This dissertation explores a variant of the theory called the N = 3 Lee-Wick
Standard Model. The Lagrangian of this theory features a yet-higher derivative operator, which produces a propagator with three physical poles and possesses even better high-energy behavior than the minimal Lee-Wick theory. An analogous auxiliary field transformation takes this higher-derivative theory into a renormalizable theory with states of alternating positive, negative, and positive norm. The phenomenology of this theory is examined in detail, with particular emphasis on the collider signatures of Lee-Wick particles, electroweak precision constraints on the masses that the new particles can take on, and scenarios in early-universe cosmology in which Lee-Wick particles can play a significant role.
The same institutions (rules, norms and strategies) that dominated with the hierarchical infrastructure system of the twentieth century are unlikely to be good fit if a more distributed infrastructure increases in dominance. As information is produced at more distributed points, it is more difficult to coordinate and manage as an interconnected system. This research examines several aspects of these, historically dominant, infrastructure provisioning strategies to understand the implications of managing more distributed information. The first chapter experimentally examines information search and sharing strategies under different information protection rules. The second and third chapters focus on strategies to model and compare distributed energy production effects on shared electricity grid infrastructure. Finally, the fourth chapter dives into the literature of co-production, and explores connections between concepts in co-production and modularity (an engineering approach to information encapsulation) using the distributed energy resource regulations for San Diego, CA. Each of these sections highlights different aspects of how information rules offer a design space to enable a more adaptive, innovative and sustainable energy system that can more easily react to the shocks of the twenty-first century.
Use of psychostimulants, such as cocaine, is associated with an increased risk of human immunodeficiency virus (HIV) infection. Dopaminergic signaling within the nucleus accumbens (NAc) is critically implicated in both disease states, mediating the addictive and reinforcing effects of cocaine and perpetuating HIV replication throughout the central nervous system (CNS). Cocaine and HIV induce neurobehavioral deficits separately; however, little is known regarding how they interact to dysregulate neuroimmune function or how this impacts relapse vulnerability. We have previously shown that inhibition of dopamine D3 receptor (D3R) signaling using MC-25-41, a novel and highly selective D3R partial agonist, attenuates cocaine-seeking behavior. Here, we sought to characterize changes in neuroimmune function in a rat model of combined HIV and cocaine use disorders across abstinence and examined the therapeutic efficacy of MC-25-41 in the presence of this comorbidity. Male rats were systemically treated with the HIV protein gp120 after establishing a history of cocaine self-administration and then, following 21 days of abstinence, were administered a systemic injection of MC-25-41 (10 mg/kg) prior to cue reactivity testing. Glial fibrillary acidic protein (GFAP) and ionized calcium-binding adapter molecule 1 (Iba1) immunoreactivity were analyzed after 5 or 21 days of cocaine abstinence as an index of glial cell levels. We demonstrate that inhibition of D3R signaling significantly attenuates cue-induced cocaine seeking among control rats but not gp120-exposed rats. Moreover, we show that NAc core GFAP and Iba1 expression is impaired by 5 days of abstinence, which persists into protracted abstinence and cue reactivity testing. However, we also demonstrate that neither gp120 nor D3R inhibition significantly altered NAc core GFAP or Iba1 expression. Altogether, these results reveal significant changes in glial cell function across cocaine abstinence and unique behavioral interactions with gp120 may inhibit the effectiveness of medication regimens, which highlights the need to consider these comorbidities when treating HIV infection.
Human societies are unique in the level of cooperation among non-kin. Evolutionary models explaining this behavior typically assume pure strategies of cooperation and defection. Behavioral experiments, however, demonstrate that humans are typically conditional co-operators who have other-regarding preferences. Building on existing models on the evolution of cooperation and costly punishment, we use a utilitarian formulation of agent decision making to explore conditions that support the emergence of cooperative behavior. Our results indicate that cooperation levels are significantly lower for larger groups in contrast to the original pure strategy model. Here, defection behavior not only diminishes the public good, but also affects the expectations of group members leading conditional co-operators to change their strategies. Hence defection has a more damaging effect when decisions are based on expectations and not only pure strategies.
We use an agent-based model to analyze the effects of spatial heterogeneity and agents’ mobility on social-ecological outcomes. Our model is a stylized representation of a dynamic population of agents moving and harvesting a renewable resource. Cooperators (agents who harvest an amount close to the maximum sustainable yield) and selfish agents (those who harvest an amount greater than the sustainable yield) are simulated in the model. Three indicators of the outcomes of the system are analyzed: the number of settlements, the resource level, and the proportion of cooperators in the population. Our paper adds a more realistic approach to previous studies on the evolution of cooperation by considering a social-ecological system in which agents move in a landscape to harvest a renewable resource. Our results conclude that resource dynamics play an important role when studying levels of cooperation and resource use. Our simulations show that the agents’ mobility significantly affects the outcomes of the system. This response is nonlinear and very sensible to the type of spatial distribution of the resource richness. In our simulations, better outcomes of long-term sustainability of the resource are obtained with moderate agent mobility and cooperation is enhanced in harsh environments with low resource level in which cooperative groups have natural boundaries fostered by agents’ low mobility.
During the last 40 years evidence from systematic case study analysis and behavioral experiments have provided a comprehensive perspective on how communities can manage common resources in a sustainable way. The conventional theory based on selfish rational actors cannot explain empirical observations. A more comprehensive theoretical framework of human behavior is emerging that include concepts such as trust, conditional cooperation, other-regarding preferences, social norms, and reputation. The new behavioral perspective also demonstrates that behavioral responses depend on social and biophysical context.
Recently, there has been an increased interest in using behavioral experiments to study hypotheses on the governance of social-ecological systems. A diversity of software tools are used to implement such experiments. We evaluated various publicly available platforms that could be used in research and education on the governance of social-ecological systems. The aims of the various platforms are distinct, and this is noticeable in the differences in their user-friendliness and their adaptability to novel research questions. The more easily accessible platforms are useful for prototyping experiments and for educational purposes to illustrate theoretical concepts. To advance novel research aims, more elaborate programming experience is required to either implement an experiment from scratch or adjust existing experimental software. There is no ideal platform best suited for all possible use cases, but we have provided a menu of options and their associated trade-offs.
Allowing resource users to communicate in behavioural experiments on commons dilemmas increases the level of cooperation. In actual common pool resource dilemmas in the real world, communication is costly, which is an important detail missing from most typical experiments. We conducted experiments where participants must give up harvesting opportunities to communicate. The constrained communication treatment is compared with the effect of limited information about the state of the resource and the actions of the other participants. We find that despite making communication costly, performance of groups improves in all treatments with communication. We also find that constraining communication has a more significant effect than limiting information on the performance of groups.
Online communities are becoming increasingly important as platforms for large-scale human cooperation. These communities allow users seeking and sharing professional skills to solve problems collaboratively. To investigate how users cooperate to complete a large number of knowledge-producing tasks, we analyze Stack Exchange, one of the largest question and answer systems in the world. We construct attention networks to model the growth of 110 communities in the Stack Exchange system and quantify individual answering strategies using the linking dynamics on attention networks. We identify two answering strategies. Strategy A aims at performing maintenance by doing simple tasks, whereas strategy B aims at investing time in doing challenging tasks. Both strategies are important: empirical evidence shows that strategy A decreases the median waiting time for answers and strategy B increases the acceptance rate of answers. In investigating the strategic persistence of users, we find that users tends to stick on the same strategy over time in a community, but switch from one strategy to the other across communities. This finding reveals the different sets of knowledge and skills between users. A balance between the population of users taking A and B strategies that approximates 2:1, is found to be optimal to the sustainable growth of communities.