Lived Experiences of Orthodox Jewish Professionals Working with At-Risk Youth in the Orthodox Community

A phenomenological approach was used to explore the lived experience of Orthodox Jewish professionals (mental health practitioner, high school rabbi, mentor) trying to break the resistance and connect with the at-risk youth in the Orthodox Jewish community (OJC). OJC at-risk youth was defined as a) youth experiencing life disruptions (in family, school, community, and/or religious contexts) related to psychological issues and reflected in externalizing (e.g., delinquent ) or internalizing (e.g., depression) behaviors, and b) excluding a youth experiencing life disruptions due to non-compliance with parental and societal expectations (i.e., religious obligations) when devoid of a significant psychological component. Thirteen textural narratives illustrate the culture-specific manifestations of successful and unsuccessful attempts to connect with at-risk youth. In addition, four structural narratives offer insights into the essential components of the connection phenomenon, including, 1) Being non-judgmental, 2) Not taking it personally, 3) Being real, and 4) Focusing on well-being, not religion. The study concludes with reflections on the findings together with communal recommendations to help the OJC address its at-risk youth phenomenon

Parallel Longest Common SubSequence Analysis In Chapel

One of the most critical problems in the field of string algorithms is the longest common subsequence problem (LCS). The problem is NP-hard for an arbitrary number of strings but can be solved in polynomial time for a fixed number of strings. In this paper, we select a typical parallel LCS algorithm and integrate it into our large-scale string analysis algorithm library to support different types of large string analysis. Specifically, we take advantage of the high-level parallel language, Chapel, to integrate Lu and Liu's parallel LCS algorithm into Arkouda, an open-source framework. Through Arkouda, data scientists can easily handle large string analytics on the back-end high-performance computing resources from the front-end Python interface. The Chapel-enabled parallel LCS algorithm can identify the longest common subsequences of two strings, and experimental results are given to show how the number of parallel resources and the length of input strings can affect the algorithm's performance.Comment: The 27th Annual IEEE High Performance Extreme Computing Conference (HPEC), Virtual, September 25-29, 202

Sod-Busting and Sage Grouse: Estimating Historical Impacts and Planning for the Future

A conservation strategy for Greater sage grouse (Centrocercus urophasianus) in the Great Plains, where conversion of native rangeland to cropland is an accelerating agent of land use change, must anticipate impacts of future sod-busting on populations. We use resource selection functions (RSF) to estimate the scale and magnitude of the effect of sod-busting on the distribution of sage-grouse leks in the Great Plains Management Zone and estimate impacts of future cropland expansion. Active leks were used to develop a distribution envelope based on topographic and climatic variables from which random pseudo-absences were drawn to fit a used-available RSF. Models with proportion cropland at scales from 800 m to 8.5 km were compared using AICc to determine the most supported scale at which cropland influences lek occurrence. Finally, we develop a buildout scenario based on a cropland suitability model to estimate potential impacts of future sod-busting on known leks. Negative effects of cropland on lek occurrence were evident at all scales tested. The 6.4 km scale was most supported, and impacts were severe, with the relative probability of lek occurrence falling by 50% when about 20 percent of the landscape within 6.4 km was in cropland. These results, which highlight the large scale and magnitude of impacts of cropland on sage grouse populations, are needed to evaluate the potential contribution of conservation easements and land-use policy to local and range-wide sage-grouse conservation goals. Population-level benefits of targeted conservation implementation are explored

A photometricity and extinction monitor at the Apache Point Observatory

An unsupervised software ``robot'' that automatically and robustly reduces and analyzes CCD observations of photometric standard stars is described. The robot measures extinction coefficients and other photometric parameters in real time and, more carefully, on the next day. It also reduces and analyzes data from an all-sky $10 \mu m$ camera to detect clouds; photometric data taken during cloudy periods are automatically rejected. The robot reports its findings back to observers and data analysts via the World-Wide Web. It can be used to assess photometricity, and to build data on site conditions. The robot's automated and uniform site monitoring represents a minimum standard for any observing site with queue scheduling, a public data archive, or likely participation in any future National Virtual Observatory.Comment: accepted for publication in A

What Is the Proper Method to Delineate Home Range of an Animal Using Today’s Advanced GPS Telemetry Systems: The Initial Step

The formal concept of an animal’s home range, or derivations thereof, has been around for over half a century (Burt 1943). Within this time frame there have been countless published studies reporting home range estimators with no consensus for any single technique (Withey et al., 2001; Laver & Kelly 2008). Recent advances in global positioning system (GPS) technology for monitoring home range and movements of wildlife have resulted in locations that are numerous, more precise than very high frequency (VHF) systems, and often are auto correlated in space and time. Along with these advances, researchers are challenged with understanding the proper methods to assess size of home range or migratory movements of various species. The most acceptable method of home-range analysis with uncorrelated locations, kernel-density estimation (KDE), has been lauded by some for use with GPS technology (Kie et al., 2010) while criticized by others for errors in proper bandwidth selection (Hemson et al., 2005) and violation of independence assumptions (Swihart & Slade 1985b). The issue of autocorrelation or independence in location data has been dissected repeatedly by users of KDE for decades (Swihart & Slade 1985a; Worton 1995, but see Fieberg 2007) and can be especially problematic with data collected with GPS technology

Improved Learning in U.S. History and Decision Competence with Decision-Focused Curriculum

Decision making is rarely taught in high school, even though improved decision skills could benefit young people facing life-shaping decisions. While decision competence has been shown to correlate with better life outcomes, few interventions designed to improve decision skills have been evaluated with rigorous quantitative measures. A randomized study showed that integrating decision making into U.S. history instruction improved students' history knowledge and decision-making competence, compared to traditional history instruction. Thus, integrating decision training enhanced academic performance and improved an important, general life skill associated with improved life outcomes. © 2012 Jacobson et al

Experimental Study of Parametric Autoresonance in Faraday Waves

The excitation of large amplitude nonlinear waves is achieved via parametric autoresonance of Faraday waves. We experimentally demonstrate that phase locking to low amplitude driving can generate persistent high-amplitude growth of nonlinear waves in a dissipative system. The experiments presented are in excellent agreement with theory.Comment: 4 pages, 4 eps figures, to appear in Phys. Rev. Let