Dopaminergic stimulation increases selfish behavior in the absence of punishment threat.

RATIONALE People often face decisions that pit self-interested behavior aimed at maximizing personal reward against normative behavior such as acting cooperatively, which benefits others. The threat of social sanctions for defying the fairness norm prevents people from behaving overly selfish. Thus, normative behavior is influenced by both seeking rewards and avoiding punishment. However, the neurochemical processes mediating the impact of these influences remain unknown. Several lines of evidence link the dopaminergic system to reward and punishment processing, respectively, but this evidence stems from studies in non-social contexts. OBJECTIVES The present study investigates dopaminergic drug effects on individuals' reward seeking and punishment avoidance in social interaction. METHODS Two-hundred one healthy male participants were randomly assigned to receive 300 mg of L-3,4-dihydroxyphenylalanine (L-DOPA) or a placebo before playing an economic bargaining game. This game involved two conditions, one in which unfair behavior could be punished and one in which unfair behavior could not be punished. RESULTS In the absence of punishment threats, L-DOPA administration led to more selfish behavior, likely mediated through an increase in reward seeking. In contrast, L-DOPA administration had no significant effect on behavior when faced with punishment threats. CONCLUSIONS The results of this study broaden the role of the dopaminergic system in reward seeking to human social interactions. We could show that even a single dose of a dopaminergic drug may bring selfish behavior to the fore, which in turn may shed new light on potential causal relationships between the dopaminergic system and norm abiding behaviors in certain clinical subpopulations.

Restriction-modification gene complexes as selfish gene entities: Roles of a regulatory system in their establishment, maintenance, and apoptotic mutual exclusion

We have reported some type II restriction-modification (RM) gene complexes on plasmids resist displacement by an incompatible plasmid through postsegregational host killing. Such selfish behavior may have contributed to the spread and maintenance of RM systems. Here we analyze the role of regulatory genes (C), often found linked to RM gene complexes, in their interaction with the host and the other RM gene complexes. We identified the C gene of EcoRV as a positive regulator of restriction. A C mutation eliminated postsegregational killing by EcoRV. The C system has been proposed to allow establishment of RM systems in new hosts by delaying the appearance of restriction activity. Consistent with this proposal, bacteria preexpressing ecoRVC were transformed at a reduced efficiency by plasmids carrying the EcoRV RM gene complex. Cells carrying the BamHI RM gene complex were transformed at a reduced efficiency by a plasmid carrying a PvuII RM gene complex, which shares the same C specificity. The reduction most likely was caused by chromosome cleavage at unmodified PvuII sites by prematurely expressed PvuII restriction enzyme. Therefore, association of the C genes of the same specificity with RM gene complexes of different sequence specificities can confer on a resident RM gene complex the capacity to abort establishment of a second, incoming RM gene complex. This phenomenon, termed “apoptotic mutual exclusion,” is reminiscent of suicidal defense against virus infection programmed by other selfish elements. pvuIIC and bamHIC genes define one incompatibility group of exclusion whereas ecoRVC gene defines another.

Interaction of natural survival instincts and internalized social norms exploring the Titanic and Lusitania disasters

To understand human behavior, it is important to know under what conditions people deviate from selfish rationality. This study explores the interaction of natural survival instincts and internalized social norms using data on the sinking of the Titanic and the Lusitania. We show that time pressure appears to be crucial when explaining behavior under extreme conditions of life and death. Even though the two vessels and the composition of their passengers were quite similar, the behavior of the individuals on board was dramatically different. On the Lusitania, selfish behavior dominated (which corresponds to the classical homo oeconomicus); on the Titanic, social norms and social status (class) dominated, which contradicts standard economics. This difference could be attributed to the fact that the Lusitania sank in 18 minutes, creating a situation in which the short-run flight impulse dominates behavior. On the slowly sinking Titanic (2 hours, 40 minutes), there was time for socially determined behavioral patterns to re-emerge. To our knowledge, this is the first time that these shipping disasters have been analyzed in a comparative manner with advanced statistical (econometric) techniques using individual data of the passengers and crew. Knowing human behavior under extreme conditions allows us to gain insights about how varied human behavior can be depending on differing external conditions.

Altruism in the (Social) Network

This paper explores the role of social integration on altruistic behavior. To this aim, we develop a two-stage experimental protocol based on the classic Dictator Game. In the first stage, we ask a group of 77 undergraduate students in Economics to elicit their social network; in the second stage, each of them has to unilaterally decide over the division of a fixed amount of money to be shared with another anonymous member in the group. Our experimental design allows to control for other variables known to be relevant for altruistic behavior: framing and friendship/acquaintance relations. Consistently with previous research, we find that subjects favor their friends and that framing enhances altruistic behavior. Once we control for these effects, social integration (measured by betweenness, a standard centrality measure in network theory) has a positive effect on giving: the larger social isolation within the group, the more likely it is the emergence of selfish behavior. These results suggest that information on the network structure in which subjects are embedded is crucial to account for their behavior.

Design of Scheduling Algorithms Using Game Theoretic Ideas

Scheduling a set of jobs over a collection of machines to optimize a certain quality-of-service measure is one of the most important research topics in both computer science theory and practice. In this thesis, we design algorithms that optimize {\em flow-time} (or delay) of jobs for scheduling problems that arise in a wide range of applications. We consider the classical model of unrelated machine scheduling and resolve several long standing open problems; we introduce new models that capture the novel algorithmic challenges in scheduling jobs in data centers or large clusters; we study the effect of selfish behavior in distributed and decentralized environments; we design algorithms that strive to balance the energy consumption and performance.

The technically interesting aspect of our work is the surprising connections we establish between approximation and online algorithms, economics, game theory, and queuing theory. It is the interplay of ideas from these different areas that lies at the heart of most of the algorithms presented in this thesis.

The main contributions of the thesis can be placed in one of the following categories.

1. Classical Unrelated Machine Scheduling: We give the first polygorithmic approximation algorithms for minimizing the average flow-time and minimizing the maximum flow-time in the offline setting. In the online and non-clairvoyant setting, we design the first non-clairvoyant algorithm for minimizing the weighted flow-time in the resource augmentation model. Our work introduces iterated rounding technique for the offline flow-time optimization, and gives the first framework to analyze non-clairvoyant algorithms for unrelated machines.

2. Polytope Scheduling Problem: To capture the multidimensional nature of the scheduling problems that arise in practice, we introduce Polytope Scheduling Problem (\psp). The \psp problem generalizes almost all classical scheduling models, and also captures hitherto unstudied scheduling problems such as routing multi-commodity flows, routing multicast (video-on-demand) trees, and multi-dimensional resource allocation. We design several competitive algorithms for the \psp problem and its variants for the objectives of minimizing the flow-time and completion time. Our work establishes many interesting connections between scheduling and market equilibrium concepts, fairness and non-clairvoyant scheduling, and queuing theoretic notion of stability and resource augmentation analysis.

3. Energy Efficient Scheduling: We give the first non-clairvoyant algorithm for minimizing the total flow-time + energy in the online and resource augmentation model for the most general setting of unrelated machines.

4. Selfish Scheduling: We study the effect of selfish behavior in scheduling and routing problems. We define a fairness index for scheduling policies called {\em bounded stretch}, and show that for the objective of minimizing the average (weighted) completion time, policies with small stretch lead to equilibrium outcomes with small price of anarchy. Our work gives the first linear/ convex programming duality based framework to bound the price of anarchy for general equilibrium concepts such as coarse correlated equilibrium.

On data-centric misbehavior detection in VANETs

Detecting misbehavior (such as transmissions of false information) in vehicular ad hoc networks (VANETs) is a very important problem with wide range of implications, including safety related and congestion avoidance applications. We discuss several limitations of existing misbehavior detection schemes (MDS) designed for VANETs. Most MDS are concerned with detection of malicious nodes. In most situations, vehicles would send wrong information because of selfish reasons of their owners, e.g. for gaining access to a particular lane. It is therefore more important to detect false information than to identify misbehaving nodes. We introduce the concept of data-centric misbehavior detection and propose algorithms which detect false alert messages and misbehaving nodes by observing their actions after sending out the alert messages. With the data-centric MDS, each node can decide whether an information received is correct or false. The decision is based on the consistency of recent messages and new alerts with reported and estimated vehicle positions. No voting or majority decisions is needed, making our MDS resilient to Sybil attacks. After misbehavior is detected, we do not revoke all the secret credentials of misbehaving nodes, as done in most schemes. Instead, we impose fines on misbehaving nodes (administered by the certification authority), discouraging them to act selfishly. This reduces the computation and communication costs involved in revoking all the secret credentials of misbehaving nodes. © 2011 IEEE.

Sexual differences in parental feeding effort during the nestling period of the White-headed Marsh-Tyrant (Arundinicola leucocephala)

Parental effort may influence the fitness and survivorship of adult birds and their offspring from one breeding season to the next. Although much is known about parental feeding effort in tyrant flycatchers, many species remain understudied. In this study, I examined parental feeding effort of the White-headed Marsh-Tyrant (Awndinicola leucocephala) at a pond in southeastern Brazil. I conducted 10.3 hrs of observations from two locations: a high place with all view of the whole pond, that allowed me to observe flight distances of parents hunting for prey; and from near the nest to observe frequency of visits to the nest. The female marsh-tyrant flew farther while hunting prey and made more visits to the nest than did the male. The adults (mainly the female) provided a variety of terrestrial and aquatic arthropods to the nestlings. Additionally, parents removed fecal sacs from the nest and nestlings eliminated arthropod remains from the nest, the first records of nest sanitation activities by this species. Nonexclusive hypotheses that may explain the lower level of parental care provided by the male include: higher predation risk due its more conspicuous plumage, commitment of male to territory defense, and its selfish behavior influenced by indirect genotype fitness inherited by the offspring. © The Neotropical Ornithological Society.

Effect of Selfish Node Behavior on Efficient Topology Design

The problem of topology control is to assign per-node transmission power such that the resulting topology is energy efficient and satisfies certain global properties such as connectivity. The conventional approach to achieve these objectives is based on the fundamental assumption that nodes are socially responsible. We examine the following question: if nodes behave in a selfish manner, how does it impact the overall connectivity and energy consumption in the resulting topologies? We pose the above problem as a noncooperative game and use game-theoretic analysis to address it. We study Nash equilibrium properties of the topology control game and evaluate the efficiency of the induced topology when nodes employ a greedy best response algorithm. We show that even when the nodes have complete information about the network, the steady-state topologies are suboptimal. We propose a modified algorithm based on a better response dynamic and show that this algorithm is guaranteed to converge to energy-efficient and connected topologies. Moreover, the node transmit power levels are more evenly distributed, and the network performance is comparable to that obtained from centralized algorithms.

Pain expressiveness and altruistic behavior

Predictions which invoke evolutionary mechanisms ar e hard to test. Agent-based modeling in artificial life offers a way to simulate behaviors and interac tions in specific physical or social environments o ver many generations. The outcomes have implications fo r understanding adaptive value of behaviors in context. Pain-related behavior in animals is communicated to other animals that might protect or help, or might exploit or predate. An agent-based model simulated the effects of displaying or not displaying pain (expresser/non-expresser strategies) when injured, and of helping, ignoring or exploiting another in pain (altruistic/non-altruistic/selfish strategies) . Agents modeled in MATLAB interacted at random while foraging (gaining energy); random injury inte rrupted foraging for a fixed time unless help from an altruistic agent, who paid an energy cost, speeded recovery. Environmental and social conditions also varied, and each model ran for 10,000 iterations. Findings were meaningful in that, in general, conti ngencies evident from experimental work with a variety of mammals, over a few interactions, were r eplicated in the agent-based model after selection pressure over many generations. More energy-demandi ng expression of pain reduced its frequency in successive generations, and increasing injury frequ ency resulted in fewer expressers and altruists. Allowing exploitation of injured agents decreased e xpression of pain to near zero, but altruists remained. Decreasing costs or increasing benefits o f helping hardly changed its frequency, while increasing interaction rate between injured agents and helpers diminished the benefits to both. Agent- based modeling allows simulation of complex behavio urs and environmental pressures over evolutionary time.

The Behavior of Hydroxyl Units of Synthetic Goethite and its Dehydroxylated Product Hematite

The behavior of the hydroxyl units of synthetic goethite and its dehydroxylated product hematite was characterized using a combination of Fourier transform infrared (FTIR) spectroscopy and X-ray diffraction (XRD) during the thermal transformation over a temperature range of 180-270 degrees C. Hematite was detected at temperatures above 200 degrees C by XRD while goethite was not observed above 230 degrees C. Five intense OH vibrations at 3212-3194, 1687-1674, 1643-1640, 888-884 and 800-798 cm(-1), and a H2O vibration at 3450-3445 cm(-1) were observed for goethite. The intensity of hydroxyl stretching and bending vibrations decreased with the extent of dehydroxylation of goethite. Infrared absorption bands clearly show the phase transformation between goethite and hematite: in particular. the migration of excess hydroxyl units from goethite to hematite. Two bands at 536-533 and 454-452 cm(-1) are the low wavenumber vibrations of Fe-O in the hematite structure. Band component analysis data of FTIR spectra support the fact that the hydroxyl units mainly affect the a plane in goethite and the equivalent c plane in hematite.

Let's Dance: A Language for Service Behavior Modeling

In Service-Oriented Architectures (SOAs), software systems are decomposed into independent units, namely services, that interact with one another through message exchanges. To promote reuse and evolvability, these interactions are explicitly described right from the early phases of the development lifecycle. Up to now, emphasis has been placed on capturing structural aspects of service interactions. Gradually though, the description of behavioral dependencies between service interactions is gaining increasing attention as a means to push forward the SOA vision. This paper deals with the description of these behavioral dependencies during the analysis and design phases. The paper outlines a set of requirements that a language for modeling service interactions at this level should fulfill, and proposes a language whose design is driven by these requirements.

Multiple-choice versus short-response items: Differences in omit behavior

The overall rate of omission of items for 28,331 17 year old Australian students on a high stakes test of achievement in the common elements or cognitive skills of the senior school curriculum is reported for a subtest in multiple choice format and a subtest in short response format. For the former, the omit rates were minuscule and there was no significant difference by gender or by type of school attended. For the latter, where an item can be 'worth' up to five times that of a single multiple choice item, the omit rates were between 10 and 20 times that for multiple choice and the difference between male and female omit rate was significant as was the difference between students from government and non-government schools. For both formats, females from single sex schools omitted significantly fewer items than did females from co-educational schools. Some possible explanations of omit behaviour are alluded to.