35 research outputs found

    Milwaukee Employer Engagement Training

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    The National Initiatives field building team delivered a training course to stakeholders in Milwaukee on effective employer engagement strategies. Employer engagement is essential to the success of transitional jobs (TJ) and subsidized employment programs. The training provided an overview of the NTJN's new Employer Engagement Toolkit, and included exercises to help providers hone their messaging to employers about the value of partnering with TJ and subsidized employment programs

    Healthy Relationships, Employment, and Reentry

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    This brief will provide an overview of the evidence supporting the interrelatedness of employment, healthy relationships, family well-being, and recidivism. It will also give the perspectives of expert program practitioners who are successfully integrating programming related to employment, prison reentry, healthy relationships, and responsible fatherhood. Finally, this brief will offer program and policy recommendations for leveraging the positive impacts of healthy relationships on employment and reentry and vice versa

    Providing True Opportunity for Opportunity Youth: Promising Practices and Principles for Helping Youth Facing Barriers to Employment

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    Many "opportunity youth" -- youth who are not working or in school -- would benefit substantially from gaining work experience but need help overcoming barriers to employment and accessing the labor market.Those opportunity youth facing the most significant challenges, such as extreme poverty, homelessness, and justice system involvement, often need even more intensive assistance in entering and keeping employment, and are at risk of being left behind even by employment programs that are specifically designed to serve opportunity youth.This paper builds on the research literature with extensive interviews with employment program providers who have had success in helping the most vulnerable opportunity youth succeed in the workforce. Six principles for effectively serving these youth are identified

    Hepatic leptospiral infections in dogs without obvious renal involvement.

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    BACKGROUND: Reports of chronic hepatitis in dogs caused by Leptospira spp. are confined to small case series. Fluorescence in situ hybridization (FISH) allows the identification of spirochetes in liver samples. Consequently, this technique may help elucidate the role of Leptospira spp. in cases of chronic hepatitis. OBJECTIVES: To describe cases of hepatic leptospirosis in dogs diagnosed by FISH and subsequent polymerase chain reaction (PCR) speciation, with the absence of clinically relevant renal involvement. ANIMALS: Ten client-owned dogs. METHODS: Retrospective case series from the University of Cambridge presented between 2013 and 2016 or cases consulted by telephone advice during this time period. Cases were selected based on histopathologically confirmed granulomatous hepatitis and leptospiral organisms identified by FISH and PCR speciation (Leptospira interrogans/kirschneri). RESULTS: All cases had increased liver enzyme activities, and FISH in combination with PCR speciation-confirmed infection with L. interrogans/kirschneri. Four dogs underwent repeat liver biopsy, FISH and PCR speciation 4-15 months after initial presentation and doxycycline treatment with 1 dog undergoing repeat sampling at necropsy. Three dogs that underwent repeat biopsy remained positive for L. interrogans/kirschneri infection. Six dogs were alive at the time of manuscript preparation and 4 dogs were euthanized as a result of progressive liver disease. CONCLUSIONS AND CLINICAL IMPORTANCE: The presence of hepatic leptospiral organisms may be associated with chronic granulomatous hepatitis without clinical evidence of renal involvement. Further studies are necessary to elucidate the etiological role of these organisms in the disease

    Receptive Field Inference with Localized Priors

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    The linear receptive field describes a mapping from sensory stimuli to a one-dimensional variable governing a neuron's spike response. However, traditional receptive field estimators such as the spike-triggered average converge slowly and often require large amounts of data. Bayesian methods seek to overcome this problem by biasing estimates towards solutions that are more likely a priori, typically those with small, smooth, or sparse coefficients. Here we introduce a novel Bayesian receptive field estimator designed to incorporate locality, a powerful form of prior information about receptive field structure. The key to our approach is a hierarchical receptive field model that flexibly adapts to localized structure in both spacetime and spatiotemporal frequency, using an inference method known as empirical Bayes. We refer to our method as automatic locality determination (ALD), and show that it can accurately recover various types of smooth, sparse, and localized receptive fields. We apply ALD to neural data from retinal ganglion cells and V1 simple cells, and find it achieves error rates several times lower than standard estimators. Thus, estimates of comparable accuracy can be achieved with substantially less data. Finally, we introduce a computationally efficient Markov Chain Monte Carlo (MCMC) algorithm for fully Bayesian inference under the ALD prior, yielding accurate Bayesian confidence intervals for small or noisy datasets

    Refinement and Pattern Formation in Neural Circuits by the Interaction of Traveling Waves with Spike-Timing Dependent Plasticity

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    Traveling waves in the developing brain are a prominent source of highly correlated spiking activity that may instruct the refinement of neural circuits. A candidate mechanism for mediating such refinement is spike-timing dependent plasticity (STDP), which translates correlated activity patterns into changes in synaptic strength. To assess the potential of these phenomena to build useful structure in developing neural circuits, we examined the interaction of wave activity with STDP rules in simple, biologically plausible models of spiking neurons. We derive an expression for the synaptic strength dynamics showing that, by mapping the time dependence of STDP into spatial interactions, traveling waves can build periodic synaptic connectivity patterns into feedforward circuits with a broad class of experimentally observed STDP rules. The spatial scale of the connectivity patterns increases with wave speed and STDP time constants. We verify these results with simulations and demonstrate their robustness to likely sources of noise. We show how this pattern formation ability, which is analogous to solutions of reaction-diffusion systems that have been widely applied to biological pattern formation, can be harnessed to instruct the refinement of postsynaptic receptive fields. Our results hold for rich, complex wave patterns in two dimensions and over several orders of magnitude in wave speeds and STDP time constants, and they provide predictions that can be tested under existing experimental paradigms. Our model generalizes across brain areas and STDP rules, allowing broad application to the ubiquitous occurrence of traveling waves and to wave-like activity patterns induced by moving stimuli
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