A theoretical and empirical study of addiction

Consumption of addictive substances poses a challenge to economic models of rational, forward-looking agents. This dissertation presents a theoretical and empirical examination of consumption of addictive goods.

The theoretical model draws on evidence from psychology and neurobiology to improve on the standard assumptions used in intertemporal consumption studies. I model agents who may misperceive the severity of the future consequences from consuming addictive substances and allow for an agent's environment to shape her preferences in a systematic way suggested by numerous studies that have found craving to be induced by the presence of environmental cues associated with past substance use. The behavior of agents in this behavioral model of addiction can mimic the pattern of quitting and relapsing that is prevalent among addictive substance users.

Chapter 3 presents an empirical analysis of the Becker and Murphy (1988) model of rational addiction using data on grocery store sales of cigarettes. This essay empirically tests the model's predictions concerning consumption responses to future and past price changes as well as the prediction that the response to an anticipated price change differs from the response to an unanticipated price change. In addition, I consider the consumption effects of three institutional changes that occur during the time period 1996 through 1999.

Social saliency : visual psychophysics and single-neuron recordings in humans

My thesis studies how people pay attention to other people and the environment. How does the brain figure out what is important and what are the neural mechanisms underlying attention? What is special about salient social cues compared to salient non-social cues? In Chapter I, I review social cues that attract attention, with an emphasis on the neurobiology of these social cues. I also review neurological and psychiatric links: the relationship between saliency, the amygdala and autism. The first empirical chapter then begins by noting that people constantly move in the environment. In Chapter II, I study the spatial cues that attract attention during locomotion using a cued speeded discrimination task. I found that when the motion was expansive, attention was attracted towards the singular point of the optic flow (the focus of expansion, FOE) in a sustained fashion. The more ecologically valid the motion features became (e.g., temporal expansion of each object, spatial depth structure implied by distribution of the size of the objects), the stronger the attentional effects. However, compared to inanimate objects and cues, people preferentially attend to animals and faces, a process in which the amygdala is thought to play an important role. To directly compare social cues and non-social cues in the same experiment and investigate the neural structures processing social cues, in Chapter III, I employ a change detection task and test four rare patients with bilateral amygdala lesions. All four amygdala patients showed a normal pattern of reliably faster and more accurate detection of animate stimuli, suggesting that advantageous processing of social cues can be preserved even without the amygdala, a key structure of the “social brain”. People not only attend to faces, but also pay attention to others’ facial emotions and analyze faces in great detail. Humans have a dedicated system for processing faces and the amygdala has long been associated with a key role in recognizing facial emotions. In Chapter IV, I study the neural mechanisms of emotion perception and find that single neurons in the human amygdala are selective for subjective judgment of others’ emotions. Lastly, people typically pay special attention to faces and people, but people with autism spectrum disorders (ASD) might not. To further study social attention and explore possible deficits of social attention in autism, in Chapter V, I employ a visual search task and show that people with ASD have reduced attention, especially social attention, to target-congruent objects in the search array. This deficit cannot be explained by low-level visual properties of the stimuli and is independent of the amygdala, but it is dependent on task demands. Overall, through visual psychophysics with concurrent eye-tracking, my thesis found and analyzed socially salient cues and compared social vs. non-social cues and healthy vs. clinical populations. Neural mechanisms underlying social saliency were elucidated through electrophysiology and lesion studies. I finally propose further research questions based on the findings in my thesis and introduce my follow-up studies and preliminary results beyond the scope of this thesis in the very last section, Future Directions.

Spatial longitudinal coherence length of a thermal source and its influence on lensless ghost imaging

The spatial longitudinal coherence length (SLCL), which is determined by the size of and the distance from the source, is introduced to investigate the longitudinal resolution of lensless ghost imaging. Its influence is discussed quantitatively by simulation. The discrepancy of position sensitivity between Scareelli et al. [Appl. Phys. Lett. 88, 061106 (2006)] and Basano and Ottonello [Appl. Phys. Lett. 88, 091109 (2006)] is clarified. (C) 2008 Optical Society of America.

Temporal and spatial variations in the quality of water in El Gergal Reservior, Seville, Spain

It is often difficult to define ‘water quality’ with any degree of precision. One approach is that suggested by Battarbee (1997) and is based on the extent to which individual lakes have changed compared with their natural ‘baseline’ status. Defining the base-line status of artificial lakes and reservoirs however, is, very difficult. In ecological terms, the definition of quality must include some consideration of their functional characteristics and the extent to which these characteristics are self-sustaining. The challenge of managing lakes in a sustainable way is particularly acute in semi-arid, Mediterranean countries. Here the quality of the water is strongly influenced by the unpredictability of the rainfall as well as year-to-year variations in the seasonal averages. Wise management requires profound knowledge of how these systems function. Thus a holistic approach must be adopted and the factors influencing the seasonal dynamics of the lakes quantified over a range of spatial and temporal scales. In this article, the authors describe some of the ways in which both long-term and short-term changes in the weather have influenced the seasonal and spatial dynamics of phytoplankton in El Gergal, a water supply reservoir situated in the south of Spain. The quality of the water stored in this reservoir is typically very good but surface blooms of algae commonly appear during warm, calm periods when the water level is low. El Gergal reservoir is managed by the Empresa Municipal de Abastecimiento y Saneamiento (EMASESA) and supplies water for domestic, commercial and industrial use to an area which includes the city of Seville and twelve of its surrounding towns (ca. 1.3 million inhabitants). El Gergal is the last of two reservoirs in a chain of four situated in the Rivera de Huelva basin, a tributary of the Guadalquivir river. It was commissioned by EMASESA in 1979 and since then the company has monitored its main limnological parameters on, at least, a monthly basis and used this information to improve the management of the reservoir. As a consequence of these intensive studies the physical, chemical and biological information acquired during this period makes the El Gergal database one of the most complete in Spain. In this article the authors focus on three ‘weather-related’ effects that have had a significant impact on the composition and distribution of phytoplankton in El Gergal: (i) the changes associated with severe droughts; (ii) the spatial variations produced by short-term changes in the weather; (iii) the impact of water transfers on the seasonal dynamics of the dinoflagellate Ceratium.

High pressure states in condensed matter: I. High pressure behavior of the iron-sulphur system with applications to the earth's core. II. Empirical equation of state for organic compounds at high pressures

Part I:

The earth's core is generally accepted to be composed primarily of iron, with an admixture of other elements. Because the outer core is observed not to transmit shear waves at seismic frequencies, it is known to be liquid or primarily liquid. A new equation of state is presented for liquid iron, in the form of parameters for the 4th order Birch-Murnaghan and Mie-Grüneisen equations of state. The parameters were constrained by a set of values for numerous properties compiled from the literature. A detailed theoretical model is used to constrain the P-T behavior of the heat capacity, based on recent advances in the understanding of the interatomic potentials for transition metals. At the reference pressure of 10⁵ Pa and temperature of 1811 K (the normal melting point of Fe), the parameters are: ρ = 7037 kg/m³, K_S0 = 110 GPa, K_S' = 4.53, K_S" = -.0337 GPa-1, and γ = 2.8, with γ α ρ^-1.17. Comparison of the properties predicted by this model with the earth model PREM indicates that the outer core is 8 to 10 % less dense than pure liquid Fe at the same conditions. The inner core is also found to be 3 to 5% less dense than pure liquid Fe, supporting the idea of a partially molten inner core. The density deficit of the outer core implies that the elements dissolved in the liquid Fe are predominantly of lower atomic weight than Fe. Of the candidate light elements favored by researchers, only sulfur readily dissolves into Fe at low pressure, which means that this element was almost certainly concentrated in the core at early times. New melting data are presented for FeS and FeS₂ which indicate that the FeS₂ is the S-hearing liquidus solid phase at inner core pressures. Consideration of the requirement that the inner core boundary be observable by seismological means and the freezing behavior of solutions leads to the possibility that the outer core may contain a significant fraction of solid material. It is found that convection in the outer core is not hindered if the solid particles are entrained in the fluid flow. This model for a core of Fe and S admits temperatures in the range 3450K to 4200K at the top of the core. An all liquid Fe-S outer core would require a temperature of about 4900 K at the top of the core.

Part II.

The abundance of uses for organic compounds in the modern world results in many applications in which these materials are subjected to high pressures. This leads to the desire to be able to describe the behavior of these materials under such conditions. Unfortunately, the number of compounds is much greater than the number of experimental data available for many of the important properties. In the past, one approach that has worked well is the calculation of appropriate properties by summing the contributions from the organic functional groups making up molecules of the compounds in question. A new set of group contributions for the molar volume, volume thermal expansivity, heat capacity, and the Rao function is presented for functional groups containing C, H, and O. This set is, in most cases, limited in application to low molecular liquids. A new technique for the calculation of the pressure derivative of the bulk modulus is also presented. Comparison with data indicates that the presented technique works very well for most low molecular hydrocarbon liquids and somewhat less well for oxygen-bearing compounds. A similar comparison of previous results for polymers indicates that the existing tabulations of group contributions for this class of materials is in need of revision. There is also evidence that the Rao function contributions for polymers and low molecular compounds are somewhat different.

A variational framework for spectral discretization of the density matrix in Kohn Sham density functional theory

Kohn-Sham density functional theory (KSDFT) is currently the main work-horse of quantum mechanical calculations in physics, chemistry, and materials science. From a mechanical engineering perspective, we are interested in studying the role of defects in the mechanical properties in materials. In real materials, defects are typically found at very small concentrations e.g., vacancies occur at parts per million, dislocation density in metals ranges from $10^{10} m^{-2}$ to $10^{15} m^{-2}$, and grain sizes vary from nanometers to micrometers in polycrystalline materials, etc. In order to model materials at realistic defect concentrations using DFT, we would need to work with system sizes beyond millions of atoms. Due to the cubic-scaling computational cost with respect to the number of atoms in conventional DFT implementations, such system sizes are unreachable. Since the early 1990s, there has been a huge interest in developing DFT implementations that have linear-scaling computational cost. A promising approach to achieving linear-scaling cost is to approximate the density matrix in KSDFT. The focus of this thesis is to provide a firm mathematical framework to study the convergence of these approximations. We reformulate the Kohn-Sham density functional theory as a nested variational problem in the density matrix, the electrostatic potential, and a field dual to the electron density. The corresponding functional is linear in the density matrix and thus amenable to spectral representation. Based on this reformulation, we introduce a new approximation scheme, called spectral binning, which does not require smoothing of the occupancy function and thus applies at arbitrarily low temperatures. We proof convergence of the approximate solutions with respect to spectral binning and with respect to an additional spatial discretization of the domain. For a standard one-dimensional benchmark problem, we present numerical experiments for which spectral binning exhibits excellent convergence characteristics and outperforms other linear-scaling methods.