Baryonic contributions to e+e- yields in a hydrodynamic model of Pb+Au collisions at the SPS

We analyze e+e- yields from matter containing baryons in addition to mesons using a hydrodynamic approach to describe Pb+Au collisions at 158 A GeV/c. We use two distinctly different e+e- production rates to provide contrast. Although the presence of baryons leads to significant enhancement of e+e- emission relative to that from mesons-only matter, the calculated results fall below the data in the range 400 < M/MeV < 600. The calculated results are, however, only 1.3-1.5 standard deviations below the data, which may not be statistically significant.Comment: 4 pages, 4 figures, proceedings of Quark Matter 9

Group Mentoring: A Study of Mentoring Groups in Three Programs

In an effort to provide more youth with mentors, mentoring programs are implementing several promising new approaches. This report describes the strengths and challenges of group mentoring-an approach that is gaining popularity. Findings suggest that group mentoring is reaching youth and volunteers who are unlikely to participate in traditional one-on-one mentoring, and that the approach may provide youth with important benefits, especially the development of social skills. On the other hand, mentoring groups vary widely in their size, structure and focus, and in the extent to which they foster strong mentoring relationships and benefits for youth. Implications for the mentoring field and for future research are discussed

AN EXAMINATION OF THE TREND IN INDUSTRIAL DISPERSION IN OKLAHOMA FROM 1963 THROUGH 1974

Industrial Organization,

Can We Build Behavioral Game Theory?

The way economists and other social scientists model how people make interdependent decisions is through the theory of games. Psychologists and behavioral economists, however, have established many deviations from the predictions of game theory. In response to these findings, a broad movement has arisen to salvage the core of game theory. Extant models of interdependent decision-making try to improve their explanatory domain by adding some corrective terms or limits. We will make the argument that this approach is misguided. For this approach to work, the deviations would have to be consistent. Drawing in part on our experimental results, we will argue that deviations from classical models are not consistent for any individual from one task to the next or between individuals for the same task. In turn, the problem of finding an equilibrium strategy is not easier but rather is exponentially more difficult. It does not seem that game theory can be repaired by adding corrective terms (such as consideration of personal characteristics, social norms, heuristic or bias terms, or cognitive limits on choice and learning). In what follows, we describe new methods for investigating interdependent decision-making. Our experimental results show that people do not choose consistently, do not hold consistent beliefs, and do not in general align actions and beliefs. We will show that experimental choices are inconsistent in ways that prevent us from drawing general characterizations of an individual’s choices or beliefs or of the general population\u27s choices and beliefs. A general behavioral game theory seems a distant and, at present, unfulfilled hope

Against Game Theory

People make choices. Often, the outcome depends on choices other people make. What mental steps do people go through when making such choices? Game theory, the most influential model of choice in economics and the social sciences, offers an answer, one based on games of strategy such as chess and checkers: the chooser considers the choices that others will make and makes a choice that will lead to a better outcome for the chooser, given all those choices by other people. It is universally established in the social sciences that classical game theory (even when heavily modified) is bad at predicting behavior. But instead of abandoning classical game theory, those in the social sciences have mounted a rescue operation under the name of “behavioral game theory.” Its main tool is to propose systematic deviations from the predictions of game theory, deviations that arise from character type, for example. Other deviations purportedly come from cognitive overload or limitations. The fundamental idea of behavioral game theory is that, if we know the deviations, then we can correct our predictions accordingly, and so get it right. There are two problems with this rescue operation, each of them is fatal. (1) For a chooser, contemplating the range of possible deviations, as there are many dozens, actually makes it exponentially harder to figure out a path to an outcome. This makes the theoretical models useless for modeling human thought or human behavior in general. (2) Modeling deviations are helpful only if the deviations are consistent, so that scientists (and indeed decision makers) can make predictions about future choices on the basis of past choices. But the deviations are not consistent. In general, deviations from classical models are not consistent for any individual from one task to the next or between individuals for the same task. In addition, people’s beliefs are in general not consistent with their choices. Accordingly, all hope is hollow that we can construct a general behavioral game theory. What can replace it? We survey some of the emerging candidates

When and where do feed-forward neural networks learn localist representations?

According to parallel distributed processing (PDP) theory in psychology, neural networks (NN) learn distributed rather than interpretable localist representations. This view has been held so strongly that few researchers have analysed single units to determine if this assumption is correct. However, recent results from psychology, neuroscience and computer science have shown the occasional existence of local codes emerging in artificial and biological neural networks. In this paper, we undertake the first systematic survey of when local codes emerge in a feed-forward neural network, using generated input and output data with known qualities. We find that the number of local codes that emerge from a NN follows a well-defined distribution across the number of hidden layer neurons, with a peak determined by the size of input data, number of examples presented and the sparsity of input data. Using a 1-hot output code drastically decreases the number of local codes on the hidden layer. The number of emergent local codes increases with the percentage of dropout applied to the hidden layer, suggesting that the localist encoding may offer a resilience to noisy networks. This data suggests that localist coding can emerge from feed-forward PDP networks and suggests some of the conditions that may lead to interpretable localist representations in the cortex. The findings highlight how local codes should not be dismissed out of hand

Estimating Potential Ground and Surface Water Pollution from Land Application of Poultry Litter - II

In Arkansas, approximately 1 Tg of poultry (Gallus gallus domesticus) manure and litter is produced annually. These waste products are commonly applied to pastures as a soil amendment or fertilizer, but excessive application rates and poor management practices could result in nutrient contamination of ground and surface water. The purpose of this study was to: (1) assess the nutrient concentrations in poultry manure and (2) evaluate the nitrogen loss from land-applied poultry litter and manure due to ammonia volatilization and denitrification. Analyses for total Kjeldahl nitrogen (TKN), inorganic nitrogen (Ni), phosphorus (P), and potassium (K) were compared in 12 wet and dry hen manure samples. Drying the manure reduced the TKN from 57 to 40 g N/kg on a dry weight basis in wet and dry manure, respectively. The Ni in the manure was in the ammoniacal form with values of 19 and 2 g N/kg for wet and dry manure, respectively. The P and K levels were not influenced by drying the manure and had values of 24 and 21 g/kg, respectively. The results indicate that the nitrogen content of hen manure can be significantly reduced by drying the sample prior to analysis. In a 10-day laboratory study and an 11-day field study to evaluate ammonia volatilization from surface-applied hen manure, results indicated that 37% of the total nitrogen content of the manure was lost. The results indicated that a substantial amount of nitrogen in surface-applied poultry waste can be lost due to ammonia volatilization. Laboratory studies to evaluate denitrification in a Captina silt loam amended with 9 Mg/ha of poultry litter were conducted. When the soil was aerobically incubated for 168 h and then flooded for 66 h, the nitrate-nitrogen level decreased a net of 17 mg N/kg. The results indicated that, if the ammoniacal nitrogen in the litter is oxidized to nitrate under aerobic conditions and then the soil is flooded and available carbon is present, denitrification can occur rapidly. Results from these studies indicate that soil and environmental conditions playa critical role in determining the potential for nitrate pollution of ground and surface water when poultry manure and litter are surface-applied to pastures