Flux tubes and their interaction in U(1) lattice gauge theory

We investigate singly and doubly charged flux tubes in U(1) lattice gauge theory. By simulating the dually transformed path integral we are able to consider large flux tube lengths, low temperatures, and multiply charged systems without loss of numerical precision. We simulate flux tubes between static sources as well as periodically closed flux tubes, calculating flux tube profiles, the total field energy and the free energy. Our main results are that the string tension in both three and four dimensions scales proportionally to the charge -- which is in contrast to previous lattice results -- and that in four-dimensional U(1) there is an attractive interaction between flux tubes for beta approaching the phase transition.Comment: 19 pages, latex2e with tex- and eps-figures; complete postscript file also available at ftp://is1.kph.tuwien.ac.at/pub/zach/np97.ps.g

Not All Trails Are Straight: The Effects of Attachment on Rural Youth Residential Aspirations

The out-migration of rural youth is a critical issue for the sustainability of rural communities. Youth out-migration poses challenges for rural communities as they strive to address workforce shortages, population decline, and broader social and economic issues. The departure of youth from rural areas can decrease the diversity of local workforce skills, change the vitality of communities, and undermine community and economic development efforts. In addition, certain groups of young people in rural areas, such as queer young adults, face additional identity-based challenges that can influence their migration decisions and distinguish aspects of their decision-making from other youth. Exploring the residential aspirations of rural youth and queer young adults provides a means for better understanding drivers of youth out-migration and ways to attract and retain youth in rural communities. We used a mixed methods approach to better understand how different groups of young people living in rural areas, mainly students and queer young adults, experience attachment to the outdoors and form residential aspirations. By analyzing 2,027 survey responses from middle iii school and high school rural youth and 17 interviews with queer young adults attending college in a rural area, we advance understanding of how rural youth form their residential aspirations. Some of our results reveal higher outdoor place attachment is related to outdoor recreation engagement and higher chances of rural youth aspiring to live in a rural area. Other results show that queer rural youth desire to live in communities that value diversity, promote acceptance, and have accessible nature. Lastly, our work showed that queer rural youth value nature for more than just outdoor recreation, they also value it as a mental health resource. Our findings offer insights and recommendations for rural communities on how to attract and retain younger residents. One way is by offering ways to form place attachment in rural youth as they grow up, through maintaining outdoor spaces in the community and providing lots of opportunities for youth to spend time outdoors. Another suggestion is to promote inclusivity visibly within rural communities, an example being using symbols of acceptance such as pride flags in community spaces

Plate Pouring III

This project, Plate Pouring III, is an automated device that fills petri dishes with a liquid solution called Agar. This is done in a sterile environment, not needing any human interaction for the mechanism to function. It safely removes the lid individually from petri dishes, injects the solution, reinserts the lid, and stacks the filled petri dishes

Improving Hospital Patient Safety Through Teamwork: The Use of TeamSTEPPS in CAHs (Policy Brief #21)

This brief, one in a series identifying and assessing evidence-based patient safety and quality improvement interventions appropriate for use by state Flex Programs and CAHs, reviews teamwork and team training which have become a standard, evidence-based intervention in small and larger hospitals alike. The focus is on TeamSTEPPS, a training program developed and disseminated by the Department of Defense and the Agency for Healthcare Research and Quality. Key Findings: State Flex programs and CAHs have successfully adapted and used TeamSTEPPS to improve patient safety through team training. The evidence indicates that team training increases communications and reduces error. The success of TeamSTEPPS depends on having appropriate expectations and identifying and cultivating internal champions. Building a patient safety infrastructure helps sustain teamwork

Dynamically generated electric charge distributions in Abelian projected SU(2) lattice gauge theories

We show in the maximal Abelian gauge the dynamical electric charge density generated by the coset fields, gauge fixing and ghosts shows antiscreening as in the case of the non-Abelian charge. We verify that with the completion of the ghost term all contributions to flux are accounted for in an exact lattice Ehrenfest relation.Comment: LATTICE98(confine

The Error is the Feature: how to Forecast Lightning using a Model Prediction Error

Despite the progress within the last decades, weather forecasting is still a challenging and computationally expensive task. Current satellite-based approaches to predict thunderstorms are usually based on the analysis of the observed brightness temperatures in different spectral channels and emit a warning if a critical threshold is reached. Recent progress in data science however demonstrates that machine learning can be successfully applied to many research fields in science, especially in areas dealing with large datasets. We therefore present a new approach to the problem of predicting thunderstorms based on machine learning. The core idea of our work is to use the error of two-dimensional optical flow algorithms applied to images of meteorological satellites as a feature for machine learning models. We interpret that optical flow error as an indication of convection potentially leading to thunderstorms and lightning. To factor in spatial proximity we use various manual convolution steps. We also consider effects such as the time of day or the geographic location. We train different tree classifier models as well as a neural network to predict lightning within the next few hours (called nowcasting in meteorology) based on these features. In our evaluation section we compare the predictive power of the different models and the impact of different features on the classification result. Our results show a high accuracy of 96% for predictions over the next 15 minutes which slightly decreases with increasing forecast period but still remains above 83% for forecasts of up to five hours. The high false positive rate of nearly 6% however needs further investigation to allow for an operational use of our approach.Comment: 10 pages, 7 figure