In this dissertation, I examine ion transport in nanopores, which has been met with increased interest in the last two decades due to its ability to detect DNA. I start with an overview of the properties of DNA and ionic transport in nanopores. I will explain some of the methods used for measuring ionic transport in nanopores using molecular dynamics. I will also discuss microcanonical formalism of electronic transport in nanoscale systems. This method of studying electronic transport is increasing in popularity as the emphasis on nanoscale devices increases. I will also discuss an open quantum systems approach to extending this formalism. Next, I will discuss the effect that small pore size has on the ionic conductance of that pore. A previous study predicted that as the radius of a nanopore increases, the conductance of a nanopore will exhibit discrete jumps when the radius of the pore is comparable to the radius of hydration layers around the current- carrying ions. I extend this prediction to different ion species, and conclude that it will be easier to detect these features by using divalent ions. I also look at what effect membrane dielectric choice and noise has on the current using the proposed theory. I will continue by proposing a new method of DNA sequencing, consisting of measuring the ionic current in a nanochannel that is transverse to a second, intersecting, nanochannel containing a single strand of DNA. The DNA will be pulled through its channel and modulations in the ionic current will allow the identities of the DNA bases to be deduced. A molecular dynamics model was used to test the feasibility of this method of sequencing. Finally, I will discuss a method for modeling electronic current in nanoscale systems. I use an open quantum systems approach (stochastic Schrodinger equation) to model a specific bath that has properties similar to how one would expect a battery to operate. This is used to increase the amount of time a system can exist in a quasi-steady current carrying state within the microcanonical formalism

We suggest the discrimination of single DNA bases via transverse ionic transport, namely by detecting the ionic current that flows in a channel while a single-stranded DNA is driven through an intersecting nanochannel. Our all-atom molecular dynamics simulations indeed show that the ionic currents of the four bases are statistically distinct, thus offering another possible approach to sequencing DNA.

We discuss a cosmology in which cold dark matter particles decay into relativistic particles. We argue that such decays could lead naturally to a bulk viscosity in the cosmic fluid. For decay lifetimes comparable to the present Hubble age, this bulk viscosity enters the cosmic energy equation as an effective negative pressure. We investigate whether this negative pressure is of sufficient magnitude to account for the observed cosmic acceleration. We show that a single decaying species in a Λ=0, flat, dark-matter dominated cosmology can not reproduce the observed magnitude-redshift relation from Type Ia supernovae. However, a delayed bulk viscosity, possibly due to a cascade of decaying particles may be able to account for a significant fraction of the apparent cosmic acceleration. Possible candidate nonrelativistic particles for this scenario include sterile neutrinos or gauge-mediated decaying supersymmetric particles. © 2007 The American Physical Society.

Epidemic trajectories and associated social responses vary widely between populations, with severe reactions sometimes observed. When confronted with fatal or novel pathogens, people exhibit a variety of behaviours from anxiety to hoarding of medical supplies, overwhelming medical infrastructure and rioting. We developed a coupled network approach to understanding and predicting social response. We couple the disease spread and panic spread processes and model them through local interactions between agents. The social contagion process depends on the prevalence of the disease, its perceived risk and a global media signal. We verify the model by analysing the spread of disease and social response during the 2009 H1N1 outbreak in Mexico City and 2003 severe acute respiratory syndrome and 2009 H1N1 outbreaks in Hong Kong, accurately predicting population-level behaviour. This kind of empirically validated model is critical to exploring strategies for public health intervention, increasing our ability to anticipate the response to infectious disease outbreaks.

We study the early evolution of the electron fraction (or, alternatively, the neutron-to-proton ratio) in the region above the hot proto-neutron star formed after a supernova explosion. We study the way in which the electron fraction in this environment is set by a competition between lepton (electron, positron, neutrino, and antineutrino) capture processes on free neutrons and protons and nuclei. Our calculations take explicit account of the effect of nuclear composition changes, such as formation of alpha particles (the alpha effect) and the shifting of nuclear abundances in nuclear statistical equilibrium associated with cooling in near-adiabatic outflow. We take detailed account of the process of weak interaction freeze-out in conjunction with these nuclear composition changes. Our detailed treatment shows that the alpha effect can cause significant increases in the electron fraction, while neutrino and antineutrino capture on heavy nuclei tends to have a buffering effect on this quantity. We also examine the effect on weak rates and the electron fraction of fluctuations in time in the neutrino and antineutrino energy spectra arising from hydrodynamic waves. Our analysis is guided by the Mayle & Wilson supernova code numerical results for the neutrino energy spectra and density and velocity profiles.

Problem

With the growth in risk-based and accountable care organization contracts, creating value by redesigning care to reduce costs and improve outcomes and the patient experience has become an urgent priority for health care systems.

Approach

In 2016, UCLA (University of California, Los Angeles) Health implemented a system-wide population health approach to identify patient populations with high expenses and promote proactive, value-based care. The authors created the Patient Health Value framework to guide value creation: (1) identify patient populations with high expenses and reasons for spending, (2) create design teams to understand the patient story, (3) create custom analytics and spending-based risk stratification, and (4) develop care pathways based on spending risk tiers. Primary care patients with three chronic conditions-dementia, chronic kidney disease (CKD), and cancer-were identified as high-cost subpopulations.

Outcomes

For each patient subpopulation, a multispecialty, multidisciplinary design team identified reasons for spending and created care pathways to meet patient needs according to spending risk. Larger, lower-risk cohorts received necessary but less intensive interventions, while smaller, higher-risk cohorts received more intensive interventions. Preliminary analyses showed a 1% monthly decrease in inpatient bed day utilization among dementia patients (incident rate ratio [IRR] 0.99, P < .03) and a 2% monthly decrease in hospitalizations (IRR 0.98, P < .001) among CKD patients.

Next steps

Use of the Patient Health Value framework is expanding across other high-cost subpopulations with chronic conditions. UCLA Health is using the framework to organize care across specialties, build capacity, and grow a culture for value.

We point out that a vμ or vτ neutrino with a cosmologically significant mass (10-100 eV) and a small mixing (vacuum mixing angle θ > 10-4) with a light ve would result in a matter-enhanced Mikheyev-Smirnov-Wolfenstein resonant transformation between these species in a region above the neutrino sphere but below the stalled shock during the reheating phase of a Type II supernova. The neutrino heating behind the shock is due to charged-current ve and v̄e captures. Since the vμ and vτ have considerably higher average energies than do the ve, neutrino flavor mixing would result in higher effective ve energies behind the shock and a concomitant increase in the heating rate. Our numerical calculations suggest that this effect results in a 60% increase in the supernova explosion energy, possibly helping to solve the energy problem of delayed-mechanism supernova models.

PROBLEM:With the growth in risk-based and accountable care organization contracts, creating value by redesigning care to reduce costs and improve outcomes and the patient experience has become an urgent priority for health care systems. APPROACH:In 2016, UCLA (University of California, Los Angeles) Health implemented a system-wide population health approach to identify patient populations with high expenses and promote proactive value-based care. The authors created the Patient Health Value framework to guide value creation: (1) identify patient populations with high expenses and reasons for spending; (2) create design teams to understand the patient story; (3) create custom analytics and spending-based risk stratification; and (4) develop targeted care pathways based on spending risk tiers. Primary care patients with three chronic conditions-dementia, chronic kidney disease (CKD), and cancer-were identified as high-cost subpopulations. OUTCOMES:For each patient subpopulation, a multispecialty, multidisciplinary design team identified reasons for spending and created care pathways to meet patient needs according to levels of spending risk. Larger, lower-risk cohorts received necessary but less intensive interventions while smaller, higher-risk cohorts received more intensive interventions. Preliminary analyses showed a 1% monthly decrease in inpatient bed day utilization among dementia patients (incident rate ratio [IRR] 0.99, P < .03) and a 2% monthly decrease in hospitalizations (IRR 0.98, P < .001) among CKD patients. NEXT STEPS:Use of the PHV framework is expanding across other high-cost subpopulations with chronic conditions. UCLA Health is using the framework to organize care across specialties, build capacity, and grow a culture for value.

Recent advances in de novo protein evolution have made it possible to create synthetic proteins from unbiased libraries that fold into stable tertiary structures with predefined functions. However, it is not known whether such proteins will be functional when expressed inside living cells or how a host organism would respond to an encounter with a non-biological protein. Here, we examine the physiology and morphology of Escherichia coli cells engineered to express a synthetic ATP-binding protein evolved entirely from non-biological origins. We show that this man-made protein disrupts the normal energetic balance of the cell by altering the levels of intracellular ATP. This disruption cascades into a series of events that ultimately limit reproductive competency by inhibiting cell division. We now describe a detailed investigation into the synthetic biology of this man-made protein in a living bacterial organism, and the effect that this protein has on normal cell physiology.