42,159 research outputs found

    Guidance on the key skills units : communication, application of number and information technology

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    Monte-Carlo Simulations of Radiation-Induced Activation in a Fast-Neutron and Gamma- Based Cargo Inspection System

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    An air cargo inspection system combining two nuclear reaction based techniques, namely Fast-Neutron Resonance Radiography and Dual-Discrete-Energy Gamma Radiography is currently being developed. This system is expected to allow detection of standard and improvised explosives as well as special nuclear materials. An important aspect for the applicability of nuclear techniques in an airport inspection facility is the inventory and lifetimes of radioactive isotopes produced by the neutron and gamma radiation inside the cargo, as well as the dose delivered by these isotopes to people in contact with the cargo during and following the interrogation procedure. Using MCNPX and CINDER90 we have calculated the activation levels for several typical inspection scenarios. One example is the activation of various metal samples embedded in a cotton-filled container. To validate the simulation results, a benchmark experiment was performed, in which metal samples were activated by fast-neutrons in a water-filled glass jar. The induced activity was determined by analyzing the gamma spectra. Based on the calculated radioactive inventory in the container, the dose levels due to the induced gamma radiation were calculated at several distances from the container and in relevant time windows after the irradiation, in order to evaluate the radiation exposure of the cargo handling staff, air crew and passengers during flight. The possibility of remanent long-lived radioactive inventory after cargo is delivered to the client is also of concern and was evaluated.Comment: Proceedings of FNDA 201

    Understanding the NASTRAN structural plotter

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    Functions of the plotting hardware and the operations performed by the NASTRAN structural plotter are summarized to provide the user an insight into how the program works. The processing performed in response to each plot command is described and the interrelationships of the various parameters are explained. To assist in the effective and efficient utilization of the system, examples are provided which also illustrate several not yet documented capabilities of the Level 16 structural plotter

    Echocardiography curriculum development for physician assistants using entrustable professional activities

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    BACKGROUND: With the projected increase of cardiovascular disease in the aging population, a higher demand for echocardiography use is predicted. However, there is a shortage in the supply of cardiologists, to the point that a 2009 American College of Cardiology survey report called it a "cardiology workforce crisis". The report also recommends a more aggressive use of PAs and NPs as one of the solutions to fill the shortage. Currently, echocardiography is not routinely included in the scope of practice for PAs in cardiology. While PAs attain strong basic science knowledge and clinical training experience in PA school, they typically do not receive additional formal postgraduate training. PAs have limited training opportunities to train in echocardiography and receive certification of recognition, but a formally standardized training program and certifying examination geared specifically for PAs are yet to be developed. This study seeks to develop a pilot curriculum in training echocardiography which can be standardized for utilization across various regions and medical subspecialties. The curriculum draws on the concept of Entrustable Professional Activities (EPA), which is being actively used in graduate medical education. HYPOTHESIS: After participating in the proposed pilot curriculum which involves online didactic learning and supervised hands-on clinical training, trained PAs will be able to reach proficiency in echocardiography operation and interpretation at level 4 supervision according to the EPA guidelines. METHODS: This study proposes a pilot curriculum with framework based on the EPA titled “performing and interpreting echocardiography” by PAs. The curriculum involves didactic and clinical training in echocardiography, with the goal to achieve mastery of level 4 supervision (minimal supervision). 2 subjects will be recruited from a teaching medical institution in the Greater Boston area with an IAC accredited echocardiography laboratory. After the 12-month training, participants will take ASCeXAM/ReASCE Online Practice Exam Simulation offered by the ASE. Upon 1) achievement of individualized EPAs as assessed by supervisor, and 2) simulation exam score of >80%, participants will earn a STAR in echocardiography. CONCLUSION: The study is the first step to establishing an effective training curriculum that will eventually be a basis for creating a certifying exam in echocardiography, designed specifically for PAs. As this study merely suggests a new curriculum, future studies should focus on identifying strengths and weaknesses of the curriculum after implementation and expansion to multiple sites, and gather data to use for continual improvement of the training curriculum

    Detecting Family Resemblance: Automated Genre Classification.

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    This paper presents results in automated genre classification of digital documents in PDF format. It describes genre classification as an important ingredient in contextualising scientific data and in retrieving targetted material for improving research. The current paper compares the role of visual layout, stylistic features and language model features in clustering documents and presents results in retrieving five selected genres (Scientific Article, Thesis, Periodicals, Business Report, and Form) from a pool of materials populated with documents of the nineteen most popular genres found in our experimental data set.

    Age grading \u3cem\u3eAn. gambiae\u3c/em\u3e and \u3cem\u3eAn. arabiensis\u3c/em\u3e using near infrared spectra and artificial neural networks

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    Background Near infrared spectroscopy (NIRS) is currently complementing techniques to age-grade mosquitoes. NIRS classifies lab-reared and semi-field raised mosquitoes into \u3c or ≥ 7 days old with an average accuracy of 80%, achieved by training a regression model using partial least squares (PLS) and interpreted as a binary classifier. Methods and findings We explore whether using an artificial neural network (ANN) analysis instead of PLS regression improves the current accuracy of NIRS models for age-grading malaria transmitting mosquitoes. We also explore if directly training a binary classifier instead of training a regression model and interpreting it as a binary classifier improves the accuracy. A total of 786 and 870 NIR spectra collected from laboratory reared An. gambiae and An. arabiensis, respectively, were used and pre-processed according to previously published protocols. The ANN regression model scored root mean squared error (RMSE) of 1.6 ± 0.2 for An. gambiae and 2.8 ± 0.2 for An. arabiensis; whereas the PLS regression model scored RMSE of 3.7 ± 0.2 for An. gambiae, and 4.5 ± 0.1 for An. arabiensis. When we interpreted regression models as binary classifiers, the accuracy of the ANN regression model was 93.7 ± 1.0% for An. gambiae, and 90.2 ± 1.7% for An. arabiensis; while PLS regression model scored the accuracy of 83.9 ± 2.3% for An. gambiae, and 80.3 ± 2.1% for An. arabiensis. We also find that a directly trained binary classifier yields higher age estimation accuracy than a regression model interpreted as a binary classifier. A directly trained ANN binary classifier scored an accuracy of 99.4 ± 1.0 for An. gambiae and 99.0 ± 0.6% for An. arabiensis; while a directly trained PLS binary classifier scored 93.6 ± 1.2% for An. gambiae and 88.7 ± 1.1% for An. arabiensis. We further tested the reproducibility of these results on different independent mosquito datasets. ANNs scored higher estimation accuracies than when the same age models are trained using PLS. Regardless of the model architecture, directly trained binary classifiers scored higher accuracies on classifying age of mosquitoes than regression models translated as binary classifiers. Conclusion We recommend training models to estimate age of An. arabiensis and An. gambiae using ANN model architectures (especially for datasets with at least 70 mosquitoes per age group) and direct training of binary classifier instead of training a regression model and interpreting it as a binary classifier

    Heat Transfer and Pressure Drop in a Developing Channel Flow with Streamwise Vortices

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    Experiments to assess the heat transfer and pressure-drop effects of delta-wing vortex generators placed at the entrance of developing channel flows are reported in this study. The experimental geometry simulates common heat exchanger configurations and tests are conducted over a velocity range important to heating, air conditioning and refrigeration. An innovative liquid-crystal thermography technique is used to determine the local and average Nusselt numbers for an isoflux channel wall, and conventional methods are used to determine the Fanning friction factor. Vortex generators with aspect ratios of A = 2 and A = 4 are studied at attack angles of a. = 20?? to 45????. The results indicate that the streamwise vortices generated by a delta wing can enhance local Nusselt numbers by more than 200% in a developing channel flow. Under some conditions, the spatially average Nusselt number nearly doubled for a heat transfer area that was 37 to 63 times the wing area. The Fanning friction factor increased by a few percent to nearly 60%, depending on the Reynolds number.Air Conditioning and Refrigeration Project 4

    Morphological changes in textile fibres exposed to environmental stresses:atomic force microscopic examination

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    The ability of the atomic force microscope (AFM) to investigate the nanoscopic morphological changes in the surfaces of fabrics was examined for the first time. This study focussed on two natural (cotton and wool), and a regenerated cellulose (viscose) textile fibres exposed to various environmental stresses for different lengths of times. Analyses of the AFM images allowed us to measure quantitatively the surface texture parameters of the environmentally stressed fabrics as a function of the exposure time. It was also possible to visualise at the nanoscale the finest details of the surfaces of three weathered fabrics and clearly distinguish between the detrimental effects of the imposed environmental conditions. This study confirmed that the AFM could become a very powerful tool in forensic examination of textile fibres to provide significant fibre evidence due to its capability of distinguishing between different environmental exposures or forced damages to fibres
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