Program Evaluation of the Summer Youth Employment & Learning Program (SYELP) at the Community Renewal Team (CRT)

The Community Renewal Team (CRT) is an anti‐poverty, non‐profit organization based in Hartford. For over 10 years they have run a Summer Youth Employment & Learning Program (SYELP). While CRT has been running this program for several years, it has recently made some structural modifications in order to improve the impact of the program. Thus, to determine the current impact of the program, to identify best practices and to suggest improvements, we conducted an evaluation of SYELP. Through student survey data collected by CRT and interviews that we conducted with supervisors, we gauged the strengths and weaknesses of the program in order to provide insight on the impact of the program and where improvements can be made to most effectively benefit the youth.https://elischolar.library.yale.edu/ysph_pbchrr/1035/thumbnail.jp

Quantitative EEG as a Prognostic Tool in Suspected Anti-N-Methyl-D-Aspartate Receptor Antibody Encephalitis

PURPOSE: Anti-N-methyl-D-aspartate receptor (anti-NMDAR) encephalitis is a form of autoimmune encephalitis associated with EEG abnormalities. In view of the potentially severe outcomes, there is a need to develop prognostic tools to inform clinical management. The authors explored whether quantitative EEG was able to predict outcomes in patients with suspected anti-NMDAR encephalitis. METHODS: A retrospective, observational study was conducted of patients admitted to a tertiary clinical neuroscience center with suspected anti-NMDAR encephalitis. Peak power and peak frequency within delta (<4 Hz), theta (4-8 Hz), alpha (8 - 13 Hz), and beta (13-30 Hz) frequency bands were calculated for the first clinical EEG recording. Outcome was based on the modified Rankin Scale (mRS) score at 1 year after hospital discharge. Binomial logistic regression using backward elimination was performed with peak frequency and power, anti-NMDAR Encephalitis One-Year Functional Status score, age, and interval from symptom onset to EEG entered as predictors. RESULTS: Twenty patients were included (mean age 48.6 years, 70% female), of which 7 (35%) had a poor clinical outcome (mRS 2-6) at 1 year. There was no association between reported EEG abnormalities and outcome. The final logistic regression model was significant (χ2(1) = 6.35, P < 0.012) with peak frequency in the delta range (<4 Hz) the only retained predictor. The model explained 38% of the variance (Nagelkerke R2) and correctly classified 85% of cases. Higher peak frequency in the delta range was significantly associated (P = 0.04) with an increased likelihood of poor outcome. CONCLUSIONS: In this exploratory study, it was found that quantitative EEG on routinely collected EEG recordings in patients with suspected anti-NMDAR encephalitis was feasible. A higher peak frequency within the delta range was associated with poorer clinical outcome and may indicate anti-NMDAR-mediated synaptic dysfunction. Quantitative EEG may have clinical utility in predicting outcomes in patients with suspected NMDAR antibody encephalitis, thereby serving as a useful adjunct to qualitative EEG assessment; however, given the small sample size, replication in a larger scale is indicated

Cognitive impact of neuronal antibodies: encephalitis and beyond.

Cognitive dysfunction is a common feature of autoimmune encephalitis. Pathogenic neuronal surface antibodies are thought to mediate distinct profiles of cognitive impairment in both the acute and chronic phases of encephalitis. In this review, we describe the cognitive impairment associated with each antibody-mediated syndrome and, using evidence from imaging and animal studies, examine how the nature of the impairment relates to the underlying neuroimmunological and receptor-based mechanisms. Neuronal surface antibodies, particularly serum NMDA receptor antibodies, are also found outside of encephalitis although the clinical significance of this has yet to be fully determined. We discuss evidence highlighting their prevalence, and association with cognitive outcomes, in a number of common disorders including cancer and schizophrenia. We consider mechanisms, including blood-brain barrier dysfunction, which could determine the impact of these antibodies outside encephalitis and account for much of the clinical heterogeneity observed

A Relational Event Approach to Modeling Behavioral Dynamics

This chapter provides an introduction to the analysis of relational event data (i.e., actions, interactions, or other events involving multiple actors that occur over time) within the R/statnet platform. We begin by reviewing the basics of relational event modeling, with an emphasis on models with piecewise constant hazards. We then discuss estimation for dyadic and more general relational event models using the relevent package, with an emphasis on hands-on applications of the methods and interpretation of results. Statnet is a collection of packages for the R statistical computing system that supports the representation, manipulation, visualization, modeling, simulation, and analysis of relational data. Statnet packages are contributed by a team of volunteer developers, and are made freely available under the GNU Public License. These packages are written for the R statistical computing environment, and can be used with any computing platform that supports R (including Windows, Linux, and Mac).

Safety assurance of a high voltage controller for an industrial robotic system

Due to the risk of discharge sparks and ignition, there are strict rules concerning the safety of high voltage electrostatic systems used in industrial painting robots. In order to assure that the system fulfils its safety requirements, formal verification is an important tool to supplement traditional testing and quality assurance procedures. The work in this paper presents formal verification of the most important safety functions of a high voltage controller. The controller has been modelled as a finite state machine, which was formally verified using two different model checking software tools; Simulink Design Verifier and RoboTool. Five safety critical properties were specified and formally verified using the two tools. Simulink was chosen as a low-threshold entry point since MathWorks products are well known to most practitioners. RoboTool serves as a software tool targeted towards model checking, thus providing more advanced options for the more experienced user. The comparative study and results show that all properties were successfully verified. The verification times in both tools were in the order of a few minutes, which was within the acceptable time limit for this particular application

Exploring the impact of mentoring functions on job satisfaction and organizational commitment of new staff nurses

<p>Abstract</p> <p>Background</p> <p>Although previous studies proved that the implementation of mentoring program is beneficial for enhancing the nursing skills and attitudes, few researchers devoted to exploring the impact of mentoring functions on job satisfaction and organizational commitment of new nurses. In this research we aimed at examining the effects of mentoring functions on the job satisfaction and organizational commitment of new nurses in Taiwan's hospitals.</p> <p>Methods</p> <p>We employed self-administered questionnaires to collect research data and select new nurses from three regional hospitals as samples in Taiwan. In all, 306 nurse samples were obtained. We adopted a multiple regression analysis to test the impact of the mentoring functions.</p> <p>Results</p> <p>Results revealed that career development and role modeling functions have positive effects on the job satisfaction and organizational commitment of new nurses; however, the psychosocial support function was incapable of providing adequate explanation for these work outcomes.</p> <p>Conclusion</p> <p>It is suggested in this study that nurse managers should improve the career development and role modeling functions of mentoring in order to enhance the job satisfaction and organizational commitment of new nurses.</p

Epidemiology of Subpatent Plasmodium Falciparum Infection: Implications for Detection of Hotspots with Imperfect Diagnostics.

At the local level, malaria transmission clusters in hotspots, which may be a group of households that experience higher than average exposure to infectious mosquitoes. Active case detection often relying on rapid diagnostic tests for mass screen and treat campaigns has been proposed as a method to detect and treat individuals in hotspots. Data from a cross-sectional survey conducted in north-western Tanzania were used to examine the spatial distribution of Plasmodium falciparum and the relationship between household exposure and parasite density. Dried blood spots were collected from consenting individuals from four villages during a survey conducted in 2010. These were analysed by PCR for the presence of P. falciparum, with the parasite density of positive samples being estimated by quantitative PCR. Household exposure was estimated using the distance-weighted PCR prevalence of infection. Parasite density simulations were used to estimate the proportion of infections that would be treated using a screen and treat approach with rapid diagnostic tests (RDT) compared to targeted mass drug administration (tMDA) and Mass Drug Administration (MDA). Polymerase chain reaction PCR analysis revealed that of the 3,057 blood samples analysed, 1,078 were positive. Mean distance-weighted PCR prevalence per household was 34.5%. Parasite density was negatively associated with transmission intensity with the odds of an infection being subpatent increasing with household exposure (OR 1.09 per 1% increase in exposure). Parasite density was also related to age, being highest in children five to ten years old and lowest in those > 40 years. Simulations of different tMDA strategies showed that treating all individuals in households where RDT prevalence was above 20% increased the number of infections that would have been treated from 43 to 55%. However, even with this strategy, 45% of infections remained untreated. The negative relationship between household exposure and parasite density suggests that DNA-based detection of parasites is needed to provide adequate sensitivity in hotspots. Targeting MDA only to households with RDT-positive individuals may allow a larger fraction of infections to be treated. These results suggest that community-wide MDA, instead of screen and treat strategies, may be needed to successfully treat the asymptomatic, subpatent parasite reservoir and reduce transmission in similar settings

Network Archaeology: Uncovering Ancient Networks from Present-day Interactions

Often questions arise about old or extinct networks. What proteins interacted in a long-extinct ancestor species of yeast? Who were the central players in the Last.fm social network 3 years ago? Our ability to answer such questions has been limited by the unavailability of past versions of networks. To overcome these limitations, we propose several algorithms for reconstructing a network's history of growth given only the network as it exists today and a generative model by which the network is believed to have evolved. Our likelihood-based method finds a probable previous state of the network by reversing the forward growth model. This approach retains node identities so that the history of individual nodes can be tracked. We apply these algorithms to uncover older, non-extant biological and social networks believed to have grown via several models, including duplication-mutation with complementarity, forest fire, and preferential attachment. Through experiments on both synthetic and real-world data, we find that our algorithms can estimate node arrival times, identify anchor nodes from which new nodes copy links, and can reveal significant features of networks that have long since disappeared.Comment: 16 pages, 10 figure