Beyond Basic Needs: Social Support and Structure for Successful Offender Reentry

Barriers to successful reentry have long been identified as impeding an offender’s ability to successfully reenter society upon release from incarceration. As a result, research has long examined what shared obstacles the majority of offenders often face upon reentering society. Much of the research identifies factors such as poor education, obtaining/maintaining employment, stable housing, and transportation as common barriers to successful reentry. By using in-depth interviews with ex-offenders deemed as successful that were conducted by two respective non-profit agencies, the present study explores what significant requirements, if any, successful offenders perceive to need and/or have experienced as lacking while attempting to successfully reenter society. Findings from this study highlight that many of the research- identified needs are not major barriers because they are often provided for by various non-profit agencies. Furthermore, successful ex-offenders overwhelmingly identify poor social support as a major barrier that oftentimes remains neglected in government and non-profit organizational programming

Use of satellite-derived heterogeneous surface soil moisture for numerical weather prediction, The

Summer 1996.Bibliography: pages [296]-320

GRO J1744-28, search for the counterpart: infrared photometry and spectroscopy

Using VLT/ISAAC, we detected 2 candidate counterparts to the bursting pulsar GRO J1744-28, one bright and one faint, within the X-ray error circles of XMM-Newton and Chandra. In determining the spectral types of the counterparts we applied 3 different extinction corrections; one for an all-sky value, one for a Galactic Bulge value and one for a local value. We find the local value, with an extinction law of alpha = 3.23 +- 0.01 is the only correction that results in colours and magnitudes for both bright and faint counterparts consistent with a small range of spectral types, and for the bright counterpart, consistent with the spectroscopic identification. Photometry of the faint candidate indicates it is a K7/M0 V star at a distance of 3.75 +- 1 kpc. This star would require a very low inclination angle (i < 9deg) to satisfy the mass function constraints; however it cannot be excluded as the counterpart without follow-up spectroscopy to detect emission signatures of accretion. Photometry and spectroscopy of the bright candidate indicate it is most likely a G/K III star. The spectrum does not show Br-gamma emission, a known indicator of accretion. The bright star's magnitudes are in agreement with the constraints placed on a probable counterpart by the calculations of Rappaport & Joss (1997) for an evolved star that has had its envelope stripped. The mass function indicates the counterpart should have M < 0.3 Msol for an inclination of i >= 15deg; a stripped giant, or a main sequence M3+ V star are consistent with this mass-function constraint. In both cases mass-transfer, if present, will be by wind-accretion as the counterpart will not fill its Roche lobe given the observed orbital period. The derived magnetic field of 2.4 x 10^{11} G will inhibit accretion by the propeller effect, hence its quiescent state.Comment: 12 pages, 6 figures, 4 table, MNRAS accepted Changes to the content and an increased analysis of the Galactic centre extinctio

Towards a formative assessment of classroom competencies (FACCs) for postgraduate medical trainees

Background An assumption of clinical competency is no longer acceptable or feasible in routine clinical practice. We sought to determine the feasibility, practicability and efficacy of undertaking a formal assessment of clinical competency for all postgraduate medical trainees in a large NHS foundation trust. Methods FY1 doctors were asked to complete a questionnaire to determine prior experience and self reported confidence in performing the GMC core competencies. From this a consensus panel of key partners considered and developed an 8 station Objective Structured Clinical Examination (OSCE) circuit to assess clinical competencies in all training grade medical staff... The OSCE was then administered to all training grade doctors as part of their NHS trust induction process. Results 106 (87.6% of all trainees) participated in the assessment during the first 14 days of appointment. Candidates achieved high median raw percentage scores for the majority of stations however analysis of pre defined critical errors and omissions identified important areas for concern. Performance of newly qualified FY1 doctor was significantly better than other grades for the arterial blood gas estimation and nasogastric tube insertion stations. Discussion Delivering a formal classroom assessment of clinical competencies to all trainees as part of the induction process was both feasible and useful. The assessment identified areas of concern for future training and also served to reassure as to the proficiency of trainees in undertaking the majority of core competencies

Modeling Wastewater Discharge with a Hybrid Nearfield and Farfield Approach

In November of 2012 the U.S. Food and Drug Administration (FDA) assisted the Washington Department of Health with a dye release experiment at the Chambers Creek Wastewater facility near Steilacoom, WA and in the vicinity of geoduck tracks. Dye was released by being pumped in via the waste stream for over a day, and the effluent tracked by three boats equipped with tracking sensors (fluorometers). We present results from an effort to model this event using a combination of a nearfield (CORMIX) and farfield (GEMSS) models. The nearfield model is used to set the plume stratification over the tidal and meteorological conditions present during the experiment. That output is fed at 15-minute intervals into a pre-existing farfield model (GEMSS) that Ecology had previously calibrated. Because the farfield model was developed for another purpose, the grid cell size was not optimized for the application. How well did this work? Results over the tidal cycle are presented along with a discussion of numerical dispersion inherent in the farfield model. Can numerical dispersion be compensated for and the approach used to explore other plan discharge scenarios

The Joint European Compound Library:boosting precompetitive research

The Joint European Compound Library (JECL) is a new high-throughput screening collection aimed at driving precompetitive drug discovery and target validation. The JECL has been established with a core of over 321000 compounds from the proprietary collections of seven pharmaceutical companies and will expand to around 500000 compounds. Here, we analyse the physicochemical profile and chemical diversity of the core collection, showing that the collection is diverse and has a broad spectrum of predicted biological activity. We also describe a model for sharing compound information from multiple proprietary collections, enabling diversity and quality analysis without disclosing structures. The JECL is available for screening at no cost to European academic laboratories and SMEs through the IMI European Lead Factory (http://www.europeanleadfactory.eu/)

Derivation and analysis of a computationally efficient discrete Backus-Gilbert footprint-matching algorithm

Includes bibliographical references.A computationally efficient discrete Backus-Gilbert (BG) method is derived that is subject to minimization constraints appropriate for footprint-matching applications. The method is flexible, since computational cost can be traded for accuracy. A comparison of the discrete BG method with a non-discrete BG method shows that the new method can be 250% more efficient while maintaining the same accuracy as traditional approaches. In addition, optimization approaches are used to further enhance the computational performance of the discretized BG method. A singular value decomposition approximation is applied that increases the computational efficiencies 43% to 106% while maintaining similar accuracies to the original discretized algorithm. Accuracies of the optimization were found to be scene dependent. In addition, alternative quadrature methods were also tested for several idealized simulated scenes. The results suggest that accuracy improvements could be made using customized quadrature methods that would be employed along known physical data discontinuities (such as along coastlines in microwave imagery data). In addition, regularization behaviors are also discussed; with a particular emphasis on the extension of the method for use with unnormalized gain functions. This work demonstrates that for some gain function configurations local biases can be intrinsic to the system. The flexibility of the discrete BG method allowed for several of the optimizations to be performed in a straightforward manner. Many additional optimizations are likely possible. Due to the lower computational cost of the method, this work is applicable toward applications in which noise may vary dynamically (such as in RFI-contaminated environments). The computational flexibility of the method also makes it well suited to computationally constrained problems such as 4D data assimilation of remote sensing observations.Research supported by the DoD Center for Geosciences/Atmospheric Research at CSU under Cooperative Agreement #DAAL01-98-0078 with the Army Research Laboratory

DiAMoNDBack: Diffusion-denoising Autoregressive Model for Non-Deterministic Backmapping of C{\alpha} Protein Traces

Coarse-grained molecular models of proteins permit access to length and time scales unattainable by all-atom models and the simulation of processes that occur on long-time scales such as aggregation and folding. The reduced resolution realizes computational accelerations but an atomistic representation can be vital for a complete understanding of mechanistic details. Backmapping is the process of restoring all-atom resolution to coarse-grained molecular models. In this work, we report DiAMoNDBack (Diffusion-denoising Autoregressive Model for Non-Deterministic Backmapping) as an autoregressive denoising diffusion probability model to restore all-atom details to coarse-grained protein representations retaining only C{\alpha} coordinates. The autoregressive generation process proceeds from the protein N-terminus to C-terminus in a residue-by-residue fashion conditioned on the C{\alpha} trace and previously backmapped backbone and side chain atoms within the local neighborhood. The local and autoregressive nature of our model makes it transferable between proteins. The stochastic nature of the denoising diffusion process means that the model generates a realistic ensemble of backbone and side chain all-atom configurations consistent with the coarse-grained C{\alpha} trace. We train DiAMoNDBack over 65k+ structures from Protein Data Bank (PDB) and validate it in applications to a hold-out PDB test set, intrinsically-disordered protein structures from the Protein Ensemble Database (PED), molecular dynamics simulations of fast-folding mini-proteins from DE Shaw Research, and coarse-grained simulation data. We achieve state-of-the-art reconstruction performance in terms of correct bond formation, avoidance of side chain clashes, and diversity of the generated side chain configurational states. We make DiAMoNDBack model publicly available as a free and open source Python package