, which makes them favorable for novel engineering applications. The recent advances in additive manufacturing and its ability to fabricate high-resolution structures have spurred interest in multiscale TO and TPMS for computationally designing finer and high-resolution designs. While multiscale TO and TPMS bring transformative opportunities in various applications, their potential for everyday use remains idle due to critical issues associated with their frameworks. The multiscale TO computational paradigm brings new challenges, including geometric frustration, non-smooth boundaries, and higher computational time that needs to be handled. Further developing design tools for TPMS brings in additional challenges such as limited design space and lack of inverse design tools for targeted properties to geometries mapping. This dissertation attempts to address these above-mentioned challenges by: (1) Employing a computationally efficient deep learning-based TO pipeline for microscale TO analysis. (2) Developing a novel CNN-based connectivity improvement solver for improving micro-structural connectivity between neighboring unit cells. (3) Utilizing a post-processing solver for neural network outputted structures to ensure physical constraints, optimized material distribution, and proper local connectivity. (4) Proposing a weighted combinatorial approach for developing novel TPMS-based lattices from baseline TPMS structures such as Schwarz-P, Diamond-D, and Schoen's F-RD surfaces. (5) Developing deep learning-based inverse design framework for predicting TPMS-based lattices for targeted effective elastic properties. (6) Developing deep learning-based multiscale TO framework for TPMS lattices-infused structures.

Autism Spectrum Disorders (ASDs) are a group of neurodevelopmental disorders for which there is no direct treatment. Understanding the disease mechanisms may lead to future therapeutic targets. In this thesis, we performed bi-directional CRISPR-Cas9 genome editing on induced pluripotent stem cells (iPSCs) derived from individuals with ASD with macrocephaly as well as controls, and uncovered that in addition to PTEN p.Ile135Leu variant, ASD genetic backgrounds also contributed to dysregulating cortical neurogenesis in both 2D neural progenitor cells and 3D cortical organoid models. Surprisingly, ASD specifc PTEN p.Ile135Leu variant dysregulates cortical neurogenesis in an ASD genetic background dependent fashion, as we found that this variant led to overproduction of neural progenitor cell (NPC) subtypes including intermediate progenitor cells (IPCs) and outer radial glia cells (oRGs) as well as neuronal subtypes such as deep and upper layer neurons in the ASD genetic background but not in the control genetic background in the cortical organoids. This study provides strong evidence that both an ASD-specifc PTEN p.Ile135Leu variant and autism genetic background are contributing to the cortical neurogenesis dysregulation.We also developed a lineage tracing system to track neurogenesis in human cortical organoids and applied this system to a control iPSC line as well as autistic isogenic CTNNB1 iPSC lines, we uncovered that the majority of the cortical neurons in the cortical organoids were indirectly generated through IPCs, and neurons derivedfrom diferent lineages were transcriptionally distinct. An ASD-linked CTNNB1 p.Gln76* variant altered the lineage specific production of deep and upper layer neurons as well as the landscape of gene expression profiles among and within different neural progenitor lineages of both deep and upper layer neuron production. Overall, this thesis provides direct evidence that variants in the PTEN and WNT pathways as well as ASD genetic background contribute to dysregulated corticalneurogenesis in ASD-affected individuals.

Leishmaniasis is a complex group of vector-borne zoonosis caused by parasites of the Leishmania genus. The prediction of annual cases of visceral leishmaniasis and cutaneous leishmaniasis combined is of more than 1 000 000 cases, with up to 20 000 deaths per year. The treatment of leishmaniasis relies on a few drugs presenting multiple shortcomings, which makes the discovery of new treatments urgent. In recent years, clemastine 27 and tamoxifen 28 have been identified in repurposing strategies and shown to display potent anti-leishmanial activity against both in vitro and in vivo models of the disease. Both molecules were proposed to target the same enzyme, inositol phosphorylceramide synthase (IPCS), which is found in the parasite but not in the host. These molecules also share similar chemical features, such as an aminoalkoxy side chain and a diaryl system. In this project, it was hypothesised that these chemical features are responsible for their antileishmanial activity. Therefore, the goal was to design and synthesise hybrid molecules between clemastine and tamoxifen and improve their antileishmanial activity. Firstly, a library of 40 compounds was synthesised varying the nature of the diaryl carbinol core and the aminoalkoxy side chain. Using a classic resazurin-based assay, all compounds were screened for antiparasitic activity against L. major and L. amazonensis promastigotes, and HepG2 cells for the evaluation of their cytotoxicity against human cells. Seven compounds with an EC50 < 2 µM against both species, and a selectivity index > 10 were the selected for testing against other two species of Leishmania promastigotes epidemiologically relevant in South America (L. braziliensis and L. infantum) as well as against two species of intracellular amastigotes (L. amazonensis and L. infantum). All compounds were highly active against L. braziliensis promastigotes, displaying EC50 values below 1 µM, and 6/7 compounds had EC50 approximate to 2 µM against L. infantum. In addition, they displayed promising activity against L. infantum amastigotes (EC50 ≤ 2 µM), but were slightly less active against L. amazonensis. Analogues 110 and 111 had the highest activity across the four species of promastigotes tested, and the most active compound against the intracellular amastigotes was 130. Collectively, these results contributed towards raising insights regarding the structure-activity relationship of this library, which led to the selection of clemastine/tamoxifen hybrids with high antileishmanial potency. Ongoing and future efforts are to explore the mechanism of action of this library. For this, two techniques were chosen to be explored; chemical proteomics, which makes use of chemical probes for the identification of binding proteins, and resistance selection followed by genomic sequencing, which allows for the identification of genes associated with the compound activity.

Computer systems are vulnerable to security exploits, and the security of the operating system (OS) is crucial as it is often a trusted entity that applications rely on. Traditional OSs have a monolithic design where all components are executed in a single privilege layer, but this design is increasingly inadequate as OS code sizes have become larger and expose a large attack surface. Microkernel OSs and multiserver OSs improve security and reliability through isolation, but they come at a performance cost due to crossing privilege layers through IPCs, system calls, and mode switches. Library OSs, on the other hand, implement kernel components as libraries which avoids crossing privilege layers in performance-critical paths and thereby improves performance. Unikernels are a specialized form of library OSs that consist of a single application compiled with the necessary kernel components, and execute in a single address space, usually atop a hypervisor for strong isolation. Unikernels have recently gained popularity in various application domains due to their better performance and security. Although unikernels offer strong isolation between each instance due to virtualization, there is no isolation within a unikernel. Since the model eliminates the traditional separation between kernel and user parts of the address space, the subversion of a kernel or application component will result in the subversion of the entire unikernel. Thus, a unikernel must be viewed as a single unit of trust, reducing security. The dissertation's first contribution is intra-unikernel isolation: we use Intel's Memory Protection Keys (MPK) primitive to provide per-thread permission control over groups of virtual memory pages within a unikernel's single address space, allowing different areas of the address space to be isolated from each other. We implement our mechanisms in RustyHermit, a unikernel written in Rust. Our evaluations show that the mechanisms have low overhead and retain unikernel's low system call latency property: 0.6% slowdown on applications including memory/compute intensive benchmarks as well as micro-benchmarks. Multiserver OS, a type of microkernel OS, has high parallelism potential due to its inherent compartmentalization. However, the model suffers from inferior performance. This is due to inter-process communication (IPC) client-server crossings that require context switches for single-core systems, which are more expensive than traditional system calls; on multi-core systems (now ubiquitous), they have poor resource utilization. The dissertation's second contribution is Aoki, a new approach to IPC design for microkernel OSs. Aoki incorporates non-blocking concurrency techniques to eliminate in-kernel blocking synchronization which causes performance challenges for state-of-the-art microkernels. Aoki's non-blocking (i.e., lock-free and wait-free) IPC design not only improves performance and scalability, but also enhances reliability by preventing thread starvation. In a multiserver OS setting, the design also enables the reconnection of stateful servers after failure without loss of IPC states. Aoki solves two problems that have plagued previous microkernel IPC designs: reducing excessive transitions between user and kernel modes and enabling efficient recovery from failures. We implement Aoki in the state-of-the-art seL4 microkernel. Results from our experiments show that Aoki outperforms the baseline seL4 in both fastpath IPC and cross-core IPC, with improvements of 2.4x and 20x, respectively. The Aoki IPC design enables the design of system servers for multiserver OSs with higher performance and reliability. The dissertation's third and final contribution is the design of a fault-tolerant storage server and a copy-free file system server. We build both servers using NetBSD OS's rumprun unikernel, which provides robust isolation through hardware virtualization, and is capable of handling a wide range of storage devices including NVMe. Both servers communicate with client applications using Aoki's IPC design, which yields scalable IPC. In the case of the storage server, the IPC also enables the server to transparently recover from server failures and reconnect to client applications, with no loss of IPC state and no significant overhead. In the copy-free file system server's design, applications grant the server direct memory access to file I/O data buffers for high performance. The performance problems solved in the server designs have challenged all prior multiserver/microkernel OSs. Our evaluations show that both servers have a performance comparable to Linux and the rumprun baseline.

Consumption of food and water is tightly regulated by the nervous system to maintain internal nutrient homeostasis. Although generally considered independently, interactions between hunger and thirst drives are important to coordinate competing needs. In chapter 1, I provide a review of hunger regulation and thirst regulation in mammals and Drosophila melanogaster. I then discuss the neural and hormonal coordination of hunger and thirst in both mammals and D. melanogaster.In Drosophila, four neurons called the Interoceptive Subesophageal zone Neurons (ISNs) respond to intrinsic hunger and thirst signals to oppositely regulate sucrose and water ingestion. In chapter 2, I characterize the neural circuit downstream of the ISNs. This work is presented in the form of a preprint first author manuscript. Using the fly brain connectome, genetic tools, behavioral assays, and functional imaging, I show, together with co-authors Gina Pontes, Nicholas Jourjine and Alexander Del Toro, that the ISNs modulate a peptidergic network of neurons. These include a novel cell type Bilateral T shaped neuron (BiT), insulin producing cells (IPC), crustacean cardioactive peptide (CCAP) neurons, and CCHamide-2 receptor isoform RA (CCHa2R-RA) neurons. These neurons contribute differentially to ingestion of sugar and water, with BiT, IPCs and CCAP neurons oppositely regulating sugar and water ingestion, and CCHa2R-RA neurons modulating only water ingestion. Thus, the decision to consume sugar or water occurs via regulation of a broad peptidergic network that integrates internal signals of nutritional state to generate nutrient-specific ingestion.In chapter 3, I characterize other neurons that are involved in sugar and/or water ingestion. Using a computational approach to identify neurons in close proximity, genetic manipulation, behavioral assays, and in vivo functional imaging, I characterized several neurons involved in sugar and/or water ingestion regulation. Aster, bidirectionally regulates sugar and water ingestion just as the ISNs, Horseshoe, decreases both sugar and water ingestion, and Cowboy likely promotes sugar ingestion. In vivo functional connectivity experiments revealed that they were not downstream of the ISNs, however, Aster, possibly Horseshoe, and another cell type Gallinule are downstream of sensory neurons. Thus, I have identified another cell type that bidirectionally regulates sugar and water ingestion, two cell types that modulate feeding, and a cell type that likely conveys gustatory information to memory centers in the fly brain.In chapter 4, I describe with co-authors Zoila Alvarez-Aponte, Rachel Brem, Diana Bautista and Denzil Streete, the development and implementation of the Inclusive Excellence in Quals Prep (IEQP) program. This program was designed to provide mentorship, community, and academic support for students from diverse backgrounds as they prepared for their QE. The main components for IEQP program included pairing students with graduate student mentors, academic and wellness workshops, and community building events. This program was first implemented on a pilot cohort of 11 graduate students. After program evaluation, the most significant component of the program was peer mentorship. After program completion, students’ perception of their preparedness, QE-related skills, the support received from their advisors, and the agency they felt over their proposed work increased.In the final part of this dissertation, chapter 5, I summarize the main findings of this dissertation and propose future directions for exploration.