The tasks and roles of social workers: a focused overview of research evidence

Options for Excellence is a joint DfES and DH-funded review of the social care workforce. Four task groups have been set up, each dealing with different aspects of social care. Task Group 3 is considering the roles and tasks of social workers. In order to inform the work of this group, the Thomas Coram Research Unit was asked to provide an overview of relevant research and data in three main areas: the effective deployment of social worker time and tasks, improving cross-professional working, and attitudes to take-up of post-qualifying qualifications

Highly electronegative metallic contacts to semiconductors using polymeric sulfur nitride

The Schottky barriers formed on n‐ZnS and n‐ZnSe by polymeric sulfur nitride have been compared to barriers formed by Au. Barrier energies as determined by photoresponse, current‐voltage, and capacitance‐voltage methods show that (SN)_x is approximately 1.0 eV higher than Au on n‐ZnS and 0.3–0.4 eV higher than Au on n‐ZnSe. We believe that this is the first report of any metallic contact more electronegative than Au

HgSe, a highly electronegative stable metallic contact for semiconductor devices

Schottky barriers formed by the highly electronegative substance HgSe on n-ZnS and on n-ZnSe have been characterized by capacitance-voltage and photoresponse measurements. The barriers are about 0.5 eV greater than Au barriers on these n-type substrates. HgSe contacts are stable under ambient conditions and are easily fabricated, making them attractive for device use

Estimating the Impacts of Storage Dry Matter Losses on Switchgrass Production

This poster estimates dry matter losses as a function of harvest method, storage treatment, and time in storage. We then calculate the cost to store switchgrass bales under alternate harvest method and storage treatment scenarios; and determine the breakeven harvest method and storage treatment as a function of biomass price and time in storage.Biomass, bioenergy crops, function form, sustainable systems, Farm Management, Production Economics, Q10, Q42,

Project management in practice: Views from the Trenches

Software development has endured radical change with the introduction of agile methods for creating software solutions. This change has prompted new considerations of how software creation should be managed. While agile methods have changed software development processes, it would be premature to assume that has also induced modification in higher-level project management processes. Software development lifecycles (SDLC) and project management lifecycles (PLC), while associated, are not the same thing and it is still unclear to what degree the overarching project management tasks, tools or techniques must change or adapt to meet the needs of undertaking successful agile projects. This exploratory pilot study investigated agile methods used to manage software projects and was conducted via an online survey and restricted to a specific sample audience with significant project experience and with background in both traditional and agile development methods. The results indicate that traditional project management phases and techniques are adapted to fit with agile. However, as the discipline evolves the potential exists for a pure agile project management framework to surface -one that can be applied to better suit the needs of the management of agile projects as well as projects beyond the realm of software development

Economics of the Variable Rate Technology Investment Decision for Agricultural Sprayers

Producers lack information about the profitability of variable rate technology (VRT) for agricultural sprayers. An economic framework was developed to evaluate the returns required to pay for VRT investments. Payback variables included input savings, yield gains, and reduced application costs. We illustrate the framework with two example investment scenarios.capital budgeting, decision aid, farm management, precision agriculture, map-based, sensor-based, site-specific management, variable rate technology, Farm Management, Q10, Q16,

Interferometric Mapping of Magnetic fields: NGC2071IR

We present polarization maps of NGC2071IR from thermal dust emission at 1.3 mm and from CO J=$2 \to 1$ line emission. The observations were obtained using the Berkeley-Illinois-Maryland Association array in the period 2002-2004. We detected dust and line polarized emission from NGC2071IR that we used to constrain the morphology of the magnetic field. From CO J=$2 \to 1$ polarized emission we found evidence for a magnetic field in the powerful bipolar outflow present in this region. We calculated a visual extinction $A_{\rm{v}} \approx 26$ mag from our dust observations. This result, when compared with early single dish work, seems to show that dust grains emit polarized radiation efficiently at higher densities than previously thought. Mechanical alignment by the outflow is proposed to explain the polarization pattern observed in NGC2071IR, which is consistent with the observed flattening in this source.Comment: 17 pages, 4 Figures, Accepted for publication in Ap

Is Switchgrass Yield Response to Nitrogen Fertilizer Dynamic? Implications for Profitability and Sustainability at the Farm Level

Revised version of the paper submitted 2/11/2010Biomass, Energy Crops, Sequential Inputs, West Tennessee, Crop Production/Industries, Farm Management, Production Economics, Resource /Energy Economics and Policy,

Switchgrass Production in Marginal Environments: A Comparative Economic Analysis across Four West Tennessee Landscapes

Switchgrass (Panicum virgatum L.) has been identified as a model feedstock for the emerging biofuels industry. Its selection was based, in part, upon the observation that switchgrass can produce high yields in marginal production environments. This trait may become particularly valuable in coming years, as renewable fuel mandates begin to take effect and concerns over the food-versus-fuel debate increase. Relatively little research information exists about how management practices and production costs vary across different production environments. The objectives of this research were (a) to compare switchgrass yields as influenced by seeding rate and nitrogen fertilization rates in low-, intermediate-, and high-yielding switchgrass production environments, (b) to determine the economically optimal seeding rate and nitrogen fertilization rate for each environment, and (c) to calculate per-ton production costs. Experimental yield data from four locations were utilized for this study. Plots were seeded in 2004 with treatments of 2.5, 5.0, 7.5, 10.0, and 12.5 lbs/acre. Nitrogen was applied in subsequent intervals at 0, 60, 120 and 180 lbs/acre. For an expected stand lifespan of 10 years, production costs ranged from $45 per ton in a well drained level upland environment ideal for the production of row crops to$70 per ton in a marginal, poorly drained flood plain in which the switchgrass stand was slow to establish and which demonstrated lower overall yields.Crop Production/Industries, International Relations/Trade,

Prospects for Theranostics in Neurosurgical Imaging: Empowering Confocal Laser Endomicroscopy Diagnostics via Deep Learning

Confocal laser endomicroscopy (CLE) is an advanced optical fluorescence imaging technology that has the potential to increase intraoperative precision, extend resection, and tailor surgery for malignant invasive brain tumors because of its subcellular dimension resolution. Despite its promising diagnostic potential, interpreting the gray tone fluorescence images can be difficult for untrained users. In this review, we provide a detailed description of bioinformatical analysis methodology of CLE images that begins to assist the neurosurgeon and pathologist to rapidly connect on-the-fly intraoperative imaging, pathology, and surgical observation into a conclusionary system within the concept of theranostics. We present an overview and discuss deep learning models for automatic detection of the diagnostic CLE images and discuss various training regimes and ensemble modeling effect on the power of deep learning predictive models. Two major approaches reviewed in this paper include the models that can automatically classify CLE images into diagnostic/nondiagnostic, glioma/nonglioma, tumor/injury/normal categories and models that can localize histological features on the CLE images using weakly supervised methods. We also briefly review advances in the deep learning approaches used for CLE image analysis in other organs. Significant advances in speed and precision of automated diagnostic frame selection would augment the diagnostic potential of CLE, improve operative workflow and integration into brain tumor surgery. Such technology and bioinformatics analytics lend themselves to improved precision, personalization, and theranostics in brain tumor treatment.Comment: See the final version published in Frontiers in Oncology here: https://www.frontiersin.org/articles/10.3389/fonc.2018.00240/ful