The structure of the equal time anticommutator of the baryon current in neutral pseudoscalar meson theory

Equal time anticommutator structure of baryon currents in neutral pseudoscalar meson interaction

Building on MacNamara v. Korean Air Lines

This Note explores the possibility of applying Title VII\u27s disparate impact liability theory against foreign companies operating under Treaties of Friendship, Commerce, and Navigation (FCN Treaties). The author questions the reasoning of MacNamara v. Korean Air Lines, which applied disparate treatment, but not disparate impact, against a Korean company operating under an FCN Treaty. According to MacNamara, if courts permit plaintiffs in Title VII-FCN Treaty cases to utilize the disparate impact theory and cite statistical disparities in the racial composition of the work force as evidence of discrimination, employers could be held liable merely for exercising their FCN Treaty rights. This Note concludes that the MacNamara court ignored the complexity and costliness of presenting statistical data. More importantly, recovery under the disparate impact theory has become extremely difficult as a result of the Supreme Court\u27s subsequent decision Wards Cove Packing v. Atonio. Furthermore, the author concludes that any increase in Title VII liability--because of either narrowed FCN Treaty rights or the application of disparate impact analysis--likely will not affect foreign investment in the United States. Fear of widespread divestment in the United States should not be the controlling factor in the resolution of tension between Title VII and FCN Treaties. The author advocates that victims of employment discrimination should be entitled to bring disparate impact, as well as disparate treatment, claims in cases involving foreign corporations operating under FCN Treaties

The Air-temperature Response to Green/blue-infrastructure Evaluation Tool (TARGET v1.0) : an efficient and user-friendly model of city cooling

The adverse impacts of urban heat and global climate change are leading policymakers to consider green and blue infrastructure (GBI) for heat mitigation benefits. Though many models exist to evaluate the cooling impacts of GBI, their complexity and computational demand leaves most of them largely inaccessible to those without specialist expertise and computing facilities. Here a new model called The Air-temperature Response to Green/blue-infrastructure Evaluation Tool (TARGET) is presented. TARGET is designed to be efficient and easy to use, with fewer user-defined parameters and less model input data required than other urban climate models. TARGET can be used to model average street-level air temperature at canyon-to-block scales (e.g. 100 m resolution), meaning it can be used to assess temperature impacts of suburb-to-city-scale GBI proposals. The model aims to balance realistic representation of physical processes and computation efficiency. An evaluation against two different datasets shows that TARGET can reproduce the magnitude and patterns of both air temperature and surface temperature within suburban environments. To demonstrate the utility of the model for planners and policymakers, the results from two precinct-scale heat mitigation scenarios are presented. TARGET is available to the public, and ongoing development, including a graphical user interface, is planned for future work

Increased affective influence: situational complexity or deliberation time?

The affect infusion model (AIM) is a prominent theory of when current emotional state is expected to influence the interpretation of a social stimulus (situation). We discuss the assumptions in AIM and conclude that its current specification predicts that both deliberation time and situational complexity should lead to affect infusion. The aim of this research was to clarify the relative importance of these factors in determining affect infusion and hence promote the development of AIM. We present an experimental design in which situational complexity and deliberation time can be manipulated orthogonally as independent factors. Our results show that the latter factor, but not the former, can influence the degree of affect infusion

Neuronal nicotinic acetylcholine receptors: common molecular substrates of nicotine and alcohol dependence

Alcohol and nicotine are often co-abused. As many as 80-95% of alcoholics are also smokers, suggesting that ethanol and nicotine, the primary addictive component of tobacco smoke, may functionally interact in the central nervous system and/or share a common mechanism of action. While nicotine initiates dependence by binding to and activating neuronal nicotinic acetylcholine receptors (nAChRs), ligand-gated cation channels normally activated by endogenous acetylcholine (ACh), ethanol is much less specific with the ability to modulate multiple gene products including those encoding voltage-gated ion channels, and excitatory/inhibitory neurotransmitter receptors. However, emerging data indicate that ethanol interacts with nAChRs, both directly and indirectly, in the mesocorticolimbic dopaminergic (DAergic) reward circuitry to affect brain reward systems. Like nicotine, ethanol activates DAergic neurons of the ventral tegmental area (VTA) which project to the nucleus accumbens (NAc). Blockade of VTA nAChRs reduces ethanol-mediated activation of DAergic neurons, NAc DA release, consumption, and operant responding for ethanol in rodents. Thus, ethanol may increase ACh release into the VTA driving activation of DAergic neurons through nAChRs. In addition, ethanol potentiates distinct nAChR subtype responses to ACh and nicotine in vitro and in DAergic neurons. The smoking cessation therapeutic and nAChR partial agonist, varenicline, reduces alcohol consumption in heavy drinking smokers and rodent models of alcohol consumption. Finally, single nucleotide polymorphisms in nAChR subunit genes are associated with alcohol dependence phenotypes and smoking behaviors in human populations. Together, results from pre-clinical, clinical, and genetic studies indicate that nAChRs may have an inherent role in the abusive properties of ethanol, as well as in nicotine and alcohol co-dependence

Cognitive biases to healthy and unhealthy food words predict change in BMI

The current study explored the predictive value of cognitive biases to food cues (assessed by emotional Stroop and dot probe tasks) on weight change over a 1-year period. This was a longitudinal study with undergraduate students (N = 102) living in shared student accommodation. After controlling for the effects of variables associated with weight (e.g., physical activity, stress, restrained eating, external eating, and emotional eating), no effects of cognitive bias were found with the dot probe. However, for the emotional Stroop, cognitive bias to unhealthy foods predicted an increase in BMI whereas cognitive bias to healthy foods was associated with a decrease in BMI. Results parallel findings in substance abuse research; cognitive biases appear to predict behavior change. Accordingly, future research should consider strategies for attentional retraining, encouraging individuals to reorient attention away from unhealthy eating cues

Estimating everyday portion size using a 'method of constant stimuli': in a student sample, portion size is predicted by gender, dietary behaviour, and hunger, but not BMI

This paper (i) explores the proposition that body weight is associated with large portion sizes and (ii) introduces a new technique for measuring everyday portion size. In our paradigm, the participant is shown a picture of a food portion and is asked to indicate whether it is larger or smaller than their usual portion. After responding to a range of different portions an estimate of everyday portion size is calculated using probit analysis. Importantly, this estimate is likely to be robust because it is based on many responses. First-year undergraduate students (N=151) completed our procedure for 12 commonly consumed foods. As expected, portion sizes were predicted by gender and by a measure of dieting and dietary restraint. Furthermore, consistent with reports of hungry supermarket shoppers, portion-size estimates tended to be higher in hungry individuals. However, we found no evidence for a relationship between BMI and portion size in any of the test foods. We consider reasons why this finding should be anticipated. In particular, we suggest that the difference in total energy expenditure of individuals with a higher and lower BMI is too small to be detected as a concomitant difference in portion size (at least in our sample)

Demonstration of FPGA acceleration of Monte Carlo simulation

We present results from a stand-alone simulation of electron single Coulomb scattering as implemented completely on an Field Programmable Gate Array (FPGA) architecture and compared with an identical simulation on a standard CPU. FPGA architectures offer unprecedented speed-up capability for Monte Carlo simulations, however with the caveats of lengthy development cycles and resource limitation, particularly in terms of on-chip memory and DSP blocks. As a proof of principle of acceleration on an FPGA, we chose a single scattering process of electrons in water at an energy of 6 MeV. The initial code-base was implemented in C++ and optimised for CPU processing. To measure the potential performance gains of FPGAs compared to modern multi-core CPUs we computed 100M histories of a 6 MeV electron interacting in water. Without performing any hardware-specific optimisation, the results show that the FPGA implementation is over 110 times faster than an optimised parallel implementation running on 12 CPU-cores, and over 270 times faster than a sequential single-core CPU implementation. The results on both architectures were statistically equivalent. The successful implementation and acceleration results are very encouraging for the future exploitation of more sophisticated Monte Carlo simulation on FPGAs for High Energy Physics applications