Taking dibaryon fields seriously

We propose a low energy effective field theory of QCD at the scale of pion mass for the $N_B=2$ sector, $N_B$ being the baryon number, which contains two dibaryon fields in addition to the nucleons and pions. It has a well defined counting, is renormalizable and the nucleon-nucleon scattering amplitudes are manifestly unitary at leading order. We work out a lower energy effective theory for nucleons with energy much lower than the pion mass and three momentum comparable to it, which also has a well defined counting and is renormalizable. The dibaryon fields must also be kept as explicit degrees of freedom in this theory. We calculate the scattering amplitudes at next-to-leading order for the $^1S_0$ and $^3S_1$ channels in this framework and obtain an excellent description of the phase shifts for center of mass energies in the $0-50 MeV$ range.Comment: 20 pages, 5 figures; misprints corrected, explanations enlarged, references added. Journal versio

Gender differences in STEM undergraduates' vocational interests: People–thing orientation and goal affordances

Citation: Yang Yang, Joan M. Barth, Gender differences in STEM undergraduates' vocational interests: People–thing orientation and goal affordances, Journal of Vocational Behavior, Volume 91, December 2015, Pages 65-75, ISSN 0001-8791, http://dx.doi.org/10.1016/j.jvb.2015.09.007. (http://www.sciencedirect.com/science/article/pii/S0001879115001062)This study addressed why women have greater representation in some STEM (science, technology, engineering, and mathematics) fields compared to others by linking two theoretical approaches, people–thing orientation (PO, TO) and role congruity theory, which emphasizes occupation goal affordances associated with traditionally feminine and masculine roles. Vocational interest and goal affordance ratings (having a positive social impact, family, and occupation status) for occupations characterized as working with people or things were assessed in 1848 students (42% female; 81% white non-Hispanic) majoring in biology (gender balanced), non-biology STEM (male-dominated), and female-dominated health fields. Participant PO and TO interests were also collected. Results indicated that non-biology STEM majors showed lower PO and higher TO interests than biology and health majors. Non-biology STEM majors also endorsed PO and TO interests at similar levels, but the other two major groups indicated higher PO than TO. People Jobs were perceived to more likely afford goals related to family and positive social impact; whereas Thing Jobs were perceived to more likely afford status goals. Interest in People Jobs was similar for women in both STEM major groups. Female non-biology STEM majors were equally interested in People and Thing Jobs; whereas biology majors preferred People Jobs. PO, TO, and goal affordance ratings independently predicted interest in People and Thing Jobs, and gender accounted for very little additional variance. Taken together, the findings point to the importance of using both person–thing orientation and role congruity theory when explaining varied gender representations in different STEM fields

A Q factor analysis approach to understanding female college students’ attitudes toward multiple STEM disciplines

Research on gender disparities in STEM (Science, Technology, Engineering, and Mathematics) has paid little attention to the fact that not all STEM disciplines experience the same degree of gender imbalance. Previous research has primarily examined a single STEM discipline or combined STEM disciplines in their analyses. This study addressed some of the limitations of previous research using an innovative statistical approach, Q factor analysis (QFA). QFA is used to explore multifaceted human perceptions, behaviors, and experiences. It enables researchers to categorize people based on their pattern of responses and opinions on a certain topic, in contrast to the more commonly used R factor analysis that categorizes variables. QFA was applied to a sample of 98 female undergraduate students who were enrolled in introductory STEM courses. Participants competed a survey that assessed their attitudes, experiences and beliefs about math, science, and computers. Questions tapped into constructs typically used in social cognitive models of academic and career choices. Two typologies emerged from the analyses. The math-computer group had favorable attitudes and beliefs toward math and computers and less interest in science; whereas the science group had more favorable attitudes and beliefs towards science. Participants? major choice and self-reported academic support aligned with the two groups in ways that were consistent with the groups? interests. The study demonstrates the potential for QFA to be applied with various types of data on a wide range of topics and to address questions that are not easily answered using traditional statistical approaches

A generalized SIRVS model incorporating non-Markovian infection processes and waning immunity

The Markovian approach, which assumes constant transmission rates and thus leads to exponentially distributed inter-infection times, is dominant in epidemic modeling. However, this assumption is unrealistic as an individual's infectiousness depends on its viral load and varies over time. In this paper, we present a SIRVS epidemic model incorporating non-Markovian infection processes. The model can be easily adapted to accurately capture the generation time distributions of emerging infectious diseases, which is essential for accurate epidemic prediction. We observe noticeable variations in the transient behavior under different infectiousness profiles and the same basic reproduction number R0. The theoretical analyses show that only R0 and the mean immunity period of the vaccinated individuals have an impact on the critical vaccination rate needed to achieve herd immunity. A vaccination level at the critical vaccination rate can ensure a relatively low incidence among the population in case of future epidemics, regardless of the infectiousness profiles

Quantifying the Economic Value of Vehicle-Grid Integration: A Case Study of Dynamic Pricing in the Sacramento Municipal Utility District

This study develops a stochastic-systems approach in modeling vehicle-grid integration (VGI), where load management strategies can be compared in terms of their economic value to plug-in electric vehicle (PEV) consumers and their local utility companies. The proposed methodology is demonstrated in an assessment of VGI for the Sacramento Municipal Utility District (SMUD) in California. Monte-Carlo simulations have been performed to randomly assign PEV charging characteristics of the households based on given statistical distributions. Consumer adoption of time-of-use (TOU) rates is modeled as an optimization problem where consumers seek the earliest PEV charge start time among the charge schedules resulting lowest cost and satisfying their transportation needs. The preliminary results show that, considering today’s grid system, the deployment of 60,000 PEVs in Sacramento Region will have significant but manageable impacts. These impacts included increasing annual peak demand by 86MWs (5%), and overloading up to 101 neighborhood transformers in the distribution system. On the other hand, adopting proper TOU rates presents a high potential for minimizing these negative impacts of widespread PEV deployment on the grid. The proposed methodology provided several improvements to the VGI modeling literature. These improvements included combining assessments for generation and distribution systems in the same model, and advancing uncertainty analysis for the PEV consumer behavior with considering real world data sets

Analysis of Sensor Coil Implemented in Maxwell-Wien Bridge Circuit for Detecting Ferrous and Non-Ferrous Particles

This paper presents an analysis of a wear debris sensor coil implemented in a Maxwell-Wien Bridge circuit used in detecting ferrous and non-ferrous particles. The sensor coil is designed to have a diameter approximately 15 times larger than the largest particle being detected. To detect particles up to 2 mm in diameter, a coil 30 mm in diameter was constructed. Simulations of the experiment indicate that the available particles should be detectable by the sensor coil. However, experimental results indicate that the Maxwell-Wien Bridge does not detect the available particles. Further simulations are presented accounting for parasitic capacitance of the sensor coil. The results from these simulations show that large parasitic capacitance affects the behavior of the bridge. The available particles were etched into smaller particles more typical of wear debris. It is expected that for a smaller coil, the effects of parasitic capacitance will be reduced