A Computational Framework for Ultrastructural Mapping of Neural Circuitry

Circuitry mapping of metazoan neural systems is difficult because canonical neural regions (regions containing one or more copies of all components) are large, regional borders are uncertain, neuronal diversity is high, and potential network topologies so numerous that only anatomical ground truth can resolve them. Complete mapping of a specific network requires synaptic resolution, canonical region coverage, and robust neuronal classification. Though transmission electron microscopy (TEM) remains the optimal tool for network mapping, the process of building large serial section TEM (ssTEM) image volumes is rendered difficult by the need to precisely mosaic distorted image tiles and register distorted mosaics. Moreover, most molecular neuronal class markers are poorly compatible with optimal TEM imaging. Our objective was to build a complete framework for ultrastructural circuitry mapping. This framework combines strong TEM-compliant small molecule profiling with automated image tile mosaicking, automated slice-to-slice image registration, and gigabyte-scale image browsing for volume annotation. Specifically we show how ultrathin molecular profiling datasets and their resultant classification maps can be embedded into ssTEM datasets and how scripted acquisition tools (SerialEM), mosaicking and registration (ir-tools), and large slice viewers (MosaicBuilder, Viking) can be used to manage terabyte-scale volumes. These methods enable large-scale connectivity analyses of new and legacy data. In well-posed tasks (e.g., complete network mapping in retina), terabyte-scale image volumes that previously would require decades of assembly can now be completed in months. Perhaps more importantly, the fusion of molecular profiling, image acquisition by SerialEM, ir-tools volume assembly, and data viewers/annotators also allow ssTEM to be used as a prospective tool for discovery in nonneural systems and a practical screening methodology for neurogenetics. Finally, this framework provides a mechanism for parallelization of ssTEM imaging, volume assembly, and data analysis across an international user base, enhancing the productivity of a large cohort of electron microscopists

An empirical study on the implementation and evaluation of a goal-driven software development risk management model

Context: Building a quality software product in the shortest possible time to satisfy the global market demand gives an enterprise a competitive advantage. However, uncertainties and risks exist at every stage of a software development project. These can have an extremely high influence on the success of the final software product. Early risk management practice is effective to manage such risks and contributes effectively towards the project success. Objective:Despite risk management approaches, a detailed guideline that explains where to integrate risk management activities into the project is still missing. Little effort has been directed towards the evaluation of the overall impact of a risk management method. We present a Goal-driven Software Development Risk Management Model (GSRM) and its explicit integration into the requirements engineering phase and an empirical investigation result of applying GSRM into a project. Method:We combined case study method with action research. This allows to guide the development team for managing risks and to attain goals as well as to identify ways to improve the proposed methodology. The data is from multiple sources and analysed both qualitative and quantitative way. Results: When risk factors are beyond the control of the project manager and project environment then it is difficult to control these risks. Project scope affects all dimensions of risk. GSRM is a reasonable risk management method that can be employed in an industrial context. The study results compare with other existing study results, to generalize findings and to identify contextual factors. Conclusion: A formal early stage risk management practice provides early warning related to the problems that exists in the project and contributes to the overall project success. It is not necessary to always consider budget and schedule constraints top priority. There exist issues such as requirements, change management, and user satisfaction influence these constraints

Research on information systems failures and successes: Status update and future directions

The final publication is available at Springer via http://dx.doi.org/10.1007/s10796-014-9500-yInformation systems success and failure are among the most prominent streams in IS research. Explanations of why some IS fulfill their expectations, whereas others fail, are complex and multi-factorial. Despite the efforts to understand the underlying factors, the IS failure rate remains stubbornly high. A Panel session was held at the IFIP Working Group 8.6 conference in Bangalore in 2013 which forms the subject of this Special Issue. Its aim was to reflect on the need for new perspectives and research directions, to provide insights and further guidance for managers on factors enabling IS success and avoiding IS failure. Several key issues emerged, such as the need to study problems from multiple perspectives, to move beyond narrow considerations of the IT artifact, and to venture into underexplored organizational contexts, such as the public sector. © 2014 Springer Science+Business Media New York

Impact of Fertilizer Quantity on Pothos (Epipremnum aurem) Vegetative Growth

Color poster with text, charts, photographs, and graphs.Pothos(Epipremnumaurem) is a common houseplant that is grown and sold at greenhouses for its lush foliage. Greenhouses apply fertilizer to both meet plant nutrient needs and produce favorable growth. Fertilizer should be applied using best greenhouse management practices (BMPs) however, many BMPs lack research to validate the practices. This research seeks to develop fertilizer application BMPs that demonstrate cost effectiveness and limit waste while still favoring production.Ralph E. Duxbury Biological Sciences Scholarship; University of Wisconsin--Eau Claire Office of Research and Sponsored Program