This thesis documents the development of a direct travel demand model for commuter rail in the San Francisco Bay Area. A direct demand model simultaneously estimates trip generation and attraction, which for this thesis would be trips between an origin-destination pair of stations. In the model, the number of trips assigned to an origin-destination pair of stations is dependent on land use characteristics at the origin and destination stations in combination with travel time on the network during congested peak periods and via transit. The model uses a multiplicative direct demand model to estimate ordinary least square regression parameters for the origin-destination trips. From the model form, the resultant estimated regression parameters are elasticities, and as such, can be used to postulate the effects of the selected land use characteristics and network travel times upon the number of trips made.

At both the origin and destination, the location of the station within the central business districts of the San Francisco Bay region had the largest effect on trip generation and attraction. Higher employment density at the destination and a larger number of workers per household at the origin had a positive effect on trips, while the total number of industrial workers at the destination and an increased number of two car households had a negative effect on trips. Longer travel times on transit appeared to have a positive effect on trips, yet longer travel times in congested peak periods appeared to have a negative effect on trips.

Abstract

Where the I Comes From

by

Ursula Kwong-Brown

Doctor of Philosophy in Music

and the

Designated Emphasis in New Media

in the

Graduate Division

University of California, Berkeley

Professor Myra Melford, Chair

I first read Josh Bell’s poem “Where the I Comes From” in the aftermath of the 2016 presidential election, at a time when it seemed like America was being torn apart by class and racial conflict. The poem spoke to me because it so honestly describes the propensity for violence which is hidden inside each of us. It is easy to blame one another for our country’s current state of xenophobia and the daily destruction of our democratic institutions, but much harder to recognize the seeds of jealousy, narcissism and hatred within ourselves. We must see our own faults clearly before we can find the common humanity from which we can address everyone – even our enemies – with love and compassion.

As one of the most sensitive in vivo molecular imaging modalities, fluorescence imaging has great potential to play an important role in preclinical and clinical studies. Indeed, in vivo fluorescence optical imaging extends across a wide range of applications, from cellular to organ levels. Unfortunately, in organ level applications, fluorescence imaging suffers from low spatial resolution due to the high scattering nature of biological tissue, especially in deep tissue (>1cm). Extensive effort has been spent to improve the spatial resolution of fluorescence tomography (FT). However, approaches such as integrating FT with other anatomic imaging modalities such as Magnetic Resonance Imaging (MRI) or computed tomography (CT) do not perform well if the fluorescent agent distribution within the medium cannot be defined in the anatomical image. There are also several techniques that attempt to modulate fluorescence signals using ultrasound to achieve higher spatial resolution. However, low modulation efficiency and extremely low signal to noise ratio (SNR) are the two primary factors that make the implementation of these techniques difficult.

Consequently, the poor spatial resolution and subsequent low quantitative accuracy are the main obstacles preventing the widespread use of this powerful technique in pre-clinical and clinical settings. To overcome these limitations, the goal of this thesis is to develop an entirely new approach termed, “Temperature-modulated fluorescence tomography (TM-FT)”, that can provide high resolution images at depths up to 6 cm without sacrificing the exceptional sensitivity of FT. In this innovative approach, FT is combined with temperature activatable fluorescence molecular probes (ThermoDots) and high intensity focused ultrasound (HIFU) which can provide localized heating of the tissue (only 3-5 °C) with high spatial resolution. The small size of the focal spot (~1.4 mm) allows imaging the distribution of these temperature sensitive agents with not only high spatial resolution but also high quantitative accuracy.

This thesis will present the development of the first TM-FT system prototype including the instrumentation and system design, image reconstruction algorithm, and ThermoDots probe development. The feasibility of this method to provide superior spatial resolution and high quantitative accuracy is validated using simulations and experimentally demonstrated in phantom and ex vivo tissue.

Major vascular surgery, including open aortic procedures, is associated with having a 30-day mortality rate greater than 6% and a perioperative complication rate greater than 50%. Published literature suggests that patients undergoing high-risk procedures benefit from having a care plan in place to not only maximize quality of life but also to ensure medical interventions align with care goals. Currently, there is a paucity of published data on the prevalence of goals of care conversations, advance care planning documentation, and palliative care evaluations in patients undergoing high-risk vascular operations. 

The measurement of cellular mechanical properties can be impactful in many areas of biosciences due to the interdependencies of mechanics and cell state or function. Mechanical cues communicated via mechanosensing and mechanotransduction can regulate cellular behavior leading to biochemical and structural modifications; conversely, native cellular processes such as differentiation, activation, and malignant transformation triggered by biochemical cues have also shown to elicit significant changes to the cellular architecture. Measurement of these mechanical biophysical changes can therefore be used to infer cell state or function. To date, there are numerous approaches used to measure the mechanical properties of cells for biophysics research, yet these are limited in their translational ability as general research or clinical tools. The biggest challenges facing successful translation of these mechanical phenotyping tools are due to the technological complexity, manual sample handling and preparation requirements, and limited sample throughput. This dissertation focuses on developing a high-throughput, label-free alternative for mechano phenotyping termed deformability cytometry. For the first time in the biophysics field, the deformability cytometry platform achieves throughputs of more than 1,000 cells/second; a rate that is three orders of magnitude greater than previous techniques. Additionally, initial work involving platform validation and proof-of-concept applications for stem cell differentiation, leukocyte activation, and cancer diagnostics are explored. The dissertation also undertakes a major engineering challenge of this system - large dataset image processing - which has led to the development of process efficient image analysis algorithms to increase the utility and robustness of this mechano phenotyping technique. Lastly, a clinical proof-of-concept study consisting of 119 patient pleural effusion samples were collected and assayed using the deformability cytometry platform to determine the diagnostic performance of mechanical biomarkers for malignant effusions. Briefly, the result of this clinical study achieved an area-under-the-curve of 0.91 with sensitivity and specificity of 100% and 69%, respectively. The high diagnostic accuracy combined with the ease-of-use, minimal sample preparations needs, and large sample sizes, satisfies many translational hurdles for a label-free mechano phenotyping platform for applications in the biosciences community.