VictorJuiz/thesis huggingface dataset:
Simple algorithmic rules for complex human decisions

Decision makers must often choose a course of action under limited time with limited knowledge. In this work, we formalize longstanding observations about the efficacy of improper linear models to construct accurate yet easily applied rules that can help resource-constrained practitioners make better informed decisions that are consistent with their stated objectives. We find that simple rules can help substantially improve the performance of human experts, while rivaling the accuracy of complex prediction models that base decisions on considerably more information. Policy makers, however, may be reluctant to adopt such analytical tools due to the difficulty in anticipating, prior to deployment, the impact of resulting policies. In particular, one generally cannot use historical data to directly observe what would have happened had the recommended actions been taken. To address this issue, we present two strategies for gauging the sensitivity of predicted policy outcomes to potentially unmeasured confounders. We further investigate how humans compare to systematic rules when explicitly asked to assess risk of recidivism in the context of criminal justice. Our results show that systematic rules often perform better than humans in terms of both accuracy and ranking. Finally, we introduce a simple three-step strategy---which we call risk-adjusted regression---for measuring disparities that existing policies may have across different groups defined by race, gender, and other protected attributes that may be of interest. One popular strategy is to estimate disparities after controlling for observed covariates, typically with a regression model. This approach, however, suffers from two statistical challenges: omitted- and included-variable bias. Our proposed method addresses both concerns in settings where decision makers have clearly measurable objectives.

Keywords: Management Science and Engineering.
Advisor: Goel Sharad
Howard Ronald
Ugander Johan
Simulation and statistical tools for clinical biomechanics

Healthy gait requires complex coordination between the neuromuscular and skeletal systems. In patients with movement disorders such as cerebral palsy, these coordination patterns may be disrupted and their walking is inefficient and unstable. Understanding the interactions between the neuromuscular and skeletal systems is necessary for designing treatments to improve gait for individuals with impaired walking. This dissertation describes two classes of tools—physics-based dynamic simulation and statistical modeling—for understanding and improving human gait. First, we developed and validated a computer model of the full body that can be used to generate dynamic simulations of gait. We demonstrated how computer simulations of gait can be used to study muscle coordination in walking and running, as well as provide clinically-relevant metrics that can be used to make treatment recommendations. Second, we developed and tested statistical models that used biomechanical and mathematical features extracted from clinical gait analysis data to predict surgical outcomes in children with cerebral palsy. These statistical models were able to identify patients that are likely to have clinically-meaningful short-term and long-term improvements in gait following orthopedic surgery. This work demonstrates the utility of combining biomechanical modeling and statistical learning to improve clinical care for patients with gait pathology. Our musculoskeletal and statistical models are shared openly with the research and clinical community to allow others to adopt and build upon our work.

Keywords: Mechanical Engineering.
Advisor: Delp Scott 
Boyd Stephen P. 
Mitiguy Paul
Simulation of turbulent airflow and particle deposition in human and animal airways

Prolonged exposure to inhaled micron-sized airborne particles is a known public health concern. These particles impact the health of staggering numbers of residents of polluted urban areas, as well as significant portions of the third world where it is still common to burn wood or charcoal indoors for cooking or heating. An understanding of the fate of inhaled particles in the lungs is useful for assessing their associated health risks, as well as improving the effectiveness of respiratory drug delivery techniques. The transport of microparticles is inseparable from behavior of the suspending airflow and this is studied using computational fluid dynamics techniques. The anatomy of the airways seems to have evolved to encourage turbulent airflow for functions such as mixing of flow to promote the warming and humidification of inhaled air, as well as for filtration. Large eddy simulation models are employed to capture turbulent flow in extremely complex patient-specific airway geometries. These collectively comprise the oral and nasal cavities, larynx, trachea, and the bronchial tree. The flow in anatomically-accurate rhesus macaque airways is also studied. Simulations are carried out for inspiratory flow rates corresponding to nominal Reynolds numbers in the hundreds to low-thousands yet somewhat surprisingly yield unsteady flows due to local geometric factors. A computed mean flow field is compared extensively with magnetic resonance velocimetry measurements carried out in the same computed-tomography--based lung geometry, showing good agreement. Microparticle deposition predictions are also verified. Focus is placed on the dynamics of the flow in the nasal airway, trachea, and bronchial tree. After becoming unsteady at constrictions in the upper airways, the flow is found to be chaotic, exhibiting fluctuations with broad-band spectra even at the most distal simulated airways in which the Reynolds numbers are as low as 300. The unsteadiness is attributed to the convection of turbulent structures produced in the upper airways as well as to local kinetic energy production throughout the bronchial tree.

Keywords: Chemical Engineering.
Advisor: Iaccarino Gianluca 
Shaqfeh Eric S. G. (Eric Stefan Garrido) 
Marsden Alison (Alison Leslie)
Single station lightning location using azimuth and time of arrival of the sferics

Lightning is a fascinating and very frequent phenomena. On average 2000 active storms with flash rate of 40-50 per second happen daily all around the world. Lightning strikes produce electromagnetic waves, now referred to as sferics, in the very low frequency (VLF, 3--30 kHz) and the extremely low frequency (ELF, 3--30 kHz) bands. Within these frequency bands, the Earth and ionosphere form a waveguide in which sferics propagate long distances with low attenuation. The structure of the received sferic waveform is mainly a function of propagation distance and the waveguide parameters. This suggests that each observed sferic waveform contains information about the distance that this sferic has propagated which can be used to geolocate lightning. There are various approaches for analyzing received sferics, which mostly rely on measurements from multiple stations. However, in these methods, each station imposes an additional cost for building, maintenance, and synchronization. In this work, we present a novel method to estimate both the emission time and location of lightning, which works by measuring sferics recorded at a single station. We first process the sferic waveforms to obtain the arrival times of the VLF and ELF components of radiations which propagate with different speeds. Once these two separate arrival times are determined, we use them to approximate the distance the sferic propagated in the Earth-ionosphere waveguide. We have used this novel method in combination with a method to find sferic direction to geolocate a significant number of lightning strikes for July 4, 2013. Using this proposed method, the distance of propagation estimates are accurate to within 6.7% of the NLDN determined propagation distance and the direction of propagation estimates are accurate to within 1.3% of the NLDN determined direction.

Keywords: Electrical Engineering.
Advisor: Fraser-Smith A. C. (Antony C.) 
Gill John T.
Widrow Bernard
Single-cell analysis of immunity in inflammatory bowel diseases

Inflammatory bowel disease (IBD) includes Crohn's disease and ulcerative colitis. Each disease is characterized by a diverse set of potential manifestations, which determine patients' disease phenotype. Disease phenotype heterogeneity is a major contributor to frequent loss or lack of therapeutic response. Gut trafficking molecules allow leukocytes to home from the periphery to the gut, which may be altered in disease phenotypes. Current understanding of phenotype determinants is limited, despite increasing prevalence and healthcare costs of IBD. Diagnosis and monitoring of disease requires invasive procedures, such as endoscopy and tissue biopsy. Here we report signatures of heterogeneity between disease diagnoses and phenotypes. Using mass cytometry, we analyze leukocyte subsets, characterize their function(s), and examine gut-homing molecule expression in blood and intestinal tissue from healthy and/or IBD subjects. Some signatures persist in IBD despite remission, and many signatures are highly represented by leukocytes that express gut trafficking molecules. Moreover, distinct systemic and local immune signatures suggest patterns of cell localization in disease. Our findings highlight the importance of gut tropic leukocytes in circulation and reveal that blood-based immune signatures differentiate clinically relevant subsets of IBD. In addition, we show that B cells are differentially dysregulated in IBD subsets despite their lack of representation by literature in the field. B cells have important functions in the pathogenesis of autoimmune diseases, which to date has been particularly well-demonstrated for rheumatic diseases. In addition to producing autoantibodies, B cells contribute to autoimmunity by serving as professional antigen presenting cells (APCs), producing cytokines and through additional mechanisms. B cell activation and effector functions are regulated by immune checkpoints, including both activating and inhibitory checkpoint receptors that contribute to the regulation of B cell tolerance, activation, antigen presentation, T cell help, class switching, antibody production and cytokine production. The various activating checkpoint receptors include B cell activating receptors that engage with cognate receptors on T cells or other cells, as well as Toll-like receptors that can provide dual-stimulation to B cells via co-engagement with the B cell receptor. Furthermore, various inhibitory checkpoint receptors, including B cell inhibitory receptors, have important functions in regulating B cell development, activation and effector functions. Therapeutically targeting B cell checkpoints represents a promising strategy for the treatment of a variety of autoimmune diseases. Based on these findings, it is likely that B cells play an important role in IBD and thus are an important area of future investigation.

Advisor: Habtezion Aida
Robinson William (William Hewitt) 
Engleman Edgar G. 
Fathman C. Garrison
Maecker Holden
Single-ended laser-based diagnostics for thermometry and speciation in detonation-driven combustors

Detonation-driven combustors have received considerable research interest over the past several decades due to their theoretical thermodynamic advantages over conventional deflagration-driven combustion devices used in propulsion and power generation systems. The rotating detonation engine (RDE) architecture, in particular, has been identified as a promising path for achieving these thermodynamic advantages in practice due to their simple hardware geometries, lack of moving parts, ability to be continuously fed with propellants, and high operating frequencies. Central to increasing the technological readiness of RDEs is the development of robust, time-resolved sensors for in situ measurements of temperature and combustion products within the detonation chamber to validate computational models and guide practical design efforts. The work presented in this dissertation details the development, validation, and demonstration of a novel laser-absorption spectroscopy (LAS) sensor platform capable of performing time-resolved and simultaneous measurements of temperature, H2O, CO2, and CO concentrations within the annular gap of RDE test articles at the Naval Postgraduate School (NPS) in Monterey, CA. Despite the highly confined geometries (with path lengths on the order of 1 cm) and intense thermodynamic conditions (temperatures and pressures ranging from 700-2000 K and 2-8 atm, respectively) in the RDE test apparatus, the sensor achieved high-precision measurements of the target quantities through the use of four lasers probing strong mid-infrared absorption transitions near 2482, 2551, 4182, and 4854 nm and the implementation of wavelength-modulation spectroscopy (WMS), a LAS sensing technique capable of correcting for or rejecting many of the signal distortion sources commonly encountered in the harsh RDE detonation environment. The reported measurement rate of 44 kilosamples per second was sufficient to resolve intra-detonation cycle dynamics within the RDE. Additionally, to minimize perturbations to the combustion environment and to limit the hardware modifications needed for optical access into the RDE detonation chamber, the single-ended LAS sensing strategy---where the laser light was delivered into and collected from the detonation chamber through a single optical port---was used

Keywords: Mechanical Engineering.
Advisor: Hanson Ronald
Bowman Craig T. (Craig Thomas)
Strand Christopher Lyle
Single-molecule studies of kinesin mechanochemistry

Kinesin is a class of ATP-powered cytoskeletal motor proteins that translocate along, or exert forces against, microtubules (MTs). Kinesin motors mediate key aspects of a wide range of cellular processes, including cell division as well as long-range transport in neurons and cilia. One of these motors, kinesin-1—the founding member of the kinesin superfamily—is a highly-processive, dimeric motor, capable of transporting cargo micron-scale distances along its MT track. My earliest work explored fundamental aspects of how the ATP hydrolysis cycle and mechanical transitions of kinesin-1 are coordinated to give rise to its remarkable processivity. A key structural element for coordinating the two motor domains, or "heads", of kinesin-1 is the neck linker (NL), which connects each head to a common stalk. By investigating the motility properties of kinesin-1 motors under load using single-molecule optical trapping approaches, we discovered that the structural change driving kinesin motility, most likely NL docking, is completed only upon ATP hydrolysis, rather than immediately after ATP binding, as commonly suggested. In related work, we found that although tension transmitted through the NL when both heads of kinesin-1 are bound to the MT enhances motor velocity, it is not crucial for inter-head coordination. Instead, it is the spatial orientation of the NL that facilitates coordination of biochemical states of the two catalytic heads of a kinesin dimer. My subsequent work entailed leveraging single-molecule kinesin motility assays to extend our mechanistic understanding of cellular processes that require multiple, different kinesins to coordinate their motility in vivo. Intraflagellar transport (IFT)—cargo transport inside cilia—is one such process and is mediated by two different kinesin-2 motors: the slower KIF3AB and the faster KIF17. Using single-molecule characterizations of the motility of both motors, we were able determine the mechanism by which ciliary cargos attain in vivo velocities that are well in excess of the velocity of KIF3AB. Due to their key roles in important cellular processes, kinesins are also central to disease states that arise when these processes go awry, including cancer. Eg5, a kinesin-5 motor, has long been a target of anti-cancer drug development efforts due to its key role in mitosis. Unfortunately, no Eg5 inhibitor has progressed beyond clinical trials, in part because a kinesin-12 motor, KIF15, can rescue cell division when Eg5 is inhibited. However, unlike Eg5, little was known about KIF15, and no studies investigating a KIF15 inhibitor were available in the peer-reviewed literature prior to our work. To address this knowledge gap, my colleagues and I characterized KIF15 motility in detail at the single-molecule level. We also characterized a small-molecule inhibitor of KIF15, and obtained experimental support for earlier proposals that a combination drug therapy employing inhibitors of both KIF15 and Eg5 may be a viable strategy for overcoming KIF15-mediated resistance to inhibitors of Eg5.

Advisor: Block Steven M.
Fordyce Polly 
Greenleaf William James
Skyline locality sensitive hashing and simplified, efficient DEM rendering for large-scale, visual geo-localization

Locality sensitive hashing (LSH) of skyline features is used to expedite large-scale visual geo-localization in mountainous terrain. For queries with 60 degree FOV, LSH provides nearly the same localization accuracy as a state of the art reverse index method, but 10 times faster. LSH also provides approximately 25% better localization accuracy than a state of the art reverse index method pruned to give the same query speed. When tested on 196 photos from Baatz's CH1 data set LSH again matched or exceeded performance of the reverse index for queries with FOV > 30 degrees but was 40x faster than the full index, and was simultaneously 3x faster than an index pruned to contain less than 30% of the features. LSH and reverse index databases of skyline contourlets based on Baatz's method were built from rendered cubemaps of the ASTER GDEM. The coarse DEM resolution, small 2.5 degree feature width, and FOV-dependent database led to modest localization success rate of no more than 17% for any FOV bin, yet the relative accuracy of LSH vs. index-based methods clearly supports the claims of superior search speed with adjustable loss of accuracy compared to index pruning. Three open source tools are also presented, written in C++. Skybox Generator allows accurate, efficient rendering of images from large-scale DEMs, removing a significant barrier to entry for research in geometric matching-based localization at large scales. IM2SKY can extract skyline contourlet feature descriptors from sky-segmented images, and can quickly process large files. SKYLSH converts feature files into minhash signatures, hashes these signatures into LSH databases with adjustable numbers of files per band, and can perform LSH search for any features that are 32-bits or less.

Keywords: Mechanical Engineering.
Advisor: Kenny Thomas William 
Rock Stephen M. 
Schwager Mac
Sluggish Schizophrenia in the Soviet Union: A Diagnosis for Political Dissenters

The Soviet Union was well-known for its commitment to official ideology and its frequent punishment of those who acted or spoke against the regime. While methods of punishment for political dissenters varied, a particularly cruel and often overlooked method was the institutionalization of dissidents in psychiatric hospital-prisons. Dissenters punished in such a manner were often diagnosed with “sluggish schizophrenia,” a diagnosis developed by leading physician Andrei Snezhnevsky. This sham diagnosis had its roots in the legitimate symptoms of schizophrenia, but instead allowed healthy individuals to be diagnosed under the pretense that the disorder had simply not yet manifested. This paper examines this phenomenon through a broad exploration of the development of psychology in the Soviet Union, and specifically focuses on the roles played by psychiatrists, psychiatric institutions, and the state. Two primary case studies investigating the institutionalization of both Vladimir Bukovsky and Natalya Gorbanevskaya provide examples of the scope and intensity of Soviet abuses. Additionally, a multi-country comparative analysis places the Soviet Union within the global context, and illustrates the ways in which the Soviet Union was unique in its abuse of psychiatry. Ultimately, this understanding of both the roots and methods of Soviet abuse is essential for the prevention of further psychiatric abuse in present-day Russia.

Keywords:  Center for Russian
psychiatry
Soviet Union
schizophrenia
Stanford Global Studies
Center for Russian East European Studies
Thesis
Advisor: Weiner Amir
Mason Daniel
SNORD50A/B and SNARE proteins as KRAS Regulators

Cancers arise from aberrant signaling pathways responsible for otherwise normal cell growth and proliferation. RAS is one of the most commonly mutated gene families in human cancers, present in nearly a quarter of all cases, and its signaling is key to cell development. Because the RAS protein lacks well-defined hydrophobic pockets for small molecule binding, it is a challenging drug target; therefore, modulating its interactors’ activities is of immense therapeutic interest. Previous research uncovered a small noncoding RNA pair, SNORD50A/B, whose deletion is associated with higher rates of tumorigenesis. Further, preliminary data showed that three vesicle transport-associated proteins (SNAREs) interacted more with KRAS in the absence of SNORD50A/B. To characterize the binding relationships among KRAS, the snoRNA pair, and SNARE proteins, far-Western blotting and proximity-ligation assay (PLA) of human lung cancers cells were conducted in this work. In order to observe the effect of the interactors (SNAREs and SNORD50A/B) on KRAS downstream pathways (e.g. ERK and AKT), phosphorylation levels were examined via Western blotting. Results showed that SNARE proteins promote KRAS activity and compete with antagonistic regulator SNORD50A/B. This research demonstrates that SNARE proteins interact with the snoRNA pair SNORD50A/B to modulate KRAS activity. Better understanding of the role of these SNARE proteins in the oncogenic KRAS signaling pathway could be influential in researching more treatment targets, and this work stands to contribute to future studies in KRAS interactor-oriented therapies.

Keywords:  Department of Biology
Biology
KRAS
intracellular signaling
vesicle transport proteins
proteomics
cell biology
cancer biology
Thesis
Advisor: Khavari Paul
Morrison Ashby
Sociability Project: Social Media and Negative Well-Being

This is a literature review that focuses on the negative effects that social media use has on psychological well-being. Current research has resulted in positive effects from social media as well as negative effects. The purpose of this is to show the different ways in which social media use can led to negative outcomes in well-being. This literature review contains numerous studies and articles that explore the different ways in which social media negatively affects the well-being of social media users. This literature review uses a simple definition of what well-being is and simply shows how relationships connect to well-being. Because social media is based off of social relationships between users, the articles chosen will show how social media usage, leads to negative well-being.

Keywords:  Department of Communication
well-being
social media use
social well-being
positive well-being
negative well-being
Thesis
Advisor: Harari Gabriella M.