VictorJuiz/thesis huggingface dataset:
Role of the Beta-2 Adrenergic Receptor in Controlling Inflammatory Dynamics After Ischemic Stroke
Keywords:  Department of Bioengineering
bioengineering
neuroscience
neuroinflammation
stroke
post-stroke
adrenergic signaling
beta-2 adrenergic receptor
Thesis

Ischemic stroke is one of the leading causes of death and disability around the world. Stroke triggers inflammation in the brain, which plays a critical role in the eventual outcome of the infarct. This neuroinflammation is a dynamic process, involving microglia (the brain resident macrophages) in addition to several peripheral immune cells subsets that enter the brain from the bloodstream after stroke. Microglia and the monocyte-lineage cells that localize to the brain post- stroke highly express the beta-2 adrenergic receptor (β2-AR). Although studies have demonstrated that β2-AR signaling alters the activity of immune cells after stroke, the specifics of this modulation remain unclear. Using a mouse model of stroke, we examined the effects of stimulating or blocking this receptor with β2- AR affecting drugs on brain inflammation and infarct outcome. In addition, in order to better characterize the role of the β2-AR specifically for the microglia and invading immune cells, we created mice that had the receptor knocked out selectively in Cx3Cr1 expressing cells. Our experiments demonstrated that the stimulation of β2-AR on microglia and other invading immune cells decreased neuroinflammation by decreasing immune cell morphologic activation, rate of proliferation, and expression of pro-inflammatory cytokines. This limited inflammation resulted in an increased stroke size. In contrast, β2-AR blockade increased the expression of pro-inflammatory cytokines and increased the overall reactivity of immune cells in the stroke region. Interestingly, however, we also demonstrated that a certain degree of β2-AR activity helps spur cell proliferation. These findings elucidate some of the specific effects of β2-AR activity after stroke, allowing us to better understand the neuroinflammatory process of stroke and to identify new potential therapeutic techniques.
Roles of AtACINUS and AtPNN in alternative splicing and developmental transitions in Arabidopsis
Keywords: Biology.

Seed germination and flowering are two major developmental transitions in the life cycle of plants; their precise control is crucial for species survival in nature and involves complex regulatory mechanisms. Here, we report that the Arabidopsis AtACINUS and AtPNN proteins redundantly play key roles in regulating seed germination and flowering through alternative splicing (AS) and transcriptional regulation of target genes, respectively. The acinus pnn double mutant lacking both AtACINUS and AtPNN, which share sequence similarity only within a protein-protein interaction domain, showed severe growth defects including dwarfism, delayed seed germination and late flowering, while neither acinus nor pnn single mutant showed obvious morphological defect. Transcriptomic analysis of acinus pnn showed high levels of the flowering repressor FLC and RNAs responsive to abscisic acid (ABA), the hormone required for seed dormancy. The acinus pnn mutant also showed intron retention in many transcripts, including those encoding two negative regulators of ABA signaling: ABA-HYPERSENSITIVE 1 (ABH1) and HYPERSENSITIVE TO ABA 1 (HAB1). Consistent with these alterations of ABA-related transcripts, the acinus pnn mutant was hypersensitive to ABA treatment. Proteomic analyses indicate that AtACINUS is associated with the spliceosome and a large number of RNA-binding/processing proteins. AtACINUS associates with the RNAs of ABH1 and HAB1 and the promoter DNA of FLC in vivo, supporting its direct involvement in regulating AS and transcription. Our study uncovers important roles of AtACINUS/AtPNN in controlling key developmental transitions through dual functions in transcription and AS of target genes in Arabidopsis.
Rural Bank Expansion, Human Capital Development, and Intra-household Bias in India
Keywords:  Department of Economics
Department of Economics
economic development
Regional Rural Banks
infant mortality
child mortality
gender bias
birth-order bias
education
Thesis

In the 1970s and 1980s, the Indian Central Bank implemented an ambitious rural branch expansion program to bring bank access to unbanked areas of the nation. Previous research has found that this bank expansion program was effective in alleviating poverty in terms of state-level headcount ratios and in increasing rural usage of formal financial services, though no studies have examined human capital outcomes and the differential effects of this program on children of different gender or birth order. In this paper, I use an instrumental variables strategy to attempt an evaluation of the bank expansion program's effects on health and education outcomes. I find that the program had significant effects in reducing infant and child mortality rates at the state level, particularly for firstborns and male children. I find evidence that the program also had significant effects on state-level enrollment rates, without evidence of differential effects by student gender.
Saddle connections on translation surfaces
Keywords: Mathematics.

In this thesis I prove several theorems on the distribution and number of saddle connections (and cylinders) on translation surfaces. The first main theorem says that saddle connections become equidistributed on the surface. To state this formally we fix a translation surface X, and consider the measures on X coming from averaging the uniform measures on all the saddle connections of length at most R. The theorem is that as R approaches infinity, the weak limit of these measures exists and is equal to the area measure on X coming from the flat metric. This implies that, on any rational-angled billiard table, the billiard trajectories that start and end at a corner of the table become equidistributed on the table. The main ingredients in the proof are new results on counting saddle connections whose angle lies in a given interval, and a theorem of Kerckhoff-Masur-Smillie. The second main theorem concerns Siegel-Veech constants, which govern counts of saddle connections averaged over different translation surfaces. We show that for any weakly convergent sequence of ergodic SL2(R)-invariant probability measures on a stratum of unit-area translation surfaces, the corresponding Siegel-Veech constants converge to the Siegel-Veech constant of the limit measure. Combined with results of McMullen and Eskin-Mirzakhani-Mohammadi, this yields the (previously conjectured) convergence of sequences of Siegel-Veech constants associated to Teichmuller curves in genus two. The key technical tool used in the proofs of both the main theorems is a recurrence result for arcs of circles in the moduli space of translation surfaces. This is proved using the "system of integral inequalities'' approach first used by Eskin-Masur for translation surfaces.
Safety and efficiency in autonomous vehicles through planning with uncertainty
Keywords: Aeronautics and Astronautics.

Safety is the highest priority for autonomous vehicles, but if they are not also efficient in terms of time and other resources, they will have a significant competitive disadvantage and may not be adopted widely. Though safety and efficiency are opposing goals, better models and planning algorithms can result in simultaneous improvements to both. The partially observable Markov decision process (POMDP) provides a systematic framework for representing the chain of decisions that an autonomous vehicle makes when driving or flying. However, it is challenging to find optimal policies for POMDPs that represent continuous physical domains. This dissertation analyzes and demonstrates improvements related to several aspects of making safe and efficient decisions. First, it considers how pseudo-random approximate algorithms can be combined with trusted deterministic algorithms to make certification easier and increase reliability in an unmanned aerial vehicle domain. Second, simulation results demonstrate that modeling uncertainty in the internal states of other road users using POMDP planning can lead to significant improvement over a formulation that models only outcome uncertainty. Third, the research shows that current leading online POMDP algorithms are unable to solve some problems with continuous observation spaces and overcomes this weakness using double progressive widening and weighted particle filtering resulting in a new algorithm called POMCPOW. Finally, a description of the POMDPs.jl software framework is given.
Santa Cruz County struggles to overcome addiction amid opioid crisis
Keywords:  Department of Communication
Santa Cruz
Santa Cruz County
opioid
heroin
benzodiazepine
fentanyl
homelessness
overdose
Stanford University
Thesis

Opioid addiction is a much more severe problem in Santa Cruz County than in other parts of California. For the last decade, the county's opioid overdose death rates have been more than twice that of the rest of the state. Santa Cruz County's opioid crisis is difficult to diagnose, with the county's culture and homelessness contributing to the epidemic. This article discusses the roots of the opioid crisis and what has made Santa Cruz County so susceptible to it, as well as what health experts are doing to help the county overcome its addiction.
A scalable, practical approach to neural modulation & recording [electronic resource]
Keywords: Materials Science and Engineering.

Electrical recording and stimulation is one of the most promising modalities for next generation Brain Machine Interface (BMI) technologies, benefiting from being unhindered by the requirement of genetic modification (a significant barrier to practical deployment), while still being capable of single cell precision. Furthermore, large numbers of electrodes are becoming a critical requirement for next-generation neural interfaces. Electrode to brain interfaces have numerous applications, including neuro-prosthetics, treatment of disorders including epilepsy, depression, Alzheimer's, and restoring function for speech, eyesight, and motion. Microwire based BMI technology is extremely appealing, given the low-immunogenicity and little physiological damage shown during and after implantation of individual microwires. However, scaling from a few wires that are each individually connectorized to more than a thousand wires in parallel has not been possible. Here we describe a new methodology whereby we perform heterogeneous integration of a bundle of microwires (e.g., a large number of microwires collected together into a cylindrically packed aggregate) to a CMOS microchip with yields > 95%, and precise microwire spacing, critical for mitigating tissue damage. This architecture allows for each wire to be independently addressable for recording and/or stimulation purposes, ameliorating issues of scalability. We additionally demonstrate massively parallel recording using a mouse model, showing both spiking activity from single neurons and local field potentials. Lastly, we explore the mechanics of microwire insertion by directly measuring force & displacement in traditional brain mimics, freshly removed murine brains (ex vivo), and in vivo. Using flat polished (FP), angle polished (AP), and electro-sharpened (ES) microwires, we quantify the dimpling of the pia and associated vasculature to < 10 nm displacements, whilst measuring the force of pia puncture and beyond as it relates to wire diameter and tip geometry. Moreover, insertions were measured while observing with 2-photon microscopy, allowing us to directly view local vasculature and astrocytic populations, directly relating force of insertion to damage dealt.
Scale-dependence of rock physics models and transforms
Keywords: Geophysics.

The subsurface is a heterogeneous mixture of porous rocks volumes. Treating a rock volume that is intrinsically heterogeneous as a homogeneous body requires characterizing it with certain "effective" attributes. Numerous rock physics models and transforms implicitly treat rocks as homogeneous bodies as they require a single value for each of the rock's attributes as input. The question is if such rock physics models and transforms were established for rock samples at a given scale of measurement and treated as homogeneous bodies, will rock samples measured at coarser scale, yet once again treated as homogeneous bodies, still obey the model? This dissertation aims to find how to adapt/apply rock physics models and transforms that treat rocks as homogeneous bodies to a composite that is inherently heterogeneous. The key contributions of this dissertation are (1) estimations of effective elastic properties of heterogeneous bodies to be used in fluid substitution operations, (2) analysis of applicability of rock-physics models established at one scale of measurement (e.g., well-log scale) to coarse-scale measurements (e.g., seismic scale), (3) introduction of the notion of elastic mineral facies concept, (4) estimations of coarse-scale relations between the effective bulk modulus of the fluid to fluid saturation in a rock volume where two fluid phases are present, and (5) estimation and prediction of effective elastic properties of digital rock samples.
Schur indices and the p-adic langlands program
Keywords: Mathematics.

This dissertation uses the lens of the p-adic Langlands program to understand arithmetic questions about representations of some finite groups of Lie type. Any irreducible complex representation V of finite group G is realizable as a representation on a K-vector space for some number field K. Whether this is possible for a particular field K (necessarily containing all of the values of the character of V) is essentially controlled by a cohomological obstruction (belonging to the Brauer group of K), which is encoded in "local obstructions" at each place of K. To be specific, we consider cuspidal representations of the degree-two general and special linear groups GL_2(F_p) and SL_2(F_p) over the field with p elements, p an odd prime, and focus on the obstructions at p-adic places of K. These obstructions have previously been shown (via group-theoretic means) to vanish. In this dissertation, we present a new proof along the following lines: relate the original representation V to an (infinite-dimensional) p-adic Banach space representation of the corresponding p-adic group GL_2(Q_p) or SL_2(Q_p), use the p-adic Langlands correspondence to further relate that to a p-adic Galois representation W (or a close cousin), and compute the obstruction using W. The p-adic Langlands correspondence was already known for the degree-two general linear group over the p-adic numbers, but here we prove that it is suitably "natural" to transfer the Brauer obstruction from V to W (making our strategy possible). For the special linear group, on the other hand, there is no existing p-adic correspondence. Therefore, in this dissertation we construct a functor D_S, which we expect to realize the correspondence. This functor is a relative of the "Montreal functor" D that realizes the GL_2(Q_p) correspondence. Using the GL_2(Q_p) case as a guide, we then prove enough (though not all) of the expected properties of the SL_2(Q_p) correspondence, including its "naturality, " to carry out our above strategy.
Searching materials for novel physics from theory and from data [electronic resource]
Keywords: Physics.

Materials search and discovery is crucially important in condensed matter physics. Besides experimental trial-and-errors, there exist two types of methods to guide materials explorations: "from theory" that starts from theoretic analysis and numerical simulations, and "from data" that leverages massive materials data via statistical machine learning. I will present one work for each of both methods of materials discovery in this dissertation. Firstly, I will discuss the theoretic proposal and materials realization of anti-ferromagnetic Dirac semimetal. I will specifically show how a non-symmorphic crystal symmetry stabilizes a four-fold degenerate point in the electronic band structure of an anti-ferromagnetic system that is invariant under the combination of time-reversal and inversion symmetry, thus realizing massless Dirac fermions as low energy excitations. Secondly, I will talk about how to learn atoms' properties from extensive materials data, inspired by ideas from computational linguistics. I will present analysis of the constructed atom vectors, as well as their applications in data-based materials prediction using machine learning.
Secondary prevention of severe pneumonia in neurologically impaired children: a comparative effectiveness study
Keywords: children with special health care needs
neurologic impairment
comparative effectiveness
pediatrics
medicine
pneumonia
pediatric hospital medicine
Thesis

Background: Children with neurologic impairment (NI) have increased risk of pneumonia compared to other children. Pneumonia prevention strategies for children with NI are largely based on expert opinion with a limited evidence base. The objective of this study is to conduct a comparative effectiveness study of pneumonia prevention strategies in children with NI.
Methods: The California Children’s Services database contains complete capture of inpatient, outpatient, and pharmacy use for the largest Title V program in the United States. Our study population included children with NI and at least one pneumonia hospitalization. We excluded children with cystic fibrosis and whose only pneumonia hospitalization occurred during the index birth hospitalization. The primary outcome variable was subsequent pneumonia hospitalization. Exposure variables included: dental care, oral secretion management, gastric acid suppression, gastrostomy tube placement, chest physiotherapy, outpatient antibiotic prior to initial pneumonia hospitalization, clinic visit prior to initial pneumonia hospitalization, and clinic visit within 30 days after discharge for initial pneumonia hospitalization. Our primary analysis used a 1:2 propensity score matched model. Covariates for propensity score generation included sociodemographics (i.e. age, gender, race/ethnicity, type of CCS insurance) and characteristics of the initial pneumonia hospitalization (i.e. length of stay, ICU admission, pleurisy, intubation). Secondary analyses included a traditional logistic regression model using propensity score covariates and an inverse probability treatment weighted model.
Results: 3632 children with NI were included in our analysis. 1362 (37.5%) had a subsequent pneumonia hospitalization. Children had increased risk of subsequent pneumonia hospitalization if they had new gastrostomy tube placement (OR 3.09, CI 2.34-4.09), had a clinic visit within 7 days prior to initial hospital admission (OR 1.33, CI 1.10-1.61), or had a clinic visit within 30 days after discharge from initial hospital admission (OR 1.85, CI 1.45-2.35). No exposures were associated with reduced risk of subsequent pneumonia hospitalization. Similar patterns persisted in our traditional logistic regression and inverse probability treatment weighted analyses.
Conclusions: None of the pneumonia prevention strategies we evaluated were associated with decreased risk of subsequent severe pneumonia. Further validation of our findings is needed in other populations due to the risk of residual confounding by indication but a randomized control trial is needed for definitive assessment. The strongest association of gastrostomy tube with increased risk of severe pneumonia warrants particular attention given the common practice of gastrostomy tube placement in children with NI.
Securing the suburbs : how elites use policing to protect their advantages
Keywords: Sociology.

In the predominantly white, strongly liberal, extremely affluent suburb of Piedmont, California, residents mobilize security strategies to protect their advantages and invoke the language of security to justify their suburb's exclusivity. Drawing on in-depth interviews and participant observation, I argue that residents collaborate with their police department to surveille the "out of place" and thereby direct suspicion toward people of color and the poor and working class. Residents and police construct multiple layers of security to limit the presence of outsiders within Piedmont. They apply a market logic to government services to justify why suburban elites deserve more attentive, proactive police than people elsewhere. They claim affinity with the surrounding city of Oakland to recuperate cultural capital threatened by their suburb's homogeneity. Suburban security strategies perpetuate exclusion based on race and class, and suburban elites use the language of security to reconcile exclusive practices with their stated inclusive ideals.
Security Update Error: The Growing Issue of Human Trafficking in Japan
Keywords:  Stanford Global Studies
Stanford University
Center for East Asian Studies
Stanford Global Studies
East Asian Studies
Human Trafficking
Transnational Crime
Japan
Digital Technology
Thesis

This discourse provides an overview of human trafficking in Japan and illustrates how digital technologies have transformed the practice worldwide. Due to Japan's enormous entertainment industry, unique relationship with the yakuza, and heavily un-surveilled migration work programs, the country's human trafficking problem is growing. At the same time, digital technologies continue to reshape the way in which the practice is conducted. This analysis assesses the presence of human trafficking in Japan and describes how the country's legal framework inadequately addresses the issue. It also recommends ways the Japanese government can improve its efforts at combating the practice.
Self-programming networks : architecture and algorithms
Keywords: Electrical Engineering.

Networking has been a transformative technology over the past 3 decades, providing "connectivity" to people and businesses, enabling massive information networks and eCommerce, and bringing devices online through IoT technology. By providing "comprehension", Artificial Intelligence (AI) and Machine Learning (ML) promise to be similarly transformative: from image and speech recognition, to chatbots and machine translation, to self-driving cars. Working together, Networking and AI/ML are significantly impacting the business world and every aspect of our daily lives. This thesis describes our research on Self-Programming Networks (SPNs). SPNs aim to bring the power of AI/ML to the sensing, understanding and controlling of the operation of networks. Just as self-driving cars are built from traditional cars by adding sensors, controllers (steering and speed), and a lot of intelligence in the form of AI/ML algorithms, so too we envision SPNs to be built from traditional networks. We restrict our attention to data center networks and cloud computing environments. Our goal is to transform such networks into SPNs by adding suitable sensing and control capabilities, as well as algorithms and systems for sensing, inferring, learning and controlling. An SPN will observe the data emitted by a network during the course of its operation, reconstruct the network's evolution, infer key performance metrics, continually learn the best responses to rapidly-changing load and operating conditions, and help the network adapt to them in real time. We describe the architecture, algorithms and systems we have developed for SPNs. Specifically, we present a NIC-centric architecture for SPNs, describe systems and algorithms for (i) fine-grained network measurement using packet and probe timestamps taken at the edge, and (ii) nanosecond-level clock synchronization in real time and at scale. We also describe how these enhancements can enable new applications on top of SPNs. While our initial work has been on developing the sensing and inference capabilities of SPNs, we also describe future work on learning and control.