Investigating the Use of a Structured Self-determination Curriculum with Students with Gifts and Talents

The purpose of K-12 education in the 21st century is to graduate students fully prepared for college and careers. The skills necessary for a successful transition from postsecondary education to adulthood are the skills of self-determination. These skills include: (a) goal setting, (b) self-evaluation, (c) collaboration, (d) listening and communication, and (e) problem solving. Though elementary students with gifts and talents express an interest in career exploration, and often choose careers that require postsecondary education, they do not receive the guidance or skills to prepare them for life beyond school. No curriculum currently exists to teach these skills to students with gifts and talents. The purpose of this study was to teach self-determination skills to students with gifts and talents. The goal was to determine the impact of systematic, structured instruction on the skills of self-determination for students with gifts and talents. Specifically this study compared the use of a structured self-determination curriculum with a traditional scope and sequence curriculum. The results of this study demonstrate that elementary students with gifts and talents can learn the skills of self-determination through direct instruction using a structured self-determination curriculum. While the students who received the structured curriculum showed growth in their knowledge of self-determination skills over all phases of the study, the students who received the traditional scope and sequence curriculum showed no significant growth over time

Gestational dating by metabolic profile at birth: a California cohort study.

BackgroundAccurate gestational dating is a critical component of obstetric and newborn care. In the absence of early ultrasound, many clinicians rely on less accurate measures, such as last menstrual period or symphysis-fundal height during pregnancy, or Dubowitz scoring or the Ballard (or New Ballard) method at birth. These measures often underestimate or overestimate gestational age and can lead to misclassification of babies as born preterm, which has both short- and long-term clinical care and public health implications.ObjectiveWe sought to evaluate whether metabolic markers in newborns measured as part of routine screening for treatable inborn errors of metabolism can be used to develop a population-level metabolic gestational dating algorithm that is robust despite intrauterine growth restriction and can be used when fetal ultrasound dating is not available. We focused specifically on the ability of these markers to differentiate preterm births (PTBs) (<37 weeks) from term births and to assign a specific gestational age in the PTB group.Study designWe evaluated a cohort of 729,503 singleton newborns with a California birth in 2005 through 2011 who had routine newborn metabolic screening and fetal ultrasound dating at 11-20 weeks' gestation. Using training and testing subsets (divided in a ratio of 3:1) we evaluated the association among PTB, target newborn characteristics, acylcarnitines, amino acids, thyroid-stimulating hormone, 17-hydroxyprogesterone, and galactose-1-phosphate-uridyl-transferase. We used multivariate backward stepwise regression to test for associations and linear discriminate analyses to create a linear function for PTB and to assign a specific week of gestation. We used sensitivity, specificity, and positive predictive value to evaluate the performance of linear functions.ResultsAlong with birthweight and infant age at test, we included 35 of the 51 metabolic markers measured in the final multivariate model comparing PTBs and term births. Using a linear discriminate analyses-derived linear function, we were able to sort PTBs and term births accurately with sensitivities and specificities of ≥95% in both the training and testing subsets. Assignment of a specific week of gestation in those identified as PTBs resulted in the correct assignment of week ±2 weeks in 89.8% of all newborns in the training and 91.7% of those in the testing subset. When PTB rates were modeled using the metabolic dating algorithm compared to fetal ultrasound, PTB rates were 7.15% vs 6.11% in the training subset and 7.31% vs 6.25% in the testing subset.ConclusionWhen considered in combination with birthweight and hours of age at test, metabolic profile evaluated within 8 days of birth appears to be a useful measure of PTB and, among those born preterm, of specific week of gestation ±2 weeks. Dating by metabolic profile may be useful in instances where there is no fetal ultrasound due to lack of availability or late entry into care

Messaging in Scalaness: A Programming Language for Wireless Sensor Networks

This paper presents the design and implementation of three types of messaging primitives for the Scalaness programming language. The main idea behind this project was to extend the current version of Scalaness to include new messaging abstractions. Scalaness is a special purpose variant of Scala for running on the hub of a wireless sensor network. The three types of messages considered here are data reports from nodes to hub via a collection tree, small values sent from hub to nodes, and larger values sent from hub to nodes. These primitives are defined in the abstract, then implemented in Scala, and the necessary specifications for translation from Scalaness command to back end Scala code are made

Strategic Leadership: Do Supply Chain Management Leaders make Better Senior Executives?

Starting in the 1990’s, various companies began to see Logistics and Supply Chain Management as tools to gain competitive advantage in the marketplace (Li et. Al., 2006). The rise of Supply Chain Management (SCM) as a critical element of various companies’ strategies raises the question of the abilities of various leaders. For most companies, there is an assumption that the senior leader(s) should be a person whose operational and tactical experiences are in the basic function the company performs (i.e., a manufacturing company would be best led by an engineer that progressed through the manufacturing process/floor/plant/etc.) However, the assumption that tactical success will result in strategic success is likely flawed. Furthermore, many organizations struggle to develop talented managers to become excellent strategic leaders. It is estimated that organizations in the United States spend up to $200 billion annually to train their workforce (Salas and Cannon-Bowers, 2001). A second study identified that over half of CEOs (62%) recognized the importance and challenges of developing trained employees (Mourao, 2018). While neither study focused specifically on strategic leadership or training, both highlight the importance companies have traditionally placed on the development of their organizations’ individuals. Given this importance across all levels of the organization, it would be safe to assume that the critical nature of strategic leadership would be equally, if not more, important to develop key employees’ skills. However, the question becomes how to select and develop the best candidates for strategic development. Traditionally, organizations were likely to choose managers for promotion that matched their primary business (Breaugh, 2011). For example, a manufacturing firm would like choose an engineer with an operations background to be its CEO or key strategic The assumption is that the functions, skills and abilities that make a person successful in an area, lead to their promotion to higher and higher levels within that organization and would be best suited to the C-level. Perhaps a better approach would be to develop strategic leaders from a pool of managers that have strategic level responsibilities within their organization. The implication is that a SCM executive is often positioned earlier in their career and has boarder set of responsibilities than many functional leaders and could possibly be a better candidate for the strategic level position. This abstract is an early step in developing the literature, theories, propositions and methodology needed to examine the role of SCM leaders as future strategic leaders in organizations

The Helioseismic and Magnetic Imager (HMI) Vector Magnetic Field Pipeline: Overview and Performance

The Helioseismic and Magnetic Imager (HMI) began near-continuous full-disk solar measurements on 1 May 2010 from the Solar Dynamics Observatory (SDO). An automated processing pipeline keeps pace with observations to produce observable quantities, including the photospheric vector magnetic field, from sequences of filtergrams. The primary 720s observables were released in mid 2010, including Stokes polarization parameters measured at six wavelengths as well as intensity, Doppler velocity, and the line-of-sight magnetic field. More advanced products, including the full vector magnetic field, are now available. Automatically identified HMI Active Region Patches (HARPs) track the location and shape of magnetic regions throughout their lifetime. The vector field is computed using the Very Fast Inversion of the Stokes Vector (VFISV) code optimized for the HMI pipeline; the remaining 180 degree azimuth ambiguity is resolved with the Minimum Energy (ME0) code. The Milne-Eddington inversion is performed on all full-disk HMI observations. The disambiguation, until recently run only on HARP regions, is now implemented for the full disk. Vector and scalar quantities in the patches are used to derive active region indices potentially useful for forecasting; the data maps and indices are collected in the SHARP data series, hmi.sharp_720s. Patches are provided in both CCD and heliographic coordinates. HMI provides continuous coverage of the vector field, but has modest spatial, spectral, and temporal resolution. Coupled with limitations of the analysis and interpretation techniques, effects of the orbital velocity, and instrument performance, the resulting measurements have a certain dynamic range and sensitivity and are subject to systematic errors and uncertainties that are characterized in this report.Comment: 42 pages, 19 figures, accepted to Solar Physic

Socioeconomic Mediators of Racial and Ethnic Disparities in Congenital Heart Disease Outcomes: A Population-Based Study in California.

Background Racial/ethnic and socioeconomic disparities exist in outcomes for children with congenital heart disease. We sought to determine the influence of race/ethnicity and mediating socioeconomic factors on 1-year outcomes for live-born infants with hypoplastic left heart syndrome and dextro-Transposition of the great arteries. Methods and Results The authors performed a population-based cohort study using the California Office of Statewide Health Planning and Development database. Live-born infants without chromosomal anomalies were included. The outcome was a composite measure of mortality or unexpected hospital readmissions within the first year of life defined as >3 (hypoplastic left heart syndrome) or >1 readmissions (dextro-Transposition of the great arteries). Hispanic ethnicity was compared with non-Hispanic white ethnicity. Mediation analyses determined the percent contribution to outcome for each mediator on the pathway between race/ethnicity and outcome. A total of 1796 patients comprised the cohort (n=964 [hypoplastic left heart syndrome], n=832 [dextro-Transposition of the great arteries]) and 1315 were included in the analysis (n=477 non-Hispanic white, n=838 Hispanic). Hispanic ethnicity was associated with a poor outcome (crude odds ratio, 1.72; 95% confidence interval [CI], 1.37-2.17). Higher maternal education (crude odds ratio 0.5; 95% CI , 0.38-0.65) and private insurance (crude odds ratio, 0.65; 95% CI , 0.45-0.71) were protective. In the mediation analysis, maternal education and insurance status explained 33.2% (95% CI , 7-66.4) and 27.6% (95% CI , 6.5-63.1) of the relationship between race/ethnicity and poor outcome, while infant characteristics played a minimal role. Conclusions Socioeconomic factors explain a significant portion of the association between Hispanic ethnicity and poor outcome in neonates with critical congenital heart disease. These findings identify vulnerable populations that would benefit from resources to lessen health disparities

Potential Negative Cyclical Effects of ADHD Medication, Mental Health, and Academic Performance

In the past decade, the misuse of non-prescription ADHD medication among college students for the goal of achieving academic success has seen a marked increase. In order to determine if there is a relationship between study drugs, mental health, and GPA, an anonymous survey was distributed asking participants questions regarding demographics, prescribed and non-prescribed Adderall use, its effects, and perceptions. A total of 879 college-aged students from several US colleges completed the survey. Using Pearson\u27s Correlation Coefficient, there was a positive correlation between using non-prescribed Adderall use and a decrease in GPA, as well as a negative impact on mental health. The survey also showed that those who have a lower GPA exhibited several mental health symptoms, suggesting that there could be a vicious cycle at hand: non-prescribed study drugs, low GPA, and negative impact on mental health all act reciprocally, inexorably worsening the effects of the drug. Our results may indicate a lack of knowledge among non-prescribed users about the effects of Adderall, demonstrating a need for education outreach and alternative study methods. Data was collected from a multiple-choice survey and analyzed using SPSS, Version 25.0.https://orb.binghamton.edu/research_days_posters_spring2020/1041/thumbnail.jp

Investigating the Correlations between Frequency of ADHD Medication Use with Perception, Dependence, and Undesired Side Effects

ADHD medications are widely used by students across college campuses in order to enhance academic performance and concentration. Often times, students use these medications illicitly and are unaware of the side effects that may be caused by use. This study collected survey based data from 879 college aged students in the Northeast United States in order to better understand the scope, causes, and effects of the misuse of ADHD medications. Data was collected using a Google Survey and analyzed using Pearson\u27s Correlation Coefficient in SPSS, Version 25.0. Our results revealed significant correlations between frequency of ADHD medication use and perception of these types of medications. Specifically, use of ADHD medication about once a day was significantly correlated with nearly all of the undesired side effects inquired about in the survey, including panic attacks, aggression, and headaches. Despite experiencing these side effects, the about once a day users reported that they still perceived Adderall and similar medications to be more safe than caffeine and marijuana use. These findings shed light on the implications of ADHD medication use and suggest that outreach activities are needed to promote awareness on side effects of misuse.https://orb.binghamton.edu/research_days_posters_spring2020/1027/thumbnail.jp