WorldWideScience

Sample records for prediction tools trained

  1. Academic Training Lecture Regular Programme: Predictive Monte Carlo tools for LHC physics (1/3)

    CERN Multimedia

    2012-01-01

    Predictive Monte Carlo tools for LHC physics (1/3), by Fabio Maltoni (Université Catholique de Louvain (BE)).   Wednesday, May 2, 2012 from 11:00 to 12:00 (Europe/Zurich) at CERN ( 503-1-001 - Council Chamber ) Simulations of events taking place at the LHC play key role in all experimental analyses. Starting from the basics concepts of QCD, we first review how accurate predictions can be obtained via fixed-order calculations at higher orders. Parton showers and event generation are then introduced as a means to achieve fully exclusive predictions. Finally  the recent merging and matching  techniques between fixed-order and fully exclusive simulations are  presented, as well as their implementations via the MLM/CKKW and MC@NLO/POWHEG methods. Organised by Mario Campanelli. More information here.

  2. A Training Technology Evaluation Tool

    National Research Council Canada - National Science Library

    Livingston, Stephen C; Dyer, Jean L; Swinson, Diadra

    2005-01-01

    A Training Technology Evaluation Tool was developed to help procurers and developers of training technologies to make informed decisions and to improve the overall effectiveness of training technologies...

  3. Accurate approximation method for prediction of class I MHC affinities for peptides of length 8, 10 and 11 using prediction tools trained on 9mers

    DEFF Research Database (Denmark)

    Lundegaard, Claus; Lund, Ole; Nielsen, Morten

    2008-01-01

    Several accurate prediction systems have been developed for prediction of class I major histocompatibility complex (MHC):peptide binding. Most of these are trained on binding affinity data of primarily 9mer peptides. Here, we show how prediction methods trained on 9mer data can be used for accurate...

  4. Advanced Prosthetic Gait Training Tool

    Science.gov (United States)

    2015-12-01

    modules to train individuals to distinguish gait deviations (trunk motion and lower-limb motion). Each of these modules help trainers improve their...AWARD NUMBER: W81XWH-10-1-0870 TITLE: Advanced Prosthetic Gait Training Tool PRINCIPAL INVESTIGATOR: Dr. Karim Abdel-Malek CONTRACTING...study is to produce a computer-based Advanced Prosthetic Gait Training Tool to aid in the training of clinicians at military treatment facilities

  5. Predictive Data Tools Find Uses in Schools

    Science.gov (United States)

    Sparks, Sarah D.

    2011-01-01

    The use of analytic tools to predict student performance is exploding in higher education, and experts say the tools show even more promise for K-12 schools, in everything from teacher placement to dropout prevention. Use of such statistical techniques is hindered in precollegiate schools, however, by a lack of researchers trained to help…

  6. Training methods, tools and aids

    International Nuclear Information System (INIS)

    Martin, H.D.

    1980-01-01

    The training programme, training methods, tools and aids necessary for staffing nuclear power plants depend very much on the overall contractual provisions. The basis for training programmes and methods is the definition of the plant organization and the prequalification of the personnel. Preselection tests are tailored to the different educational levels and precede the training programme, where emphasis is put on practical on-the-job training. Technical basic and introductory courses follow language training and give a broad but basic spectrum of power plant technology. Plant-related theoretical training consists of reactor technology training combined with practical work in laboratories, on a test reactor and of the nuclear power plant course on design philosophy and operation. Classroom instruction together with video tapes and other audiovisual material which are used during this phase are described; as well as the various special courses for the different specialists. The first step of on-the-job training is a practical observation phase in an operating nuclear power plant, where the participants are assigned to shift work or to the different special departments, depending on their future assignment. Training in manufacturers' workshops, in laboratories or in engineering departments necessitate other training methods. The simulator training for operating personnel, for key personnel and, to some extent, also for maintenance personnel and specialists gives the practical feeling for nuclear power plant behaviour during normal and abnormal conditions. During the commissioning phase of the own nuclear power plant, which is the most important practical training, the participants are integrated into the commissioning staff and are assisted during their process of practical learning on-the-job by special instructors. Personnel training also includes performance of training of instructors and assistance in building up special training programmes and material as well

  7. New Tool to Predict Glaucoma

    Science.gov (United States)

    ... In This Section A New Tool to Predict Glaucoma email Send this article to a friend by ... Close Send Thanks for emailing that article! Tweet Glaucoma can be difficult to detect and diagnose. Measurement ...

  8. Laser safety tools and training

    CERN Document Server

    Barat, Ken

    2008-01-01

    Lasers perform many unique functions in a plethora of applications, but there are many inherent risks with this continually burgeoning technology. Laser Safety: Tools and Training presents simple, effective ways for users in a variety of facilities to evaluate the hazards of any laser procedure and ensure they are following documented laser safety standards.Designed for use as either a stand-alone volume or a supplement to Laser Safety Management, this text includes fundamental laser and laser safety information and critical laser use information rarely found in a single source. The first lase

  9. Small Business Management Training Tools Directory.

    Science.gov (United States)

    American Association of Community and Junior Colleges, Washington, DC. National Small Business Training Network.

    This directory is designed to assist in the identification of supplementary materials to support program development for small businesses. Following introductory comments and an overview of small business management training, section I lists training tools available from the Small Business Administration (SBA). Section II provides descriptions and…

  10. Academic Training: Predicting Natural Catastrophes

    CERN Multimedia

    Françoise Benz

    2005-01-01

    2005-2006 ACADEMIC TRAINING PROGRAMME LECTURE SERIES 12, 13, 14, 15, 16 December from 11:00 to 12:00 - Main Auditorium, bldg. 500 Predicting Natural Catastrophes E. OKAL / Northwestern University, Evanston, USA 1. Tsunamis -- Introduction Definition of phenomenon - basic properties of the waves Propagation and dispersion Interaction with coasts - Geological and societal effects Origin of tsunamis - natural sources Scientific activities in connection with tsunamis. Ideas about simulations 2. Tsunami generation The earthquake source - conventional theory The earthquake source - normal mode theory The landslide source Near-field observation - The Plafker index Far-field observation - Directivity 3. Tsunami warning General ideas - History of efforts Mantle magnitudes and TREMOR algorithms The challenge of 'tsunami earthquakes' Energy-moment ratios and slow earthquakes Implementation and the components of warning centers 4. Tsunami surveys Principles and methodologies Fifteen years of field surveys and re...

  11. Automatic Train Operation Using Autonomic Prediction of Train Runs

    Science.gov (United States)

    Asuka, Masashi; Kataoka, Kenji; Komaya, Kiyotoshi; Nishida, Syogo

    In this paper, we present an automatic train control method adaptable to disturbed train traffic conditions. The proposed method presumes transmission of detected time of a home track clearance to trains approaching to the station by employing equipment of Digital ATC (Automatic Train Control). Using the information, each train controls its acceleration by the method that consists of two approaches. First, by setting a designated restricted speed, the train controls its running time to arrive at the next station in accordance with predicted delay. Second, the train predicts the time at which it will reach the current braking pattern generated by Digital ATC, along with the time when the braking pattern transits ahead. By comparing them, the train correctly chooses the coasting drive mode in advance to avoid deceleration due to the current braking pattern. We evaluated the effectiveness of the proposed method regarding driving conditions, energy consumption and reduction of delays by simulation.

  12. Tools & training for more secure software

    CERN Multimedia

    CERN. Geneva

    2017-01-01

    Just by fate of nature, software today is shipped out as “beta”, coming with vulnerabilities and weaknesses, which should already have been fixed at the programming stage. This presentation will show the consequences of suboptimal software, why good programming, thorough software design, and a proper software development process is imperative for the overall security of the Organization, and how a few simple tools and training are supposed to make CERN software more secure.

  13. Behavior Prediction Tools Strengthen Nanoelectronics

    Science.gov (United States)

    2013-01-01

    Several years ago, NASA started making plans to send robots to explore the deep, dark craters on the Moon. As part of these plans, NASA needed modeling tools to help engineer unique electronics to withstand extremely cold temperatures. According to Jonathan Pellish, a flight systems test engineer at Goddard Space Flight Center, "An instrument sitting in a shadowed crater on one of the Moon s poles would hover around 43 K", that is, 43 kelvin, equivalent to -382 F. Such frigid temperatures are one of the main factors that make the extreme space environments encountered on the Moon and elsewhere so extreme. Radiation is another main concern. "Radiation is always present in the space environment," says Pellish. "Small to moderate solar energetic particle events happen regularly and extreme events happen less than a handful of times throughout the 7 active years of the 11-year solar cycle." Radiation can corrupt data, propagate to other systems, require component power cycling, and cause a host of other harmful effects. In order to explore places like the Moon, Jupiter, Saturn, Venus, and Mars, NASA must use electronic communication devices like transmitters and receivers and data collection devices like infrared cameras that can resist the effects of extreme temperature and radiation; otherwise, the electronics would not be reliable for the duration of the mission.

  14. PISCES: A Tool for Predicting Software Testability

    Science.gov (United States)

    Voas, Jeffrey M.; Miller, Keith W.; Payne, Jeffery E.

    1991-01-01

    Before a program can fail, a software fault must be executed, that execution must alter the data state, and the incorrect data state must propagate to a state that results directly in an incorrect output. This paper describes a tool called PISCES (developed by Reliable Software Technologies Corporation) for predicting the probability that faults in a particular program location will accomplish all three of these steps causing program failure. PISCES is a tool that is used during software verification and validation to predict a program's testability.

  15. What predicts performance during clinical psychology training?

    OpenAIRE

    Scior, Katrina; Bradley, Caroline E; Potts, Henry W W; Woolf, Katherine; de C Williams, Amanda C

    2013-01-01

    Objectives While the question of who is likely to be selected for clinical psychology training has been studied, evidence on performance during training is scant. This study explored data from seven consecutive intakes of the UK's largest clinical psychology training course, aiming to identify what factors predict better or poorer outcomes. Design Longitudinal cross-sectional study using prospective and retrospective data. Method Characteristics at application were analysed in relation to a r...

  16. Daylight prediction techniques in energy design tools

    Energy Technology Data Exchange (ETDEWEB)

    Milne, M.; Zurick, J. [California Univ., Los Angeles, Dept. of Architecture, CA (United States)

    1998-09-01

    Four different whole-building energy design tool systems that calculate energy savings from daylighting and that display annual performance on an-hour-by-hour basis, have been tested. The nature of design tools, the sources of hourly outdoor illuminance data, the ways of predicting indoor illumination, the assumptions of each tool, and the resulting energy savings of the design tools tested are discussed. The tests were carried out with the essential criteria for evaluating whole-building daylighting and energy design tools in mind. These have been identified as user confidence, accuracy, response time, and the amount of detail. Results of the tests, all four of them run on a single elementary school classroom for the sake of comparability, were provided. 9 refs., 2 figs.

  17. Turning inspection regulations into training tools

    International Nuclear Information System (INIS)

    Finley, D.; Wheatcraft, D.

    1996-01-01

    In response to suggestions from internal and State of California auditors, the Hazardous Waste Management Division (HWM) at Lawrence Livermore National Laboratory prepared an Inspection Schedule and Guidance Document that summarizes the Laboratory's inspection schedule and procedures for waste treatment, storage, and disposal facilities (TSDFs). Because it explains and comments in detail on the inspection schedule, forms, and procedures, this document is a centralized reference for HWM managers and personnel performing TSDF inspections at the Laboratory. It is also a training tool for experienced and new inspectors, standardizing the inspections of personnel with experience and explaining to novices what to look for and why. This poster presentation traces the team effort that created this document and provides specific examples of how the document was developed and how it is used

  18. Gaussian process regression for tool wear prediction

    Science.gov (United States)

    Kong, Dongdong; Chen, Yongjie; Li, Ning

    2018-05-01

    To realize and accelerate the pace of intelligent manufacturing, this paper presents a novel tool wear assessment technique based on the integrated radial basis function based kernel principal component analysis (KPCA_IRBF) and Gaussian process regression (GPR) for real-timely and accurately monitoring the in-process tool wear parameters (flank wear width). The KPCA_IRBF is a kind of new nonlinear dimension-increment technique and firstly proposed for feature fusion. The tool wear predictive value and the corresponding confidence interval are both provided by utilizing the GPR model. Besides, GPR performs better than artificial neural networks (ANN) and support vector machines (SVM) in prediction accuracy since the Gaussian noises can be modeled quantitatively in the GPR model. However, the existence of noises will affect the stability of the confidence interval seriously. In this work, the proposed KPCA_IRBF technique helps to remove the noises and weaken its negative effects so as to make the confidence interval compressed greatly and more smoothed, which is conducive for monitoring the tool wear accurately. Moreover, the selection of kernel parameter in KPCA_IRBF can be easily carried out in a much larger selectable region in comparison with the conventional KPCA_RBF technique, which helps to improve the efficiency of model construction. Ten sets of cutting tests are conducted to validate the effectiveness of the presented tool wear assessment technique. The experimental results show that the in-process flank wear width of tool inserts can be monitored accurately by utilizing the presented tool wear assessment technique which is robust under a variety of cutting conditions. This study lays the foundation for tool wear monitoring in real industrial settings.

  19. GAPIT: genome association and prediction integrated tool.

    Science.gov (United States)

    Lipka, Alexander E; Tian, Feng; Wang, Qishan; Peiffer, Jason; Li, Meng; Bradbury, Peter J; Gore, Michael A; Buckler, Edward S; Zhang, Zhiwu

    2012-09-15

    Software programs that conduct genome-wide association studies and genomic prediction and selection need to use methodologies that maximize statistical power, provide high prediction accuracy and run in a computationally efficient manner. We developed an R package called Genome Association and Prediction Integrated Tool (GAPIT) that implements advanced statistical methods including the compressed mixed linear model (CMLM) and CMLM-based genomic prediction and selection. The GAPIT package can handle large datasets in excess of 10 000 individuals and 1 million single-nucleotide polymorphisms with minimal computational time, while providing user-friendly access and concise tables and graphs to interpret results. http://www.maizegenetics.net/GAPIT. zhiwu.zhang@cornell.edu Supplementary data are available at Bioinformatics online.

  20. TSORT - an automated tool for allocating tasks to training strategies

    International Nuclear Information System (INIS)

    Carter, R.J.; Jorgensen, C.C.

    1986-01-01

    An automated tool (TSORT) that can aid training system developers in determining which training strategy should be applied to a particular task and in grouping similar tasks into training categories has been developed. This paper describes the rationale for TSORT's development and addresses its structure, including training categories, task description dimensions, and categorization metrics. It also provides some information on TSORT's application

  1. Web tools for predictive toxicology model building.

    Science.gov (United States)

    Jeliazkova, Nina

    2012-07-01

    The development and use of web tools in chemistry has accumulated more than 15 years of history already. Powered by the advances in the Internet technologies, the current generation of web systems are starting to expand into areas, traditional for desktop applications. The web platforms integrate data storage, cheminformatics and data analysis tools. The ease of use and the collaborative potential of the web is compelling, despite the challenges. The topic of this review is a set of recently published web tools that facilitate predictive toxicology model building. The focus is on software platforms, offering web access to chemical structure-based methods, although some of the frameworks could also provide bioinformatics or hybrid data analysis functionalities. A number of historical and current developments are cited. In order to provide comparable assessment, the following characteristics are considered: support for workflows, descriptor calculations, visualization, modeling algorithms, data management and data sharing capabilities, availability of GUI or programmatic access and implementation details. The success of the Web is largely due to its highly decentralized, yet sufficiently interoperable model for information access. The expected future convergence between cheminformatics and bioinformatics databases provides new challenges toward management and analysis of large data sets. The web tools in predictive toxicology will likely continue to evolve toward the right mix of flexibility, performance, scalability, interoperability, sets of unique features offered, friendly user interfaces, programmatic access for advanced users, platform independence, results reproducibility, curation and crowdsourcing utilities, collaborative sharing and secure access.

  2. Training generalized improvisation of tools by preschool children1

    Science.gov (United States)

    Parsonson, Barry S.; Baer, Donald M.

    1978-01-01

    The development of new, “creative” behaviors was examined in a problem-solving context. One form of problem solving, improvisation, was defined as finding a substitute to replace the specifically designated, but currently unavailable, tool ordinarily used to solve the problem. The study examined whether preschool children spontaneously displayed generalized improvisation skills, and if not, whether they could be trained to do so within different classes of tools. Generalization across different tool classes was monitored but not specifically trained. Five preschool children participated in individual sessions that first probed their skill at improvising tools, and later trained and probed generalized improvisation in one or more of three tool classes (Hammers, Containers, and Shoelaces), using a multiple-baseline design. All five children were trained with Hammers, two were trained in two classes, and two were trained in all three tool classes. Four of the five children improvised little in Baseline. During Training, all five showed increased generalized improvisation within the trained class, but none across classes. Tools fabricated by item combinations were rare in Baseline, but common in Training. Followup probes showed that the training effects were durable. PMID:16795596

  3. Occupational Safety. Hand Tools. Pre-Apprenticeship Phase 1 Training.

    Science.gov (United States)

    Lane Community Coll., Eugene, OR.

    This self-paced student training module on safety when using hand tools is one of a number of modules developed for Pre-apprenticeship Phase 1 Training. Purpose of the module is to teach students the correct safety techniques for operating common hand- and arm-powered tools, including selection, maintenance, technique, and uses. The module may…

  4. Introduction of the computer-based operation training tools in classrooms to support simulator training

    International Nuclear Information System (INIS)

    Noji, K.; Suzuki, K.; Kobayashi, A.

    1997-01-01

    Operation training with full-scope simulators is effective to improve trainees operation competency. To obtain more effective results of simulator training, roles of the ''classroom operation training'' closely cooperated to simulator training are important. The ''classroom operation training'' is aimed at pre- and post-studies for operation knowledge related to operation training using full-scope simulators. We have been developing computer-based operation training tools which are used in classroom training sessions. As the first step, we developed the Simulator Training Replay System. This is an aiding tool in the classroom used to enhance trainees operation performance. This system can synchronously replay plant behavior on CRT display with operators action on a video monitor in the simulator training sessions. This system is used to review plant behavior - trainees response after simulator training sessions and to understand plant behavior - operation procedure before operation training. (author)

  5. Online Manufacturing Training. ToolingU Review (U)

    Energy Technology Data Exchange (ETDEWEB)

    Montano, Joshua Daniel [Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

    2016-03-23

    The following report is a review of ToolingU, an online manufacturing training website. ToolingU provided the author with a trail account where a number of courses were taken and the overall program was evaluated. A review of the classes revealed that most of the offerings directly align with work at the Laboratory. Ease of use, effectiveness of the system and price all make ToolingU an attractive option for manufacturing training needs.

  6. GOPET: A tool for automated predictions of Gene Ontology terms

    Directory of Open Access Journals (Sweden)

    Glatting Karl-Heinz

    2006-03-01

    Full Text Available Abstract Background Vast progress in sequencing projects has called for annotation on a large scale. A Number of methods have been developed to address this challenging task. These methods, however, either apply to specific subsets, or their predictions are not formalised, or they do not provide precise confidence values for their predictions. Description We recently established a learning system for automated annotation, trained with a broad variety of different organisms to predict the standardised annotation terms from Gene Ontology (GO. Now, this method has been made available to the public via our web-service GOPET (Gene Ontology term Prediction and Evaluation Tool. It supplies annotation for sequences of any organism. For each predicted term an appropriate confidence value is provided. The basic method had been developed for predicting molecular function GO-terms. It is now expanded to predict biological process terms. This web service is available via http://genius.embnet.dkfz-heidelberg.de/menu/biounit/open-husar Conclusion Our web service gives experimental researchers as well as the bioinformatics community a valuable sequence annotation device. Additionally, GOPET also provides less significant annotation data which may serve as an extended discovery platform for the user.

  7. Classification and optimization of training tools for NPP simulator

    International Nuclear Information System (INIS)

    Billoen, G. van

    1994-01-01

    The training cycle of nuclear power plant (NPP) operators has evolved during the last decade in parallel with the evolution of the training tools. The phases of the training cycle can be summarized as follows: (1) basic principle learning, (2) specific functional training, (3) full operating range training, and (4) detailed accident analyses. The progress in simulation technology and man/machine interface (MMI) gives the training centers new opportunities to improve their training methods and effectiveness in the transfer of knowledge. To take advantage of these new opportunities a significant investment in simulation tools may be required. It is therefore important to propose an optimized approach when dealing with the overall equipment program for these training centers. An overall look of tools proposed on the international simulation market shows that there is a need for systematic approach in this field. Classification of the different training tools needed for each training cycle is the basis for an optimized approach in terms of hardware configuration and software specifications of the equipment to install in training centers. The 'Multi-Function Simulator' is one of the approaches. (orig.) (3 tabs.)

  8. 32 CFR 806b.53 - Training tools.

    Science.gov (United States)

    2010-07-01

    ... Justice Privacy web pages. Go to http://www.foia.af.mil. Click on “Resources.” (b) “The Privacy Act of... Privacy Act 101 and is available on-line at http://www.foia.af.mil. (d) Training slides for use by the... http://www.foia.af.mil, under “Resources.” Note: Formal school training groups that develop or modify...

  9. A new methodology for predictive tool wear

    Science.gov (United States)

    Kim, Won-Sik

    turned with various cutting conditions and the results were compared with the proposed analytical wear models. The crater surfaces after machining have been carefully studied to shed light on the physics behind the crater wear. In addition, the abrasive wear mechanism plays a major role in the development of crater wear. Laser shock processing (LSP) has been applied to locally relieve the deleterious tensile residual stresses on the crater surface of a coated tool, thus to improve the hardness of the coating. This thesis shows that LSP has indeed improve wear resistance of CVD coated alumina tool inserts, which has residual stress due to high processing temperature. LSP utilizes a very short laser pulse with high energy density, which induces high-pressure stress wave propagation. The residual stresses are relieved by incident shock waves on the coating surface. Residual stress levels of LSP CVD alumina-coated carbide insert were evaluated by the X-ray diffractometer. Based on these results, LSP parameters such as number of laser pulses and laser energy density can be controlled to reduce residual stress. Crater wear shows that the wear resistance increase with LSP treated tool inserts. Because the hardness data are used to predict the wear, the improvement in hardness and wear resistance shows that the mechanism of crater wear also involves abrasive wear.

  10. Simulation-Based Tool for Traffic Management Training, Phase II

    Data.gov (United States)

    National Aeronautics and Space Administration — Both the current NAS, as well as NextGen, need successful use of advanced tools. Successful training is required today because more information gathering and...

  11. Simulation-Based Tool for Traffic Management Training, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — Both the current NAS, as well as NextGen, need successful use of advanced tools. Successful training is required today because more information gathering and...

  12. Blended learning tools for teaching and training

    CERN Document Server

    Allan, Barbara

    2007-01-01

    Offers a holistic blended learning approach, combining the best of traditional approaches to learning and teaching to make best use of the advantages of each while minimizing the disadvantages. It provides information professionals with a practical guide to the design and delivery of such training programmes.

  13. Development of an attrition risk prediction tool.

    Science.gov (United States)

    Fowler, John; Norrie, Peter

    To review lecturers' and students' perceptions of the factors that may lead to attrition from pre-registration nursing and midwifery programmes and to identify ways to reduce the impact of such factors on the student's experience. Comparable attrition rates for nursing and midwifery students across various universities are difficult to monitor accurately; however, estimates that there is approximately a 25% national attrition rate are not uncommon. The financial and human implications of this are significant and worthy of investigation. A study was carried out in one medium-sized UK school of nursing and midwifery, aimed at identifying perceived factors associated with attrition and retention. Thirty-five lecturers were interviewed individually; 605 students completed a questionnaire, and of these, 10 were individually interviewed. Attrition data kept by the student service department were reviewed. Data were collected over an 18-month period in 2007-2008. Regression analysis of the student data identified eight significant predictors. Four of these were 'positive' factors in that they aided student retention and four were 'negative' in that they were associated with students' thoughts of resigning. Student attrition and retention is multifactorial, and, as such, needs to be managed holistically. One aspect of this management could be an attrition risk prediction tool.

  14. Predicting space telerobotic operator training performance from human spatial ability assessment

    Science.gov (United States)

    Liu, Andrew M.; Oman, Charles M.; Galvan, Raquel; Natapoff, Alan

    2013-11-01

    Our goal was to determine whether existing tests of spatial ability can predict an astronaut's qualification test performance after robotic training. Because training astronauts to be qualified robotics operators is so long and expensive, NASA is interested in tools that can predict robotics performance before training begins. Currently, the Astronaut Office does not have a validated tool to predict robotics ability as part of its astronaut selection or training process. Commonly used tests of human spatial ability may provide such a tool to predict robotics ability. We tested the spatial ability of 50 active astronauts who had completed at least one robotics training course, then used logistic regression models to analyze the correlation between spatial ability test scores and the astronauts' performance in their evaluation test at the end of the training course. The fit of the logistic function to our data is statistically significant for several spatial tests. However, the prediction performance of the logistic model depends on the criterion threshold assumed. To clarify the critical selection issues, we show how the probability of correct classification vs. misclassification varies as a function of the mental rotation test criterion level. Since the costs of misclassification are low, the logistic models of spatial ability and robotic performance are reliable enough only to be used to customize regular and remedial training. We suggest several changes in tracking performance throughout robotics training that could improve the range and reliability of predictive models.

  15. An intelligent tool for the training of nuclear plant operators

    International Nuclear Information System (INIS)

    Cordier, B.

    1990-01-01

    A new type of pedagogical tool has been developped for the training of nuclear power plant operation. This tool combines simulation and expert system. The first process developped is about Steam Generator Tube Rupture (S.G.T.R.). All nuclear power plants will be equiped with this system in 1989 and 1990. After this first experiment, others processes will be developped for this tool

  16. NBL Pistol Grip Tool for Underwater Training of Astronauts

    Science.gov (United States)

    Liszka, Michael; Ashmore, Matthew; Behnke, Mark; Smith, Walter; Waterman, Tod

    2011-01-01

    A document discusses a lightweight, functional mockup of the Pistol Grip Tool for use during underwater astronaut training. Previous training tools have caused shoulder injuries. This new version is more than 50 percent lighter [in water, weight is 2.4 lb (=1.1 kg)], and can operate for a six-hour training session after 30 minutes of prep for submersion. Innovations in the design include the use of lightweight materials (aluminum and Delrin(Registered TradeMark)), creating a thinner housing, and the optimization of internal space with the removal of as much excess material as possible. This reduces tool weight and maximizes buoyancy. Another innovation for this tool is the application of a vacuum that seats the Orings in place and has shown to be reliable in allowing underwater usage for up to six hours.

  17. Developing a comprehensive training curriculum for integrated predictive maintenance

    Science.gov (United States)

    Wurzbach, Richard N.

    2002-03-01

    On-line equipment condition monitoring is a critical component of the world-class production and safety histories of many successful nuclear plant operators. From addressing availability and operability concerns of nuclear safety-related equipment to increasing profitability through support system reliability and reduced maintenance costs, Predictive Maintenance programs have increasingly become a vital contribution to the maintenance and operation decisions of nuclear facilities. In recent years, significant advancements have been made in the quality and portability of many of the instruments being used, and software improvements have been made as well. However, the single most influential component of the success of these programs is the impact of a trained and experienced team of personnel putting this technology to work. Changes in the nature of the power generation industry brought on by competition, mergers, and acquisitions, has taken the historically stable personnel environment of power generation and created a very dynamic situation. As a result, many facilities have seen a significant turnover in personnel in key positions, including predictive maintenance personnel. It has become the challenge for many nuclear operators to maintain the consistent contribution of quality data and information from predictive maintenance that has become important in the overall equipment decision process. These challenges can be met through the implementation of quality training to predictive maintenance personnel and regular updating and re-certification of key technology holders. The use of data management tools and services aid in the sharing of information across sites within an operating company, and with experts who can contribute value-added data management and analysis. The overall effectiveness of predictive maintenance programs can be improved through the incorporation of newly developed comprehensive technology training courses. These courses address the use of

  18. An innovative virtual reality training tool for orthognathic surgery.

    Science.gov (United States)

    Pulijala, Y; Ma, M; Pears, M; Peebles, D; Ayoub, A

    2018-02-01

    Virtual reality (VR) surgery using Oculus Rift and Leap Motion devices is a multi-sensory, holistic surgical training experience. A multimedia combination including 360° videos, three-dimensional interaction, and stereoscopic videos in VR has been developed to enable trainees to experience a realistic surgery environment. The innovation allows trainees to interact with the individual components of the maxillofacial anatomy and apply surgical instruments while watching close-up stereoscopic three-dimensional videos of the surgery. In this study, a novel training tool for Le Fort I osteotomy based on immersive virtual reality (iVR) was developed and validated. Seven consultant oral and maxillofacial surgeons evaluated the application for face and content validity. Using a structured assessment process, the surgeons commented on the content of the developed training tool, its realism and usability, and the applicability of VR surgery for orthognathic surgical training. The results confirmed the clinical applicability of VR for delivering training in orthognathic surgery. Modifications were suggested to improve the user experience and interactions with the surgical instruments. This training tool is ready for testing with surgical trainees. Copyright © 2018 International Association of Oral and Maxillofacial Surgeons. Published by Elsevier Ltd. All rights reserved.

  19. Training for vigilance: using predictive power to evaluate feedback effectiveness.

    Science.gov (United States)

    Szalma, James L; Hancock, Peter A; Warm, Joel S; Dember, William N; Parsons, Kelley S

    2006-01-01

    We examined the effects of knowledge of results (KR) on vigilance accuracy and report the first use of positive and negative predictive power (PPP and NPP) to assess vigilance training effectiveness. Training individuals to detect infrequent signals among a plethora of nonsignals is critical to success in many failure-intolerant monitoring technologies. KR has been widely used for vigilance training, but the effect of the schedule of KR presentation on accuracy has been neglected. Previous research on training for vigilance has used signal detection metrics or hits and false alarms. In this study diagnosticity measures were applied to augment traditional analytic methods. We examined the effects of continuous KR and a partial-KR regimen versus a no-KR control on decision diagnosticity. Signal detection theory (SDT) analysis indicated that KR induced conservatism in responding but did not enhance sensitivity. However, KR in both forms equally enhanced PPP while selectively impairing NPP. There is a trade-off in the effectiveness of KR in reducing false alarms and misses. Together, SDT and PPP/NPP measures provide a more complete portrait of performance effects. PPP and NPP together provide another assessment technique for vigilance performance, and as additional diagnostic tools, these measures are potentially useful to the human factors community.

  20. Bronchoscopy Simulation Training as a Tool in Medical School Education.

    Science.gov (United States)

    Gopal, Mallika; Skobodzinski, Alexus A; Sterbling, Helene M; Rao, Sowmya R; LaChapelle, Christopher; Suzuki, Kei; Litle, Virginia R

    2018-07-01

    Procedural simulation training is rare at the medical school level and little is known about its usefulness in improving anatomic understanding and procedural confidence in students. Our aim is to assess the impact of bronchoscopy simulation training on bronchial anatomy knowledge and technical skills in medical students. Medical students were recruited by email, consented, and asked to fill out a survey regarding their baseline experience. Two thoracic surgeons measured their knowledge of bronchoscopy on a virtual reality bronchoscopy simulator using the Bronchoscopy Skills and Tasks Assessment Tool (BSTAT), a validated 65-point checklist (46 for anatomy, 19 for simulation). Students performed four self-directed training sessions of 15 minutes per week. A posttraining survey and BSTAT were completed afterward. Differences between pretraining and posttraining scores were analyzed with paired Student's t tests and random intercept linear regression models accounting for baseline BSTAT score, total training time, and training year. The study was completed by 47 medical students with a mean training time of 81.5 ± 26.8 minutes. Mean total BSTAT score increased significantly from 12.3 ± 5.9 to 48.0 ± 12.9 (p training time and frequency of training did not have a significant impact on level of improvement. Self-driven bronchoscopy simulation training in medical students led to improvements in bronchial anatomy knowledge and bronchoscopy skills. Further investigation is under way to determine the impact of bronchoscopy simulation training on future specialty interest and long-term skills retention. Copyright © 2018 The Society of Thoracic Surgeons. Published by Elsevier Inc. All rights reserved.

  1. A tool for assessing cultural competence training in dental education.

    Science.gov (United States)

    Holyfield, Lavern J; Miller, Barbara H

    2013-08-01

    Policies exist to promote fairness and equal access to opportunities and services that address basic human needs of all U.S. citizens. Nonetheless, health disparities continue to persist among certain subpopulations, including those of racial, ethnic, geographic, socioeconomic, and other cultural identity groups. The Commission on Dental Accreditation (CODA) has added standards to address this concern. According to the most recent standards, adopted in 2010 for implementation in July 2013, CODA stipulates that "students should learn about factors and practices associated with disparities in health." Thus, it is imperative that dental schools develop strategies to comply with this addition. One key strategy for compliance is the inclusion of cultural competence training in the dental curriculum. A survey, the Dental Tool for Assessing Cultural Competence Training (D-TACCT), based on the Association of American Medical Colleges' Tool for Assessing Cultural Competence Training (TACCT), was sent to the academic deans at seventy-one U.S. and Canadian dental schools to determine best practices for cultural competence training. The survey was completed by thirty-seven individuals, for a 52 percent response rate. This article describes the use of this survey as a guide for developing culturally competent strategies and enhancing cultural competence training in dental schools.

  2. Common features of microRNA target prediction tools

    Directory of Open Access Journals (Sweden)

    Sarah M. Peterson

    2014-02-01

    Full Text Available The human genome encodes for over 1800 microRNAs, which are short noncoding RNA molecules that function to regulate gene expression post-transcriptionally. Due to the potential for one microRNA to target multiple gene transcripts, microRNAs are recognized as a major mechanism to regulate gene expression and mRNA translation. Computational prediction of microRNA targets is a critical initial step in identifying microRNA:mRNA target interactions for experimental validation. The available tools for microRNA target prediction encompass a range of different computational approaches, from the modeling of physical interactions to the incorporation of machine learning. This review provides an overview of the major computational approaches to microRNA target prediction. Our discussion highlights three tools for their ease of use, reliance on relatively updated versions of miRBase, and range of capabilities, and these are DIANA-microT-CDS, miRanda-mirSVR, and TargetScan. In comparison across all microRNA target prediction tools, four main aspects of the microRNA:mRNA target interaction emerge as common features on which most target prediction is based: seed match, conservation, free energy, and site accessibility. This review explains these features and identifies how they are incorporated into currently available target prediction tools. MicroRNA target prediction is a dynamic field with increasing attention on development of new analysis tools. This review attempts to provide a comprehensive assessment of these tools in a manner that is accessible across disciplines. Understanding the basis of these prediction methodologies will aid in user selection of the appropriate tools and interpretation of the tool output.

  3. Musite, a tool for global prediction of general and kinase-specific phosphorylation sites.

    Science.gov (United States)

    Gao, Jianjiong; Thelen, Jay J; Dunker, A Keith; Xu, Dong

    2010-12-01

    Reversible protein phosphorylation is one of the most pervasive post-translational modifications, regulating diverse cellular processes in various organisms. High throughput experimental studies using mass spectrometry have identified many phosphorylation sites, primarily from eukaryotes. However, the vast majority of phosphorylation sites remain undiscovered, even in well studied systems. Because mass spectrometry-based experimental approaches for identifying phosphorylation events are costly, time-consuming, and biased toward abundant proteins and proteotypic peptides, in silico prediction of phosphorylation sites is potentially a useful alternative strategy for whole proteome annotation. Because of various limitations, current phosphorylation site prediction tools were not well designed for comprehensive assessment of proteomes. Here, we present a novel software tool, Musite, specifically designed for large scale predictions of both general and kinase-specific phosphorylation sites. We collected phosphoproteomics data in multiple organisms from several reliable sources and used them to train prediction models by a comprehensive machine-learning approach that integrates local sequence similarities to known phosphorylation sites, protein disorder scores, and amino acid frequencies. Application of Musite on several proteomes yielded tens of thousands of phosphorylation site predictions at a high stringency level. Cross-validation tests show that Musite achieves some improvement over existing tools in predicting general phosphorylation sites, and it is at least comparable with those for predicting kinase-specific phosphorylation sites. In Musite V1.0, we have trained general prediction models for six organisms and kinase-specific prediction models for 13 kinases or kinase families. Although the current pretrained models were not correlated with any particular cellular conditions, Musite provides a unique functionality for training customized prediction models

  4. Water Impact Prediction Tool for Recoverable Rockets

    Science.gov (United States)

    Rooker, William; Glaese, John; Clayton, Joe

    2011-01-01

    Reusing components from a rocket launch can be cost saving. NASA's space shuttle system has reusable components that return to the Earth and impact the ocean. A primary example is the Space Shuttle Solid Rocket Booster (SRB) that descends on parachutes to the Earth after separation and impacts the ocean. Water impact generates significant structural loads that can damage the booster, so it is important to study this event in detail in the design of the recovery system. Some recent examples of damage due to water impact include the Ares I-X First Stage deformation as seen in Figure 1 and the loss of the SpaceX Falcon 9 First Stage.To ensure that a component can be recovered or that the design of the recovery system is adequate, an adequate set of structural loads is necessary for use in failure assessments. However, this task is difficult since there are many conditions that affect how a component impacts the water and the resulting structural loading that a component sees. These conditions include the angle of impact with respect to the water, the horizontal and vertical velocities, the rotation rate, the wave height and speed, and many others. There have been attempts to simulate water impact. One approach is to analyze water impact using explicit finite element techniques such as those employed by the LS-Dyna tool [1]. Though very detailed, this approach is time consuming and would not be suitable for running Monte Carlo or optimization analyses. The purpose of this paper is to describe a multi-body simulation tool that runs quickly and that captures the environments a component might see. The simulation incorporates the air and water interaction with the component, the component dynamics (i.e. modes and mode shapes), any applicable parachutes and lines, the interaction of winds and gusts, and the wave height and speed. It is capable of quickly conducting Monte Carlo studies to better capture the environments and genetic algorithm optimizations to reproduce a

  5. Prediction of Machine Tool Condition Using Support Vector Machine

    International Nuclear Information System (INIS)

    Wang Peigong; Meng Qingfeng; Zhao Jian; Li Junjie; Wang Xiufeng

    2011-01-01

    Condition monitoring and predicting of CNC machine tools are investigated in this paper. Considering the CNC machine tools are often small numbers of samples, a condition predicting method for CNC machine tools based on support vector machines (SVMs) is proposed, then one-step and multi-step condition prediction models are constructed. The support vector machines prediction models are used to predict the trends of working condition of a certain type of CNC worm wheel and gear grinding machine by applying sequence data of vibration signal, which is collected during machine processing. And the relationship between different eigenvalue in CNC vibration signal and machining quality is discussed. The test result shows that the trend of vibration signal Peak-to-peak value in surface normal direction is most relevant to the trend of surface roughness value. In trends prediction of working condition, support vector machine has higher prediction accuracy both in the short term ('One-step') and long term (multi-step) prediction compared to autoregressive (AR) model and the RBF neural network. Experimental results show that it is feasible to apply support vector machine to CNC machine tool condition prediction.

  6. Virtual Beach: Decision Support Tools for Beach Pathogen Prediction

    Science.gov (United States)

    The Virtual Beach Managers Tool (VB) is decision-making software developed to help local beach managers make decisions as to when beaches should be closed due to predicted high levels of water borne pathogens. The tool is being developed under the umbrella of EPA's Advanced Monit...

  7. Development and content validation of the power mobility training tool.

    Science.gov (United States)

    Kenyon, Lisa K; Farris, John P; Cain, Brett; King, Emily; VandenBerg, Ashley

    2018-01-01

    This paper outlines the development and content validation of the power mobility training tool (PMTT), an observational tool designed to assist therapists in developing power mobility training programs for children who have multiple, severe impairments. Initial items on the PMTT were developed based on a literature review and in consultation with therapists experienced in the use of power mobility. Items were trialled in clinical settings, reviewed, and refined. Items were then operationalized and an administration manual detailing scoring for each item was created. Qualitative and quantitative methods were used to establish content validity via a 15 member, international expert panel. The content validity ratio (CVR) was determined for each possible item. Of the 19 original items, 10 achieved minimum required CVR values and were included in the final version of the PMTT. Items related to manoeuvring a power mobility device were merged and an item related to the number of switches used concurrently to operate a power mobility device were added to the PMTT. The PMTT may assist therapists in developing training programs that facilitate the acquisition of beginning power mobility skills in children who have multiple, severe impairments. Implications for Rehabilitation The Power Mobility Training Tool (PMTT) was developed to help guide the development of power mobility intervention programs for children who have multiple, severe impairments. The PMTT can be used with children who access a power mobility device using either a joystick or a switch. Therapists who have limited experience with power mobility may find the PMTT to be helpful in setting up and conducting power mobility training interventions as a feasible aspect of a plan of care for children who have multiple, severe impairments.

  8. Translating and validating a Training Needs Assessment tool into Greek

    OpenAIRE

    Markaki, Adelais; Antonakis, Nikos; Hicks, Carolyn M; Lionis, Christos

    2007-01-01

    Abstract Background The translation and cultural adaptation of widely accepted, psychometrically tested tools is regarded as an essential component of effective human resource management in the primary care arena. The Training Needs Assessment (TNA) is a widely used, valid instrument, designed to measure professional development needs of health care professionals, especially in primary health care. This study aims to describe the translation, adaptation and validation of the TNA questionnaire...

  9. A new tool to evaluate postgraduate training posts: the Job Evaluation Survey Tool (JEST).

    Science.gov (United States)

    Wall, David; Goodyear, Helen; Singh, Baldev; Whitehouse, Andrew; Hughes, Elizabeth; Howes, Jonathan

    2014-10-02

    Three reports in 2013 about healthcare and patient safety in the UK, namely Berwick, Francis and Keogh have highlighted the need for junior doctors' views about their training experience to be heard. In the UK, the General Medical Council (GMC) quality assures medical training programmes and requires postgraduate deaneries to undertake quality management and monitoring of all training posts in their area. The aim of this study was to develop a simple trainee questionnaire for evaluation of postgraduate training posts based on the GMC, UK standards and to look at the reliability and validity including comparison with a well-established and internationally validated tool, the Postgraduate Hospital Educational Environment Measure (PHEEM). The Job Evaluation Survey Tool (JEST), a fifteen item job evaluation questionnaire was drawn up in 2006, piloted with Foundation doctors (2007), field tested with specialist paediatric registrars (2008) and used over a three year period (2008-11) by Foundation Doctors. Statistical analyses including descriptives, reliability, correlation and factor analysis were undertaken and JEST compared with PHEEM. The JEST had a reliability of 0.91 in the pilot study of 76 Foundation doctors, 0.88 in field testing of 173 Paediatric specialist registrars and 0.91 in three years of general use in foundation training with 3367 doctors completing JEST. Correlation of JEST with PHEEM was 0.80 (p training posts.

  10. RNA-SSPT: RNA Secondary Structure Prediction Tools.

    Science.gov (United States)

    Ahmad, Freed; Mahboob, Shahid; Gulzar, Tahsin; Din, Salah U; Hanif, Tanzeela; Ahmad, Hifza; Afzal, Muhammad

    2013-01-01

    The prediction of RNA structure is useful for understanding evolution for both in silico and in vitro studies. Physical methods like NMR studies to predict RNA secondary structure are expensive and difficult. Computational RNA secondary structure prediction is easier. Comparative sequence analysis provides the best solution. But secondary structure prediction of a single RNA sequence is challenging. RNA-SSPT is a tool that computationally predicts secondary structure of a single RNA sequence. Most of the RNA secondary structure prediction tools do not allow pseudoknots in the structure or are unable to locate them. Nussinov dynamic programming algorithm has been implemented in RNA-SSPT. The current studies shows only energetically most favorable secondary structure is required and the algorithm modification is also available that produces base pairs to lower the total free energy of the secondary structure. For visualization of RNA secondary structure, NAVIEW in C language is used and modified in C# for tool requirement. RNA-SSPT is built in C# using Dot Net 2.0 in Microsoft Visual Studio 2005 Professional edition. The accuracy of RNA-SSPT is tested in terms of Sensitivity and Positive Predicted Value. It is a tool which serves both secondary structure prediction and secondary structure visualization purposes.

  11. Echo simulator with novel training and competency testing tools.

    Science.gov (United States)

    Sheehan, Florence H; Otto, Catherine M; Freeman, Rosario V

    2013-01-01

    We developed and validated an echo simulator with three novel tools that facilitate training and enable quantitative and objective measurement of psychomotor as well as cognitive skill. First, the trainee can see original patient images - not synthetic or simulated images - that morph in real time as the mock transducer is manipulated on the mannequin. Second, augmented reality is used for Visual Guidance, a tool that assists the trainee in scanning by displaying the target organ in 3-dimensions (3D) together with the location of the current view plane and the plane of the anatomically correct view. Third, we introduce Image Matching, a tool that leverages the aptitude of the human brain for recognizing similarities and differences to help trainees learn to perform visual assessment of ultrasound images. Psychomotor competence is measured in terms of the view plane angle error. The construct validity of the simulator for competency testing was established by demonstrating its ability to discriminate novices vs. experts.

  12. A training and educational tool for neutron coincidence measurements

    International Nuclear Information System (INIS)

    Huszti, J.; Bagi, J.; Langner, D.

    2009-01-01

    Neutron coincidence counting techniques are widely used for nuclear safeguards inspection. They are based on the detection of time correlated neutrons created from spontaneous or induced fission of plutonium and some other actinides. IAEA inspectors are trained to know and to use this technique, but it is not easy to illustrate and explain the basics of the neutron coincidence counting. The traditional shift registers or multiplicity counters give only multiplicity distributions and the singles, doubles and triples count rates. Using the list mode method for the recording and evaluation of neutron coincidence data makes it easier to teach this technique. List mode acquisition is a relatively new way to collect data in neutron coincidence counting. It is based on the recording of the follow-up times of neutron pulses originating from a neutron detector into a file. The recorded pulse train can be evaluated with special software after the measurement. Hardware and software for list mode neutron coincidence acquisition have been developed in the Institute of Isotopes and is called a Pulse Train Reader. A system called Virtual Source for replaying pulse trains registered with the list mode device has also been developed. The list mode device and the pulse train 're-player' together build a good educational tool for teaching the basics of neutron coincidence counting. Some features of the follow-up time, multiplicity and Rossi-alpha distributions can be well demonstrated by replaying artificially generated or pre-recorded pulse trains. The choice of real sources is stored on DVD. There is no need to transport and maintain real sources for the training. Virtual sources also give the possibility of investigating rare sources that trainees would not have access to otherwise. (authors)

  13. Updating risk prediction tools: a case study in prostate cancer.

    Science.gov (United States)

    Ankerst, Donna P; Koniarski, Tim; Liang, Yuanyuan; Leach, Robin J; Feng, Ziding; Sanda, Martin G; Partin, Alan W; Chan, Daniel W; Kagan, Jacob; Sokoll, Lori; Wei, John T; Thompson, Ian M

    2012-01-01

    Online risk prediction tools for common cancers are now easily accessible and widely used by patients and doctors for informed decision-making concerning screening and diagnosis. A practical problem is as cancer research moves forward and new biomarkers and risk factors are discovered, there is a need to update the risk algorithms to include them. Typically, the new markers and risk factors cannot be retrospectively measured on the same study participants used to develop the original prediction tool, necessitating the merging of a separate study of different participants, which may be much smaller in sample size and of a different design. Validation of the updated tool on a third independent data set is warranted before the updated tool can go online. This article reports on the application of Bayes rule for updating risk prediction tools to include a set of biomarkers measured in an external study to the original study used to develop the risk prediction tool. The procedure is illustrated in the context of updating the online Prostate Cancer Prevention Trial Risk Calculator to incorporate the new markers %freePSA and [-2]proPSA measured on an external case-control study performed in Texas, U.S.. Recent state-of-the art methods in validation of risk prediction tools and evaluation of the improvement of updated to original tools are implemented using an external validation set provided by the U.S. Early Detection Research Network. Copyright © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  14. Simulation training tools for nonlethal weapons using gaming environments

    Science.gov (United States)

    Donne, Alexsana; Eagan, Justin; Tse, Gabriel; Vanderslice, Tom; Woods, Jerry

    2006-05-01

    Modern simulation techniques have a growing role for evaluating new technologies and for developing cost-effective training programs. A mission simulator facilitates the productive exchange of ideas by demonstration of concepts through compellingly realistic computer simulation. Revolutionary advances in 3D simulation technology have made it possible for desktop computers to process strikingly realistic and complex interactions with results depicted in real-time. Computer games now allow for multiple real human players and "artificially intelligent" (AI) simulated robots to play together. Advances in computer processing power have compensated for the inherent intensive calculations required for complex simulation scenarios. The main components of the leading game-engines have been released for user modifications, enabling game enthusiasts and amateur programmers to advance the state-of-the-art in AI and computer simulation technologies. It is now possible to simulate sophisticated and realistic conflict situations in order to evaluate the impact of non-lethal devices as well as conflict resolution procedures using such devices. Simulations can reduce training costs as end users: learn what a device does and doesn't do prior to use, understand responses to the device prior to deployment, determine if the device is appropriate for their situational responses, and train with new devices and techniques before purchasing hardware. This paper will present the status of SARA's mission simulation development activities, based on the Half-Life gameengine, for the purpose of evaluating the latest non-lethal weapon devices, and for developing training tools for such devices.

  15. Flight Experiment Verification of Shuttle Boundary Layer Transition Prediction Tool

    Science.gov (United States)

    Berry, Scott A.; Berger, Karen T.; Horvath, Thomas J.; Wood, William A.

    2016-01-01

    Boundary layer transition at hypersonic conditions is critical to the design of future high-speed aircraft and spacecraft. Accurate methods to predict transition would directly impact the aerothermodynamic environments used to size a hypersonic vehicle's thermal protection system. A transition prediction tool, based on wind tunnel derived discrete roughness correlations, was developed and implemented for the Space Shuttle return-to-flight program. This tool was also used to design a boundary layer transition flight experiment in order to assess correlation uncertainties, particularly with regard to high Mach-number transition and tunnel-to-flight scaling. A review is provided of the results obtained from the flight experiment in order to evaluate the transition prediction tool implemented for the Shuttle program.

  16. Predictions of titanium alloy properties using thermodynamic modeling tools

    Science.gov (United States)

    Zhang, F.; Xie, F.-Y.; Chen, S.-L.; Chang, Y. A.; Furrer, D.; Venkatesh, V.

    2005-12-01

    Thermodynamic modeling tools have become essential in understanding the effect of alloy chemistry on the final microstructure of a material. Implementation of such tools to improve titanium processing via parameter optimization has resulted in significant cost savings through the elimination of shop/laboratory trials and tests. In this study, a thermodynamic modeling tool developed at CompuTherm, LLC, is being used to predict β transus, phase proportions, phase chemistries, partitioning coefficients, and phase boundaries of multicomponent titanium alloys. This modeling tool includes Pandat, software for multicomponent phase equilibrium calculations, and PanTitanium, a thermodynamic database for titanium alloys. Model predictions are compared with experimental results for one α-β alloy (Ti-64) and two near-β alloys (Ti-17 and Ti-10-2-3). The alloying elements, especially the interstitial elements O, N, H, and C, have been shown to have a significant effect on the β transus temperature, and are discussed in more detail herein.

  17. Predicting tool life in turning operations using neural networks and image processing

    Science.gov (United States)

    Mikołajczyk, T.; Nowicki, K.; Bustillo, A.; Yu Pimenov, D.

    2018-05-01

    A two-step method is presented for the automatic prediction of tool life in turning operations. First, experimental data are collected for three cutting edges under the same constant processing conditions. In these experiments, the parameter of tool wear, VB, is measured with conventional methods and the same parameter is estimated using Neural Wear, a customized software package that combines flank wear image recognition and Artificial Neural Networks (ANNs). Second, an ANN model of tool life is trained with the data collected from the first two cutting edges and the subsequent model is evaluated on two different subsets for the third cutting edge: the first subset is obtained from the direct measurement of tool wear and the second is obtained from the Neural Wear software that estimates tool wear using edge images. Although the complete-automated solution, Neural Wear software for tool wear recognition plus the ANN model of tool life prediction, presented a slightly higher error than the direct measurements, it was within the same range and can meet all industrial requirements. These results confirm that the combination of image recognition software and ANN modelling could potentially be developed into a useful industrial tool for low-cost estimation of tool life in turning operations.

  18. Empirical comparison of web-based antimicrobial peptide prediction tools.

    Science.gov (United States)

    Gabere, Musa Nur; Noble, William Stafford

    2017-07-01

    Antimicrobial peptides (AMPs) are innate immune molecules that exhibit activities against a range of microbes, including bacteria, fungi, viruses and protozoa. Recent increases in microbial resistance against current drugs has led to a concomitant increase in the need for novel antimicrobial agents. Over the last decade, a number of AMP prediction tools have been designed and made freely available online. These AMP prediction tools show potential to discriminate AMPs from non-AMPs, but the relative quality of the predictions produced by the various tools is difficult to quantify. We compiled two sets of AMP and non-AMP peptides, separated into three categories-antimicrobial, antibacterial and bacteriocins. Using these benchmark data sets, we carried out a systematic evaluation of ten publicly available AMP prediction methods. Among the six general AMP prediction tools-ADAM, CAMPR3(RF), CAMPR3(SVM), MLAMP, DBAASP and MLAMP-we find that CAMPR3(RF) provides a statistically significant improvement in performance, as measured by the area under the receiver operating characteristic (ROC) curve, relative to the other five methods. Surprisingly, for antibacterial prediction, the original AntiBP method significantly outperforms its successor, AntiBP2 based on one benchmark dataset. The two bacteriocin prediction tools, BAGEL3 and BACTIBASE, both provide very good performance and BAGEL3 outperforms its predecessor, BACTIBASE, on the larger of the two benchmarks. gaberemu@ngha.med.sa or william-noble@uw.edu. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com

  19. NEEMO 20: Science Training, Operations, and Tool Development

    Science.gov (United States)

    Graff, T.; Miller, M.; Rodriguez-Lanetty, M.; Chappell, S.; Naids, A.; Hood, A.; Coan, D.; Abell, P.; Reagan, M.; Janoiko, B.

    2016-01-01

    The 20th mission of the National Aeronautics and Space Administration (NASA) Extreme Environment Mission Operations (NEEMO) was a highly integrated evaluation of operational protocols and tools designed to enable future exploration beyond low-Earth orbit. NEEMO 20 was conducted from the Aquarius habitat off the coast of Key Largo, FL in July 2015. The habitat and its surroundings provide a convincing analog for space exploration. A crew of six (comprised of astronauts, engineers, and habitat technicians) lived and worked in and around the unique underwater laboratory over a mission duration of 14-days. Incorporated into NEEMO 20 was a diverse Science Team (ST) comprised of geoscientists from the Astromaterials Research and Exploration Science (ARES/XI) Division from the Johnson Space Center (JSC), as well as marine scientists from the Department of Biological Sciences at Florida International University (FIU). This team trained the crew on the science to be conducted, defined sampling techniques and operational procedures, and planned and coordinated the science focused Extra Vehicular Activities (EVAs). The primary science objectives of NEEMO 20 was to study planetary sampling techniques and tools in partial gravity environments under realistic mission communication time delays and operational pressures. To facilitate these objectives two types of science sites were employed 1) geoscience sites with available rocks and regolith for testing sampling procedures and tools and, 2) marine science sites dedicated to specific research focused on assessing the photosynthetic capability of corals and their genetic connectivity between deep and shallow reefs. These marine sites and associated research objectives included deployment of handheld instrumentation, context descriptions, imaging, and sampling; thus acted as a suitable proxy for planetary surface exploration activities. This abstract briefly summarizes the scientific training, scientific operations, and tool

  20. WPPT, a tool for on-line wind power prediction

    Energy Technology Data Exchange (ETDEWEB)

    Skov Nielsen, T. [Dept. of Mathematical Modelling (IMM-DTU), Kgs. Lyngby (Denmark); Madsen, H. [Dept. of Mathematical Modelling (IMM-DTU) Kgs. Lyngby (Denmark); Toefting, J. [Elsam, Fredericia (Denmark)

    2004-07-01

    This paper dsecribes VPPT (Wind Power Prediction Tool), an application for assessing the future available wind power up to 36 hours ahead in time. WPPT has been installed in the Eltra/Elsam central dispatch center since October 1997. The paper describes the prediction model used, the actual implementation of WPPT as well as the experience gained by the operators in the dispatch center (au)

  1. Prediction Of Abrasive And Diffusive Tool Wear Mechanisms In Machining

    Science.gov (United States)

    Rizzuti, S.; Umbrello, D.

    2011-01-01

    Tool wear prediction is regarded as very important task in order to maximize tool performance, minimize cutting costs and improve the quality of workpiece in cutting. In this research work, an experimental campaign was carried out at the varying of cutting conditions with the aim to measure both crater and flank tool wear, during machining of an AISI 1045 with an uncoated carbide tool P40. Parallel a FEM-based analysis was developed in order to study the tool wear mechanisms, taking also into account the influence of the cutting conditions and the temperature reached on the tool surfaces. The results show that, when the temperature of the tool rake surface is lower than the activation temperature of the diffusive phenomenon, the wear rate can be estimated applying an abrasive model. In contrast, in the tool area where the temperature is higher than the diffusive activation temperature, the wear rate can be evaluated applying a diffusive model. Finally, for a temperature ranges within the above cited values an adopted abrasive-diffusive wear model furnished the possibility to correctly evaluate the tool wear phenomena.

  2. AgMIP Training in Multiple Crop Models and Tools

    Science.gov (United States)

    Boote, Kenneth J.; Porter, Cheryl H.; Hargreaves, John; Hoogenboom, Gerrit; Thornburn, Peter; Mutter, Carolyn

    2015-01-01

    The Agricultural Model Intercomparison and Improvement Project (AgMIP) has the goal of using multiple crop models to evaluate climate impacts on agricultural production and food security in developed and developing countries. There are several major limitations that must be overcome to achieve this goal, including the need to train AgMIP regional research team (RRT) crop modelers to use models other than the ones they are currently familiar with, plus the need to harmonize and interconvert the disparate input file formats used for the various models. Two activities were followed to address these shortcomings among AgMIP RRTs to enable them to use multiple models to evaluate climate impacts on crop production and food security. We designed and conducted courses in which participants trained on two different sets of crop models, with emphasis on the model of least experience. In a second activity, the AgMIP IT group created templates for inputting data on soils, management, weather, and crops into AgMIP harmonized databases, and developed translation tools for converting the harmonized data into files that are ready for multiple crop model simulations. The strategies for creating and conducting the multi-model course and developing entry and translation tools are reviewed in this chapter.

  3. Enhancing Nuclear Newcomer Training with 3D Visualization Learning Tools

    International Nuclear Information System (INIS)

    Gagnon, V.

    2016-01-01

    Full text: While the nuclear power industry is trying to reinforce its safety and regain public support post-Fukushima, it is also faced with a very real challenge that affects its day-to-day activities: a rapidly aging workforce. Statistics show that close to 40% of the current nuclear power industry workforce will retire within the next five years. For newcomer countries, the challenge is even greater, having to develop a completely new workforce. The workforce replacement effort introduces nuclear newcomers of a new generation with different backgrounds and affinities. Major lifestyle differences between the two generations of workers result, amongst other things, in different learning habits and needs for this new breed of learners. Interactivity, high visual content and quick access to information are now necessary to achieve a high level of retention. To enhance existing training programmes or to support the establishment of new training programmes for newcomer countries, L-3 MAPPS has devised learning tools to enhance these training programmes focused on the “Practice-by-Doing” principle. L-3 MAPPS has coupled 3D computer visualization with high-fidelity simulation to bring real-time, simulation-driven animated components and systems allowing immersive and participatory, individual or classroom learning. (author

  4. MONRATE, a descriptive tool for calculation and prediction of re ...

    African Journals Online (AJOL)

    The objective of the study was to develop an interactive and systematic descriptive tool, MONRATE for calculating and predicting reinfection rates and time of Ascaris lumbricoides following mass chemotherapy using levamisole. Each pupil previously treated was retreated 6 or 7 months after the initial treatment in Ogun ...

  5. Predictability of psychic outcome for exercise training and exercise training including relaxation therapy after myocardial infarction

    NARCIS (Netherlands)

    H.J. Duivenvoorden (Hugo); J. van Dixhoorn (J.)

    1991-01-01

    markdownabstractAbstract Predictability of the psychic outcome for two cardiac rehabilitation programmes was investigated in 119 myocardial infarction patients. They were randomly assigned to either a five-week daily exercise training or to an identical training in combination with six sessions

  6. KT Training: Introduction to knowledge transfer tools | 7 October

    CERN Multimedia

    2016-01-01

    Target population: All CERN staff and fellows Prerequisites: None Objectives: Get an overview of different forms of knowledge transfer Learn about available tools to: • Facilitate knowledge and technology transfer • Securing ownership and recognition for knowledge and technology Understand what services and support are available to the CERN community from the KT group Content: Why CERN engages in knowledge and technology transfer Modes of knowledge transfer and the general workflow of a knowledge transfer project Introduction to intellectual property with a focus on patents Overview of contracts for knowledge transfer and the basic structure and content of a typical contract Entrepreneurship and available support for starting a company Examples of knowledge transfer projects at CERN For more information, see the Training catalogue.

  7. The Predictive Validity of the ABFM's In-Training Examination.

    Science.gov (United States)

    O'Neill, Thomas R; Li, Zijia; Peabody, Michael R; Lybarger, Melanie; Royal, Kenneth; Puffer, James C

    2015-05-01

    Our objective was to examine the predictive validity of the American Board of Family Medicine's (ABFM) In-Training Examination (ITE) with regard to predicting outcomes on the ABFM certification examination. This study used a repeated measures design across three levels of medical training (PGY1--PGY2, PGY2--PGY3, and PGY3--initial certification) with three different cohorts (2010--2011, 2011--2012, and 2012--2013) to examine: (1) how well the residents' ITE scores correlated with their test scores in the following year, (2) what the typical score increase was across training years, and (3) what was the sensitivity, specificity, positive predictive value, and negative predictive value of the PGY3 scores with regard to predicting future results on the MC-FP Examination. ITE scores generally correlate at about .7 with the following year's ITE or with the following year's certification examination. The mean growth from PGY1 to PGY2 was 52 points, from PGY2 to PGY3 was 34 points, and from PGY3 to initial certification was 27 points. The sensitivity, specificity, positive predictive value, and negative predictive value were .91, .47, .96, and .27, respectively. The ITE is a useful predictor of future ITE and initial certification examination performance.

  8. Interactive Media and Simulation Tools for Technical Training

    Science.gov (United States)

    Gramoll, Kurt

    1997-01-01

    Over the last several years, integration of multiple media sources into a single information system has been rapidly developing. It has been found that when sound, graphics, text, animations, and simulations are skillfully integrated, the sum of the parts exceeds the individual parts for effective learning. In addition, simulations can be used to design and understand complex engineering processes. With the recent introduction of many high-level authoring, animation, modeling, and rendering programs for personal computers, significant multimedia programs can be developed by practicing engineers, scientists and even managers for both training and education. However, even with these new tools, a considerable amount of time is required to produce an interactive multimedia program. The development of both CD-ROM and Web-based programs are discussed in addition to the use of technically oriented animations. Also examined are various multimedia development tools and how they are used to develop effective engineering education courseware. Demonstrations of actual programs in engineering mechanics are shown.

  9. Improving training tools for continuing operator qualification in Spain

    International Nuclear Information System (INIS)

    Marti, F.; San Antonio, S.

    1991-01-01

    There are currently nine nuclear power plants in service in Spain; the most recent started commercial operation in 1988. Spanish legislation requires operators to have an academic technical background of at least 3 yr. The turnover rate is <5%, and in recent years, symptom-based emergency procedure has been introduced. These facts have given rise to a situation in which Spanish licensed operators are demanding more in-depth training to avoid a stagnant routine and boredom. In responding to this challenge, Tecnatom has had to significantly update its two simulators for boiling water reactor (BWR) and pressurized water reactor (PSR) plants, to ensure coverage of the emergency procedures and has had to create a tool - the Interactive Graphics Simulator - that allows these problems to be ameliorated. With a view to updating its simulators, Tecnatom initiated in 1985 a project known as advanced simulation models (MAS), which was completed at the end of 1990. The TRACS code is a real-time advanced thermohydraulic code for upgrading Tecnatom's nuclear plant simulators. The interactive graphic simulator, (SGI) is a system that provides a graphic display of the models of a full-scope simulator by means of color monitors. The two new tools used are enabling higher levels of motivation to be achieved among the plant operations personnel, especially with respect to requalification

  10. Predicting malicious behavior tools and techniques for ensuring global security

    CERN Document Server

    Jackson, Gary M

    2012-01-01

    A groundbreaking exploration of how to identify and fight security threats at every level This revolutionary book combines real-world security scenarios with actual tools to predict and prevent incidents of terrorism, network hacking, individual criminal behavior, and more. Written by an expert with intelligence officer experience who invented the technology, it explores the keys to understanding the dark side of human nature, various types of security threats (current and potential), and how to construct a methodology to predict and combat malicious behavior. The companion CD demonstrates ava

  11. Radiation protection education and training infrastructure. Open and distance learning tools for training in radiation protection

    Energy Technology Data Exchange (ETDEWEB)

    Marco, M.; Rodriguez, M.; Gonzalez Giralda, C.G.; Bailador Ferreras, A.B. [CIEMAT, Madrid (Spain); Coeck, M.C. [Studiecentrum voor Kernenergie - Centre d' Etude de l' Energie Nucleaire, Mol (Belgium); Etard, C.E. [CEA Saclay, 91 - Gif sur Yvette (France). INSTN, Institut National des Sciences et Techniques Nucleaires; Moebius, S.M. [FZK -FTU, Munich (Germany); Schmitt-Hanning, A.S. [BfS, Karlsruhe (Germany); Luciani, A.I. [ENEA, Bologna (Italy); Van Der Steen, J.V. [NRG, Petten (Netherlands)

    2006-07-01

    Full text: A sustainable Education and Training (E.T.) infrastructure for Radiation Protection is an essential component to combat the decline in expertise and to ensure the continuation of the high level of radiation protection knowledge in the future. Such infrastructure has to be built in such a way that both the initial training (Education) and the unceasing maintenance of the level of competencies (referred to as 'Training') are available. The E.N.E.T.R.A.P. project intends to develop the E.T. infrastructure mentioned. To achieve the aims of the different tasks and activities, the work programme for the E.N.E.T.R.A.P. Network is divided in eight work packages developed by 11 partners: Each partner will assume responsibility for the W.P.s. C.I.E.M.A.T. is involved in the W.P.-5 'New concepts and new tools for an E.R.P.C.'. The tasks of the W.P.-5 are focussed in the investigation of the electronic tools used in R.P. training and education. This paper presents the first results of this working group. The first task is an approach to the development and usage of learning resources. A review on the e-learning methodologies, the present state of art and its evolution, are being carried out. Results will be used to select the best way to host learning activities in the framework of the E.N.E.T.R.A.P. project. Another important task is to identify, analyse and evaluate the Open and Distance learning tools and material existing for train ing in Radiation Protection. A review on the evolutions, approaches and methodologies aiming to provide education and training in radiation protection, will be carried out. The results of this task will be a summary of links referred to the most interesting R.P. e-learning. Finally, taking in account the previous results a pilot R.P. module of E.R.P.C. should be prepared. (authors)

  12. Radiation protection education and training infrastructure. Open and distance learning tools for training in radiation protection

    International Nuclear Information System (INIS)

    Marco, M.; Rodriguez, M.; Gonzalez Giralda, C.G.; Bailador Ferreras, A.B.; Coeck, M.C.; Etard, C.E.; Schmitt-Hanning, A.S.; Luciani, A.I.; Van Der Steen, J.V.

    2006-01-01

    Full text: A sustainable Education and Training (E.T.) infrastructure for Radiation Protection is an essential component to combat the decline in expertise and to ensure the continuation of the high level of radiation protection knowledge in the future. Such infrastructure has to be built in such a way that both the initial training (Education) and the unceasing maintenance of the level of competencies (referred to as 'Training') are available. The E.N.E.T.R.A.P. project intends to develop the E.T. infrastructure mentioned. To achieve the aims of the different tasks and activities, the work programme for the E.N.E.T.R.A.P. Network is divided in eight work packages developed by 11 partners: Each partner will assume responsibility for the W.P.s. C.I.E.M.A.T. is involved in the W.P.-5 'New concepts and new tools for an E.R.P.C.'. The tasks of the W.P.-5 are focussed in the investigation of the electronic tools used in R.P. training and education. This paper presents the first results of this working group. The first task is an approach to the development and usage of learning resources. A review on the e-learning methodologies, the present state of art and its evolution, are being carried out. Results will be used to select the best way to host learning activities in the framework of the E.N.E.T.R.A.P. project. Another important task is to identify, analyse and evaluate the Open and Distance learning tools and material existing for train ing in Radiation Protection. A review on the evolutions, approaches and methodologies aiming to provide education and training in radiation protection, will be carried out. The results of this task will be a summary of links referred to the most interesting R.P. e-learning. Finally, taking in account the previous results a pilot R.P. module of E.R.P.C. should be prepared. (authors)

  13. Popularity prediction tool for ATLAS distributed data management

    International Nuclear Information System (INIS)

    Beermann, T; Maettig, P; Stewart, G; Lassnig, M; Garonne, V; Barisits, M; Vigne, R; Serfon, C; Goossens, L; Nairz, A; Molfetas, A

    2014-01-01

    This paper describes a popularity prediction tool for data-intensive data management systems, such as ATLAS distributed data management (DDM). It is fed by the DDM popularity system, which produces historical reports about ATLAS data usage, providing information about files, datasets, users and sites where data was accessed. The tool described in this contribution uses this historical information to make a prediction about the future popularity of data. It finds trends in the usage of data using a set of neural networks and a set of input parameters and predicts the number of accesses in the near term future. This information can then be used in a second step to improve the distribution of replicas at sites, taking into account the cost of creating new replicas (bandwidth and load on the storage system) compared to gain of having new ones (faster access of data for analysis). To evaluate the benefit of the redistribution a grid simulator is introduced that is able replay real workload on different data distributions. This article describes the popularity prediction method and the simulator that is used to evaluate the redistribution.

  14. Popularity Prediction Tool for ATLAS Distributed Data Management

    Science.gov (United States)

    Beermann, T.; Maettig, P.; Stewart, G.; Lassnig, M.; Garonne, V.; Barisits, M.; Vigne, R.; Serfon, C.; Goossens, L.; Nairz, A.; Molfetas, A.; Atlas Collaboration

    2014-06-01

    This paper describes a popularity prediction tool for data-intensive data management systems, such as ATLAS distributed data management (DDM). It is fed by the DDM popularity system, which produces historical reports about ATLAS data usage, providing information about files, datasets, users and sites where data was accessed. The tool described in this contribution uses this historical information to make a prediction about the future popularity of data. It finds trends in the usage of data using a set of neural networks and a set of input parameters and predicts the number of accesses in the near term future. This information can then be used in a second step to improve the distribution of replicas at sites, taking into account the cost of creating new replicas (bandwidth and load on the storage system) compared to gain of having new ones (faster access of data for analysis). To evaluate the benefit of the redistribution a grid simulator is introduced that is able replay real workload on different data distributions. This article describes the popularity prediction method and the simulator that is used to evaluate the redistribution.

  15. SitesIdentify: a protein functional site prediction tool

    Directory of Open Access Journals (Sweden)

    Doig Andrew J

    2009-11-01

    Full Text Available Abstract Background The rate of protein structures being deposited in the Protein Data Bank surpasses the capacity to experimentally characterise them and therefore computational methods to analyse these structures have become increasingly important. Identifying the region of the protein most likely to be involved in function is useful in order to gain information about its potential role. There are many available approaches to predict functional site, but many are not made available via a publicly-accessible application. Results Here we present a functional site prediction tool (SitesIdentify, based on combining sequence conservation information with geometry-based cleft identification, that is freely available via a web-server. We have shown that SitesIdentify compares favourably to other functional site prediction tools in a comparison of seven methods on a non-redundant set of 237 enzymes with annotated active sites. Conclusion SitesIdentify is able to produce comparable accuracy in predicting functional sites to its closest available counterpart, but in addition achieves improved accuracy for proteins with few characterised homologues. SitesIdentify is available via a webserver at http://www.manchester.ac.uk/bioinformatics/sitesidentify/

  16. Tools for Predicting Cleaning Efficiency in the LHC

    CERN Document Server

    Assmann, R W; Brugger, M; Hayes, M; Jeanneret, J B; Kain, V; Kaltchev, D I; Schmidt, F

    2003-01-01

    The computer codes SIXTRACK and DIMAD have been upgraded to include realistic models of proton scattering in collimator jaws, mechanical aperture restrictions, and time-dependent fields. These new tools complement long-existing simplified linear tracking programs used up to now for tracking with collimators. Scattering routines from STRUCT and K2 have been compared with one another and the results have been cross-checked to the FLUKA Monte Carlo package. A systematic error is assigned to the predictions of cleaning efficiency. Now, predictions of the cleaning efficiency are possible with a full LHC model, including chromatic effects, linear and nonlinear errors, beam-beam kicks and associated diffusion, and time-dependent fields. The beam loss can be predicted around the ring, both for regular and irregular beam losses. Examples are presented.

  17. HostPhinder: A Phage Host Prediction Tool

    Directory of Open Access Journals (Sweden)

    Julia Villarroel

    2016-05-01

    Full Text Available The current dramatic increase of antibiotic resistant bacteria has revitalised the interest in bacteriophages as alternative antibacterial treatment. Meanwhile, the development of bioinformatics methods for analysing genomic data places high-throughput approaches for phage characterization within reach. Here, we present HostPhinder, a tool aimed at predicting the bacterial host of phages by examining the phage genome sequence. Using a reference database of 2196 phages with known hosts, HostPhinder predicts the host species of a query phage as the host of the most genomically similar reference phages. As a measure of genomic similarity the number of co-occurring k-mers (DNA sequences of length k is used. Using an independent evaluation set, HostPhinder was able to correctly predict host genus and species for 81% and 74% of the phages respectively, giving predictions for more phages than BLAST and significantly outperforming BLAST on phages for which both had predictions. HostPhinder predictions on phage draft genomes from the INTESTI phage cocktail corresponded well with the advertised targets of the cocktail. Our study indicates that for most phages genomic similarity correlates well with related bacterial hosts. HostPhinder is available as an interactive web service [1] and as a stand alone download from the Docker registry [2].

  18. Virtual Reality as an Educational and Training Tool for Medicine.

    Science.gov (United States)

    Izard, Santiago González; Juanes, Juan A; García Peñalvo, Francisco J; Estella, Jesús Mª Gonçalvez; Ledesma, Mª José Sánchez; Ruisoto, Pablo

    2018-02-01

    Until very recently, we considered Virtual Reality as something that was very close, but it was still science fiction. However, today Virtual Reality is being integrated into many different areas of our lives, from videogames to different industrial use cases and, of course, it is starting to be used in medicine. There are two great general classifications for Virtual Reality. Firstly, we find a Virtual Reality in which we visualize a world completely created by computer, three-dimensional and where we can appreciate that the world we are visualizing is not real, at least for the moment as rendered images are improving very fast. Secondly, there is a Virtual Reality that basically consists of a reflection of our reality. This type of Virtual Reality is created using spherical or 360 images and videos, so we lose three-dimensional visualization capacity (until the 3D cameras are more developed), but on the other hand we gain in terms of realism in the images. We could also mention a third classification that merges the previous two, where virtual elements created by computer coexist with 360 images and videos. In this article we will show two systems that we have developed where each of them can be framed within one of the previous classifications, identifying the technologies used for their implementation as well as the advantages of each one. We will also analize how these systems can improve the current methodologies used for medical training. The implications of these developments as tools for teaching, learning and training are discussed.

  19. Translating and validating a Training Needs Assessment tool into Greek

    Directory of Open Access Journals (Sweden)

    Hicks Carolyn M

    2007-05-01

    Full Text Available Abstract Background The translation and cultural adaptation of widely accepted, psychometrically tested tools is regarded as an essential component of effective human resource management in the primary care arena. The Training Needs Assessment (TNA is a widely used, valid instrument, designed to measure professional development needs of health care professionals, especially in primary health care. This study aims to describe the translation, adaptation and validation of the TNA questionnaire into Greek language and discuss possibilities of its use in primary care settings. Methods A modified version of the English self-administered questionnaire consisting of 30 items was used. Internationally recommended methodology, mandating forward translation, backward translation, reconciliation and pretesting steps, was followed. Tool validation included assessing item internal consistency, using the alpha coefficient of Cronbach. Reproducibility (test – retest reliability was measured by the kappa correlation coefficient. Criterion validity was calculated for selected parts of the questionnaire by correlating respondents' research experience with relevant research item scores. An exploratory factor analysis highlighted how the items group together, using a Varimax (oblique rotation and subsequent Cronbach's alpha assessment. Results The psychometric properties of the Greek version of the TNA questionnaire for nursing staff employed in primary care were good. Internal consistency of the instrument was very good, Cronbach's alpha was found to be 0.985 (p 1.0, KMO (Kaiser-Meyer-Olkin measure of sampling adequacy = 0.680 and Bartlett's test of sphericity, p Conclusion The translated and adapted Greek version is comparable with the original English instrument in terms of validity and reliability and it is suitable to assess professional development needs of nursing staff in Greek primary care settings.

  20. Translating and validating a Training Needs Assessment tool into Greek

    Science.gov (United States)

    Markaki, Adelais; Antonakis, Nikos; Hicks, Carolyn M; Lionis, Christos

    2007-01-01

    Background The translation and cultural adaptation of widely accepted, psychometrically tested tools is regarded as an essential component of effective human resource management in the primary care arena. The Training Needs Assessment (TNA) is a widely used, valid instrument, designed to measure professional development needs of health care professionals, especially in primary health care. This study aims to describe the translation, adaptation and validation of the TNA questionnaire into Greek language and discuss possibilities of its use in primary care settings. Methods A modified version of the English self-administered questionnaire consisting of 30 items was used. Internationally recommended methodology, mandating forward translation, backward translation, reconciliation and pretesting steps, was followed. Tool validation included assessing item internal consistency, using the alpha coefficient of Cronbach. Reproducibility (test – retest reliability) was measured by the kappa correlation coefficient. Criterion validity was calculated for selected parts of the questionnaire by correlating respondents' research experience with relevant research item scores. An exploratory factor analysis highlighted how the items group together, using a Varimax (oblique) rotation and subsequent Cronbach's alpha assessment. Results The psychometric properties of the Greek version of the TNA questionnaire for nursing staff employed in primary care were good. Internal consistency of the instrument was very good, Cronbach's alpha was found to be 0.985 (p 1.0, KMO (Kaiser-Meyer-Olkin) measure of sampling adequacy = 0.680 and Bartlett's test of sphericity, p < 0.001. Conclusion The translated and adapted Greek version is comparable with the original English instrument in terms of validity and reliability and it is suitable to assess professional development needs of nursing staff in Greek primary care settings. PMID:17474989

  1. Analysis and Prediction of Micromilling Stability with Variable Tool Geometry

    Directory of Open Access Journals (Sweden)

    Ziyang Cao

    2014-11-01

    Full Text Available Micromilling can fabricate miniaturized components using micro-end mill at high rotational speeds. The analysis of machining stability in micromilling plays an important role in characterizing the cutting process, estimating the tool life, and optimizing the process. A numerical analysis and experimental method are presented to investigate the chatter stability in micro-end milling process with variable milling tool geometry. The schematic model of micromilling process is constructed and the calculation formula to predict cutting force and displacements is derived. This is followed by a detailed numerical analysis on micromilling forces between helical ball and square end mills through time domain and frequency domain method and the results are compared. Furthermore, a detailed time domain simulation for micro end milling with straight teeth and helical teeth end mill is conducted based on the machine-tool system frequency response function obtained through modal experiment. The forces and displacements are predicted and the simulation result between variable cutter geometry is deeply compared. The simulation results have important significance for the actual milling process.

  2. Webcams as a tool for teaching in Optometry training

    Science.gov (United States)

    Gargallo, A.; Arines, J.

    2015-04-01

    Clinical Optometry lab training is devoted to develop the students skills needed in eye healthcare professional practice. Nevertheless, students always find difficulties in the management of some optometric instruments and in the understanding of the evaluation techniques. Moreover, teachers also have problems in explaining the eye evaluation tests or making demonstrations of instruments handling. In order to facilitate the learning process, webcams adapted to the optometric devices represent a helpful and useful tool. In this work we present the use of webcams in some of the most common clinical test in Optometry as ocular refraction, colour vision test, eye health evaluation with slip-lamp, retinoscopy, ophthalmoscopy and contact lens fitting. Our experience shows that with this simple approach we can do things easier: show the instrument handling to all the students at the same time; take pictures or videos of different eye health conditions or exploratory routines for posterior visualization with all the students; recreate visual experience of the patient during optometric exam; simulate colour vision pathologies; increase the interactions between students allowing them to help and correct each other; and also record the final routine exam in order to make possible its revision with the students.

  3. NEEMO 21: Tools, Techniques, Technologies and Training for Science Exploration

    Science.gov (United States)

    Graff, T.; Young, K.; Coan, D.; Merselis, D.; Bellantuono, A.; Dougan, K.; Rodriguez-Lanetty, M.; Nedimyer, K.; Chappell, S.; Beaton, K.; hide

    2017-01-01

    The 21st mission of the National Aeronautics and Space Administration (NASA) Extreme Environment Mission Operations (NEEMO) was a highly integrated operational field test and evaluation of tools, techniques, technologies, and training for science driven exploration during extravehicular activity (EVA). The mission was conducted in July 2016 from the Aquarius habitat, an underwater laboratory, off the coast of Key Largo in the Florida Keys National Marine Sanctuary. An international crew of eight (comprised of NASA and ESA astronauts, engineers, medical personnel, and habitat technicians) lived and worked in and around Aquarius and its surrounding reef environment for 16 days. The integrated testing (both interior and exterior objectives) conducted from this unique facility continues to support current and future human space exploration endeavors. Expanding on the scientific and operational evaluations conducted during NEEMO 20, the 21st NEEMO mission further incorporated a diverse Science Team comprised of planetary geoscientists from the Astromaterials Research and Exploration Science (ARES/XI) Division from the Johnson Space Center, marine scientists from the Department of Biological Sciences at Florida International University (FIU) Integrative Marine Genomics and Symbiosis (IMaGeS) Lab, and conservationists from the Coral Restoration Foundation. The Science Team worked in close coordination with the long-standing EVA operations, planning, engineering, and research components of NEEMO in all aspects of mission planning, development, and execution.

  4. Popularity Prediction Tool for ATLAS Distributed Data Management

    CERN Document Server

    Beermann, T; The ATLAS collaboration; Stewart, G; Lassnig, M; Garonne, V; Barisits, M; Vigne, R; Serfon, C; Goossens, L; Nairz, A; Molfetas, A

    2013-01-01

    This paper describes a popularity prediction tool for data-intensive data management systems, such as ATLAS distributed data management (DDM). It is fed by the DDM popularity system, which produces historical reports about ATLAS data usage, providing information about files, datasets, users and sites where data was accessed. The tool described in this contribution uses this historical information to make a prediction about the future popularity of data. It finds trends in the usage of data using a set of neural networks and a set of input parameters and predicts the number of accesses in the near term future. This information can then be used in a second step to improve the distribution of replicas at sites, taking into account the cost of creating new replicas (bandwidth and load on the storage system) compared to gain of having new ones (faster access of data for analysis). To evaluate the benefit of the redistribution a grid simulator is introduced that is able replay real workload on different data distri...

  5. Popularity Prediction Tool for ATLAS Distributed Data Management

    CERN Document Server

    Beermann, T; The ATLAS collaboration; Stewart, G; Lassnig, M; Garonne, V; Barisits, M; Vigne, R; Serfon, C; Goossens, L; Nairz, A; Molfetas, A

    2014-01-01

    This paper describes a popularity prediction tool for data-intensive data management systems, such as ATLAS distributed data management (DDM). It is fed by the DDM popularity system, which produces historical reports about ATLAS data usage, providing information about files, datasets, users and sites where data was accessed. The tool described in this contribution uses this historical information to make a prediction about the future popularity of data. It finds trends in the usage of data using a set of neural networks and a set of input parameters and predicts the number of accesses in the near term future. This information can then be used in a second step to improve the distribution of replicas at sites, taking into account the cost of creating new replicas (bandwidth and load on the storage system) compared to gain of having new ones (faster access of data for analysis). To evaluate the benefit of the redistribution a grid simulator is introduced that is able replay real workload on different data distri...

  6. PRmePRed: A protein arginine methylation prediction tool.

    Directory of Open Access Journals (Sweden)

    Pawan Kumar

    Full Text Available Protein methylation is an important Post-Translational Modification (PTMs of proteins. Arginine methylation carries out and regulates several important biological functions, including gene regulation and signal transduction. Experimental identification of arginine methylation site is a daunting task as it is costly as well as time and labour intensive. Hence reliable prediction tools play an important task in rapid screening and identification of possible methylation sites in proteomes. Our preliminary assessment using the available prediction methods on collected data yielded unimpressive results. This motivated us to perform a comprehensive data analysis and appraisal of features relevant in the context of biological significance, that led to the development of a prediction tool PRmePRed with better performance. The PRmePRed perform reasonably well with an accuracy of 84.10%, 82.38% sensitivity, 83.77% specificity, and Matthew's correlation coefficient of 66.20% in 10-fold cross-validation. PRmePRed is freely available at http://bioinfo.icgeb.res.in/PRmePRed/.

  7. Development of Next Generation Multiphase Pipe Flow Prediction Tools

    Energy Technology Data Exchange (ETDEWEB)

    Cem Sarica; Holden Zhang

    2006-05-31

    The developments of oil and gas fields in deep waters (5000 ft and more) will become more common in the future. It is inevitable that production systems will operate under multiphase flow conditions (simultaneous flow of gas, oil and water possibly along with sand, hydrates, and waxes). Multiphase flow prediction tools are essential for every phase of hydrocarbon recovery from design to operation. Recovery from deep-waters poses special challenges and requires accurate multiphase flow predictive tools for several applications, including the design and diagnostics of the production systems, separation of phases in horizontal wells, and multiphase separation (topside, seabed or bottom-hole). It is crucial for any multiphase separation technique, either at topside, seabed or bottom-hole, to know inlet conditions such as flow rates, flow patterns, and volume fractions of gas, oil and water coming into the separation devices. Therefore, the development of a new generation of multiphase flow predictive tools is needed. The overall objective of the proposed study is to develop a unified model for gas-oil-water three-phase flow in wells, flow lines, and pipelines to predict flow characteristics such as flow patterns, phase distributions, and pressure gradient encountered during petroleum production at different flow conditions (pipe diameter and inclination, fluid properties and flow rates). In the current multiphase modeling approach, flow pattern and flow behavior (pressure gradient and phase fractions) prediction modeling are separated. Thus, different models based on different physics are employed, causing inaccuracies and discontinuities. Moreover, oil and water are treated as a pseudo single phase, ignoring the distinct characteristics of both oil and water, and often resulting in inaccurate design that leads to operational problems. In this study, a new model is being developed through a theoretical and experimental study employing a revolutionary approach. The

  8. An Engineering Tool for the Prediction of Internal Dielectric Charging

    Science.gov (United States)

    Rodgers, D. J.; Ryden, K. A.; Wrenn, G. L.; Latham, P. M.; Sorensen, J.; Levy, L.

    1998-11-01

    A practical internal charging tool has been developed. It provides an easy-to-use means for satellite engineers to predict whether on-board dielectrics are vulnerable to electrostatic discharge in the outer radiation belt. The tool is designed to simulate irradiation of single-dielectric planar or cylindrical structures with or without shielding. Analytical equations are used to describe current deposition in the dielectric. This is fast and gives charging currents to sufficient accuracy given the uncertainties in other aspects of the problem - particularly material characteristics. Time-dependent internal electric fields are calculated, taking into account the effect on conductivity of electric field, dose rate and temperature. A worst-case model of electron fluxes in the outer belt has been created specifically for the internal charging problem and is built into the code. For output, the tool gives a YES or NO decision on the susceptibility of the structure to internal electrostatic breakdown and if necessary, calculates the required changes to bring the system below the breakdown threshold. A complementary programme of laboratory irradiations has been carried out to validate the tool. The results for Epoxy-fibreglass samples show that the code models electric field realistically for a wide variety of shields, dielectric thicknesses and electron spectra. Results for Teflon samples indicate that some further experimentation is required and the radiation-induced conductivity aspects of the code have not been validated.

  9. Illusory Motion Reproduced by Deep Neural Networks Trained for Prediction.

    Science.gov (United States)

    Watanabe, Eiji; Kitaoka, Akiyoshi; Sakamoto, Kiwako; Yasugi, Masaki; Tanaka, Kenta

    2018-01-01

    The cerebral cortex predicts visual motion to adapt human behavior to surrounding objects moving in real time. Although the underlying mechanisms are still unknown, predictive coding is one of the leading theories. Predictive coding assumes that the brain's internal models (which are acquired through learning) predict the visual world at all times and that errors between the prediction and the actual sensory input further refine the internal models. In the past year, deep neural networks based on predictive coding were reported for a video prediction machine called PredNet. If the theory substantially reproduces the visual information processing of the cerebral cortex, then PredNet can be expected to represent the human visual perception of motion. In this study, PredNet was trained with natural scene videos of the self-motion of the viewer, and the motion prediction ability of the obtained computer model was verified using unlearned videos. We found that the computer model accurately predicted the magnitude and direction of motion of a rotating propeller in unlearned videos. Surprisingly, it also represented the rotational motion for illusion images that were not moving physically, much like human visual perception. While the trained network accurately reproduced the direction of illusory rotation, it did not detect motion components in negative control pictures wherein people do not perceive illusory motion. This research supports the exciting idea that the mechanism assumed by the predictive coding theory is one of basis of motion illusion generation. Using sensory illusions as indicators of human perception, deep neural networks are expected to contribute significantly to the development of brain research.

  10. Illusory Motion Reproduced by Deep Neural Networks Trained for Prediction

    Directory of Open Access Journals (Sweden)

    Eiji Watanabe

    2018-03-01

    Full Text Available The cerebral cortex predicts visual motion to adapt human behavior to surrounding objects moving in real time. Although the underlying mechanisms are still unknown, predictive coding is one of the leading theories. Predictive coding assumes that the brain's internal models (which are acquired through learning predict the visual world at all times and that errors between the prediction and the actual sensory input further refine the internal models. In the past year, deep neural networks based on predictive coding were reported for a video prediction machine called PredNet. If the theory substantially reproduces the visual information processing of the cerebral cortex, then PredNet can be expected to represent the human visual perception of motion. In this study, PredNet was trained with natural scene videos of the self-motion of the viewer, and the motion prediction ability of the obtained computer model was verified using unlearned videos. We found that the computer model accurately predicted the magnitude and direction of motion of a rotating propeller in unlearned videos. Surprisingly, it also represented the rotational motion for illusion images that were not moving physically, much like human visual perception. While the trained network accurately reproduced the direction of illusory rotation, it did not detect motion components in negative control pictures wherein people do not perceive illusory motion. This research supports the exciting idea that the mechanism assumed by the predictive coding theory is one of basis of motion illusion generation. Using sensory illusions as indicators of human perception, deep neural networks are expected to contribute significantly to the development of brain research.

  11. A tool model for predicting atmospheric kinetics with sensitivity analysis

    Institute of Scientific and Technical Information of China (English)

    2001-01-01

    A package( a tool model) for program of predicting atmospheric chemical kinetics with sensitivity analysis is presented. The new direct method of calculating the first order sensitivity coefficients using sparse matrix technology to chemical kinetics is included in the tool model, it is only necessary to triangularize the matrix related to the Jacobian matrix of the model equation. The Gear type procedure is used to integrate amodel equation and its coupled auxiliary sensitivity coefficient equations. The FORTRAN subroutines of the model equation, the sensitivity coefficient equations, and their Jacobian analytical expressions are generated automatically from a chemical mechanism. The kinetic representation for the model equation and its sensitivity coefficient equations, and their Jacobian matrix is presented. Various FORTRAN subroutines in packages, such as SLODE, modified MA28, Gear package, with which the program runs in conjunction are recommended.The photo-oxidation of dimethyl disulfide is used for illustration.

  12. Predicting SPE Fluxes: Coupled Simulations and Analysis Tools

    Science.gov (United States)

    Gorby, M.; Schwadron, N.; Linker, J.; Caplan, R. M.; Wijaya, J.; Downs, C.; Lionello, R.

    2017-12-01

    Presented here is a nuts-and-bolts look at the coupled framework of Predictive Science Inc's Magnetohydrodynamics Around a Sphere (MAS) code and the Energetic Particle Radiation Environment Module (EPREM). MAS simulated coronal mass ejection output from a variety of events can be selected as the MHD input to EPREM and a variety of parameters can be set to run against: bakground seed particle spectra, mean free path, perpendicular diffusion efficiency, etc.. A standard set of visualizations are produced as well as a library of analysis tools for deeper inquiries. All steps will be covered end-to-end as well as the framework's user interface and availability.

  13. Using social media as a tool to predict syphilis.

    Science.gov (United States)

    Young, Sean D; Mercer, Neil; Weiss, Robert E; Torrone, Elizabeth A; Aral, Sevgi O

    2018-04-01

    Syphilis rates have been rapidly rising in the United States. New technologies, such as social media, might be used to anticipate and prevent the spread of disease. Because social media data collection is easy and inexpensive, integration of social media data into syphilis surveillance may be a cost-effective surveillance strategy, especially in low-resource regions. People are increasingly using social media to discuss health-related issues, such as sexual risk behaviors, allowing social media to be a potential tool for public health and medical research. This study mined Twitter data to assess whether social media could be used to predict syphilis cases in 2013 based on 2012 data. We collected 2012 and 2013 county-level primary and secondary (P&S) and early latent syphilis cases reported to the Center for Disease Control and Prevention, along with >8500 geolocated tweets in the United States that were filtered to include sexual risk-related keywords, including colloquial terms for intercourse. We assessed the relationship between syphilis-related tweets and actual case reports by county, controlling for socioeconomic indicators and prior year syphilis cases. We found a significant positive relationship between tweets and cases of P&S and early latent syphilis. This study shows that social media may be an additional tool to enhance syphilis prediction and surveillance. Copyright © 2017 Elsevier Inc. All rights reserved.

  14. Predictive tools for designing new insulins and treatment regimens

    DEFF Research Database (Denmark)

    Klim, Søren

    The thesis deals with the development of "Predictive tools for designing new insulins and treatments regimens" and consists of two parts: A model based approach for bridging properties of new insulin analogues from glucose clamp experiments to meal tolerance tests (MTT) and a second part that des......The thesis deals with the development of "Predictive tools for designing new insulins and treatments regimens" and consists of two parts: A model based approach for bridging properties of new insulin analogues from glucose clamp experiments to meal tolerance tests (MTT) and a second part...... that describes an implemented software program able to handle stochastic differential equations (SDEs) with mixed effects. The thesis is supplemented with scientific papers published during the PhD. Developing an insulin analogue from candidate molecule to a clinical drug consists of a development programme...... and efficacy are investigated. Numerous methods are used to quantify dose and efficacy in Phase II - especially of interest is the 24-hour meal tolerance test as it tries to portray near normal living conditions. Part I describes an integrated model for insulin and glucose which is aimed at simulating 24-hour...

  15. Tools for predicting the PK/PD of therapeutic proteins.

    Science.gov (United States)

    Diao, Lei; Meibohm, Bernd

    2015-07-01

    Assessments of the pharmacokinetic/pharmacodynamic (PK/PD) characteristics are an integral part in the development of novel therapeutic agents. Compared with traditional small molecule drugs, therapeutic proteins possess many distinct PK/PD features that necessitate the application of modified or separate approaches for assessing their PK/PD relationships. In this review, the authors discuss tools that are utilized to describe and predict the PK/PD features of therapeutic proteins and that are valuable additions in the armamentarium of drug development approaches to facilitate and accelerate their successful preclinical and clinical development. A variety of state-of-the-art PK/PD tools is currently being applied and has been adjusted to support the development of proteins as therapeutics, including allometric scaling approaches, target-mediated disposition models, first-in-man dose calculations, physiologically based PK models and empirical and semi-mechanistic PK/PD modeling. With the advent of the next generation of biologics including bioengineered antibody constructs being developed, these tools will need to be further refined and adapted to ensure their applicability and successful facilitation of the drug development process for these novel scaffolds.

  16. Cardiovascular risk prediction tools for populations in Asia.

    Science.gov (United States)

    Barzi, F; Patel, A; Gu, D; Sritara, P; Lam, T H; Rodgers, A; Woodward, M

    2007-02-01

    Cardiovascular risk equations are traditionally derived from the Framingham Study. The accuracy of this approach in Asian populations, where resources for risk factor measurement may be limited, is unclear. To compare "low-information" equations (derived using only age, systolic blood pressure, total cholesterol and smoking status) derived from the Framingham Study with those derived from the Asian cohorts, on the accuracy of cardiovascular risk prediction. Separate equations to predict the 8-year risk of a cardiovascular event were derived from Asian and Framingham cohorts. The performance of these equations, and a subsequently "recalibrated" Framingham equation, were evaluated among participants from independent Chinese cohorts. Six cohort studies from Japan, Korea and Singapore (Asian cohorts); six cohort studies from China; the Framingham Study from the US. 172,077 participants from the Asian cohorts; 25,682 participants from Chinese cohorts and 6053 participants from the Framingham Study. In the Chinese cohorts, 542 cardiovascular events occurred during 8 years of follow-up. Both the Asian cohorts and the Framingham equations discriminated cardiovascular risk well in the Chinese cohorts; the area under the receiver-operator characteristic curve was at least 0.75 for men and women. However, the Framingham risk equation systematically overestimated risk in the Chinese cohorts by an average of 276% among men and 102% among women. The corresponding average overestimation using the Asian cohorts equation was 11% and 10%, respectively. Recalibrating the Framingham risk equation using cardiovascular disease incidence from the non-Chinese Asian cohorts led to an overestimation of risk by an average of 4% in women and underestimation of risk by an average of 2% in men. A low-information Framingham cardiovascular risk prediction tool, which, when recalibrated with contemporary data, is likely to estimate future cardiovascular risk with similar accuracy in Asian

  17. Tools to improve Angra 1/2 general training program

    International Nuclear Information System (INIS)

    Barroso, Haroldo Jr.

    2003-01-01

    Since Brazil restarted Angra 2 construction in 1995, as a result of the studies of future energy consumption, the Training Department of Eletronuclear developed the training program for site personnel. This new situation has demanded additional efforts and new routines. In the following paragraphs there is a description of significant aspects in this concern. Most of them are now under discussion in the Training Department and some alternative solutions are being adopted in order to face the new challenges. (author)

  18. SU-D-BRB-01: A Predictive Planning Tool for Stereotactic Radiosurgery

    Energy Technology Data Exchange (ETDEWEB)

    Palefsky, S; Roper, J; Elder, E; Dhabaan, A [Winship Cancer Institute of Emory University, Atlanta, GA (United States)

    2015-06-15

    Purpose: To demonstrate the feasibility of a predictive planning tool which provides SRS planning guidance based on simple patient anatomical properties: PTV size, PTV shape and distance from critical structures. Methods: Ten framed SRS cases treated at Winship Cancer Institute of Emory University were analyzed to extract data on PTV size, sphericity (shape), and distance from critical structures such as the brainstem and optic chiasm. The cases consisted of five pairs. Each pair consisted of two cases with a similar diagnosis (such as pituitary adenoma or arteriovenous malformation) that were treated with different techniques: DCA, or IMRS. A Naive Bayes Classifier was trained on this data to establish the conditions under which each treatment modality was used. This model was validated by classifying ten other randomly-selected cases into DCA or IMRS classes, calculating the probability of each technique, and comparing results to the treated technique. Results: Of the ten cases used to validate the model, nine had their technique predicted correctly. The three cases treated with IMRS were all identified as such. Their probabilities of being treated with IMRS ranged between 59% and 100%. Six of the seven cases treated with DCA were correctly classified. These probabilities ranged between 51% and 95%. One case treated with DCA was incorrectly predicted to be an IMRS plan. The model’s confidence in this case was 91%. Conclusion: These findings indicate that a predictive planning tool based on simple patient anatomical properties can predict the SRS technique used for treatment. The algorithm operated with 90% accuracy. With further validation on larger patient populations, this tool may be used clinically to guide planners in choosing an appropriate treatment technique. The prediction algorithm could also be adapted to guide selection of treatment parameters such as treatment modality and number of fields for radiotherapy across anatomical sites.

  19. SU-D-BRB-01: A Predictive Planning Tool for Stereotactic Radiosurgery

    International Nuclear Information System (INIS)

    Palefsky, S; Roper, J; Elder, E; Dhabaan, A

    2015-01-01

    Purpose: To demonstrate the feasibility of a predictive planning tool which provides SRS planning guidance based on simple patient anatomical properties: PTV size, PTV shape and distance from critical structures. Methods: Ten framed SRS cases treated at Winship Cancer Institute of Emory University were analyzed to extract data on PTV size, sphericity (shape), and distance from critical structures such as the brainstem and optic chiasm. The cases consisted of five pairs. Each pair consisted of two cases with a similar diagnosis (such as pituitary adenoma or arteriovenous malformation) that were treated with different techniques: DCA, or IMRS. A Naive Bayes Classifier was trained on this data to establish the conditions under which each treatment modality was used. This model was validated by classifying ten other randomly-selected cases into DCA or IMRS classes, calculating the probability of each technique, and comparing results to the treated technique. Results: Of the ten cases used to validate the model, nine had their technique predicted correctly. The three cases treated with IMRS were all identified as such. Their probabilities of being treated with IMRS ranged between 59% and 100%. Six of the seven cases treated with DCA were correctly classified. These probabilities ranged between 51% and 95%. One case treated with DCA was incorrectly predicted to be an IMRS plan. The model’s confidence in this case was 91%. Conclusion: These findings indicate that a predictive planning tool based on simple patient anatomical properties can predict the SRS technique used for treatment. The algorithm operated with 90% accuracy. With further validation on larger patient populations, this tool may be used clinically to guide planners in choosing an appropriate treatment technique. The prediction algorithm could also be adapted to guide selection of treatment parameters such as treatment modality and number of fields for radiotherapy across anatomical sites

  20. Predicted impact and evaluation of North Carolina's phosphorus indexing tool.

    Science.gov (United States)

    Johnson, Amy M; Osmond, Deanna L; Hodges, Steven C

    2005-01-01

    Increased concern about potential losses of phosphorus (P) from agricultural fields receiving animal waste has resulted in the implementation of new state and federal regulations related to nutrient management. In response to strengthened nutrient management standards that require consideration of P, North Carolina has developed a site-specific P indexing system called the Phosphorus Loss Assessment Tool (PLAT) to predict relative amounts of potential P loss from agricultural fields. The purpose of this study was to apply the PLAT index on farms throughout North Carolina in an attempt to predict the percentage and types of farms that will be forced to change management practices due to implementation of new regulations. Sites from all 100 counties were sampled, with the number of samples taken from each county depending on the proportion of the state's agricultural land that occurs in that county. Results showed that approximately 8% of producers in the state will be required to apply animal waste or inorganic fertilizer on a P rather than nitrogen basis, with the percentage increasing for farmers who apply animal waste (approximately 27%). The PLAT index predicted the greatest amounts of P loss from sites in the Coastal Plain region of North Carolina and from sites receiving poultry waste. Loss of dissolved P through surface runoff tended to be greater than other loss pathways and presents an area of concern as no best management practices (BMPs) currently exist for the reduction of in-field dissolved P. The PLAT index predicted the areas in the state that are known to be disproportionately vulnerable to P loss due to histories of high P applications, high densities of animal units, or soil type and landscapes that are most susceptible to P loss.

  1. Web-Enabled Training-Development Tool for Pre-Deployment and Deployed Training

    National Research Council Canada - National Science Library

    Cianciolo, Anna T

    2006-01-01

    ...) researched the Army training process, identified methods for relieving the constraints on rapid, contextualized training development, and developed these methods into a prototype TA capability for feasibility analysis...

  2. Using Search Engine Data as a Tool to Predict Syphilis.

    Science.gov (United States)

    Young, Sean D; Torrone, Elizabeth A; Urata, John; Aral, Sevgi O

    2018-07-01

    Researchers have suggested that social media and online search data might be used to monitor and predict syphilis and other sexually transmitted diseases. Because people at risk for syphilis might seek sexual health and risk-related information on the internet, we investigated associations between internet state-level search query data (e.g., Google Trends) and reported weekly syphilis cases. We obtained weekly counts of reported primary and secondary syphilis for 50 states from 2012 to 2014 from the US Centers for Disease Control and Prevention. We collected weekly internet search query data regarding 25 risk-related keywords from 2012 to 2014 for 50 states using Google Trends. We joined 155 weeks of Google Trends data with 1-week lag to weekly syphilis data for a total of 7750 data points. Using the least absolute shrinkage and selection operator, we trained three linear mixed models on the first 10 weeks of each year. We validated models for 2012 and 2014 for the following 52 weeks and the 2014 model for the following 42 weeks. The models, consisting of different sets of keyword predictors for each year, accurately predicted 144 weeks of primary and secondary syphilis counts for each state, with an overall average R of 0.9 and overall average root mean squared error of 4.9. We used Google Trends search data from the prior week to predict cases of syphilis in the following weeks for each state. Further research could explore how search data could be integrated into public health monitoring systems.

  3. Development of Next Generation Multiphase Pipe Flow Prediction Tools

    Energy Technology Data Exchange (ETDEWEB)

    Tulsa Fluid Flow

    2008-08-31

    The developments of fields in deep waters (5000 ft and more) is a common occurrence. It is inevitable that production systems will operate under multiphase flow conditions (simultaneous flow of gas-oil-and water possibly along with sand, hydrates, and waxes). Multiphase flow prediction tools are essential for every phase of the hydrocarbon recovery from design to operation. The recovery from deep-waters poses special challenges and requires accurate multiphase flow predictive tools for several applications including the design and diagnostics of the production systems, separation of phases in horizontal wells, and multiphase separation (topside, seabed or bottom-hole). It is very crucial to any multiphase separation technique that is employed either at topside, seabed or bottom-hole to know inlet conditions such as the flow rates, flow patterns, and volume fractions of gas, oil and water coming into the separation devices. The overall objective was to develop a unified model for gas-oil-water three-phase flow in wells, flow lines, and pipelines to predict the flow characteristics such as flow patterns, phase distributions, and pressure gradient encountered during petroleum production at different flow conditions (pipe diameter and inclination, fluid properties and flow rates). The project was conducted in two periods. In Period 1 (four years), gas-oil-water flow in pipes were investigated to understand the fundamental physical mechanisms describing the interaction between the gas-oil-water phases under flowing conditions, and a unified model was developed utilizing a novel modeling approach. A gas-oil-water pipe flow database including field and laboratory data was formed in Period 2 (one year). The database was utilized in model performance demonstration. Period 1 primarily consisted of the development of a unified model and software to predict the gas-oil-water flow, and experimental studies of the gas-oil-water project, including flow behavior description and

  4. The Training Evaluation Inventory (TEI)--Evaluation of Training Design and Measurement of Training Outcomes for Predicting Training Success

    Science.gov (United States)

    Ritzmann, Sandrina; Hagemann, Vera; Kluge, Annette

    2014-01-01

    Training evaluation in research and organisational contexts is vital to ensure informed decisions regarding the value of training. The present study describes the development of a valid and reliable training evaluation inventory (TEI), as it does not exist so far. The objectives were a) to construct an instrument that is theoretically and…

  5. Prediction of ttt curves of cold working tool steels using support vector machine model

    Science.gov (United States)

    Pillai, Nandakumar; Karthikeyan, R., Dr.

    2018-04-01

    The cold working tool steels are of high carbon steels with metallic alloy additions which impart higher hardenability, abrasion resistance and less distortion in quenching. The microstructure changes occurring in tool steel during heat treatment is of very much importance as the final properties of the steel depends upon these changes occurred during the process. In order to obtain the desired performance the alloy constituents and its ratio plays a vital role as the steel transformation itself is complex in nature and depends very much upon the time and temperature. The proper treatment can deliver satisfactory results, at the same time process deviation can completely spoil the results. So knowing time temperature transformation (TTT) of phases is very critical which varies for each type depending upon its constituents and proportion range. To obtain adequate post heat treatment properties the percentage of retained austenite should be lower and metallic carbides obtained should be fine in nature. Support vector machine is a computational model which can learn from the observed data and use these to predict or solve using mathematical model. Back propagation feedback network will be created and trained for further solutions. The points on the TTT curve for the known transformations curves are used to plot the curves for different materials. These data will be trained to predict TTT curves for other steels having similar alloying constituents but with different proportion range. The proposed methodology can be used for prediction of TTT curves for cold working steels and can be used for prediction of phases for different heat treatment methods.

  6. An evidence-based decision assistance model for predicting training outcome in juvenile guide dogs.

    Science.gov (United States)

    Harvey, Naomi D; Craigon, Peter J; Blythe, Simon A; England, Gary C W; Asher, Lucy

    2017-01-01

    Working dog organisations, such as Guide Dogs, need to regularly assess the behaviour of the dogs they train. In this study we developed a questionnaire-style behaviour assessment completed by training supervisors of juvenile guide dogs aged 5, 8 and 12 months old (n = 1,401), and evaluated aspects of its reliability and validity. Specifically, internal reliability, temporal consistency, construct validity, predictive criterion validity (comparing against later training outcome) and concurrent criterion validity (comparing against a standardised behaviour test) were evaluated. Thirty-nine questions were sourced either from previously published literature or created to meet requirements identified via Guide Dogs staff surveys and staff feedback. Internal reliability analyses revealed seven reliable and interpretable trait scales named according to the questions within them as: Adaptability; Body Sensitivity; Distractibility; Excitability; General Anxiety; Trainability and Stair Anxiety. Intra-individual temporal consistency of the scale scores between 5-8, 8-12 and 5-12 months was high. All scales excepting Body Sensitivity showed some degree of concurrent criterion validity. Predictive criterion validity was supported for all seven scales, since associations were found with training outcome, at at-least one age. Thresholds of z-scores on the scales were identified that were able to distinguish later training outcome by identifying 8.4% of all dogs withdrawn for behaviour and 8.5% of all qualified dogs, with 84% and 85% specificity. The questionnaire assessment was reliable and could detect traits that are consistent within individuals over time, despite juvenile dogs undergoing development during the study period. By applying thresholds to scores produced from the questionnaire this assessment could prove to be a highly valuable decision-making tool for Guide Dogs. This is the first questionnaire-style assessment of juvenile dogs that has shown value in predicting

  7. Evaluation of workplace based assessment tools in dental foundation training.

    Science.gov (United States)

    Grieveson, B; Kirton, J A; Palmer, N O A; Balmer, M C

    2011-08-26

    The aims of this survey were to evaluate the effectiveness of workplace based assessments (WPAs) in dental foundation training (formerly vocational training [VT]). Two online questionnaire surveys were sent to 53 foundation dental practitioners (FDPs) and their 51 trainers in the Mersey Deanery at month four and month nine of the one year of dental foundation training. The questionnaires investigated the effectiveness of and trainers' and trainees' satisfaction with the WPAs used in foundation training, namely dental evaluation of performance (D-EPs), case-based discussions (DcBD) and patients' assessment questionnaires (PAQs). The questionnaires also investigated the perceived impact of reflection and feedback associated with WPAs on clinical practise and improving patient care. A total of 41 (7.4%) FDPs and 44 (86.3%) trainers responded. Of the 41 FDPs, the majority found that feedback from WPAs had a positive effect on their training, giving them insight into their development needs. Overall 84.1% of the FDPs felt the WPAs helped them improve patient care and 82.5% of trainers agreed with that outcome. The findings from this study demonstrate the value of WPAs in dental foundation training by the use of feedback and reflection in directing the learning of foundation dental practitioners and that this can lead to improved clinical practise and patient care.

  8. Does the Risk Assessment and Prediction Tool Predict Discharge Disposition After Joint Replacement?

    DEFF Research Database (Denmark)

    Hansen, Viktor J.; Gromov, Kirill; Lebrun, Lauren M

    2015-01-01

    BACKGROUND: Payers of health services and policymakers place a major focus on cost containment in health care. Studies have shown that early planning of discharge is essential in reducing length of stay and achieving financial benefit; tools that can help predict discharge disposition would...... populations is unknown. A low RAPT score is reported to indicate a high risk of needing any form of inpatient rehabilitation after TJA, including short-term nursing facilities. QUESTIONS/PURPOSES: This study attempts (1) to assess predictive accuracy of the RAPT on US patients undergoing total hip and knee....... Based on our findings, the risk categories in our populations should be high risk intermediate risk 7 to 10, and low risk > 10. CONCLUSIONS: The RAPT accurately predicted discharge disposition for high- and low-risk patients in our cohort. Based on our data, intermediate-risk patients should...

  9. Training in motivational interviewing in obstetrics: a quantitative analytical tool.

    Science.gov (United States)

    Lindhardt, Christina L; Rubak, Sune; Mogensen, Ole; Hansen, Helle P; Lamont, Ronald F; Jørgensen, Jan S

    2014-07-01

    To examine whether a 3-day training course in motivational interviewing, which is an approach to helping people to change, could improve the communication skills of obstetric healthcare professionals in their interaction with obese pregnant women. Intervention study. The Region of Southern Denmark. Eleven obstetric healthcare professionals working with obese pregnant women underwent a 3-day course in motivational interviewing techniques and were assessed before and after training to measure the impact on their overall performance as well as the effect on specific behavioral techniques observed during interviews. With a few exceptions, the participants changed their behavior appropriate to the motivational interviewing technique. The participants made more interventions towards the principles of motivational interviewing (adherent and nonadherent interventions). Furthermore, the participants asked fewer closed and more open questions before training in motivational interview. In the assessment of proficiency and competency, most of the participants scored higher after the training in motivational interviewing. Training in motivational interviewing improves healthcare professionals' proficiency and competency when communicating with obese pregnant women, albeit that the effect was not universal. © 2014 Nordic Federation of Societies of Obstetrics and Gynecology.

  10. STUDENT PREDICTION SYSTEM FOR PLACEMENT TRAINING USING FUZZY INFERENCE SYSTEM

    Directory of Open Access Journals (Sweden)

    Ravi Kumar Rathore

    2017-04-01

    Full Text Available Proposed student prediction system is most vital approach which may be used to differentiate the student data/information on the basis of the student performance. Managing placement and training records in any larger organization is quite difficult as the student number are high; in such condition differentiation and classification on different categories becomes tedious. Proposed fuzzy inference system will classify the student data with ease and will be helpful to many educational organizations. There are lots of classification algorithms and statistical base technique which may be taken as good assets for classify the student data set in the education field. In this paper, Fuzzy Inference system has been applied to predict student performance which will help to identify performance of the students and also provides an opportunity to improve to performance. For instance, here we will classify the student’s data set for placement and non-placement classes.

  11. A new tool to measure training load in soccer training and match play

    DEFF Research Database (Denmark)

    Rebelo, A; Brito, J; Seabra, A

    2012-01-01

    -based methods (TRIMP and Edwards' method). 51 soccer players (age 15.6±0.3 years) answered 2 questions to assess perceived exertion and fatigue (VAS1-TL, and VAS2-TL) after training sessions and official matches. Performance in the Yo-Yo tests, VAS scores and heart rate of training sessions and matches......An accurate evaluation of training load is paramount for the planning and periodization of training. The aim of the present study was to evaluate the relationship between a new method to monitor training load in soccer (Visual Analogic Scale training load; VAS-TL), and two established heart rate...

  12. Video games as a tool to train visual skills.

    Science.gov (United States)

    Achtman, R L; Green, C S; Bavelier, D

    2008-01-01

    Adult brain plasticity, although possible, is often difficult to elicit. Training regimens in adults can produce specific improvements on the trained task without leading to general enhancements that would improve quality of life. This paper considers the case of playing action video games as a way to induce widespread enhancement in vision. We review the range of visual skills altered by action video game playing as well as the game components important in promoting visual plasticity. Further, we discuss what these results might mean in terms of rehabilitation for different patient populations.

  13. Video games as a tool to train visual skills

    Science.gov (United States)

    Achtman, R.L.; Green, C.S.; Bavelier, D.

    2010-01-01

    Purpose Adult brain plasticity, although possible, is often difficult to elicit. Training regimens in adults can produce specific improvements on the trained task without leading to general enhancements that would improve quality of life. This paper considers the case of playing action video games as a way to induce widespread enhancement in vision. Conclusions We review the range of visual skills altered by action video game playing as well as the game components important in promoting visual plasticity. Further, we discuss what these results might mean in terms of rehabilitation for different patient populations. PMID:18997318

  14. Computer-Assisted Visual Search/Decision Aids as a Training Tool for Mammography

    National Research Council Canada - National Science Library

    Nodine, Calvin

    2000-01-01

    The primary goal of the project is to develop a computer-assisted visual search (CAVS) mammography training tool that will improve the perceptual and cognitive skills of trainees leading to mammographic expertise...

  15. Computer-Assisted Visual Search/Decision Aids as a Training Tool for Mammography

    National Research Council Canada - National Science Library

    Nodine, Calvin

    1999-01-01

    The primary goal of the project is to develop a computer-assisted visual search (CAVS) mammography training tool that will improve the perceptual and cognitive skills of trainees leading to mammographic expertise...

  16. Computer-Assisted Visual Search/Decision Aids as a Training Tool for Mammography

    National Research Council Canada - National Science Library

    Nodine, Calvin

    1998-01-01

    The primary goal of the project is to develop a computer-assisted visual search (CAVS) mammography training tool that will improve the perceptual and cognitive skills of trainees leading to mammographic expertise...

  17. idSpace Tooling and Training for collaborative distributed product innovation

    NARCIS (Netherlands)

    Rutjens, Marjo; Bitter-Rijpkema, Marlies; Grube, Pascal; Heider, Thomas

    2009-01-01

    Rutjens, M., Bitter-Rijpkema, M., Grube, P. P., & Heider, T. (2009). idSpace Tooling and Training for collaborative distributed product innovation. Workshop during the e-Learning Baltic conference. June, 17-19, 2009, Rostock, Germany.

  18. A clinical tool to predict Plasmodium vivax recurrence in Malaysia.

    Science.gov (United States)

    Mat Ariffin, Norliza; Islahudin, Farida; Kumolosasi, Endang; Makmor-Bakry, Mohd

    2017-12-08

    Recurrence rates of Plasmodium vivax infections differ across various geographic regions. Interestingly, South-East Asia and the Asia-Pacific region are documented to exhibit the most frequent recurrence incidences. Identifying patients at a higher risk for recurrences gives valuable information in strengthening the efforts to control P. vivax infections. The aim of the study was to develop a tool to identify P. vivax- infected patients that are at a higher risk of recurrence in Malaysia. Patient data was obtained retrospectively through the Ministry of Health, Malaysia, from 2011 to 2016. Patients with incomplete data were excluded. A total of 2044 clinical P. vivax malaria cases treated with primaquine were included. Data collected were patient, disease, and treatment characteristics. Two-thirds of the cases (n = 1362) were used to develop a clinical risk score, while the remaining third (n = 682) was used for validation. Using multivariate analysis, age (p = 0.03), gametocyte sexual count (p = 0.04), indigenous transmission (p = 0.04), type of treatment (p = 0.12), and incomplete primaquine treatment (p = 0.14) were found to be predictors of recurrence after controlling for other confounding factors; these predictors were then used in developing the final model. The beta-coefficient values were used to develop a clinical scoring tool to predict possible recurrence. The total scores ranged between 0 and 8. A higher score indicated a higher risk for recurrence (odds ratio [OR]: 1.971; 95% confidence interval [CI]: 1.562-2.487; p ≤ 0.001). The area under the receiver operating characteristic (ROC) curve of the developed (n = 1362) and validated model (n = 682) was of good accuracy (ROC: 0.728, 95% CI: 0.670-0.785, p value useful tool in targeting patients at a higher risk for recurrence for closer monitoring during follow-up, after treatment with primaquine.

  19. Bitter or not? BitterPredict, a tool for predicting taste from chemical structure.

    Science.gov (United States)

    Dagan-Wiener, Ayana; Nissim, Ido; Ben Abu, Natalie; Borgonovo, Gigliola; Bassoli, Angela; Niv, Masha Y

    2017-09-21

    Bitter taste is an innately aversive taste modality that is considered to protect animals from consuming toxic compounds. Yet, bitterness is not always noxious and some bitter compounds have beneficial effects on health. Hundreds of bitter compounds were reported (and are accessible via the BitterDB http://bitterdb.agri.huji.ac.il/dbbitter.php ), but numerous additional bitter molecules are still unknown. The dramatic chemical diversity of bitterants makes bitterness prediction a difficult task. Here we present a machine learning classifier, BitterPredict, which predicts whether a compound is bitter or not, based on its chemical structure. BitterDB was used as the positive set, and non-bitter molecules were gathered from literature to create the negative set. Adaptive Boosting (AdaBoost), based on decision trees machine-learning algorithm was applied to molecules that were represented using physicochemical and ADME/Tox descriptors. BitterPredict correctly classifies over 80% of the compounds in the hold-out test set, and 70-90% of the compounds in three independent external sets and in sensory test validation, providing a quick and reliable tool for classifying large sets of compounds into bitter and non-bitter groups. BitterPredict suggests that about 40% of random molecules, and a large portion (66%) of clinical and experimental drugs, and of natural products (77%) are bitter.

  20. Comparison of the Nosocomial Pneumonia Mortality Prediction (NPMP) model with standard mortality prediction tools.

    Science.gov (United States)

    Srinivasan, M; Shetty, N; Gadekari, S; Thunga, G; Rao, K; Kunhikatta, V

    2017-07-01

    Severity or mortality prediction of nosocomial pneumonia could aid in the effective triage of patients and assisting physicians. To compare various severity assessment scoring systems for predicting intensive care unit (ICU) mortality in nosocomial pneumonia patients. A prospective cohort study was conducted in a tertiary care university-affiliated hospital in Manipal, India. One hundred patients with nosocomial pneumonia, admitted in the ICUs who developed pneumonia after >48h of admission, were included. The Nosocomial Pneumonia Mortality Prediction (NPMP) model, developed in our hospital, was compared with Acute Physiology and Chronic Health Evaluation II (APACHE II), Mortality Probability Model II (MPM 72  II), Simplified Acute Physiology Score II (SAPS II), Multiple Organ Dysfunction Score (MODS), Sequential Organ Failure Assessment (SOFA), Clinical Pulmonary Infection Score (CPIS), Ventilator-Associated Pneumonia Predisposition, Insult, Response, Organ dysfunction (VAP-PIRO). Data and clinical variables were collected on the day of pneumonia diagnosis. The outcome for the study was ICU mortality. The sensitivity and specificity of the various scoring systems was analysed by plotting receiver operating characteristic (ROC) curves and computing the area under the curve for each of the mortality predicting tools. NPMP, APACHE II, SAPS II, MPM 72  II, SOFA, and VAP-PIRO were found to have similar and acceptable discrimination power as assessed by the area under the ROC curve. The AUC values for the above scores ranged from 0.735 to 0.762. CPIS and MODS showed least discrimination. NPMP is a specific tool to predict mortality in nosocomial pneumonia and is comparable to other standard scores. Copyright © 2017 The Healthcare Infection Society. Published by Elsevier Ltd. All rights reserved.

  1. The assessment of training efficiency. A management tool in Sta. Ma de Garona NPP

    International Nuclear Information System (INIS)

    Carretero, Felipe; Sanchez Alvarez, Francisco J.; Soriano, Santiago Lucas

    2003-01-01

    Nowadays, one of the critical factors which determines the success of the companies is their adaptability to changes and the development of key competencies in a more global and competitive market. The acquisition, maintenance and updating of those competencies is a fundamental concern of the training managers. Training management implies also to answer, as accurate as possible, questions as following: Which is the quality of the training activities? Are the taught knowledge, skills and attitudes fully assimilated? Are they transferred to job position? Is it possible to correlate training effort and company results? Which is the comprehensive cost of the training programme? and finally, Is the cost reasonable according to the results?, in other words, has been the training programme efficient enough?The present paper introduces the experience in implementing an assessment system of training efficiency, in Sta. M a de Garona, as a training management tool for decision making. (author)

  2. Training Tools for Nontechnical Skills for Surgeons-A Systematic Review.

    Science.gov (United States)

    Wood, Thomas Charles; Raison, Nicholas; Haldar, Shreya; Brunckhorst, Oliver; McIlhenny, Craig; Dasgupta, Prokar; Ahmed, Kamran

    Development of nontechnical skills for surgeons has been recognized as an important factor in surgical care. Training tools for this specific domain are being created and validated to maximize the surgeon's nontechnical ability. This systematic review aims to outline, address, and recommend these training tools. A full and comprehensive literature search, using a systematic format, was performed on ScienceDirect and PubMed, with data extraction occurring in line with specified inclusion criteria. Systematic review was performed fully at King's College London. A total of 84 heterogeneous articles were used in this review. Further, 23 training tools including scoring systems, training programs, and mixtures of the two for a range of specialities were identified in the literature. Most can be applied to surgery overall, although some tools target specific specialities (such as neurosurgery). Interrater reliability, construct, content, and face validation statuses were variable according to the specific tool in question. Study results pertaining to nontechnical skill training tools have thus far been universally positive, but further studies are required for those more recently developed and less extensively used tools. Recommendations can be made for individual training tools based on their level of validation and for their target audience. Based on the number of studies performed and their status of validity, NOTSS and Oxford NOTECHS II can be considered the gold standard for individual- and team-based nontechnical skills training, respectively, especially when used in conjunction with a training program. Copyright © 2017 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.

  3. Prediction models : the right tool for the right problem

    NARCIS (Netherlands)

    Kappen, Teus H.; Peelen, Linda M.

    2016-01-01

    PURPOSE OF REVIEW: Perioperative prediction models can help to improve personalized patient care by providing individual risk predictions to both patients and providers. However, the scientific literature on prediction model development and validation can be quite technical and challenging to

  4. Basic Botany On-Line: A Training Tool for the Master Gardener Program.

    Science.gov (United States)

    VanDerZanden, Ann Marie; Rost, Bob; Eckel, Rick

    2002-01-01

    A noncredit, online training module on botany was offered to participants in the Oregon Master Gardener program. The 48 participants felt the module was a useful training tool. They also noted that the convenience of completing the material at their own pace and during a time that fit into their schedule. (SK)

  5. The in-training examination: an analysis of its predictive value on performance on the general pediatrics certification examination.

    Science.gov (United States)

    Althouse, Linda A; McGuinness, Gail A

    2008-09-01

    This study investigates the predictive validity of the In-Training Examination (ITE). Although studies have confirmed the predictive validity of ITEs in other medical specialties, no study has been done for general pediatrics. Each year, residents in accredited pediatric training programs take the ITE as a self-assessment instrument. The ITE is similar to the American Board of Pediatrics General Pediatrics Certifying Examination. First-time takers of the certifying examination over a 5-year period who took at least 1 ITE examination were included in the sample. Regression models analyzed the predictive value of the ITE. The predictive power of the ITE in the first training year is minimal. However, the predictive power of the ITE increases each year, providing the greatest power in the third year of training. Even though ITE scores provide information regarding the likelihood of passing the certification examination, the data should be used with caution, particularly in the first training year. Other factors also must be considered when predicting performance on the certification examination. This study continues to support the ITE as an assessment tool for program directors, as well as a means of providing residents with feedback regarding their acquisition of pediatric knowledge.

  6. Impact of relationships between test and training animals and among training animals on reliability of genomic prediction.

    Science.gov (United States)

    Wu, X; Lund, M S; Sun, D; Zhang, Q; Su, G

    2015-10-01

    One of the factors affecting the reliability of genomic prediction is the relationship among the animals of interest. This study investigated the reliability of genomic prediction in various scenarios with regard to the relationship between test and training animals, and among animals within the training data set. Different training data sets were generated from EuroGenomics data and a group of Nordic Holstein bulls (born in 2005 and afterwards) as a common test data set. Genomic breeding values were predicted using a genomic best linear unbiased prediction model and a Bayesian mixture model. The results showed that a closer relationship between test and training animals led to a higher reliability of genomic predictions for the test animals, while a closer relationship among training animals resulted in a lower reliability. In addition, the Bayesian mixture model in general led to a slightly higher reliability of genomic prediction, especially for the scenario of distant relationships between training and test animals. Therefore, to prevent a decrease in reliability, constant updates of the training population with animals from more recent generations are required. Moreover, a training population consisting of less-related animals is favourable for reliability of genomic prediction. © 2015 Blackwell Verlag GmbH.

  7. USE OF MULTIMEDIA TOOLS IN THE TRAINING OF PEDAGOGICAL COLLEGES STUDENTS

    Directory of Open Access Journals (Sweden)

    Olga M. Naumenko

    2010-08-01

    Full Text Available Current questions concerning the introduction of information and communication technologies tools into the pedagogical college teacher training using the essentially new ways of informative activity are considered. On the basis of the researches having been spent in the pedagogical colleges of Kyiv, there are analyzed possible scenarios of use of such multimedia tools in educational process.

  8. USE OF MULTIMEDIA TOOLS IN THE TRAINING OF PEDAGOGICAL COLLEGES STUDENTS

    OpenAIRE

    Olga M. Naumenko

    2010-01-01

    Current questions concerning the introduction of information and communication technologies tools into the pedagogical college teacher training using the essentially new ways of informative activity are considered. On the basis of the researches having been spent in the pedagogical colleges of Kyiv, there are analyzed possible scenarios of use of such multimedia tools in educational process.

  9. Using Web-Based Technologies and Tools in Future Choreographers' Training: British Experience

    Science.gov (United States)

    Bidyuk, Dmytro

    2016-01-01

    In the paper the problem of using effective web-based technologies and tools in teaching choreography in British higher education institutions has been discussed. Researches on the usage of web-based technologies and tools for practical dance courses in choreographers' professional training at British higher education institutions by such British…

  10. Development of a Bilingual Training Tool to Train Dairy Workers on the Prevention and Management of Non-Ambulatory Cows

    Science.gov (United States)

    Roman-Muniz, Ivette N.; Van Metre, David C.

    2011-01-01

    Dairy cows at risk of becoming non-ambulatory or downers represent economic losses and animal well-being issues for the dairy industry. Colorado State University researchers and Extension faculty collaborated with Colorado's dairy industry to create a training tool for the early identification and management of cows at risk of becoming downers on…

  11. TSSPlant: a new tool for prediction of plant Pol II promoters

    KAUST Repository

    Shahmuradov, Ilham A.

    2017-01-13

    Our current knowledge of eukaryotic promoters indicates their complex architecture that is often composed of numerous functional motifs. Most of known promoters include multiple and in some cases mutually exclusive transcription start sites (TSSs). Moreover, TSS selection depends on cell/tissue, development stage and environmental conditions. Such complex promoter structures make their computational identification notoriously difficult. Here, we present TSSPlant, a novel tool that predicts both TATA and TATA-less promoters in sequences of a wide spectrum of plant genomes. The tool was developed by using large promoter collections from ppdb and PlantProm DB. It utilizes eighteen significant compositional and signal features of plant promoter sequences selected in this study, that feed the artificial neural network-based model trained by the backpropagation algorithm. TSSPlant achieves significantly higher accuracy compared to the next best promoter prediction program for both TATA promoters (MCC≃0.84 and F1-score≃0.91 versus MCC≃0.51 and F1-score≃0.71) and TATA-less promoters (MCC≃0.80, F1-score≃0.89 versus MCC≃0.29 and F1-score≃0.50). TSSPlant is available to download as a standalone program at http://www.cbrc.kaust.edu.sa/download/.

  12. TSSPlant: a new tool for prediction of plant Pol II promoters

    KAUST Repository

    Shahmuradov, Ilham A.; Umarov, Ramzan; Solovyev, Victor V.

    2017-01-01

    Our current knowledge of eukaryotic promoters indicates their complex architecture that is often composed of numerous functional motifs. Most of known promoters include multiple and in some cases mutually exclusive transcription start sites (TSSs). Moreover, TSS selection depends on cell/tissue, development stage and environmental conditions. Such complex promoter structures make their computational identification notoriously difficult. Here, we present TSSPlant, a novel tool that predicts both TATA and TATA-less promoters in sequences of a wide spectrum of plant genomes. The tool was developed by using large promoter collections from ppdb and PlantProm DB. It utilizes eighteen significant compositional and signal features of plant promoter sequences selected in this study, that feed the artificial neural network-based model trained by the backpropagation algorithm. TSSPlant achieves significantly higher accuracy compared to the next best promoter prediction program for both TATA promoters (MCC≃0.84 and F1-score≃0.91 versus MCC≃0.51 and F1-score≃0.71) and TATA-less promoters (MCC≃0.80, F1-score≃0.89 versus MCC≃0.29 and F1-score≃0.50). TSSPlant is available to download as a standalone program at http://www.cbrc.kaust.edu.sa/download/.

  13. Availability of Ada and C++ Compilers, Tools, Education and Training

    Science.gov (United States)

    1991-07-01

    executable mini-specs, to support import of existing code. Automated database population/change propagation. 9. Documentation generation: via FrameMaker . 10...formats. 12. Links to other tools: i. Atherton’s Software Backplane. ii. 4GLS iii. Interleaf and FrameMaker publishing. 13. Output formats: PostScript...by end 󈨟. 11. Output formats: ASCII, PostScript, Interleaf, HPGL, Troff, nroff, FrameMaker , WordPerfect. 12. User interface: Menu and mouse

  14. A Statistically Based Training Diagnostic Tool for Marine Aviation

    Science.gov (United States)

    2014-06-01

    the behavioral and social sciences in pursuit of an assessment tool to measure the tactical cognitive skills of officers in the combat arms...presence, flow and interaction, media for mood and arousal, media to attract and persuade, media for emotional effects, media to attract attention, and...expletive] better know how to read and execute checklist items, or they shouldn’t have made it out of the FRS. I could rant , but I won’t. Suffice it

  15. Simulator as a tool of training to modern equipment management

    Directory of Open Access Journals (Sweden)

    Ahmedyanova Gulnara

    2017-01-01

    Full Text Available In the work, the learning process with the use of a simulator was studied. In this case, both the design and algorithmic content of the simulator, as well as the trainee, must pass their part of the path, only in this case the result of learning is maximized. Theoretically, it is shown that the effectiveness of simulator training is primarily a function of the cognitive-operational and professional-personal aspects of the trainee's competence. The experiment confirmed that, despite the differences above the indicated qualities, the result can be estimated as the sum of their estimates.

  16. Early Antenatal Prediction of Gestational Diabetes in Obese Women: Development of Prediction Tools for Targeted Intervention.

    Directory of Open Access Journals (Sweden)

    Sara L White

    Full Text Available All obese women are categorised as being of equally high risk of gestational diabetes (GDM whereas the majority do not develop the disorder. Lifestyle and pharmacological interventions in unselected obese pregnant women have been unsuccessful in preventing GDM. Our aim was to develop a prediction tool for early identification of obese women at high risk of GDM to facilitate targeted interventions in those most likely to benefit. Clinical and anthropometric data and non-fasting blood samples were obtained at 15+0-18+6 weeks' gestation in 1303 obese pregnant women from UPBEAT, a randomised controlled trial of a behavioural intervention. Twenty one candidate biomarkers associated with insulin resistance, and a targeted nuclear magnetic resonance (NMR metabolome were measured. Prediction models were constructed using stepwise logistic regression. Twenty six percent of women (n = 337 developed GDM (International Association of Diabetes and Pregnancy Study Groups criteria. A model based on clinical and anthropometric variables (age, previous GDM, family history of type 2 diabetes, systolic blood pressure, sum of skinfold thicknesses, waist:height and neck:thigh ratios provided an area under the curve of 0.71 (95%CI 0.68-0.74. This increased to 0.77 (95%CI 0.73-0.80 with addition of candidate biomarkers (random glucose, haemoglobin A1c (HbA1c, fructosamine, adiponectin, sex hormone binding globulin, triglycerides, but was not improved by addition of NMR metabolites (0.77; 95%CI 0.74-0.81. Clinically translatable models for GDM prediction including readily measurable variables e.g. mid-arm circumference, age, systolic blood pressure, HbA1c and adiponectin are described. Using a ≥35% risk threshold, all models identified a group of high risk obese women of whom approximately 50% (positive predictive value later developed GDM, with a negative predictive value of 80%. Tools for early pregnancy identification of obese women at risk of GDM are described

  17. Augmented reality assisted surgery: a urologic training tool.

    Science.gov (United States)

    Dickey, Ryan M; Srikishen, Neel; Lipshultz, Larry I; Spiess, Philippe E; Carrion, Rafael E; Hakky, Tariq S

    2016-01-01

    Augmented reality is widely used in aeronautics and is a developing concept within surgery. In this pilot study, we developed an application for use on Google Glass ® optical head-mounted display to train urology residents in how to place an inflatable penile prosthesis. We use the phrase Augmented Reality Assisted Surgery to describe this novel application of augmented reality in the setting of surgery. The application demonstrates the steps of the surgical procedure of inflatable penile prosthesis placement. It also contains software that allows for detection of interest points using a camera feed from the optical head-mounted display to enable faculty to interact with residents during placement of the penile prosthesis. Urology trainees and faculty who volunteered to take part in the study were given time to experience the technology in the operative or perioperative setting and asked to complete a feedback survey. From 30 total participants using a 10-point scale, educational usefulness was rated 8.6, ease of navigation was rated 7.6, likelihood to use was rated 7.4, and distraction in operating room was rated 4.9. When stratified between trainees and faculty, trainees found the technology more educationally useful, and less distracting. Overall, 81% of the participants want this technology in their residency program, and 93% see this technology in the operating room in the future. Further development of this technology is warranted before full release, and further studies are necessary to better characterize the effectiveness of Augmented Reality Assisted Surgery in urologic surgical training.

  18. Augmented reality assisted surgery: a urologic training tool

    Science.gov (United States)

    Dickey, Ryan M; Srikishen, Neel; Lipshultz, Larry I; Spiess, Philippe E; Carrion, Rafael E; Hakky, Tariq S

    2016-01-01

    Augmented reality is widely used in aeronautics and is a developing concept within surgery. In this pilot study, we developed an application for use on Google Glass® optical head-mounted display to train urology residents in how to place an inflatable penile prosthesis. We use the phrase Augmented Reality Assisted Surgery to describe this novel application of augmented reality in the setting of surgery. The application demonstrates the steps of the surgical procedure of inflatable penile prosthesis placement. It also contains software that allows for detection of interest points using a camera feed from the optical head-mounted display to enable faculty to interact with residents during placement of the penile prosthesis. Urology trainees and faculty who volunteered to take part in the study were given time to experience the technology in the operative or perioperative setting and asked to complete a feedback survey. From 30 total participants using a 10-point scale, educational usefulness was rated 8.6, ease of navigation was rated 7.6, likelihood to use was rated 7.4, and distraction in operating room was rated 4.9. When stratified between trainees and faculty, trainees found the technology more educationally useful, and less distracting. Overall, 81% of the participants want this technology in their residency program, and 93% see this technology in the operating room in the future. Further development of this technology is warranted before full release, and further studies are necessary to better characterize the effectiveness of Augmented Reality Assisted Surgery in urologic surgical training. PMID:26620455

  19. Augmented reality assisted surgery: a urologic training tool

    Directory of Open Access Journals (Sweden)

    Ryan M Dickey

    2016-01-01

    Full Text Available Augmented reality is widely used in aeronautics and is a developing concept within surgery. In this pilot study, we developed an application for use on Google Glass ® optical head-mounted display to train urology residents in how to place an inflatable penile prosthesis. We use the phrase Augmented Reality Assisted Surgery to describe this novel application of augmented reality in the setting of surgery. The application demonstrates the steps of the surgical procedure of inflatable penile prosthesis placement. It also contains software that allows for detection of interest points using a camera feed from the optical head-mounted display to enable faculty to interact with residents during placement of the penile prosthesis. Urology trainees and faculty who volunteered to take part in the study were given time to experience the technology in the operative or perioperative setting and asked to complete a feedback survey. From 30 total participants using a 10-point scale, educational usefulness was rated 8.6, ease of navigation was rated 7.6, likelihood to use was rated 7.4, and distraction in operating room was rated 4.9. When stratified between trainees and faculty, trainees found the technology more educationally useful, and less distracting. Overall, 81% of the participants want this technology in their residency program, and 93% see this technology in the operating room in the future. Further development of this technology is warranted before full release, and further studies are necessary to better characterize the effectiveness of Augmented Reality Assisted Surgery in urologic surgical training.

  20. Predicting Great Lakes fish yields: tools and constraints

    Science.gov (United States)

    Lewis, C.A.; Schupp, D.H.; Taylor, W.W.; Collins, J.J.; Hatch, Richard W.

    1987-01-01

    Prediction of yield is a critical component of fisheries management. The development of sound yield prediction methodology and the application of the results of yield prediction are central to the evolution of strategies to achieve stated goals for Great Lakes fisheries and to the measurement of progress toward those goals. Despite general availability of species yield models, yield prediction for many Great Lakes fisheries has been poor due to the instability of the fish communities and the inadequacy of available data. A host of biological, institutional, and societal factors constrain both the development of sound predictions and their application to management. Improved predictive capability requires increased stability of Great Lakes fisheries through rehabilitation of well-integrated communities, improvement of data collection, data standardization and information-sharing mechanisms, and further development of the methodology for yield prediction. Most important is the creation of a better-informed public that will in turn establish the political will to do what is required.

  1. Methodology to develop a training program as a tool for energy management

    Directory of Open Access Journals (Sweden)

    Mónica Rosario Berenguer-Ungaro

    2017-12-01

    Full Text Available The paperaims to present the methodology to develop a training program improve labor skills that enhance the efficient use of energy resources, which aims to make training a timely and meet the training needs as they arise and that the protagonist of it is he who receives training. It is based on the training-action and action research method and model for evaluating training Krikpatrick, it evaluates four levels, reaction, learning, behavior and results. The methodology is structured in three stages: 1 diagnosis of knowledge, 2 intervention based on the results and 3 evaluation and feedback for continuous improvement. Each stage has identified the objectives and implementation tools. Evaluation is transverse to the entire program and it is through it that decisions for feedback loops are taken.

  2. Identification of New Tools to Predict Surgical Performance of Novices using a Plastic Surgery Simulator.

    Science.gov (United States)

    Kazan, Roy; Viezel-Mathieu, Alex; Cyr, Shantale; Hemmerling, Thomas M; Lin, Samuel J; Gilardino, Mirko S

    2018-04-09

    To identify new tools capable of predicting surgical performance of novices on an augmentation mammoplasty simulator. The pace of technical skills acquisition varies between residents and may necessitate more time than that allotted by residency training before reaching competence. Identifying applicants with superior innate technical abilities might shorten learning curves and the time to reach competence. The objective of this study is to identify new tools that could predict surgical performance of novices on a mammoplasty simulator. We recruited 14 medical students and recorded their performance in 2 skill-games: Mikado and Perplexus Epic, and in 2 video games: Star War Racer (Sony Playstation 3) and Super Monkey Ball 2 (Nintendo Wii). Then, each participant performed an augmentation mammoplasty procedure on a Mammoplasty Part-task Trainer, which allows the simulation of the essential steps of the procedure. The average age of participants was 25.4 years. Correlation studies showed significant association between Perplexus Epic, Star Wars Racer, Super Monkey Ball scores and the modified OSATS score with r s = 0.8491 (p 41 (p = 0.005), and r s = 0.7309 (p < 0.003), but not with the Mikado score r s = -0.0255 (p = 0.9). Linear regressions were strongest for Perplexus Epic and Super Monkey Ball scores with coefficients of determination of 0.59 and 0.55, respectively. A combined score (Perplexus/Super-Monkey-Ball) was computed and showed a significant correlation with the modified OSATS score having an r s = 0.8107 (p < 0.001) and R 2 = 0.75, respectively. This study identified a combination of skill games that correlated to better performance of novices on a surgical simulator. With refinement, such tools could serve to help screen plastic surgery applicants and identify those with higher surgical performance predictors. Copyright © 2018 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.

  3. IPMP 2013 - A comprehensive data analysis tool for predictive microbiology

    Science.gov (United States)

    Predictive microbiology is an area of applied research in food science that uses mathematical models to predict the changes in the population of pathogenic or spoilage microorganisms in foods undergoing complex environmental changes during processing, transportation, distribution, and storage. It f...

  4. An Examination of Cultural Competence Training in US Medical Education Guided by the Tool for Assessing Cultural Competence Training.

    Science.gov (United States)

    Jernigan, Valarie Blue Bird; Hearod, Jordan B; Tran, Kim; Norris, Keith C; Buchwald, Dedra

    2016-01-01

    In the United States, medical students must demonstrate a standard level of "cultural competence," upon graduation. Cultural competence is most often defined as a set of congruent behaviors, attitudes, and policies that come together in a system, organization, or among professionals that enables effective work in cross-cultural situations. The Association of American Medical Colleges developed the Tool for Assessing Cultural Competence Training (TACCT) to assist schools in developing and evaluating cultural competence curricula to meet these requirements. This review uses the TACCT as a guideline to describe and assess pedagogical approaches to cultural competence training in US medical education and identify content gaps and opportunities for curriculum improvement. A total of 18 programs are assessed. Findings support previous research that cultural competence training can improve the knowledge, attitudes, and skills of medical trainees. However, wide variation in the conceptualization, implementation, and evaluation of cultural competence training programs exists, leading to differences in training quality and outcomes. More research is needed to establish optimal approaches to implementing and evaluating cultural competence training that incorporate cultural humility, the social determinants of health, and broader structural competency within the medical system.

  5. An Examination of Cultural Competence Training in US Medical Education Guided by the Tool for Assessing Cultural Competence Training

    Science.gov (United States)

    Jernigan, Valarie Blue Bird; Hearod, Jordan B.; Tran, Kim; Norris, Keith C.; Buchwald, Dedra

    2015-01-01

    In the United States, medical students must demonstrate a standard level of “cultural competence,” upon graduation. Cultural competence is most often defined as a set of congruent behaviors, attitudes, and policies that come together in a system, organization, or among professionals that enables effective work in cross-cultural situations. The Association of American Medical Colleges developed the Tool for Assessing Cultural Competence Training (TACCT) to assist schools in developing and evaluating cultural competence curricula to meet these requirements. This review uses the TACCT as a guideline to describe and assess pedagogical approaches to cultural competence training in US medical education and identify content gaps and opportunities for curriculum improvement. A total of 18 programs are assessed. Findings support previous research that cultural competence training can improve the knowledge, attitudes, and skills of medical trainees. However, wide variation in the conceptualization, implementation, and evaluation of cultural competence training programs exists, leading to differences in training quality and outcomes. More research is needed to establish optimal approaches to implementing and evaluating cultural competence training that incorporate cultural humility, the social determinants of health, and broader structural competency within the medical system. PMID:27818848

  6. Prediction of the maximum absorption wavelength of azobenzene dyes by QSPR tools

    Science.gov (United States)

    Xu, Xuan; Luan, Feng; Liu, Huitao; Cheng, Jianbo; Zhang, Xiaoyun

    2011-12-01

    The maximum absorption wavelength ( λmax) of a large data set of 191 azobenzene dyes was predicted by quantitative structure-property relationship (QSPR) tools. The λmax was correlated with the 4 molecular descriptors calculated from the structure of the dyes alone. The multiple linear regression method (MLR) and the non-linear radial basis function neural network (RBFNN) method were applied to develop the models. The statistical parameters provided by the MLR model were R2 = 0.893, Radj2=0.893, qLOO2=0.884, F = 1214.871, RMS = 11.6430 for the training set; and R2 = 0.849, Radj2=0.845, qext2=0.846, F = 207.812, RMS = 14.0919 for the external test set. The RBFNN model gave even improved statistical results: R2 = 0.920, Radj2=0.919, qLOO2=0.898, F = 1664.074, RMS = 9.9215 for the training set, and R2 = 0.895, Radj2=0.892, qext2=0.895, F = 314.256, RMS = 11.6427 for the external test set. This theoretical method provides a simple, precise and an alternative method to obtain λmax of azobenzene dyes.

  7. The Efficacy of Violence Prediction: A Meta-Analytic Comparison of Nine Risk Assessment Tools

    Science.gov (United States)

    Yang, Min; Wong, Stephen C. P.; Coid, Jeremy

    2010-01-01

    Actuarial risk assessment tools are used extensively to predict future violence, but previous studies comparing their predictive accuracies have produced inconsistent findings as a result of various methodological issues. We conducted meta-analyses of the effect sizes of 9 commonly used risk assessment tools and their subscales to compare their…

  8. Development of Innovative Tools and Models for Vocational Education and Training in Central and Western Romania

    Directory of Open Access Journals (Sweden)

    Liviu Moldovan

    2009-12-01

    Full Text Available This paper presents an initiative developed by two partner universities from Romania and Norway entitled „Innovative Tools and models for Vocational Education and Training in Central and western Romania” (MoVE-IT financed by SEE mechanism [1]. It has the priority to develop human resource through promotion of education and training, by means of distance learning. The objective, legal issues, outcome and results and envisaged impact of the project are presented.

  9. [The specialty program as a training tool: an individual training plan for each resident].

    Science.gov (United States)

    Rodríguez González, R; Capilla Cabezuelo, E

    2010-01-01

    The official training program for the specialty "Diagnostic Imaging" establishes minimum learning objectives that must be fulfilled. Each accredited teaching unit is responsible for designing and carrying out a curriculum to ensure that these objectives are met, and this approach permits a degree of flexibility. Various aspects must be considered in the individual training plans for each resident: the rotation scheme according to the way the department is organized, plans for recovering missed material or reinforcing weak points, optional rotations, increasing degrees of responsibility as skills are acquired during training, and accommodating special needs of handicapped persons. Nevertheless, the individual plan must be fitted to the established curriculum and guarantee that the content of the official program is covered and that the objectives stipulated therein are met. Furthermore, the methods of teaching must be adapted to the individual characteristics of the residents, and this is the most important aspect of the individualization of training. To this end, it is fundamental for residents to take on an active role in their training, guided by their tutor and with the participation of all the radiologists in the department including the other residents, all of whom should act as teachers. Copyright © 2010 SERAM. Published by Elsevier Espana. All rights reserved.

  10. Comparison of four modeling tools for the prediction of potential distribution for non-indigenous weeds in the United States

    Science.gov (United States)

    Magarey, Roger; Newton, Leslie; Hong, Seung C.; Takeuchi, Yu; Christie, Dave; Jarnevich, Catherine S.; Kohl, Lisa; Damus, Martin; Higgins, Steven I.; Miller, Leah; Castro, Karen; West, Amanda; Hastings, John; Cook, Gericke; Kartesz, John; Koop, Anthony

    2018-01-01

    This study compares four models for predicting the potential distribution of non-indigenous weed species in the conterminous U.S. The comparison focused on evaluating modeling tools and protocols as currently used for weed risk assessment or for predicting the potential distribution of invasive weeds. We used six weed species (three highly invasive and three less invasive non-indigenous species) that have been established in the U.S. for more than 75 years. The experiment involved providing non-U. S. location data to users familiar with one of the four evaluated techniques, who then developed predictive models that were applied to the United States without knowing the identity of the species or its U.S. distribution. We compared a simple GIS climate matching technique known as Proto3, a simple climate matching tool CLIMEX Match Climates, the correlative model MaxEnt, and a process model known as the Thornley Transport Resistance (TTR) model. Two experienced users ran each modeling tool except TTR, which had one user. Models were trained with global species distribution data excluding any U.S. data, and then were evaluated using the current known U.S. distribution. The influence of weed species identity and modeling tool on prevalence and sensitivity effects was compared using a generalized linear mixed model. Each modeling tool itself had a low statistical significance, while weed species alone accounted for 69.1 and 48.5% of the variance for prevalence and sensitivity, respectively. These results suggest that simple modeling tools might perform as well as complex ones in the case of predicting potential distribution for a weed not yet present in the United States. Considerations of model accuracy should also be balanced with those of reproducibility and ease of use. More important than the choice of modeling tool is the construction of robust protocols and testing both new and experienced users under blind test conditions that approximate operational conditions.

  11. A survey of diagnostic ultrasound within the physiotherapy profession for the design of future training tools

    International Nuclear Information System (INIS)

    McKiernan, Sharmaine; Chiarelli, Pauline; Warren-Forward, Helen

    2011-01-01

    The expansion of diagnostic ultrasound outside of the traditional radiology profession into the physiotherapy profession is occurring. The purpose of this study was to determine if physiotherapists are purchasing diagnostic ultrasound machines, receiving training in the modality and what imaging procedures they are performing. For the design of future training tools, also investigated were the methods of training that physiotherapists might find most beneficial and what content they deem necessary to be covered during such training for the use of diagnostic ultrasound for their profession. An e-mail invitation was sent to physiotherapists throughout Australian who were registered on two databases, asking them to complete a web based survey. The survey was comprised of 18 questions including open and closed items. The data was then categorised into themes in accordance with the purpose of the study. Of the respondents, 39% did not own a diagnostic ultrasound machine, 33% had access to a machine that was owned by their employer and 18% actually owned a machine themselves. Training in diagnostic ultrasound had been received by 61% of the respondents however for 67% of those who had been trained, this training had only lasted for several hours, not days or weeks. For future training in ultrasound the majority of respondents would prefer either a workshop or DVD to cover imaging anatomy, the use of machine controls and scanning the pelvic floor, abdominal muscles and shoulder. From this survey it can be concluded that physiotherapists have an interest in or are using diagnostic ultrasound in their practice. While some form of training is being provided, further training is considered necessary and wanted by the physiotherapists so training tools need to be developed.

  12. A survey of diagnostic ultrasound within the physiotherapy profession for the design of future training tools

    Energy Technology Data Exchange (ETDEWEB)

    McKiernan, Sharmaine, E-mail: sharmaine.mckiernan@newcastle.edu.a [School of Health Sciences, University of Newcastle, Callaghan, NSW (Australia); Chiarelli, Pauline; Warren-Forward, Helen [School of Health Sciences, University of Newcastle, Callaghan, NSW (Australia)

    2011-05-15

    The expansion of diagnostic ultrasound outside of the traditional radiology profession into the physiotherapy profession is occurring. The purpose of this study was to determine if physiotherapists are purchasing diagnostic ultrasound machines, receiving training in the modality and what imaging procedures they are performing. For the design of future training tools, also investigated were the methods of training that physiotherapists might find most beneficial and what content they deem necessary to be covered during such training for the use of diagnostic ultrasound for their profession. An e-mail invitation was sent to physiotherapists throughout Australian who were registered on two databases, asking them to complete a web based survey. The survey was comprised of 18 questions including open and closed items. The data was then categorised into themes in accordance with the purpose of the study. Of the respondents, 39% did not own a diagnostic ultrasound machine, 33% had access to a machine that was owned by their employer and 18% actually owned a machine themselves. Training in diagnostic ultrasound had been received by 61% of the respondents however for 67% of those who had been trained, this training had only lasted for several hours, not days or weeks. For future training in ultrasound the majority of respondents would prefer either a workshop or DVD to cover imaging anatomy, the use of machine controls and scanning the pelvic floor, abdominal muscles and shoulder. From this survey it can be concluded that physiotherapists have an interest in or are using diagnostic ultrasound in their practice. While some form of training is being provided, further training is considered necessary and wanted by the physiotherapists so training tools need to be developed.

  13. The Predictive Accuracy of PREDICT : A Personalized Decision-Making Tool for Southeast Asian Women With Breast Cancer

    NARCIS (Netherlands)

    Wong, Hoong-Seam; Subramaniam, Shridevi; Alias, Zarifah; Taib, Nur Aishah; Ho, Gwo-Fuang; Ng, Char-Hong; Yip, Cheng-Har; Verkooijen, Helena M.; Hartman, Mikael; Bhoo Pathy, N

    Web-based prognostication tools may provide a simple and economically feasible option to aid prognostication and selection of chemotherapy in early breast cancers. We validated PREDICT, a free online breast cancer prognostication and treatment benefit tool, in a resource-limited setting. All 1480

  14. Kenya develops tool to predict malaria | IDRC - International ...

    International Development Research Centre (IDRC) Digital Library (Canada)

    2010-10-13

    Oct 13, 2010 ... In collaboration with scientists from the Kenya Meteorological Department and the International Centre ... a scientific model that uses weather predictions, information about the reproductive mechanisms of ... Related articles ...

  15. GameTeen: new tools for evaluating and training emotional regulation strategies

    OpenAIRE

    Rodriguez Ortega, Alejandro; Rey, Beatriz; Alcañiz Raya, Mariano Luis; BAÑOS, R.; Guixeres Provinciale, Jaime; Wrzesien, Maja; Gómez Martínez, Mario; Pérez Lopez, David Clemente; Rasal, Paloma; Parra Vargas, Elena

    2012-01-01

    The aim of this paper is to describe GameTeen, a novel instrument for the assessment and training of Emotional Regulation (ER) strategies in adolescent population. These new tools are based on the use of 3D serious games that can be played under different settings. The evolution of ER strategies will be monitored in two ways depending on the setting where the tool is presented. Firstly, in the laboratory, physiological signals and facial expressions of participants will be recorded. Secondly,...

  16. Biochemical assessment of physical training: a tool to sports dietitians-nutritionists

    Directory of Open Access Journals (Sweden)

    Aritz Urdampilleta

    2013-06-01

    Full Text Available The high demand in athletes creates the need to control the process of adaptation to training. The aim of this review is to analyze the biochemical parameters of utility for biological control of the athlete, and provide tools to sports dietitian-nutritionist in the follow-up of the training.Glucose and lipid profile parameters are widely used but insufficient to control training. The lactic acid level in the plasma is the most common tool to assess training load, where values higher than 4 mmol/l, suggest an intensive training. Other enzymes in high concentrations such as creatine kinase (CK, lactate dehydrogenase (LDH and two transaminases: glutamic oxaloacetic transaminase (GOT or aspartate transaminase (AST or aspartate aminotransferase (AAT and glutamic pyruvic transaminase (GPT or alanine transaminase or aminotransferase (ALT suggest that the training load was high producing microscopic tearing of the muscle fibers. Determination of other substrates such as ammonia, glutamine, or testosterone/cortisol ratio, used to detect a possible overtraining syndrome. Likewise the latest research suggest that high cortisol levels decrease the immune system.Moreover, an increase of urea, alanine or ketone bodies are related to muscle glycogen stores depleted. Therefore, the information provided by these parameters is useful for the sports dietitian-nutritionist for dietary and nutritional interventions to achieve more effective in function of the training goals.

  17. Casual Video Games as Training Tools for Attentional Processes in Everyday Life.

    Science.gov (United States)

    Stroud, Michael J; Whitbourne, Susan Krauss

    2015-11-01

    Three experiments examined the attentional components of the popular match-3 casual video game, Bejeweled Blitz (BJB). Attentionally demanding, BJB is highly popular among adults, particularly those in middle and later adulthood. In experiment 1, 54 older adults (Mage = 70.57) and 33 younger adults (Mage = 19.82) played 20 rounds of BJB, and completed online tasks measuring reaction time, simple visual search, and conjunction visual search. Prior experience significantly predicted BJB scores for younger adults, but for older adults, both prior experience and simple visual search task scores predicted BJB performance. Experiment 2 tested whether BJB practice alone would result in a carryover benefit to a visual search task in a sample of 58 young adults (Mage = 19.57) who completed 0, 10, or 30 rounds of BJB followed by a BJB-like visual search task with targets present or absent. Reaction times were significantly faster for participants who completed 30 but not 10 rounds of BJB compared with the search task only. This benefit was evident when targets were both present and absent, suggesting that playing BJB improves not only target detection, but also the ability to quit search effectively. Experiment 3 tested whether the attentional benefit in experiment 2 would apply to non-BJB stimuli. The results revealed a similar numerical but not significant trend. Taken together, the findings suggest there are benefits of casual video game playing to attention and relevant everyday skills, and that these games may have potential value as training tools.

  18. Analytical Model of Underground Train Induced Vibrations on Nearby Building Structures in Cameroon: Assessment and Prediction

    Directory of Open Access Journals (Sweden)

    Lezin Seba MINSILI

    2013-11-01

    Full Text Available The purpose of this research paper was to assess and predict the effect of vibrations induced by an underground railway on nearby-existing buildings prior to the construction of projected new railway lines of the National Railway Master Plan of Cameroon and after upgrading of the railway conceded to CAMRAIL linking the two most densely populated cities of Cameroon: Douala and Yaoundé. With the source-transmitter-receiver mathematical model as the train-soil-structure interaction model, taking into account sub-model parameters such as type of the train-railway system, typical geotechnical conditions of the ground and the sensitivity of the nearby buildings, the analysis is carried out over the entire system using the dynamic finite element method in the time domain. This subdivision of the model is a powerful tool that allows to consider different alternatives of sub-models with different characteristics, and thus to determine any critical excessive vibration impact. Based on semi-empirical analytical results obtained from presented models, the present work assesses and predicts characteristics of traffic-induced vibrations as a function of time duration, intensity and vehicle speed, as well as their influence on buildings at different levels.

  19. Training using a new multidirectional reach tool improves balance in individuals with stroke.

    Science.gov (United States)

    Khumsapsiri, Numpung; Siriphorn, Akkradate; Pooranawatthanakul, Kanokporn; Oungphalachai, Tanyarut

    2018-04-01

    Previous studies suggested that limits of stability (LOS) training with visual feedback using commercial equipment could be used to improve balance ability in individuals with stroke. However, this system is expensive. In this study, we created a new tool from inexpensive elements based on LOS training using visual feedback. The aim of this study was to investigate the effect of training using a new multidirectional reach tool on balance in individuals with stroke. A single-blind randomized control trial was conducted. Individuals with stroke (n = 16; age range 38-72 years) were recruited. Participants in the experimental group were trained with the multidirectional reach training for 30 min and conventional physical therapy for 30 min per day, 3 days a week for 4 weeks. Participants in the control group received conventional physical therapy for 30 min per day, 3 days a week for 4 weeks. The outcomes were LOS, weight-bearing squat, and Fullerton Advanced Balance scale. All of the outcome measures were measured at pretraining, post-training, and 1 month follow-up. At post-training and 1-month follow-up, the participants in the experimental group had an improvement of dynamic balance than the control group. Furthermore, the activity assessment by Fullerton Advanced Balance scale was more improved at 1 month follow-up in the experimental group than control group. The results of this study provide evidence that training using a new multidirectional reach tool is effective for improving balance in individuals with stroke. Copyright © 2018 John Wiley & Sons, Ltd.

  20. Predictive Monte Carlo tools for LHC physics (1/3)

    CERN Multimedia

    CERN. Geneva

    2012-01-01

    Simulations of events taking place at the LHC play key role in all experimental analyses. Starting from the basics concepts of QCD, we first review how accurate predictions can be obtained via fixed-order calculations at higher orders. Parton showers and event generation are then introduced as a means to achieve fully exclusive predictions. Finally the recent merging and matching techniques between fixed-order and fully exclusive simulations are presented, as well as their implementations via the MLM/CKKW and MC@NLO/POWHEG methods.

  1. Predictive Monte Carlo tools for LHC physics (3/3)

    CERN Multimedia

    CERN. Geneva

    2012-01-01

    Simulations of events taking place at the LHC play key role in all experimental analyses. Starting from the basics concepts of QCD, we first review how accurate predictions can be obtained via fixed-order calculations at higher orders. Parton showers and event generation are then introduced as a means to achieve fully exclusive predictions. Finally the recent merging and matching techniques between fixed-order and fully exclusive simulations are presented, as well as their implementations via the MLM/CKKW and MC@NLO/POWHEG methods.

  2. Predictive Monte Carlo tools for LHC physics (2/3)

    CERN Multimedia

    CERN. Geneva

    2012-01-01

    Simulations of events taking place at the LHC play key role in all experimental analyses. Starting from the basics concepts of QCD, we first review how accurate predictions can be obtained via fixed-order calculations at higher orders. Parton showers and event generation are then introduced as a means to achieve fully exclusive predictions. Finally the recent merging and matching techniques between fixed-order and fully exclusive simulations are presented, as well as their implementations via the MLM/CKKW and MC@NLO/POWHEG methods.

  3. Developing a computational tool for predicting physical parameters of a typical VVER-1000 core based on artificial neural network

    International Nuclear Information System (INIS)

    Mirvakili, S.M.; Faghihi, F.; Khalafi, H.

    2012-01-01

    Highlights: ► Thermal–hydraulics parameters of a VVER-1000 core based on neural network (ANN), are carried out. ► Required data for ANN training are found based on modified COBRA-EN code and then linked each other using MATLAB software. ► Based on ANN method, average and maximum temperature of fuel and clad as well as MDNBR of each FA are predicted. -- Abstract: The main goal of the present article is to design a computational tool to predict physical parameters of the VVER-1000 nuclear reactor core based on artificial neural network (ANN), taking into account a detailed physical model of the fuel rods and coolant channels in a fuel assembly. Predictions of thermal characteristics of fuel, clad and coolant are performed using cascade feed forward ANN based on linear fission power distribution and power peaking factors of FAs and hot channels factors (which are found based on our previous neutronic calculations). A software package has been developed to prepare the required data for ANN training which applies a modified COBRA-EN code for sub-channel analysis and links the codes using the MATLAB software. Based on the current estimation system, five main core TH parameters are predicted, which include the average and maximum temperatures of fuel and clad as well as the minimum departure from nucleate boiling ratio (MDNBR) for each FA. To get the best conditions for the considered ANNs training, a comprehensive sensitivity study has been performed to examine the effects of variation of hidden neurons, hidden layers, transfer functions, and the learning algorithms on the training and simulation results. Performance evaluation results show that the developed ANN can be trained to estimate the core TH parameters of a typical VVER-1000 reactor quickly without loss of accuracy.

  4. Toward a powerful problem-based training tool for harnessing lessons learned

    International Nuclear Information System (INIS)

    May, W. E.; Richards, R. E.

    2006-01-01

    One of the purposes of this paper is to describe a training method and supporting technologies (tool) to increase personnel awareness of error precursors. This model-centered method may be an effective 'part task training' to precede more expensive fall-blown multimedia scenarios (behavioral simulations). The training is designed to efficiently increase positive transfer from lessons learned case studies. The tool enables developers to take actual instances and inexpensively frame them within an interactive computer learning environment. The learning is engaging and helps model the kind of causal thinking needed to prevent future occurrences. This method and tool could help workers 'see' the problems and feel the need to take action when they are in real settings. Another purpose of this paper is to present the results of research into the process of designing and developing this training software. The benefits for attendees are insights that may enable more rapid proto-typing of software for training the workforce. The authors will present the models, methodologies, and patterns in the participants' design activities. Results show that participants used a cyclical, spiral process that revisited design topics until they were clarified. (authors)

  5. Development of a Portable Training Tool for Simulating Visceral Angiographic Procedures for Beginners

    International Nuclear Information System (INIS)

    Yamagami, Takuji; Osuga, Keigo; Yoshimatsu, Rika; Matsumoto, Tomohiro; Miura, Hiroshi; Terayama, Koshi; Anai, Hiroshi; Takahashi, Masahide; Hasebe, Terumitsu; Nishimura, Tsunehiko

    2009-01-01

    The purpose of this study was to evaluate the usefulness of a tool that we developed to simulate performance of visceral angiography to train beginners in the field of splanchnic angiography. Seven residents and two fellows who were rotating within the Division of Interventional Radiology at our institution between June and August 2008 participated in the evaluation of this tool. They had no experience in performing visceral angiography as an operator. Time for selection of arterial branches arising from the celiac axis on the model was measured before and after training. After such training, the participants performed actual visceral angiography as an operator with instructors beside them. Success of the trainees in selecting visceral arterial branches was evaluated in these real-life cases. In the first test using the model, seven of nine trainees (77.8%) succeeded in selecting all required arteries, while the remaining two failed to select all required arteries. After training using the model, all trainees succeeded in selecting all required arteries just before the actual angiographic study. In the actual angiography, the catheter was successfully inserted from the femoral artery and advanced to the superior mesenteric, celiac, splenic, common hepatic, gastroduodenal, and right and left hepatic arteries by all trainees with only two exceptions. In conclusion, this tool is helpful for training beginners in visceral angiographic procedures.

  6. A comparison of text and technology based training tools to improve cognitive skills in older adults.

    Science.gov (United States)

    Power, Kevin; Kirwan, Grainne; Palmer, Marion

    2011-01-01

    Research has indicated that use of cognitive skills training tools can produce positive benefits with older adults. However, little research has compared the efficacy of technology-based interventions and more traditional, text-based interventions which are also available. This study aimed to investigate cognitive skills improvements experienced by 40 older adults using cognitive skills training tools. A Solomon 4 group design was employed to determine which intervention demonstrated the greatest improvement. Participants were asked to use the interventions for 5-10 minutes per day, over a period of 60 days. Pre and post-tests consisted of measures of numerical ability, self-reported memory and intelligence. Following training, older adults indicated significant improvements on numerical ability and intelligence regardless of intervention type. No improvement in selfreported memory was observed. This research provides a critical appraisal of brain training tools and can help point the way for future improvements in the area. Brain training improvements could lead to improved quality of life, and perhaps, have financial and independent living ramifications for older adults.

  7. A study of unstable slopes in permafrost areas : Alaskan case studies used as a training tool.

    Science.gov (United States)

    2011-12-01

    This report is the companion to the PowerPoint presentation for the project A Study of Unstable Slopes in Permafrost: Alaskan Case Studies Used as a Training Tool. The objectives of this study are 1) to provide a comprehensive review of literat...

  8. TNO-ADVANCE: a modular power train simulation and design tool

    NARCIS (Netherlands)

    Venne, J.W.C. van de; Hendriksen, P.; Smokers, R.T.M.; Verkiel, M.

    1998-01-01

    To support its activities in the field of conventional and hybrid vehicles, TNO has developed ADVANCE, a modular simulation tool for the design and evaluation of advanced power trains. In this paper the various features and the potential of ADVANCE are described and illustrated by means of two case

  9. The development of a myoelectric training tool for above-elbow amputees.

    Science.gov (United States)

    Dawson, Michael R; Fahimi, Farbod; Carey, Jason P

    2012-01-01

    The objective of above-elbow myoelectric prostheses is to reestablish the functionality of missing limbs and increase the quality of life of amputees. By using electromyography (EMG) electrodes attached to the surface of the skin, amputees are able to control motors in myoelectric prostheses by voluntarily contracting the muscles of their residual limb. This work describes the development of an inexpensive myoelectric training tool (MTT) designed to help upper limb amputees learn how to use myoelectric technology in advance of receiving their actual myoelectric prosthesis. The training tool consists of a physical and simulated robotic arm, signal acquisition hardware, controller software, and a graphical user interface. The MTT improves over earlier training systems by allowing a targeted muscle reinnervation (TMR) patient to control up to two degrees of freedom simultaneously. The training tool has also been designed to function as a research prototype for novel myoelectric controllers. A preliminary experiment was performed in order to evaluate the effectiveness of the MTT as a learning tool and to identify any issues with the system. Five able-bodied participants performed a motor-learning task using the EMG controlled robotic arm with the goal of moving five balls from one box to another as quickly as possible. The results indicate that the subjects improved their skill in myoelectric control over the course of the trials. A usability survey was administered to the subjects after their trials. Results from the survey showed that the shoulder degree of freedom was the most difficult to control.

  10. Training Theory of Mind and Executive Control: A Tool for Improving School Achievement?

    Science.gov (United States)

    Kloo, Daniela; Perner, Josef

    2008-01-01

    In the preschool years, there are marked improvements in theory of mind (ToM) and executive functions. And, children's competence in these two core cognitive domains is associated with their academic achievement. Therefore, training ToM and executive control could be a valuable tool for improving children's success in school. This article reviews…

  11. Development and Assessment of a New 3D Neuroanatomy Teaching Tool for MRI Training

    Science.gov (United States)

    Drapkin, Zachary A.; Lindgren, Kristen A.; Lopez, Michael J.; Stabio, Maureen E.

    2015-01-01

    A computerized three-dimensional (3D) neuroanatomy teaching tool was developed for training medical students to identify subcortical structures on a magnetic resonance imaging (MRI) series of the human brain. This program allows the user to transition rapidly between two-dimensional (2D) MRI slices, 3D object composites, and a combined model in…

  12. Development of an Evaluation Tool for Online Food Safety Training Programs

    Science.gov (United States)

    Neal, Jack A., Jr.; Murphy, Cheryl A.; Crandall, Philip G.; O'Bryan, Corliss A.; Keifer, Elizabeth; Ricke, Steven C.

    2011-01-01

    The objective of this study was to provide the person in charge and food safety instructors an assessment tool to help characterize, identify strengths and weaknesses, determine the completeness of the knowledge gained by the employee, and evaluate the level of content presentation and usability of current retail food safety training platforms. An…

  13. Emerging Tools to Estimate and to Predict Exposures to ...

    Science.gov (United States)

    The timely assessment of the human and ecological risk posed by thousands of existing and emerging commercial chemicals is a critical challenge facing EPA in its mission to protect public health and the environment The US EPA has been conducting research to enhance methods used to estimate and forecast exposures for tens of thousands of chemicals. This research is aimed at both assessing risks and supporting life cycle analysis, by developing new models and tools for high throughput exposure screening and prioritization, as well as databases that support these and other tools, especially regarding consumer products. The models and data address usage, and take advantage of quantitative structural activity relationships (QSARs) for both inherent chemical properties and function (why the chemical is a product ingredient). To make them more useful and widely available, the new tools, data and models are designed to be: • Flexible • Intraoperative • Modular (useful to more than one, stand-alone application) • Open (publicly available software) Presented at the Society for Risk Analysis Forum: Risk Governance for Key Enabling Technologies, Venice, Italy, March 1-3, 2017

  14. Enhanced clinical pharmacy service targeting tools: risk-predictive algorithms.

    Science.gov (United States)

    El Hajji, Feras W D; Scullin, Claire; Scott, Michael G; McElnay, James C

    2015-04-01

    This study aimed to determine the value of using a mix of clinical pharmacy data and routine hospital admission spell data in the development of predictive algorithms. Exploration of risk factors in hospitalized patients, together with the targeting strategies devised, will enable the prioritization of clinical pharmacy services to optimize patient outcomes. Predictive algorithms were developed using a number of detailed steps using a 75% sample of integrated medicines management (IMM) patients, and validated using the remaining 25%. IMM patients receive targeted clinical pharmacy input throughout their hospital stay. The algorithms were applied to the validation sample, and predicted risk probability was generated for each patient from the coefficients. Risk threshold for the algorithms were determined by identifying the cut-off points of risk scores at which the algorithm would have the highest discriminative performance. Clinical pharmacy staffing levels were obtained from the pharmacy department staffing database. Numbers of previous emergency admissions and admission medicines together with age-adjusted co-morbidity and diuretic receipt formed a 12-month post-discharge and/or readmission risk algorithm. Age-adjusted co-morbidity proved to be the best index to predict mortality. Increased numbers of clinical pharmacy staff at ward level was correlated with a reduction in risk-adjusted mortality index (RAMI). Algorithms created were valid in predicting risk of in-hospital and post-discharge mortality and risk of hospital readmission 3, 6 and 12 months post-discharge. The provision of ward-based clinical pharmacy services is a key component to reducing RAMI and enabling the full benefits of pharmacy input to patient care to be realized. © 2014 John Wiley & Sons, Ltd.

  15. Predicting Attrition in a Military Special Program Training Command

    Science.gov (United States)

    2016-05-20

    made by assessing additional psychological factors. Specifically, motivation (s) to enter the training program (e.g., intrinsic versus extrinsic ...this and other training programs. Motivations to enter the training program could be assessed using a measure such as the Work Extrinsic and...MEDICINE GRADUATE PROGRAMS Graduate Education Office (A 1045), 4301 Jones Bridge Road, Bethesda, MD 20814 APPROVAL OF THE DOCTORAL DISSERTATION IN THE

  16. Dairy Tool Box Talks: A Comprehensive Worker Training in Dairy Farming.

    Science.gov (United States)

    Rovai, Maristela; Carroll, Heidi; Foos, Rebecca; Erickson, Tracey; Garcia, Alvaro

    2016-01-01

    Today's dairies are growing rapidly, with increasing dependence on Latino immigrant workers. This requires new educational strategies for improving milk quality and introduction to state-of-the-art dairy farming practices. It also creates knowledge gaps pertaining to the health of animals and workers, mainly due to the lack of time and language barriers. Owners, managers, and herdsmen assign training duties to more experienced employees, which may not promote "best practices" and may perpetuate bad habits. A comprehensive and periodic training program administered by qualified personnel is currently needed and will enhance the sustainability of the dairy industry. Strategic management and employee satisfaction will be achieved through proper training in the employee's language, typically Spanish. The training needs to address not only current industry standards but also social and cultural differences. An innovative training course was developed following the same structure used by the engineering and construction industries, giving farm workers basic understanding of animal care and handling, cow comfort, and personal safety. The "Dairy Tool Box Talks" program was conducted over a 10-week period with nine sessions according to farm's various employee work shifts. Bulk milk bacterial counts and somatic cell counts were used to evaluate milk quality on the three dairy farms participating in the program. "Dairy Tool Box Talks" resulted in a general sense of employee satisfaction, significant learning outcomes, and enthusiasm about the topics covered. We conclude this article by highlighting the importance of educational programs aimed at improving overall cross-cultural training.

  17. The Human Factor: Training and Professional Development as a Policy Tool

    Directory of Open Access Journals (Sweden)

    Lucian CIOLAN

    2014-11-01

    Full Text Available In this paper, we try to make a case for the risky approach of many decision-makers and pol- icy specialists to overuse authority and regula- tion-based tools, while neglecting the ones more focused on human capacity and persuasion. Especially in fields like education, we consider that the human factor should be at the core of any policy mix, and a tool like training and pro- fessional development should gain a more visible and persistent role in policy interventions. Firstly, we try to analyze the distribution of policy tools on the authority-complexity axes. The value we see in the mapping of policy tools is that it can be used for investigating and positioning the activity of a specific governing body or central gover- nance. Thus, a fundamental question remains as to what really influences the choice of policy tools or instruments, as a basis for better understand- ing the rationales behind a specific policy mix. We argue that policy failure could be ex- plained in many cases by the incapacity to ad- dress in a consistent and professional way the human capacities needed for implementation. Thus, training and professional development are, at least, poorly used from the perspective of the potential they have. As an argument, we tried to look at training and professional development in the specific area of teachers in pre-university education in Romania, situating it in the broader context of European policies in lifelong learning and participation of adults in continuing educa- tion and training, but also in the local policy en- vironment. The results of the research led us to the conclusion that educational policies should be among the first in the broader spectrum of public policies valuing and emphasizing learning, through training and professional development of the stakeholders involved in policy change together with adding more value to the Human Factor in educational policies. 

  18. PROFITABILITY RATIO AS A TOOL FOR BANKRUPTCY PREDICTION

    Directory of Open Access Journals (Sweden)

    Daniel BRÎNDESCU – OLARIU

    2016-07-01

    Full Text Available The current study evaluates the potential of the profitability ratio in predicting corporate bankruptcy. The research is focused on Romanian companies, with the targeted event being represented by the manifestation of bankruptcy 2 years after the date of the financial statements of reference. All tests were conducted over 2 paired samples of 1176 Romanian companies. The methodology employed in evaluating the potential of the profitability ratio was based on the Area Under the ROC Curve (0.663 and the general accuracy ensured by the ratio (62.6% out-of-sample accuracy. The results confirm the practical utility of the profitability ratio in the prediction of bankruptcy and thus validate the need for further research focused on developing a methodology of analysis.

  19. SOLVENCY RATIO AS A TOOL FOR BANKRUPTCY PREDICTION

    Directory of Open Access Journals (Sweden)

    Daniel BRÎNDESCU–OLARIU

    2016-08-01

    Full Text Available The current study evaluates the potential of the solvency ratio in predicting corporate bankruptcy. The research is focused on Romania and, in particular, on Timis County. The interest for the solvency ratio was based on the recommendations of the scientific literature, as well as on the availability of information concerning its values to all stakeholders. The event on which the research was focused was represented by the manifestation of bankruptcy 2 years after the date of the financial statements of reference. All tests were performed over 2 paired samples of 1176 companies in total. The methodology employed in evaluating the potential of the solvency ratio was based on the Area Under the ROC Curve (0.646 and the general accuracy ensured by the ratio (64.5% out-of-sample accuracy. The results confirm the practical utility of the solvency ratio in the prediction of bankruptcy.

  20. ACL-RSI and KOOS Measures Predict Normal Knee Function after ACL-SPORTS Training

    OpenAIRE

    White, Kathleen; Zeni, Joseph; Snyder-Mackler, Lynn

    2014-01-01

    Objectives: After anterior cruciate ligament reconstruction (ACLR) athletes commonly report increased fear of re-injury and below normal knee function. Implementing a post-operative training protocol (ACL-SPORTS Training) to improve patient perceived knee function, may improve short term outcomes after surgery. Identifying pre-training measures that predict normal knee function after training may allow us to determine who may respond to the treatment intervention. The purpose of this study wa...

  1. iRaster: a novel information visualization tool to explore spatiotemporal patterns in multiple spike trains.

    Science.gov (United States)

    Somerville, J; Stuart, L; Sernagor, E; Borisyuk, R

    2010-12-15

    Over the last few years, simultaneous recordings of multiple spike trains have become widely used by neuroscientists. Therefore, it is important to develop new tools for analysing multiple spike trains in order to gain new insight into the function of neural systems. This paper describes how techniques from the field of visual analytics can be used to reveal specific patterns of neural activity. An interactive raster plot called iRaster has been developed. This software incorporates a selection of statistical procedures for visualization and flexible manipulations with multiple spike trains. For example, there are several procedures for the re-ordering of spike trains which can be used to unmask activity propagation, spiking synchronization, and many other important features of multiple spike train activity. Additionally, iRaster includes a rate representation of neural activity, a combined representation of rate and spikes, spike train removal and time interval removal. Furthermore, it provides multiple coordinated views, time and spike train zooming windows, a fisheye lens distortion, and dissemination facilities. iRaster is a user friendly, interactive, flexible tool which supports a broad range of visual representations. This tool has been successfully used to analyse both synthetic and experimentally recorded datasets. In this paper, the main features of iRaster are described and its performance and effectiveness are demonstrated using various types of data including experimental multi-electrode array recordings from the ganglion cell layer in mouse retina. iRaster is part of an ongoing research project called VISA (Visualization of Inter-Spike Associations) at the Visualization Lab in the University of Plymouth. The overall aim of the VISA project is to provide neuroscientists with the ability to freely explore and analyse their data. The software is freely available from the Visualization Lab website (see www.plymouth.ac.uk/infovis). Copyright © 2010

  2. Development of Antimicrobial Peptide Prediction Tool for Aquaculture Industries.

    Science.gov (United States)

    Gautam, Aditi; Sharma, Asuda; Jaiswal, Sarika; Fatma, Samar; Arora, Vasu; Iquebal, M A; Nandi, S; Sundaray, J K; Jayasankar, P; Rai, Anil; Kumar, Dinesh

    2016-09-01

    Microbial diseases in fish, plant, animal and human are rising constantly; thus, discovery of their antidote is imperative. The use of antibiotic in aquaculture further compounds the problem by development of resistance and consequent consumer health risk by bio-magnification. Antimicrobial peptides (AMPs) have been highly promising as natural alternative to chemical antibiotics. Though AMPs are molecules of innate immune defense of all advance eukaryotic organisms, fish being heavily dependent on their innate immune defense has been a good source of AMPs with much wider applicability. Machine learning-based prediction method using wet laboratory-validated fish AMP can accelerate the AMP discovery using available fish genomic and proteomic data. Earlier AMP prediction servers are based on multi-phyla/species data, and we report here the world's first AMP prediction server in fishes. It is freely accessible at http://webapp.cabgrid.res.in/fishamp/ . A total of 151 AMPs related to fish collected from various databases and published literature were taken for this study. For model development and prediction, N-terminus residues, C-terminus residues and full sequences were considered. Best models were with kernels polynomial-2, linear and radial basis function with accuracy of 97, 99 and 97 %, respectively. We found that performance of support vector machine-based models is superior to artificial neural network. This in silico approach can drastically reduce the time and cost of AMP discovery. This accelerated discovery of lead AMP molecules having potential wider applications in diverse area like fish and human health as substitute of antibiotics, immunomodulator, antitumor, vaccine adjuvant and inactivator, and also for packaged food can be of much importance for industries.

  3. PROFITABILITY RATIO AS A TOOL FOR BANKRUPTCY PREDICTION

    OpenAIRE

    Daniel BRÎNDESCU – OLARIU

    2016-01-01

    The current study evaluates the potential of the profitability ratio in predicting corporate bankruptcy. The research is focused on Romanian companies, with the targeted event being represented by the manifestation of bankruptcy 2 years after the date of the financial statements of reference. All tests were conducted over 2 paired samples of 1176 Romanian companies. The methodology employed in evaluating the potential of the profitability ratio was based on the Area Under the ROC Curve (0.663...

  4. Prediction of boiling points of organic compounds by QSPR tools.

    Science.gov (United States)

    Dai, Yi-min; Zhu, Zhi-ping; Cao, Zhong; Zhang, Yue-fei; Zeng, Ju-lan; Li, Xun

    2013-07-01

    The novel electro-negativity topological descriptors of YC, WC were derived from molecular structure by equilibrium electro-negativity of atom and relative bond length of molecule. The quantitative structure-property relationships (QSPR) between descriptors of YC, WC as well as path number parameter P3 and the normal boiling points of 80 alkanes, 65 unsaturated hydrocarbons and 70 alcohols were obtained separately. The high-quality prediction models were evidenced by coefficient of determination (R(2)), the standard error (S), average absolute errors (AAE) and predictive parameters (Qext(2),RCV(2),Rm(2)). According to the regression equations, the influences of the length of carbon backbone, the size, the degree of branching of a molecule and the role of functional groups on the normal boiling point were analyzed. Comparison results with reference models demonstrated that novel topological descriptors based on the equilibrium electro-negativity of atom and the relative bond length were useful molecular descriptors for predicting the normal boiling points of organic compounds. Copyright © 2013 Elsevier Inc. All rights reserved.

  5. Web-Enabled Training-Development Tool for Pre-Deployment and Deployed Training

    Science.gov (United States)

    2006-11-01

    ACKNOWLEDGEMENT We gratefully acknowledge the 8upport of the US Army National Training Center Broncos Team, especially Lieutenant Colonel Rock Marcone...apply the ROE to this situation with the perso•mel in the area? El Am I still able to accomplish my original missioUo Model a Thinldng Enemy You got 50... El A d dress ri4)hl:f/-w~.La~ta.com/dbAO plip~aowldn1lthrspstact=previestnep=backgrou-rd US Ary Leder’rainig Assstan FeEdt V~eW FaltsTcrOE Fk~p__

  6. Workplace-based assessments of junior doctors: do scores predict training difficulties?

    Science.gov (United States)

    Mitchell, Colin; Bhat, Sarita; Herbert, Anne; Baker, Paul

    2011-12-01

    Workplace-based assessment (WPBA) is an increasingly important part of postgraduate medical training and its results may be used as evidence of professional competence. This study evaluates the ability of WPBA to distinguish UK Foundation Programme (FP) doctors with training difficulties and its effectiveness as a surrogate marker for deficiencies in professional competence. We conducted a retrospective observational study using anonymised records for 1646 trainees in a single UK postgraduate deanery. Data for WPBAs conducted from August 2005 to April 2009 were extracted from the e-portfolio database. These data included all scores submitted by trainees in FP years 1 and 2 on mini-clinical evaluation exercise (mini-CEX), case-based discussion (CbD), direct observation of procedural skills (DOPS) and mini-peer assessment tool (mini-PAT) assessments. Records of trainees in difficulty, as identified by their educational supervisors, were tagged as index cases. Main outcome measures were odds ratios (ORs) for associations between mean WPBA scores and training difficulties. Further analyses by the reported aetiology of the training difficulty (health-, conduct- or performance-related) were performed. Of the 1646 trainees, 92 had been identified as being in difficulty. Mean CbD and mini-CEX scores were lower for trainees in difficulty and an association was found between identified training difficulties and average scores on the mini-CEX (OR = 0.54; p = 0.034) and CbD (OR = 0.39; p = 0.002). A receiver operator characteristic curve analysis of mean WPBA scores for diagnosing 'in difficulty' status yielded an area under the curve of 0.64, indicating weak predictive value. There was no statistical evidence that mean scores on DOPS and mini-PAT assessments differed between the two groups. Analysis of a large dataset of WPBA scores revealed significant associations between training difficulties and lower mean scores on both the mini-CEX and CbD. Models show that using WPBA

  7. Cardiodynamicsgram: a novel tool for monitoring cardiac function in exercise training.

    Science.gov (United States)

    Wen, Xu; Guo, Bokai; Gong, Yinglan; Xia, Ling; Yu, Jie

    2018-04-27

    This study evaluated the feasibility of cardiodynamicsgram (CDG) for monitoring the cardiac functions of athletes and exercisers. CDG could provide an effective, simple, and economical tool for exercise training. Seventeen middle-distance race athletes aged 14-28 years old were recruited. CDG tests and blood test including creatine kinase (CK), CK-MB isoenzyme, and high-sensitivity troponin I (hsTnI) were performed before a high-intensity prolonged training, as well as 2 and 14 h after training, respectively. The CDG test result was unsatisfactory when the CK test result was used as standard. However, the accuracy of CDG test was about 80% when CK-MB and hsTnI were used as standards. Thus, CDG offers a noninvasive, simple, and economical approach for monitoring the cardiac function of athletes and exercisers during exercise training. Nonetheless, the applicability of CDG needs further investigation.

  8. JV Task 5 - Predictive Coal Quality Effects Screening Tool (PCQUEST)

    Energy Technology Data Exchange (ETDEWEB)

    Jason Laumb; Joshua Stanislowski

    2007-07-01

    PCQUEST, a package of eight predictive indices, was developed with U.S. Department of Energy (DOE) support by the Energy & Environmental Research Center to predict fireside performance in coal-fired utility boilers more reliably than traditional indices. Since the development of PCQUEST, the need has arisen for additional improvement, validation, and enhancement of the model, as well as to incorporate additional fuel types into the program database. PCQUEST was developed using combustion inorganic transformation theory from previous projects and from empirical data derived from laboratory experiments and coal boiler field observations. The goal of this joint venture project between commercial industry clients and DOE is to further enhance PCQUEST and improve its utility for a variety of new fuels and systems. Specific objectives include initiating joint venture projects with utilities, boiler vendors, and coal companies that involve real-world situations and needs in order to strategically improve algorithms and input-output functions of PCQUEST, as well as to provide technology transfer to the industrial sector. The main body of this report provides a short summary of the projects that were closed from February 1999 through July 2007. All of the reports sent to the commercial clients can be found in the appendix.

  9. Cluster analysis as a prediction tool for pregnancy outcomes.

    Science.gov (United States)

    Banjari, Ines; Kenjerić, Daniela; Šolić, Krešimir; Mandić, Milena L

    2015-03-01

    Considering specific physiology changes during gestation and thinking of pregnancy as a "critical window", classification of pregnant women at early pregnancy can be considered as crucial. The paper demonstrates the use of a method based on an approach from intelligent data mining, cluster analysis. Cluster analysis method is a statistical method which makes possible to group individuals based on sets of identifying variables. The method was chosen in order to determine possibility for classification of pregnant women at early pregnancy to analyze unknown correlations between different variables so that the certain outcomes could be predicted. 222 pregnant women from two general obstetric offices' were recruited. The main orient was set on characteristics of these pregnant women: their age, pre-pregnancy body mass index (BMI) and haemoglobin value. Cluster analysis gained a 94.1% classification accuracy rate with three branch- es or groups of pregnant women showing statistically significant correlations with pregnancy outcomes. The results are showing that pregnant women both of older age and higher pre-pregnancy BMI have a significantly higher incidence of delivering baby of higher birth weight but they gain significantly less weight during pregnancy. Their babies are also longer, and these women have significantly higher probability for complications during pregnancy (gestosis) and higher probability of induced or caesarean delivery. We can conclude that the cluster analysis method can appropriately classify pregnant women at early pregnancy to predict certain outcomes.

  10. Physics-based Modeling Tools for Life Prediction and Durability Assessment of Advanced Materials, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — The technical objectives of this program are: (1) to develop a set of physics-based modeling tools to predict the initiation of hot corrosion and to address pit and...

  11. About Using Predictive Models and Tools To Assess Chemicals under TSCA

    Science.gov (United States)

    As part of EPA's effort to promote chemical safety, OPPT provides public access to predictive models and tools which can help inform the public on the hazards and risks of substances and improve chemical management decisions.

  12. An Evaluation of Growth Models as Predictive Tools for Estimates at Completion (EAC)

    National Research Council Canada - National Science Library

    Trahan, Elizabeth N

    2009-01-01

    ...) as the Estimates at Completion (EAC). Our research evaluates the prospect of nonlinear growth modeling as an alternative to the current predictive tools used for calculating EAC, such as the Cost Performance Index (CPI...

  13. Predictive Maintenance--An Effective Money Saving Tool Being Applied in Industry Today.

    Science.gov (United States)

    Smyth, Tom

    2000-01-01

    Looks at preventive/predictive maintenance as it is used in industry. Discusses core preventive maintenance tools that must be understood to prepare students. Includes a list of websites related to the topic. (JOW)

  14. Development of Web tools to predict axillary lymph node metastasis and pathological response to neoadjuvant chemotherapy in breast cancer patients.

    Science.gov (United States)

    Sugimoto, Masahiro; Takada, Masahiro; Toi, Masakazu

    2014-12-09

    Nomograms are a standard computational tool to predict the likelihood of an outcome using multiple available patient features. We have developed a more powerful data mining methodology, to predict axillary lymph node (AxLN) metastasis and response to neoadjuvant chemotherapy (NAC) in primary breast cancer patients. We developed websites to use these tools. The tools calculate the probability of AxLN metastasis (AxLN model) and pathological complete response to NAC (NAC model). As a calculation algorithm, we employed a decision tree-based prediction model known as the alternative decision tree (ADTree), which is an analog development of if-then type decision trees. An ensemble technique was used to combine multiple ADTree predictions, resulting in higher generalization abilities and robustness against missing values. The AxLN model was developed with training datasets (n=148) and test datasets (n=143), and validated using an independent cohort (n=174), yielding an area under the receiver operating characteristic curve (AUC) of 0.768. The NAC model was developed and validated with n=150 and n=173 datasets from a randomized controlled trial, yielding an AUC of 0.787. AxLN and NAC models require users to input up to 17 and 16 variables, respectively. These include pathological features, including human epidermal growth factor receptor 2 (HER2) status and imaging findings. Each input variable has an option of "unknown," to facilitate prediction for cases with missing values. The websites developed facilitate the use of these tools, and serve as a database for accumulating new datasets.

  15. Acceptability of the Predicting Abusive Head Trauma (PredAHT) clinical prediction tool: A qualitative study with child protection professionals.

    Science.gov (United States)

    Cowley, Laura E; Maguire, Sabine; Farewell, Daniel M; Quinn-Scoggins, Harriet D; Flynn, Matthew O; Kemp, Alison M

    2018-05-09

    The validated Predicting Abusive Head Trauma (PredAHT) tool estimates the probability of abusive head trauma (AHT) based on combinations of six clinical features: head/neck bruising; apnea; seizures; rib/long-bone fractures; retinal hemorrhages. We aimed to determine the acceptability of PredAHT to child protection professionals. We conducted qualitative semi-structured interviews with 56 participants: clinicians (25), child protection social workers (10), legal practitioners (9, including 4 judges), police officers (8), and pathologists (4), purposively sampled across southwest United Kingdom. Interviews were recorded, transcribed and imported into NVivo for thematic analysis (38% double-coded). We explored participants' evaluations of PredAHT, their opinions about the optimal way to present the calculated probabilities, and their interpretation of probabilities in the context of suspected AHT. Clinicians, child protection social workers and police thought PredAHT would be beneficial as an objective adjunct to their professional judgment, to give them greater confidence in their decisions. Lawyers and pathologists appreciated its value for prompting multidisciplinary investigations, but were uncertain of its usefulness in court. Perceived disadvantages included: possible over-reliance and false reassurance from a low score. Interpretations regarding which percentages equate to 'low', 'medium' or 'high' likelihood of AHT varied; participants preferred a precise % probability over these general terms. Participants would use PredAHT with provisos: if they received multi-agency training to define accepted risk thresholds for consistent interpretation; with knowledge of its development; if it was accepted by colleagues. PredAHT may therefore increase professionals' confidence in their decision-making when investigating suspected AHT, but may be of less value in court. Copyright © 2018 Elsevier Ltd. All rights reserved.

  16. The Effects of Webopac Self Training Tool with Guided Exploration on Information Literacy Skills among First Year Degree Students

    Science.gov (United States)

    Ismail, Mohd Nasir; Mamat, Nurfaezah; Jamaludin, Adnan

    2018-01-01

    The purpose of this study is to investigate effects of WebOPAC Self Training Tool with Guided Exploration (WSTTG), WebOPAC Self Training Tool with non-guided exploration (WSTT) and Traditional (T) groups as the learning strategies on information literacy (IL) skills standards among first year degree students in Malaysian public university. The…

  17. A clinical tool for predicting survival in ALS.

    Science.gov (United States)

    Knibb, Jonathan A; Keren, Noa; Kulka, Anna; Leigh, P Nigel; Martin, Sarah; Shaw, Christopher E; Tsuda, Miho; Al-Chalabi, Ammar

    2016-12-01

    Amyotrophic lateral sclerosis (ALS) is a progressive and usually fatal neurodegenerative disease. Survival from diagnosis varies considerably. Several prognostic factors are known, including site of onset (bulbar or limb), age at symptom onset, delay from onset to diagnosis and the use of riluzole and non-invasive ventilation (NIV). Clinicians and patients would benefit from a practical way of using these factors to provide an individualised prognosis. 575 consecutive patients with incident ALS from a population-based registry in South-East England register for ALS (SEALS) were studied. Their survival was modelled as a two-step process: the time from diagnosis to respiratory muscle involvement, followed by the time from respiratory involvement to death. The effects of predictor variables were assessed separately for each time interval. Younger age at symptom onset, longer delay from onset to diagnosis and riluzole use were associated with slower progression to respiratory involvement, and NIV use was associated with lower mortality after respiratory involvement, each with a clinically significant effect size. Riluzole may have a greater effect in younger patients and those with longer delay to diagnosis. A patient's survival time has a roughly 50% chance of falling between half and twice the predicted median. A simple and clinically applicable graphical method of predicting an individual patient's survival from diagnosis is presented. The model should be validated in an independent cohort, and extended to include other important prognostic factors. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

  18. Relevance of balance measurement tools and balance training for fall prevention in older adults

    OpenAIRE

    Majumi M. Noohu, MPTh; Aparajit B. Dey, MD; Mohammed E. Hussain, PhD

    2014-01-01

    Approximately one in three older people fall each year owing to gait/balance disorder/weakness, the second leading cause of falls in older adults. This review evaluates the capability of different balance measurement tools to predict falls in the elderly, which are used routinely for assessing balance impairment. Balance measurement tools reviewed are the Timed Up and Go test, Berg Balance Scale, Tinetti Performance Oriented Mobility Assessment, Functional Reach Test, Clinical Test of Sensory...

  19. Customised 3D Printing: An Innovative Training Tool for the Next Generation of Orbital Surgeons.

    Science.gov (United States)

    Scawn, Richard L; Foster, Alex; Lee, Bradford W; Kikkawa, Don O; Korn, Bobby S

    2015-01-01

    Additive manufacturing or 3D printing is the process by which three dimensional data fields are translated into real-life physical representations. 3D printers create physical printouts using heated plastics in a layered fashion resulting in a three-dimensional object. We present a technique for creating customised, inexpensive 3D orbit models for use in orbital surgical training using 3D printing technology. These models allow trainee surgeons to perform 'wet-lab' orbital decompressions and simulate upcoming surgeries on orbital models that replicate a patient's bony anatomy. We believe this represents an innovative training tool for the next generation of orbital surgeons.

  20. Predictive tool of energy performance of cold storage in agrifood industries: The Portuguese case study

    International Nuclear Information System (INIS)

    Nunes, José; Neves, Diogo; Gaspar, Pedro D.; Silva, Pedro D.; Andrade, Luís P.

    2014-01-01

    Highlights: • A predictive tool for assessment of the energy performance in agrifood industries that use cold storage is developed. • The correlations used by the predictive tool result from the greatest number of data sets collected to date in Portugal. • Strong relationships between raw material, energy consumption and volume of cold stores were established. • Case studies were analyzed that demonstrate the applicability of the tool. • The tool results are useful in the decision-making process of practice measures for the improvement of energy efficiency. - Abstract: Food processing and conservation represent decisive factors for the sustainability of the planet given the significant growth of the world population in the last decades. Therefore, the cooling process during the manufacture and/or storage of food products has been subject of study and improvement in order to ensure the food supply with good quality and safety. A predictive tool for assessment of the energy performance in agrifood industries that use cold storage is developed in order to contribute to the improvement of the energy efficiency of this industry. The predictive tool is based on a set of characteristic correlated parameters: amount of raw material annually processed, annual energy consumption and volume of cold rooms. Case studies of application of the predictive tool consider industries in the meat sector, specifically slaughterhouses. The results obtained help on the decision-making of practice measures for improvement of the energy efficiency in this industry

  1. Variability in Predictions from Online Tools: A Demonstration Using Internet-Based Melanoma Predictors.

    Science.gov (United States)

    Zabor, Emily C; Coit, Daniel; Gershenwald, Jeffrey E; McMasters, Kelly M; Michaelson, James S; Stromberg, Arnold J; Panageas, Katherine S

    2018-02-22

    Prognostic models are increasingly being made available online, where they can be publicly accessed by both patients and clinicians. These online tools are an important resource for patients to better understand their prognosis and for clinicians to make informed decisions about treatment and follow-up. The goal of this analysis was to highlight the possible variability in multiple online prognostic tools in a single disease. To demonstrate the variability in survival predictions across online prognostic tools, we applied a single validation dataset to three online melanoma prognostic tools. Data on melanoma patients treated at Memorial Sloan Kettering Cancer Center between 2000 and 2014 were retrospectively collected. Calibration was assessed using calibration plots and discrimination was assessed using the C-index. In this demonstration project, we found important differences across the three models that led to variability in individual patients' predicted survival across the tools, especially in the lower range of predictions. In a validation test using a single-institution data set, calibration and discrimination varied across the three models. This study underscores the potential variability both within and across online tools, and highlights the importance of using methodological rigor when developing a prognostic model that will be made publicly available online. The results also reinforce that careful development and thoughtful interpretation, including understanding a given tool's limitations, are required in order for online prognostic tools that provide survival predictions to be a useful resource for both patients and clinicians.

  2. Omics AnalySIs System for PRecision Oncology (OASISPRO): A Web-based Omics Analysis Tool for Clinical Phenotype Prediction.

    Science.gov (United States)

    Yu, Kun-Hsing; Fitzpatrick, Michael R; Pappas, Luke; Chan, Warren; Kung, Jessica; Snyder, Michael

    2017-09-12

    Precision oncology is an approach that accounts for individual differences to guide cancer management. Omics signatures have been shown to predict clinical traits for cancer patients. However, the vast amount of omics information poses an informatics challenge in systematically identifying patterns associated with health outcomes, and no general-purpose data-mining tool exists for physicians, medical researchers, and citizen scientists without significant training in programming and bioinformatics. To bridge this gap, we built the Omics AnalySIs System for PRecision Oncology (OASISPRO), a web-based system to mine the quantitative omics information from The Cancer Genome Atlas (TCGA). This system effectively visualizes patients' clinical profiles, executes machine-learning algorithms of choice on the omics data, and evaluates the prediction performance using held-out test sets. With this tool, we successfully identified genes strongly associated with tumor stage, and accurately predicted patients' survival outcomes in many cancer types, including mesothelioma and adrenocortical carcinoma. By identifying the links between omics and clinical phenotypes, this system will facilitate omics studies on precision cancer medicine and contribute to establishing personalized cancer treatment plans. This web-based tool is available at http://tinyurl.com/oasispro ;source codes are available at http://tinyurl.com/oasisproSourceCode . © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

  3. Prediction of Running Injuries from Training Load: a Machine Learning Approach.

    NARCIS (Netherlands)

    Dijkhuis, Talko; Otter, Ruby; Velthuijsen, H.; Lemmink, Koen A.P.M.

    2017-01-01

    The prediction of the running injuries based on selfreported training data on load is difficult. At present, coaches and researchers have no validated system to predict if a runner has an increased risk of injuries. We aim to develop an algorithm to predict the increase of the risk of a runner to

  4. DEEP--a tool for differential expression effector prediction.

    Science.gov (United States)

    Degenhardt, Jost; Haubrock, Martin; Dönitz, Jürgen; Wingender, Edgar; Crass, Torsten

    2007-07-01

    High-throughput methods for measuring transcript abundance, like SAGE or microarrays, are widely used for determining differences in gene expression between different tissue types, dignities (normal/malignant) or time points. Further analysis of such data frequently aims at the identification of gene interaction networks that form the causal basis for the observed properties of the systems under examination. To this end, it is usually not sufficient to rely on the measured gene expression levels alone; rather, additional biological knowledge has to be taken into account in order to generate useful hypotheses about the molecular mechanism leading to the realization of a certain phenotype. We present a method that combines gene expression data with biological expert knowledge on molecular interaction networks, as described by the TRANSPATH database on signal transduction, to predict additional--and not necessarily differentially expressed--genes or gene products which might participate in processes specific for either of the examined tissues or conditions. In a first step, significance values for over-expression in tissue/condition A or B are assigned to all genes in the expression data set. Genes with a significance value exceeding a certain threshold are used as starting points for the reconstruction of a graph with signaling components as nodes and signaling events as edges. In a subsequent graph traversal process, again starting from the previously identified differentially expressed genes, all encountered nodes 'inherit' all their starting nodes' significance values. In a final step, the graph is visualized, the nodes being colored according to a weighted average of their inherited significance values. Each node's, or sub-network's, predominant color, ranging from green (significant for tissue/condition A) over yellow (not significant for either tissue/condition) to red (significant for tissue/condition B), thus gives an immediate visual clue on which molecules

  5. Simulation-Based Laparoscopic Surgery Crisis Resource Management Training-Predicting Technical and Nontechnical Skills.

    Science.gov (United States)

    Goldenberg, Mitchell G; Fok, Kai H; Ordon, Michael; Pace, Kenneth T; Lee, Jason Y

    2017-12-19

    To develop a unique simulation-based assessment using a laparoscopic inferior vena cava (IVC) injury scenario that allows for the safe assessment of urology resident's technical and nontechnical skills, and investigate the effect of personality traits performance in a surgical crisis. Urology residents from our institution were recruited to participate in a simulation-based training laparoscopic nephrectomy exercise. Residents completed demographic and multidimensional personality questionnaires and were instructed to play the role of staff urologist. A vasovagal response to pneumoperitoneum and an IVC injury event were scripted into the scenario. Technical and nontechnical skills were assessed by expert laparoscopic surgeons using validated tools (task checklist, GOALS, and NOTSS). Ten junior and five senior urology residents participated. Five residents were unable to complete the exercise safely. Senior residents outperformed juniors on technical (checklist score 15.1 vs 9.9, p Technical performance scores correlated with NOTSS scores (p technical performance (p technical score (p = 0.03) and pass/fail rating (p = 0.04). Resident level of training and laparoscopic experience correlated with technical performance during a simulation-based laparoscopic IVC injury crisis management scenario, as well as multiple domains of nontechnical performance. Personality traits of our surgical residents are similar and did not predict technical skill. Copyright © 2017 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.

  6. A systematic review on popularity, application and characteristics of protein secondary structure prediction tools.

    Science.gov (United States)

    Kashani-Amin, Elaheh; Tabatabaei-Malazy, Ozra; Sakhteman, Amirhossein; Larijani, Bagher; Ebrahim-Habibi, Azadeh

    2018-02-27

    Prediction of proteins' secondary structure is one of the major steps in the generation of homology models. These models provide structural information which is used to design suitable ligands for potential medicinal targets. However, selecting a proper tool between multiple secondary structure prediction (SSP) options is challenging. The current study is an insight onto currently favored methods and tools, within various contexts. A systematic review was performed for a comprehensive access to recent (2013-2016) studies which used or recommended protein SSP tools. Three databases, Web of Science, PubMed and Scopus were systematically searched and 99 out of 209 studies were finally found eligible to extract data. Four categories of applications for 59 retrieved SSP tools were: (I) prediction of structural features of a given sequence, (II) evaluation of a method, (III) providing input for a new SSP method and (IV) integrating a SSP tool as a component for a program. PSIPRED was found to be the most popular tool in all four categories. JPred and tools utilizing PHD (Profile network from HeiDelberg) method occupied second and third places of popularity in categories I and II. JPred was only found in the two first categories, while PHD was present in three fields. This study provides a comprehensive insight about the recent usage of SSP tools which could be helpful for selecting a proper tool's choice. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  7. Can clinical prediction tools predict the need for computed tomography in blunt abdominal? A systematic review.

    Science.gov (United States)

    Sharples, Alistair; Brohi, Karim

    2016-08-01

    Blunt abdominal trauma is a common reason for admission to the Emergency Department. Early detection of injuries is an important goal but is often not straightforward as physical examination alone is not a good predictor of serious injury. Computed tomography (CT) has become the primary method for assessing the stable trauma patient. It has high sensitivity and specificity but there remains concern regarding the long term consequences of high doses of radiation. Therefore an accurate and reliable method of assessing which patients are at higher risk of injury and hence require a CT would be clinically useful. We perform a systematic review to investigate the use of clinical prediction tools (CPTs) for the identification of abdominal injuries in patients suffering blunt trauma. A literature search was performed using Medline, Embase, The Cochrane Library and NHS Evidence up to August 2014. English language, prospective and retrospective studies were included if they derived, validated or assessed a CPT, aimed at identifying intra-abdominal injuries or the need for intervention to treat an intra-abdominal after blunt trauma. Methodological quality was assessed using a 14 point scale. Performance was assessed predominantly by sensitivity. Seven relevant studies were identified. All studies were derivative studies and no CPT was validated in a separate study. There were large differences in the study design, composition of the CPTs, the outcomes analysed and the methodological quality of the included studies. Sensitivities ranged from 86 to 100%. The highest performing CPT had a lower limit of the 95% CI of 95.8% and was of high methodological quality (11 of 14). Had this rule been applied to the population then 25.1% of patients would have avoided a CT scan. Seven CPTs were identified of varying designs and methodological quality. All demonstrate relatively high sensitivity with some achieving very high sensitivity whilst still managing to reduce the number of CTs

  8. Evaluating the utility of workplace-based assessment tools for speciality training.

    Science.gov (United States)

    Setna, Z; Jha, V; Boursicot, K A M; Roberts, T E

    2010-12-01

    Workplace assessment has been incorporated into speciality training in the UK following changes in the training and work patterns within the National Health Service (NHS). There are various types of assessment tools that have been adopted to assess the clinical competence of trainees. In obstetrics and gynaecology, these include mini-CEX, Objective Structured Assessment of Technical skills (OSATS) and case-based discussion (CbDs). This review provides a theoretical background of workplace assessment and the educational framework that may be adopted to evaluate their effectiveness. It summarises current evidence for the utility of these tools with regard to reliability, validity, acceptability, educational impact and cost. Copyright © 2010 Elsevier Ltd. All rights reserved.

  9. A Tool for Balance Control Training Using Muscle Synergies and Multimodal Interfaces

    Directory of Open Access Journals (Sweden)

    D. Galeano

    2014-01-01

    Full Text Available Balance control plays a key role in neuromotor rehabilitation after stroke or spinal cord injuries. Computerized dynamic posturography (CDP is a classic technological tool to assess the status of balance control and to identify potential disorders. Despite the more accurate diagnosis generated by these tools, the current strategies to promote rehabilitation are still limited and do not take full advantage of the technologies available. This paper presents a novel balance training platform which combines a CDP device made from low-cost interfaces, such as the Nintendo Wii Balance Board and the Microsoft Kinect. In addition, it integrates a custom electrical stimulator that uses the concept of muscle synergies to promote natural interaction. The aim of the platform is to support the exploration of innovative multimodal therapies. Results include the technical validation of the platform using mediolateral and anteroposterior sways as basic balance training therapies.

  10. Clinical Prediction Model and Tool for Assessing Risk of Persistent Pain After Breast Cancer Surgery

    DEFF Research Database (Denmark)

    Meretoja, Tuomo J; Andersen, Kenneth Geving; Bruce, Julie

    2017-01-01

    are missing. The aim was to develop a clinically applicable risk prediction tool. Methods The prediction models were developed and tested using three prospective data sets from Finland (n = 860), Denmark (n = 453), and Scotland (n = 231). Prediction models for persistent pain of moderate to severe intensity......), high body mass index ( P = .039), axillary lymph node dissection ( P = .008), and more severe acute postoperative pain intensity at the seventh postoperative day ( P = .003) predicted persistent pain in the final prediction model, which performed well in the Danish (ROC-AUC, 0.739) and Scottish (ROC......-AUC, 0.740) cohorts. At the 20% risk level, the model had 32.8% and 47.4% sensitivity and 94.4% and 82.4% specificity in the Danish and Scottish cohorts, respectively. Conclusion Our validated prediction models and an online risk calculator provide clinicians and researchers with a simple tool to screen...

  11. Chronic condition self-management support for Aboriginal people: Adapting tools and training.

    Science.gov (United States)

    Battersby, Malcolm; Lawn, Sharon; Kowanko, Inge; Bertossa, Sue; Trowbridge, Coral; Liddicoat, Raylene

    2018-04-22

    Chronic conditions are major health problems for Australian Aboriginal people. Self-management programs can improve health outcomes. However, few health workers are skilled in self-management support and existing programs are not always appropriate in Australian Aboriginal contexts. The goal was to increase the capacity of the Australian health workforce to support Australian Aboriginal people to self-manage their chronic conditions by adapting the Flinders Program of chronic condition self-management support for Australian Aboriginal clients and develop and deliver training for health professionals to implement the program. Feedback from health professionals highlighted that the Flinders Program assessment and care planning tools needed to be adapted to suit Australian Aboriginal contexts. Through consultation with Australian Aboriginal Elders and other experts, the tools were condensed into an illustrated booklet called 'My Health Story'. Associated training courses and resources focusing on cultural safety and effective engagement were developed. A total of 825 health professionals  across Australia was trained and 61 people qualified as accredited trainers in the program, ensuring sustainability. The capacity and skills of the Australian health workforce to engage with and support Australian Aboriginal people to self-manage their chronic health problems significantly increased as a result of this project. The adapted tools and training were popular and appreciated by the health care organisations, health professionals and clients involved. The adapted tools have widespread appeal for cultures that do not have Western models of health care and where there are health literacy challenges. My Health Story has already been used internationally. © 2018 National Rural Health Alliance Ltd.

  12. A Discussion of Virtual Reality As a New Tool for Training Healthcare Professionals

    OpenAIRE

    Caroline Fertleman; Caroline Fertleman; Phoebe Aubugeau-Williams; Carmel Sher; Carmel Sher; Ai-Nee Lim; Sophie Lumley; Sylvie Delacroix; Xueni Pan

    2018-01-01

    BackgroundVirtual reality technology is an exciting and emerging field with vast applications. Our study sets out the viewpoint that virtual reality software could be a new focus of direction in the development of training tools in medical education. We carried out a panel discussion at the Center for Behavior Change 3rd Annual Conference, prompted by the study, “The Responses of Medical General Practitioners to Unreasonable Patient Demand for Antibiotics––A Study of Medical Ethics Using Imme...

  13. A Discussion of Virtual Reality As a New Tool for Training Healthcare Professionals

    OpenAIRE

    Fertleman, Caroline; Aubugeau-Williams, Phoebe; Sher, Carmel; Lim, Ai-Nee; Lumley, Sophie; Delacroix, Sylvie; Pan, Xueni

    2018-01-01

    Background: Virtual reality technology is an exciting and emerging field with vast applications. Our study sets out the viewpoint that virtual reality software could be a new focus of direction in the development of training tools in medical education. We carried out a panel discussion at the Center for Behavior Change 3rd Annual Conference, prompted by the study, “The Responses of Medical General Practitioners to Unreasonable Patient Demand for Antibiotics––A Study of Medical Ethics Using Im...

  14. Validation of the online prediction tool PREDICT v. 2.0 in the Dutch breast cancer population

    NARCIS (Netherlands)

    Maaren, M.C. van; Steenbeek, C.D. van; Pharoah, P.D.; Witteveen, A.; Sonke, G.S.; Strobbe, L.J.A.; Poortmans, P.; Siesling, S.

    2017-01-01

    BACKGROUND: PREDICT version 2.0 is increasingly used to estimate prognosis in breast cancer. This study aimed to validate this tool in specific prognostic subgroups in the Netherlands. METHODS: All operated women with non-metastatic primary invasive breast cancer, diagnosed in 2005, were selected

  15. Validation of the online prediction tool PREDICT v. 2.0 in the Dutch breast cancer population

    NARCIS (Netherlands)

    van Maaren, M. C.; van Steenbeek, C. D.; Pharoah, P. D.P.; Witteveen, A.; Sonke, Gabe S.; Strobbe, L.J.A.; Poortmans, P.M.P.; Siesling, S.

    2017-01-01

    Background PREDICT version 2.0 is increasingly used to estimate prognosis in breast cancer. This study aimed to validate this tool in specific prognostic subgroups in the Netherlands. Methods All operated women with non-metastatic primary invasive breast cancer, diagnosed in 2005, were selected from

  16. Dairy Tool Box Talks: a comprehensive worker training in dairy farming

    Directory of Open Access Journals (Sweden)

    Maristela Rovai

    2016-07-01

    Full Text Available Today’s dairies are growing rapidly, with increasing dependence on Latino immigrant workers. This requires new educational strategies for improving milk quality and introduction to state-of-the-art dairy farming practices. It also creates knowledge gaps pertaining to the health of animals and workers, mainly due to lack of time and language barriers. Owners, managers and herdsmen assign training duties to more experienced employees, which may not promote ‘best practices’ and may perpetuate bad habits. A comprehensive and periodic training program administered by qualified personnel is currently needed and will enhance the sustainability of the dairy industry. Strategic management and employee satisfaction will be achieved through proper training in the employee’s language, typically Spanish. The training needs to address not only current industry standards but also social and cultural differences. An innovative training course was developed following the same structure used by the engineering and construction industries, giving farm workers basic understanding of animal care and handling, cow comfort and personal safety. The Dairy Tool Box Talks program was conducted over a ten week period with nine 30-minute sessions according to farm’s various employee work shifts. Bulk milk bacterial counts and somatic cell count were used to evaluate milk quality on the three dairy farms participating in the program.Dairy Tool Box Talks resulted in a general sense of employee satisfaction, significant learning outcomes, and enthusiasm about the topics covered. We conclude this article by highlighting the importance of educational programs aimed at improving overall cross-cultural training.

  17. Don't Be a Stranger-Designing a Digital Intercultural Sensitivity Training Tool that is Culture General

    NARCIS (Netherlands)

    Degens, Nick; Hofstede, Gert Jan; Beulens, Adrie; Krumhuber, E.; Kappas, Arvid

    2016-01-01

    Digital intercultural training tools play an important role in helping people to mediate cultural misunderstandings. In recent years, these tools were made to teach about specific cultures, but there has been little attention for the design of a tool to teach about differences across a wide range

  18. Don't Be a Stranger--Designing a Digital Intercultural Sensitivity Training Tool That Is Culture General

    Science.gov (United States)

    Degens, Nick; Hofstede, Gert Jan; Beulens, Adrie; Krumhuber, Eva; Kappas, Arvid

    2016-01-01

    Digital intercultural training tools play an important role in helping people to mediate cultural misunderstandings. In recent years, these tools were made to teach about specific cultures, but there has been little attention for the design of a tool to teach about differences across a wide range of cultures. In this work, we take the first steps…

  19. Predicting Autonomous and Controlled Motivation to Transfer Training

    Science.gov (United States)

    Gegenfurtner, Andreas; Festner, Dagmar; Gallenberger, Wolfgang; Lehtinen, Erno; Gruber, Hans

    2009-01-01

    In spite of a broad consensus on the importance of motivation for the transfer of learning from training to the job in work organizations, studies investigating motivation to transfer are limited. This study combines the self-determination theory, the expectancy theory and the theory of planned behaviour to provide a theoretical framework for…

  20. Resistance training and predicted risk of coronary heart disease in ...

    African Journals Online (AJOL)

    The purpose of this study was to determine the impact of resistance training, designed to prevent the development of coronary heart disease (CHD) based on the Framingham Risk Assessment (FRA) score. Twenty-five healthy sedentary men with low CHD risk were assigned to participate in a 16-week (three days per week) ...

  1. Influence of Genotype on Warfarin Maintenance Dose Predictions Produced Using a Bayesian Dose Individualization Tool.

    Science.gov (United States)

    Saffian, Shamin M; Duffull, Stephen B; Roberts, Rebecca L; Tait, Robert C; Black, Leanne; Lund, Kirstin A; Thomson, Alison H; Wright, Daniel F B

    2016-12-01

    A previously established Bayesian dosing tool for warfarin was found to produce biased maintenance dose predictions. In this study, we aimed (1) to determine whether the biased warfarin dose predictions previously observed could be replicated in a new cohort of patients from 2 different clinical settings, (2) to explore the influence of CYP2C9 and VKORC1 genotype on predictive performance of the Bayesian dosing tool, and (3) to determine whether the previous population used to develop the kinetic-pharmacodynamic model underpinning the Bayesian dosing tool was sufficiently different from the test (posterior) population to account for the biased dose predictions. The warfarin maintenance doses for 140 patients were predicted using the dosing tool and compared with the observed maintenance dose. The impact of genotype was assessed by predicting maintenance doses with prior parameter values known to be altered by genetic variability (eg, EC50 for VKORC1 genotype). The prior population was evaluated by fitting the published kinetic-pharmacodynamic model, which underpins the Bayesian tool, to the observed data using NONMEM and comparing the model parameter estimates with published values. The Bayesian tool produced positively biased dose predictions in the new cohort of patients (mean prediction error [95% confidence interval]; 0.32 mg/d [0.14-0.5]). The bias was only observed in patients requiring ≥7 mg/d. The direction and magnitude of the observed bias was not influenced by genotype. The prior model provided a good fit to our data, which suggests that the bias was not caused by different prior and posterior populations. Maintenance doses for patients requiring ≥7 mg/d were overpredicted. The bias was not due to the influence of genotype nor was it related to differences between the prior and posterior populations. There is a need for a more mechanistic model that captures warfarin dose-response relationship at higher warfarin doses.

  2. Development and assessment of a new 3D neuroanatomy teaching tool for MRI training.

    Science.gov (United States)

    Drapkin, Zachary A; Lindgren, Kristen A; Lopez, Michael J; Stabio, Maureen E

    2015-01-01

    A computerized three-dimensional (3D) neuroanatomy teaching tool was developed for training medical students to identify subcortical structures on a magnetic resonance imaging (MRI) series of the human brain. This program allows the user to transition rapidly between two-dimensional (2D) MRI slices, 3D object composites, and a combined model in which 3D objects are overlaid onto the 2D MRI slices, all while rotating the brain in any direction and advancing through coronal, sagittal, or axial planes. The efficacy of this tool was assessed by comparing scores from an MRI identification quiz and survey in two groups of first-year medical students. The first group was taught using this new 3D teaching tool, and the second group was taught the same content for the same amount of time but with traditional methods, including 2D images of brain MRI slices and 3D models from widely used textbooks and online sources. Students from the experimental group performed marginally better than the control group on overall test score (P = 0.07) and significantly better on test scores extracted from questions involving C-shaped internal brain structures (P teaching tool is an effective way to train medical students to read an MRI of the brain and is particularly effective for teaching C-shaped internal brain structures. © 2015 American Association of Anatomists.

  3. Who Is Going to College? Predicting Education Training from Pre-VR Consumer Characteristics

    Science.gov (United States)

    Boutin, Daniel L.; Wilson, Keith B.

    2012-01-01

    The relationship of receiving college and university training within the state vocational rehabilitation (VR) program to pre-VR consumer characteristics was investigated with a multiple direct logistic regression technique. A model containing 11 pre-VR characteristics predict the reception of college and university training for a multidisability…

  4. Individual Differences in Executive Functioning Predict Preschoolers' Improvement from Theory-of-Mind Training

    Science.gov (United States)

    Benson, Jeannette E.; Sabbagh, Mark A.; Carlson, Stephanie M.; Zelazo, Philip David

    2013-01-01

    Twenty-four 3.5-year-old children who initially showed poor performance on false-belief tasks participated in a training protocol designed to promote performance on these tasks. Our aim was to determine whether the extent to which children benefited from training was predicted by their performance on a battery of executive functioning tasks.…

  5. Application of the PredictAD Software Tool to Predict Progression in Patients with Mild Cognitive Impairment

    DEFF Research Database (Denmark)

    Simonsen, Anja H; Mattila, Jussi; Hejl, Anne-Mette

    2012-01-01

    of incremental data presentation using the software tool. A 5th phase was done with all available patient data presented on paper charts. Classifications by the clinical raters were compared to the clinical diagnoses made by the Alzheimer's Disease Neuroimaging Initiative investigators. Results: A statistical...... significant trend (p classification accuracy (from 62.6 to 70.0%) was found when using the PredictAD tool during the stepwise procedure. When the same data were presented on paper, classification accuracy of the raters dropped significantly from 70.0 to 63.2%. Conclusion: Best...... classification accuracy was achieved by the clinical raters when using the tool for decision support, suggesting that the tool can add value in diagnostic classification when large amounts of heterogeneous data are presented....

  6. USING SECOND LIFE VIRTUAL COMPUTER WORLD AS A TRAINING TOOL FOR THE SUBJECTIVE GLOBAL ASSESSMENT (sga.

    Directory of Open Access Journals (Sweden)

    G. Clark Connery

    2012-06-01

    Full Text Available The SGA is a clinical tool used to assess protein energy wasting. Although well validated, it is still not widely incorporated into clinical practice. A barrier to use may be the physical assessment section. Therefore, the purpose of this project was to develop a free and effective tool to train clinicians on performing the SGA. Second Life (SL is a free virtual reality program accessed through the internet using human-like “avatars.” A museum environment was created with panels presenting SGA background information through text, images, and videos of SGA being performed. Users are able to navigate the information by logging onto a provided avatar. After the initial panels, this avatar is able to interact with avatar bots and perform animations which mimic each body assessment within the SGA. Two trial periods were conducted to assess the efficacy of this training tool. The alpha trial consisted of 3 hospital dietitians and 3 nutrition students. These subjects came to the investigators’ facility to test the program. Subjective responses were collected and used to improve the training tool. Feedback was positive regarding the information, delivery, and direction of the project; however, they did complain of difficulty with controlling the avatar. The beta trial consists of users accessing the module remotely. These users include academic and clinical dietitians. Responses are being collected via 5 surveys covering each portion of the module. While 16 dietitians responded to the beta trial, only 4 have completed the training. Current survey responses state: the use of SL is easy and enjoyable; all SGA information was clear and in a desirable format; tactile comparison objects were beneficial for understanding; the in depth description of each assessment is beneficial; the animations that the avatars perform on the bots needs improvement; a patient avatar on which users could perform the full SGA is desirable; the use of SL in the learning

  7. Impact of design research on industrial practice tools, technology, and training

    CERN Document Server

    Lindemann, Udo

    2016-01-01

    Showcasing exemplars of how various aspects of design research were successfully transitioned into and influenced, design practice, this book features chapters written by eminent international researchers and practitioners from industry on the Impact of Design Research on Industrial Practice. Chapters written by internationally acclaimed researchers of design analyse the findings (guidelines, methods and tools), technologies/products and educational approaches that have been transferred as tools, technologies and people to transform industrial practice of engineering design, whilst the chapters that are written by industrial practitioners describe their experience of how various tools, technologies and training impacted design practice. The main benefit of this book, for educators, researchers and practitioners in (engineering) design, will be access to a comprehensive coverage of case studies of successful transfer of outcomes of design research into practice; as well as guidelines and platforms for successf...

  8. Active Video Games as a Training Tool for Individuals With Chronic Respiratory Diseases: A SYSTEMATIC REVIEW.

    Science.gov (United States)

    Butler, Stacey J; Lee, Annemarie L; Goldstein, Roger S; Brooks, Dina

    2018-02-26

    Exercise is an effective treatment for reducing symptom severity and improving quality of life for patients with chronic respiratory diseases. Active video games offer a new and enjoyable way to exercise and have gained popularity in a rehabilitation setting. However, it is unclear whether they achieve comparable physiological and clinical effects as traditional exercise training. A systematic literature search was performed to identify studies that included an active video game component as a form of exercise training and a comparator group in chronic respiratory disease. Two assessors independently reviewed study quality using the Cochrane risk of bias tool and extracted data for exercise capacity, quality of life, and preference of exercise model. Six studies were included in this review. Because of the heterogeneity of the populations, study designs, length of intervention, and outcome measures, meta-analysis could not be performed. Active video game training resulted in comparable training maximal heart rate and dyspnea levels to those achieved when exercising using a treadmill or cycle (n = 5). There was insufficient evidence (n = 3) to determine whether active video game training improved exercise capacity as measured by 6-min walk test or treadmill endurance walking. Although the quality of evidence was low, in a small number of studies active video games induced peak heart rates and dyspnea levels comparable with traditional exercise training. Larger and longer-term randomized controlled trials are needed to establish the impact of video game training for individuals with chronic respiratory diseases.This is an open-access article distributed under the terms of the Creative Commons Attribution-Non Commercial-No Derivatives License 4.0 (CCBY-NC-ND), where it is permissible to download and share the work provided it is properly cited. The work cannot be changed in any way or used commercially without permission from the journal.

  9. A national evaluation of workplace-based assessment tools (WPBAs) in foundation dental training: a UK study. Effective and useful but do they provide an equitable training experience?

    Science.gov (United States)

    Kirton, J A; Palmer, N O A; Grieveson, B; Balmer, M C

    2013-03-01

    A questionnaire study was undertaken with trainers and trainees from 12 deaneries in England and Northern Ireland in June 2010 to evaluate workplace-based assessments (WPBAs) in foundation training. From the sample consisting of 741 trainers and 643 foundation trainees, experience of WPBAs was positive overall, playing an important role in trainees' learning during foundation training and building confidence. However, there is a need for comprehensive training in the WPBA tools used to ensure their efficacy.

  10. Automatic generation of bioinformatics tools for predicting protein-ligand binding sites.

    Science.gov (United States)

    Komiyama, Yusuke; Banno, Masaki; Ueki, Kokoro; Saad, Gul; Shimizu, Kentaro

    2016-03-15

    Predictive tools that model protein-ligand binding on demand are needed to promote ligand research in an innovative drug-design environment. However, it takes considerable time and effort to develop predictive tools that can be applied to individual ligands. An automated production pipeline that can rapidly and efficiently develop user-friendly protein-ligand binding predictive tools would be useful. We developed a system for automatically generating protein-ligand binding predictions. Implementation of this system in a pipeline of Semantic Web technique-based web tools will allow users to specify a ligand and receive the tool within 0.5-1 day. We demonstrated high prediction accuracy for three machine learning algorithms and eight ligands. The source code and web application are freely available for download at http://utprot.net They are implemented in Python and supported on Linux. shimizu@bi.a.u-tokyo.ac.jp Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press.

  11. Natural training tools of informatics in conditions of embodied and mental approach realization

    Directory of Open Access Journals (Sweden)

    Daria A. Barkhatova

    2017-01-01

    Full Text Available Modern processes of globalization and informatization of human activity cause the necessity of change of the educational paradigm in the field of information training of a person, focused on the formation of the strong fundamental knowledge and abilities, which are necessary for person’s information activities and self-education during all life.In connection with these requirements, it is necessary to pay attention to new approaches in education, based on achievements of cognitive science and modern pedagogic. One of such approaches is embodied and mental approach. The paper is devoted to the description of a way of realization of embodied and mental approach in training of informatics through application of the natural tools, providing the fullest and deep understanding of the educational material, and development of cognitive abilities of students.In the paper the theoretical analysis of psychology-pedagogical and methodical literature on a research subject is carried out, results are generalized, natural tools are modeled and results of their partial approbation are described. Achievement of necessary quality of education is offered due to the use of modern techniques, focused on the development of cognitive abilities and improvement of quality of the knowledge. In the conditions of information education, the combination of embodied and mental approaches will allow to acquaint students with the essence of the studied subject due to activation of motor area of the memory and the kinesthetic and visual perception channels. The instrument of realization of this idea is offered to use natural tools in informatics, what is actualized by age features of cognitive abilities of students and individual requirements to ways of perception and mastering of the material, matched according to the level of their knowledge.The research results describe the models of natural tools, developed by students and lecturers of the basic Department of Informatics

  12. Tool-use training in a species of rodent: the emergence of an optimal motor strategy and functional understanding.

    Directory of Open Access Journals (Sweden)

    Kazuo Okanoya

    Full Text Available BACKGROUND: Tool use is defined as the manipulation of an inanimate object to change the position or form of a separate object. The expansion of cognitive niches and tool-use capabilities probably stimulated each other in hominid evolution. To understand the causes of cognitive expansion in humans, we need to know the behavioral and neural basis of tool use. Although a wide range of animals exhibit tool use in nature, most studies have focused on primates and birds on behavioral or psychological levels and did not directly address questions of which neural modifications contributed to the emergence of tool use. To investigate such questions, an animal model suitable for cellular and molecular manipulations is needed. METHODOLOGY/PRINCIPAL FINDINGS: We demonstrated for the first time that rodents can be trained to use tools. Through a step-by-step training procedure, we trained degus (Octodon degus to use a rake-like tool with their forelimbs to retrieve otherwise out-of-reach rewards. Eventually, they mastered effective use of the tool, moving it in an elegant trajectory. After the degus were well trained, probe tests that examined whether they showed functional understanding of the tool were performed. Degus did not hesitate to use tools of different size, colors, and shapes, but were reluctant to use the tool with a raised nonfunctional blade. Thus, degus understood the functional and physical properties of the tool after extensive training. CONCLUSIONS/SIGNIFICANCE: Our findings suggest that tool use is not a specific faculty resulting from higher intelligence, but is a specific combination of more general cognitive faculties. Studying the brains and behaviors of trained rodents can provide insights into how higher cognitive functions might be broken down into more general faculties, and also what cellular and molecular mechanisms are involved in the emergence of such cognitive functions.

  13. USAF Enlisted Air Traffic Controller Selection: Examination of the Predictive Validity of the FAA Air Traffic Selection and Training Battery versus Training Performance

    National Research Council Canada - National Science Library

    Carretta, Thomas R; King, Raymond E

    2008-01-01

    .... The current study examined the utility of the FAA Air Traffic Selection and Training (AT-SAT) battery for incrementing the predictiveness of the ASVAB versus several enlisted ATC training criteria...

  14. An Event-Based Approach to Design a Teamwork Training Scenario and Assessment Tool in Surgery.

    Science.gov (United States)

    Nguyen, Ngan; Watson, William D; Dominguez, Edward

    2016-01-01

    Simulation is a technique recommended for teaching and measuring teamwork, but few published methodologies are available on how best to design simulation for teamwork training in surgery and health care in general. The purpose of this article is to describe a general methodology, called event-based approach to training (EBAT), to guide the design of simulation for teamwork training and discuss its application to surgery. The EBAT methodology draws on the science of training by systematically introducing training exercise events that are linked to training requirements (i.e., competencies being trained and learning objectives) and performance assessment. The EBAT process involves: Of the 4 teamwork competencies endorsed by the Agency for Healthcare Research Quality and Department of Defense, "communication" was chosen to be the focus of our training efforts. A total of 5 learning objectives were defined based on 5 validated teamwork and communication techniques. Diagnostic laparoscopy was chosen as the clinical context to frame the training scenario, and 29 KSAs were defined based on review of published literature on patient safety and input from subject matter experts. Critical events included those that correspond to a specific phase in the normal flow of a surgical procedure as well as clinical events that may occur when performing the operation. Similar to the targeted KSAs, targeted responses to the critical events were developed based on existing literature and gathering input from content experts. Finally, a 29-item EBAT-derived checklist was created to assess communication performance. Like any instructional tool, simulation is only effective if it is designed and implemented appropriately. It is recognized that the effectiveness of simulation depends on whether (1) it is built upon a theoretical framework, (2) it uses preplanned structured exercises or events to allow learners the opportunity to exhibit the targeted KSAs, (3) it assesses performance, and (4

  15. ToxiM: A Toxicity Prediction Tool for Small Molecules Developed Using Machine Learning and Chemoinformatics Approaches

    Directory of Open Access Journals (Sweden)

    Ashok K. Sharma

    2017-11-01

    Full Text Available The experimental methods for the prediction of molecular toxicity are tedious and time-consuming tasks. Thus, the computational approaches could be used to develop alternative methods for toxicity prediction. We have developed a tool for the prediction of molecular toxicity along with the aqueous solubility and permeability of any molecule/metabolite. Using a comprehensive and curated set of toxin molecules as a training set, the different chemical and structural based features such as descriptors and fingerprints were exploited for feature selection, optimization and development of machine learning based classification and regression models. The compositional differences in the distribution of atoms were apparent between toxins and non-toxins, and hence, the molecular features were used for the classification and regression. On 10-fold cross-validation, the descriptor-based, fingerprint-based and hybrid-based classification models showed similar accuracy (93% and Matthews's correlation coefficient (0.84. The performances of all the three models were comparable (Matthews's correlation coefficient = 0.84–0.87 on the blind dataset. In addition, the regression-based models using descriptors as input features were also compared and evaluated on the blind dataset. Random forest based regression model for the prediction of solubility performed better (R2 = 0.84 than the multi-linear regression (MLR and partial least square regression (PLSR models, whereas, the partial least squares based regression model for the prediction of permeability (caco-2 performed better (R2 = 0.68 in comparison to the random forest and MLR based regression models. The performance of final classification and regression models was evaluated using the two validation datasets including the known toxins and commonly used constituents of health products, which attests to its accuracy. The ToxiM web server would be a highly useful and reliable tool for the prediction of toxicity

  16. Implementation of a digital preparation validation tool in dental skills laboratory training.

    Science.gov (United States)

    Kozarovska, A; Larsson, C

    2018-05-01

    To describe the implementation of a digital tool for preparation validation and evaluate it as an aid in students' self-assessment. Students at the final semester of skills laboratory training were asked to use a digital preparation validation tool (PVT) when performing two different tasks; preparation of crowns for teeth 11 and 21. The students were divided into two groups. Group A self-assessed and scanned all three attempts at 21 ("prep-and-scan"). Group B self-assessed all attempts chose the best one and scanned it ("best-of-three"). The situation was reversed for 11. The students assessed five parameters of the preparation and marked them as approved (A) or failed (F). These marks were compared with the information from the PVT. The students also completed a questionnaire. Each question was rated from 1 to 5. Teachers' opinions were collected at staff meetings throughout the project. Most students in the "prep-and-scan" groups showed an increase in agreement between their self-assessment and the information from the PVT, whereas students in the "best-of-three" groups showed lower levels of agreement. All students rated the PVT positively. Most strongly agreed that the tool was helpful in developing skills (mean 4.15), easy to use (mean 4.23) and that it added benefits in comparison to existing assessment tools (mean 4.05). They did not however, fully agree that the tool is time efficient (mean 2.55), and they did not consider it a substitute for verbal teacher feedback. Teachers' feedback suggested advantages of the tool in the form of ease of use, visual aid and increasing interest and motivation during skills laboratory training however, they did not notice a reduction in need of verbal feedback. Within the limitations of the study, our conclusion is that a digital PVT may be a valuable adjunct to other assessment tools in skills laboratory training. © 2017 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

  17. Trained student pharmacists’ telephonic collection of patient medication information: Evaluation of a structured interview tool

    Science.gov (United States)

    Margolis, Amanda R.; Martin, Beth A.; Mott, David A.

    2016-01-01

    Objective To determine the feasibility and fidelity of student pharmacists collecting patient medication list information using a structured interview tool and the accuracy of documenting the information. The medication lists were used by a community pharmacist to provide a targeted medication therapy management (MTM) intervention. Design Descriptive analysis of patient medication lists collected via telephone interviews. Participants 10 trained student pharmacists collected the medication lists. Intervention Trained student pharmacists conducted audio-recorded telephone interviews with 80 English-speaking community dwelling older adults using a structured interview tool to collect and document medication lists. Main outcome measures Feasibility was measured using the number of completed interviews, the time student pharmacists took to collect the information, and pharmacist feedback. Fidelity to the interview tool was measured by assessing student pharmacists’ adherence to asking all scripted questions and probes. Accuracy was measured by comparing the audio recorded interviews to the medication list information documented in an electronic medical record. Results On average it took student pharmacists 26.7 minutes to collect the medication lists. The community pharmacist said the medication lists were complete and that having the medication lists saved time and allowed him to focus on assessment, recommendations, and education during the targeted MTM session. Fidelity was high with an overall proportion of asked scripted probes of 83.75% (95%CI: 80.62–86.88%). Accuracy was also high for both prescription (95.1%, 95%CI: 94.3–95.8%) and non-prescription (90.5%, 95%CI: 89.4–91.4%) medications. Conclusion Trained student pharmacists were able to use an interview tool to collect and document medication lists with a high degree of fidelity and accuracy. This study suggests that student pharmacists or trained technicians may be able to collect patient medication

  18. Trained student pharmacists' telephonic collection of patient medication information: Evaluation of a structured interview tool.

    Science.gov (United States)

    Margolis, Amanda R; Martin, Beth A; Mott, David A

    2016-01-01

    To determine the feasibility and fidelity of student pharmacists collecting patient medication list information using a structured interview tool and the accuracy of documenting the information. The medication lists were used by a community pharmacist to provide a targeted medication therapy management (MTM) intervention. Descriptive analysis of patient medication lists collected with telephone interviews. Ten trained student pharmacists collected the medication lists. Trained student pharmacists conducted audio-recorded telephone interviews with 80 English-speaking, community-dwelling older adults using a structured interview tool to collect and document medication lists. Feasibility was measured using the number of completed interviews, the time student pharmacists took to collect the information, and pharmacist feedback. Fidelity to the interview tool was measured by assessing student pharmacists' adherence to asking all scripted questions and probes. Accuracy was measured by comparing the audio-recorded interviews to the medication list information documented in an electronic medical record. On average, it took student pharmacists 26.7 minutes to collect the medication lists. The community pharmacist said the medication lists were complete and that having the medication lists saved time and allowed him to focus on assessment, recommendations, and education during the targeted MTM session. Fidelity was high, with an overall proportion of asked scripted probes of 83.75% (95% confidence interval [CI], 80.62-86.88%). Accuracy was also high for both prescription (95.1%; 95% CI, 94.3-95.8%) and nonprescription (90.5%; 95% CI, 89.4-91.4%) medications. Trained student pharmacists were able to use an interview tool to collect and document medication lists with a high degree of fidelity and accuracy. This study suggests that student pharmacists or trained technicians may be able to collect patient medication lists to facilitate MTM sessions in the community pharmacy

  19. Towards early software reliability prediction for computer forensic tools (case study).

    Science.gov (United States)

    Abu Talib, Manar

    2016-01-01

    Versatility, flexibility and robustness are essential requirements for software forensic tools. Researchers and practitioners need to put more effort into assessing this type of tool. A Markov model is a robust means for analyzing and anticipating the functioning of an advanced component based system. It is used, for instance, to analyze the reliability of the state machines of real time reactive systems. This research extends the architecture-based software reliability prediction model for computer forensic tools, which is based on Markov chains and COSMIC-FFP. Basically, every part of the computer forensic tool is linked to a discrete time Markov chain. If this can be done, then a probabilistic analysis by Markov chains can be performed to analyze the reliability of the components and of the whole tool. The purposes of the proposed reliability assessment method are to evaluate the tool's reliability in the early phases of its development, to improve the reliability assessment process for large computer forensic tools over time, and to compare alternative tool designs. The reliability analysis can assist designers in choosing the most reliable topology for the components, which can maximize the reliability of the tool and meet the expected reliability level specified by the end-user. The approach of assessing component-based tool reliability in the COSMIC-FFP context is illustrated with the Forensic Toolkit Imager case study.

  20. Integrating Contemplative Tools into Biomedical Science Education and Research Training Programs

    Directory of Open Access Journals (Sweden)

    Rodney R. Dietert

    2014-01-01

    Full Text Available Academic preparation of science researchers and/or human or veterinary medicine clinicians through the science, technology, engineering, and mathematics (STEM curriculum has usually focused on the students (1 acquiring increased disciplinary expertise, (2 learning needed methodologies and protocols, and (3 expanding their capacity for intense, persistent focus. Such educational training is effective until roadblocks or problems arise via this highly-learned approach. Then, the health science trainee may have few tools available for effective problem solving. Training to achieve flexibility, adaptability, and broadened perspectives using contemplative practices has been rare among biomedical education programs. To address this gap, a Cornell University-based program involving formal biomedical science coursework, and health science workshops has been developed to offer science students, researchers and health professionals a broader array of personal, contemplation-based, problem-solving tools. This STEM educational initiative includes first-person exercises designed to broaden perceptional awareness, decrease emotional drama, and mobilize whole-body strategies for creative problem solving. Self-calibration and journaling are used for students to evaluate the personal utility of each exercise. The educational goals are to increase student self-awareness and self-regulation and to provide trainees with value-added tools for career-long problem solving. Basic elements of this educational initiative are discussed using the framework of the Tree of Contemplative Practices.

  1. Which screening tools can predict injury to the lower extremities in team sports?: a systematic review.

    Science.gov (United States)

    Dallinga, Joan M; Benjaminse, Anne; Lemmink, Koen A P M

    2012-09-01

    Injuries to lower extremities are common in team sports such as soccer, basketball, volleyball, football and field hockey. Considering personal grief, disabling consequences and high costs caused by injuries to lower extremities, the importance for the prevention of these injuries is evident. From this point of view it is important to know which screening tools can identify athletes who are at risk of injury to their lower extremities. The aim of this article is to determine the predictive values of anthropometric and/or physical screening tests for injuries to the leg, anterior cruciate ligament (ACL), knee, hamstring, groin and ankle in team sports. A systematic review was conducted in MEDLINE (1966 to September 2011), EMBASE (1989 to September 2011) and CINAHL (1982 to September 2011). Based on inclusion criteria defined a priori, titles, abstracts and full texts were analysed to find relevant studies. The analysis showed that different screening tools can be predictive for injuries to the knee, ACL, hamstring, groin and ankle. For injuries in general there is some support in the literature to suggest that general joint laxity is a predictive measure for leg injuries. The anterior right/left reach distance >4 cm and the composite reach distance injuries. Furthermore, an increasing age, a lower hamstring/quadriceps (H : Q) ratio and a decreased range of motion (ROM) of hip abduction may predict the occurrence of leg injuries. Hyperextension of the knee, side-to-side differences in anterior-posterior knee laxity and differences in knee abduction moment between both legs are suggested to be predictive tests for sustaining an ACL injury and height was a predictive screening tool for knee ligament injuries. There is some evidence that when age increases, the probability of sustaining a hamstring injury increases. Debate exists in the analysed literature regarding measurement of the flexibility of the hamstring as a predictive screening tool, as well as using the H

  2. Maximizing lipocalin prediction through balanced and diversified training set and decision fusion.

    Science.gov (United States)

    Nath, Abhigyan; Subbiah, Karthikeyan

    2015-12-01

    Lipocalins are short in sequence length and perform several important biological functions. These proteins are having less than 20% sequence similarity among paralogs. Experimentally identifying them is an expensive and time consuming process. The computational methods based on the sequence similarity for allocating putative members to this family are also far elusive due to the low sequence similarity existing among the members of this family. Consequently, the machine learning methods become a viable alternative for their prediction by using the underlying sequence/structurally derived features as the input. Ideally, any machine learning based prediction method must be trained with all possible variations in the input feature vector (all the sub-class input patterns) to achieve perfect learning. A near perfect learning can be achieved by training the model with diverse types of input instances belonging to the different regions of the entire input space. Furthermore, the prediction performance can be improved through balancing the training set as the imbalanced data sets will tend to produce the prediction bias towards majority class and its sub-classes. This paper is aimed to achieve (i) the high generalization ability without any classification bias through the diversified and balanced training sets as well as (ii) enhanced the prediction accuracy by combining the results of individual classifiers with an appropriate fusion scheme. Instead of creating the training set randomly, we have first used the unsupervised Kmeans clustering algorithm to create diversified clusters of input patterns and created the diversified and balanced training set by selecting an equal number of patterns from each of these clusters. Finally, probability based classifier fusion scheme was applied on boosted random forest algorithm (which produced greater sensitivity) and K nearest neighbour algorithm (which produced greater specificity) to achieve the enhanced predictive performance

  3. Competency-based evaluation tools for integrative medicine training in family medicine residency: a pilot study

    Directory of Open Access Journals (Sweden)

    Schneider Craig

    2007-04-01

    Full Text Available Abstract Background As more integrative medicine educational content is integrated into conventional family medicine teaching, the need for effective evaluation strategies grows. Through the Integrative Family Medicine program, a six site pilot program of a four year residency training model combining integrative medicine and family medicine training, we have developed and tested a set of competency-based evaluation tools to assess residents' skills in integrative medicine history-taking and treatment planning. This paper presents the results from the implementation of direct observation and treatment plan evaluation tools, as well as the results of two Objective Structured Clinical Examinations (OSCEs developed for the program. Methods The direct observation (DO and treatment plan (TP evaluation tools developed for the IFM program were implemented by faculty at each of the six sites during the PGY-4 year (n = 11 on DO and n = 8 on TP. The OSCE I was implemented first in 2005 (n = 6, revised and then implemented with a second class of IFM participants in 2006 (n = 7. OSCE II was implemented in fall 2005 with only one class of IFM participants (n = 6. Data from the initial implementation of these tools are described using descriptive statistics. Results Results from the implementation of these tools at the IFM sites suggest that we need more emphasis in our curriculum on incorporating spirituality into history-taking and treatment planning, and more training for IFM residents on effective assessment of readiness for change and strategies for delivering integrative medicine treatment recommendations. Focusing our OSCE assessment more narrowly on integrative medicine history-taking skills was much more effective in delineating strengths and weaknesses in our residents' performance than using the OSCE for both integrative and more basic communication competencies. Conclusion As these tools are refined further they will be of value both in improving

  4. Running speed during training and percent body fat predict race time in recreational male marathoners.

    Science.gov (United States)

    Barandun, Ursula; Knechtle, Beat; Knechtle, Patrizia; Klipstein, Andreas; Rüst, Christoph Alexander; Rosemann, Thomas; Lepers, Romuald

    2012-01-01

    Recent studies have shown that personal best marathon time is a strong predictor of race time in male ultramarathoners. We aimed to determine variables predictive of marathon race time in recreational male marathoners by using the same characteristics of anthropometry and training as used for ultramarathoners. Anthropometric and training characteristics of 126 recreational male marathoners were bivariately and multivariately related to marathon race times. After multivariate regression, running speed of the training units (β = -0.52, P marathon race times. Marathon race time for recreational male runners may be estimated to some extent by using the following equation (r (2) = 0.44): race time ( minutes) = 326.3 + 2.394 × (percent body fat, %) - 12.06 × (speed in training, km/hours). Running speed during training sessions correlated with prerace percent body fat (r = 0.33, P = 0.0002). The model including anthropometric and training variables explained 44% of the variance of marathon race times, whereas running speed during training sessions alone explained 40%. Thus, training speed was more predictive of marathon performance times than anthropometric characteristics. The present results suggest that low body fat and running speed during training close to race pace (about 11 km/hour) are two key factors for a fast marathon race time in recreational male marathoner runners.

  5. The interactive graphic simulator (IGS): A helpful tool for an efficient training

    International Nuclear Information System (INIS)

    Santiago Lucas, A.

    1996-01-01

    The IGS is a natural response, in the training area, to the high technological advances in the computer disciplines for the graphic representations and advanced process models with a high level of reliability and friendliness. Tecnatom has integrated a representation of advanced models in several workstations which permits, through its high resolution colour screens, the visualization of all the information available in control room with graphical representation of NPP's system. Simultaneously with this, the IGS permits to operate any component in order to change its status, in the same way that operations upon the panels. Through the flexibility of the software for graphic representations and the advanced models. Tecnatom has generated, based in the use of IGS, several training courses which have provided a tutorial worth, to understand complex phenomena, with a man-machine interface more friendly than the full scope simulator. Therefore, the IGS appears as an important flexible tool which can adapt itself to the training of several collectives in a NPP, and it has a special importance for those which the ignorance of panels interferes with the training in a full scope simulator. (author)

  6. Atomic Oxygen Erosion Yield Predictive Tool for Spacecraft Polymers in Low Earth Orbit

    Science.gov (United States)

    Bank, Bruce A.; de Groh, Kim K.; Backus, Jane A.

    2008-01-01

    A predictive tool was developed to estimate the low Earth orbit (LEO) atomic oxygen erosion yield of polymers based on the results of the Polymer Erosion and Contamination Experiment (PEACE) Polymers experiment flown as part of the Materials International Space Station Experiment 2 (MISSE 2). The MISSE 2 PEACE experiment accurately measured the erosion yield of a wide variety of polymers and pyrolytic graphite. The 40 different materials tested were selected specifically to represent a variety of polymers used in space as well as a wide variety of polymer chemical structures. The resulting erosion yield data was used to develop a predictive tool which utilizes chemical structure and physical properties of polymers that can be measured in ground laboratory testing to predict the in-space atomic oxygen erosion yield of a polymer. The properties include chemical structure, bonding information, density and ash content. The resulting predictive tool has a correlation coefficient of 0.914 when compared with actual MISSE 2 space data for 38 polymers and pyrolytic graphite. The intent of the predictive tool is to be able to make estimates of atomic oxygen erosion yields for new polymers without requiring expensive and time consumptive in-space testing.

  7. Development of METAL-ACTIVE SITE and ZINCCLUSTER tool to predict active site pockets.

    Science.gov (United States)

    Ajitha, M; Sundar, K; Arul Mugilan, S; Arumugam, S

    2018-03-01

    The advent of whole genome sequencing leads to increasing number of proteins with known amino acid sequences. Despite many efforts, the number of proteins with resolved three dimensional structures is still low. One of the challenging tasks the structural biologists face is the prediction of the interaction of metal ion with any protein for which the structure is unknown. Based on the information available in Protein Data Bank, a site (METALACTIVE INTERACTION) has been generated which displays information for significant high preferential and low-preferential combination of endogenous ligands for 49 metal ions. User can also gain information about the residues present in the first and second coordination sphere as it plays a major role in maintaining the structure and function of metalloproteins in biological system. In this paper, a novel computational tool (ZINCCLUSTER) is developed, which can predict the zinc metal binding sites of proteins even if only the primary sequence is known. The purpose of this tool is to predict the active site cluster of an uncharacterized protein based on its primary sequence or a 3D structure. The tool can predict amino acids interacting with a metal or vice versa. This tool is based on the occurrence of significant triplets and it is tested to have higher prediction accuracy when compared to that of other available techniques. © 2017 Wiley Periodicals, Inc.

  8. Accurate Prediction of Motor Failures by Application of Multi CBM Tools: A Case Study

    Science.gov (United States)

    Dutta, Rana; Singh, Veerendra Pratap; Dwivedi, Jai Prakash

    2018-02-01

    Motor failures are very difficult to predict accurately with a single condition-monitoring tool as both electrical and the mechanical systems are closely related. Electrical problem, like phase unbalance, stator winding insulation failures can, at times, lead to vibration problem and at the same time mechanical failures like bearing failure, leads to rotor eccentricity. In this case study of a 550 kW blower motor it has been shown that a rotor bar crack was detected by current signature analysis and vibration monitoring confirmed the same. In later months in a similar motor vibration monitoring predicted bearing failure and current signature analysis confirmed the same. In both the cases, after dismantling the motor, the predictions were found to be accurate. In this paper we will be discussing the accurate predictions of motor failures through use of multi condition monitoring tools with two case studies.

  9. Online Lexicological Tools in ESP – Towards an Approach to Strategy Training

    Directory of Open Access Journals (Sweden)

    Jaroslaw Krajka

    2015-11-01

    Full Text Available Together with great proliferation of online resources on the one hand and a striking lack of commercially published materials for specific ESP domains on the other, the ESP teacher needs to reflect on using Internet materials judiciously in the language classroom. An indispensable element of the teaching process in any context is effective resourcing, or the ability to find, evaluate and use reference tools of various kinds. This strategy is also necessary in the ESP context, and the range of available resources goes beyond dictionaries only and encompasses, among others, specialized dictionaries, glossaries, terminology databanks. The purpose of the present paper is to outline the procedure of online resourcing, by giving specific steps for the training of the skill based on ESP materials of various types. The theoretical discussion of strategy training will be substantiated with the practical activities for the procedure.

  10. INFORMATION TECHNOLOGIES AS THE TOOL OF EFFICIENCY IMPROVING OF FUTURE PHYSICS TEACHERS TRAINING TO LABORATORY SESSION IN OPTICS

    Directory of Open Access Journals (Sweden)

    Goncharenko T.

    2017-12-01

    Full Text Available The analysis of the problem of the use of information technologies implementation as the tool of the efficiency improving of future physics teachers training to execution of laboratory session in Optics is considered in the article. The problems and contradictions concerning ICT tools use in higher education institutions, the work of which is aimed at future physics teachers training are described. Due to the specifics of future teachers training in higher education institutions, labor market requirements and public procurement, the main ICT tools are identified, that are effective in students’ self-activity work to laboratory session execution. The developed list of electronic resources is divided into blocks according to the topics of laboratory works in Optics. The methodology of using of ICT tools at future students training for laboratory session on the example of individual topics is considered.

  11. [Multicenter validation of an evaluation tool for clinical training activities (SVAT) of the nursing students].

    Science.gov (United States)

    Finotto, Sergio; Gradellini, Cinzia; Bandini, Stefania; Burrai, Francesco; Lucchi Casadei, Sandra; Villani, Carolina; Vincenzi, Simone; Mecugni, Daniela

    2017-01-01

    To evaluate the psychometric characteristics of the Scheda di Valutazione delle Attività di Tirocinio (SVAT). The degree courses in Nursing of the University of Modena and Reggio Emilia, site of Reggio Emilia, the University of Bologna Formative Section BO1, Imola and training center of Cesena, the University of Ferrara training centers of Ferrara and Codigoro were all enrolled in the research. For the content validation the reactive Delphi method was chosen. The panel of experts expressed a qualitative-intuitive judgment on the adequacy of language and on the stimulus material (SVAT). For internal consistency Cronbach's alpha was calculated the. The test-retest method was used for the reliability of stability. all indicators of the SVAT have achieved a degree of consensus not less than 80% demonstrating its content validity. The face validity is demonstrated by an average score equal to or greater than 7 obtained by all indicators. The reliability of internal consistency of the SVAT was appraised by Cronbach's alpha that was 0.987 for the entire instrument. The reliability of the stability has been calculated through the correlation's coefficient expressed by Pearson's r that was 0.983 (p = 1.3E-198). in Italy there is no a "gold standard" tool to evaluate the clinical performance of nursing students during and at the end of their clinical training. The SVAT proves to be a valuable and reliable tool it furthermore could stimulate the discussion and the debate among educators and nurses, so that also in our country, it may be possible develop and refine tools that support the evaluation of clinical skills of nursing students.

  12. Development and Validation of a Multidisciplinary Tool for Accurate and Efficient Rotorcraft Noise Prediction (MUTE)

    Science.gov (United States)

    Liu, Yi; Anusonti-Inthra, Phuriwat; Diskin, Boris

    2011-01-01

    A physics-based, systematically coupled, multidisciplinary prediction tool (MUTE) for rotorcraft noise was developed and validated with a wide range of flight configurations and conditions. MUTE is an aggregation of multidisciplinary computational tools that accurately and efficiently model the physics of the source of rotorcraft noise, and predict the noise at far-field observer locations. It uses systematic coupling approaches among multiple disciplines including Computational Fluid Dynamics (CFD), Computational Structural Dynamics (CSD), and high fidelity acoustics. Within MUTE, advanced high-order CFD tools are used around the rotor blade to predict the transonic flow (shock wave) effects, which generate the high-speed impulsive noise. Predictions of the blade-vortex interaction noise in low speed flight are also improved by using the Particle Vortex Transport Method (PVTM), which preserves the wake flow details required for blade/wake and fuselage/wake interactions. The accuracy of the source noise prediction is further improved by utilizing a coupling approach between CFD and CSD, so that the effects of key structural dynamics, elastic blade deformations, and trim solutions are correctly represented in the analysis. The blade loading information and/or the flow field parameters around the rotor blade predicted by the CFD/CSD coupling approach are used to predict the acoustic signatures at far-field observer locations with a high-fidelity noise propagation code (WOPWOP3). The predicted results from the MUTE tool for rotor blade aerodynamic loading and far-field acoustic signatures are compared and validated with a variation of experimental data sets, such as UH60-A data, DNW test data and HART II test data.

  13. On-Line, Self-Learning, Predictive Tool for Determining Payload Thermal Response

    Science.gov (United States)

    Jen, Chian-Li; Tilwick, Leon

    2000-01-01

    This paper will present the results of a joint ManTech / Goddard R&D effort, currently under way, to develop and test a computer based, on-line, predictive simulation model for use by facility operators to predict the thermal response of a payload during thermal vacuum testing. Thermal response was identified as an area that could benefit from the algorithms developed by Dr. Jeri for complex computer simulations. Most thermal vacuum test setups are unique since no two payloads have the same thermal properties. This requires that the operators depend on their past experiences to conduct the test which requires time for them to learn how the payload responds while at the same time limiting any risk of exceeding hot or cold temperature limits. The predictive tool being developed is intended to be used with the new Thermal Vacuum Data System (TVDS) developed at Goddard for the Thermal Vacuum Test Operations group. This model can learn the thermal response of the payload by reading a few data points from the TVDS, accepting the payload's current temperature as the initial condition for prediction. The model can then be used as a predictive tool to estimate the future payload temperatures according to a predetermined shroud temperature profile. If the error of prediction is too big, the model can be asked to re-learn the new situation on-line in real-time and give a new prediction. Based on some preliminary tests, we feel this predictive model can forecast the payload temperature of the entire test cycle within 5 degrees Celsius after it has learned 3 times during the beginning of the test. The tool will allow the operator to play "what-if' experiments to decide what is his best shroud temperature set-point control strategy. This tool will save money by minimizing guess work and optimizing transitions as well as making the testing process safer and easier to conduct.

  14. Prediction and Control of Cutting Tool Vibration in Cnc Lathe with Anova and Ann

    Directory of Open Access Journals (Sweden)

    S. S. Abuthakeer

    2011-06-01

    Full Text Available Machining is a complex process in which many variables can deleterious the desired results. Among them, cutting tool vibration is the most critical phenomenon which influences dimensional precision of the components machined, functional behavior of the machine tools and life of the cutting tool. In a machining operation, the cutting tool vibrations are mainly influenced by cutting parameters like cutting speed, depth of cut and tool feed rate. In this work, the cutting tool vibrations are controlled using a damping pad made of Neoprene. Experiments were conducted in a CNC lathe where the tool holder is supported with and without damping pad. The cutting tool vibration signals were collected through a data acquisition system supported by LabVIEW software. To increase the buoyancy and reliability of the experiments, a full factorial experimental design was used. Experimental data collected were tested with analysis of variance (ANOVA to understand the influences of the cutting parameters. Empirical models have been developed using analysis of variance (ANOVA. Experimental studies and data analysis have been performed to validate the proposed damping system. Multilayer perceptron neural network model has been constructed with feed forward back-propagation algorithm using the acquired data. On the completion of the experimental test ANN is used to validate the results obtained and also to predict the behavior of the system under any cutting condition within the operating range. The onsite tests show that the proposed system reduces the vibration of cutting tool to a greater extend.

  15. AllerTool: a web server for predicting allergenicity and allergic cross-reactivity in proteins.

    Science.gov (United States)

    Zhang, Zong Hong; Koh, Judice L Y; Zhang, Guang Lan; Choo, Khar Heng; Tammi, Martti T; Tong, Joo Chuan

    2007-02-15

    Assessment of potential allergenicity and patterns of cross-reactivity is necessary whenever novel proteins are introduced into human food chain. Current bioinformatic methods in allergology focus mainly on the prediction of allergenic proteins, with no information on cross-reactivity patterns among known allergens. In this study, we present AllerTool, a web server with essential tools for the assessment of predicted as well as published cross-reactivity patterns of allergens. The analysis tools include graphical representation of allergen cross-reactivity information; a local sequence comparison tool that displays information of known cross-reactive allergens; a sequence similarity search tool for assessment of cross-reactivity in accordance to FAO/WHO Codex alimentarius guidelines; and a method based on support vector machine (SVM). A 10-fold cross-validation results showed that the area under the receiver operating curve (A(ROC)) of SVM models is 0.90 with 86.00% sensitivity (SE) at specificity (SP) of 86.00%. AllerTool is freely available at http://research.i2r.a-star.edu.sg/AllerTool/.

  16. Training, Quality Assurance Factors, and Tools Investigation: a Work Report and Suggestions on Software Quality Assurance

    Science.gov (United States)

    Lee, Pen-Nan

    1991-01-01

    Previously, several research tasks have been conducted, some observations were obtained, and several possible suggestions have been contemplated involving software quality assurance engineering at NASA Johnson. These research tasks are briefly described. Also, a brief discussion is given on the role of software quality assurance in software engineering along with some observations and suggestions. A brief discussion on a training program for software quality assurance engineers is provided. A list of assurance factors as well as quality factors are also included. Finally, a process model which can be used for searching and collecting software quality assurance tools is presented.

  17. Predictive technologies: Can smart tools augment the brain’s predictive abilities?

    Directory of Open Access Journals (Sweden)

    Giovanni ePezzulo

    2016-04-01

    Full Text Available The ability of looking into the future – namely, the capacity of anticipating future states of the environment or of the body – represents a fundamental function of human (and animal brains. A goalkeeper who tries to guess the ball’s direction; a chess player who attempts to anticipate the opponent’s next move; or a man-in-love who tries to calculate what are the chances of her saying yes – in all these cases, people are simulating possible future states of the world, in order to maximize the success of their decisions or actions. Research in neuroscience is showing that our ability to predict the behaviour of physical or social phenomena is largely dependent on the brain’s ability to integrate current and past information to generate (probabilistic simulations of the future. But could predictive processing be augmented using advanced technologies? In this contribution, we discuss how computational technologies may be used to support, facilitate or enhance the prediction of future events, by considering exemplificative scenarios across different domains, from simpler sensorimotor decisions to more complex cognitive tasks. We also examine the key scientific and technical challenges that must be faced to turn this vision into reality.

  18. Improving Student Employee Training: A Study of Web 2.0 Social Media Tools as a Delivery Model

    Science.gov (United States)

    Smith, Sharon D.

    2012-01-01

    Training student employees in Educational Outreach and Student Services (EOSS) at Arizona State University's West campus is important to maintaining a knowledgeable and productive workforce. This dissertation describes the results of an action research study in which social media tools were utilized as a delivery mechanism for training student…

  19. Small-Sided Games : An Optimal Training Tool to Represent Tactical Match Demands in Elite-Standard Youth Soccer Players?

    NARCIS (Netherlands)

    Olthof, S. B. H.; Frencken, W. G. P.; Lemmink, K. A. P. M.

    2016-01-01

    Small-sided games are an often used training tool in soccer practices. It has proven to provide a simultaneous physical, technical and tactical training stimulus for soccer players[1]. Small-sided games replicate the tactical character of a match, but in a simplified format with reductions in number

  20. Using of pH as a tool to predict salinity of groundwater for irrigation purpose using artificial neural network

    Directory of Open Access Journals (Sweden)

    Mahmoud Nasr

    2014-01-01

    Full Text Available Monitoring of groundwater quality is one of the important tools to provide adequate information about water management. In the present study, artificial neural network (ANN with a feed-forward back-propagation was designed to predict groundwater salinity, expressed by total dissolved solids (TDS, using pH as an input parameter. Groundwater samples were collected from a 36 m depth well located in the experimental farm of the City of Scientific Researches and Technological Applications (SRTA City, New Borg El-Arab City, Alexandria, Egypt. The network structure was 1–5–3–1 and used the default Levenberg–Marquardt algorithm for training. It was observed that, the best validation performance, based on the mean square error, was 14819 at epoch 0, and no major problems or over-fitting occurred with the training step. The simulated output tracked the measured data with a correlation coefficient (R-value of 0.64, 0.67 and 0.90 for training, validation and test, respectively. In this case, the network response was acceptable, and simulation could be used for entering new inputs.

  1. A Simple Evaluation Tool (ET-CET) Indicates Increase of Diagnostic Skills From Small Bowel Capsule Endoscopy Training Courses

    OpenAIRE

    Albert, J.G.; Humbla, O.; McAlindon, M.E.; Davison, C.; Seitz, U.; Fraser, C.; Hagenm?ller, F.; Noetzel, E.; Spada, C.; Riccioni, M.E.; Barnert, J.; Filmann, N.; Keuchel, M.

    2015-01-01

    Abstract Small bowel capsule endoscopy (SBCE) has become a first line diagnostic tool. Several training courses with a similar format have been established in Europe; however, data on learning curve and training in SBCE remain sparse. Between 2008 and 2011, different basic SBCE training courses were organized internationally in UK (n?=?2), Italy (n?=?2), Germany (n?=?2), Finland (n?=?1), and nationally in Germany (n?=?10), applying similar 8-hour curricula with 50% lectures and 50% hands-on t...

  2. PROSPER: an integrated feature-based tool for predicting protease substrate cleavage sites.

    Directory of Open Access Journals (Sweden)

    Jiangning Song

    Full Text Available The ability to catalytically cleave protein substrates after synthesis is fundamental for all forms of life. Accordingly, site-specific proteolysis is one of the most important post-translational modifications. The key to understanding the physiological role of a protease is to identify its natural substrate(s. Knowledge of the substrate specificity of a protease can dramatically improve our ability to predict its target protein substrates, but this information must be utilized in an effective manner in order to efficiently identify protein substrates by in silico approaches. To address this problem, we present PROSPER, an integrated feature-based server for in silico identification of protease substrates and their cleavage sites for twenty-four different proteases. PROSPER utilizes established specificity information for these proteases (derived from the MEROPS database with a machine learning approach to predict protease cleavage sites by using different, but complementary sequence and structure characteristics. Features used by PROSPER include local amino acid sequence profile, predicted secondary structure, solvent accessibility and predicted native disorder. Thus, for proteases with known amino acid specificity, PROSPER provides a convenient, pre-prepared tool for use in identifying protein substrates for the enzymes. Systematic prediction analysis for the twenty-four proteases thus far included in the database revealed that the features we have included in the tool strongly improve performance in terms of cleavage site prediction, as evidenced by their contribution to performance improvement in terms of identifying known cleavage sites in substrates for these enzymes. In comparison with two state-of-the-art prediction tools, PoPS and SitePrediction, PROSPER achieves greater accuracy and coverage. To our knowledge, PROSPER is the first comprehensive server capable of predicting cleavage sites of multiple proteases within a single substrate

  3. Predicting Knowledge Workers' Participation in Voluntary Learning with Employee Characteristics and Online Learning Tools

    Science.gov (United States)

    Hicks, Catherine

    2018-01-01

    Purpose: This paper aims to explore predicting employee learning activity via employee characteristics and usage for two online learning tools. Design/methodology/approach: Statistical analysis focused on observational data collected from user logs. Data are analyzed via regression models. Findings: Findings are presented for over 40,000…

  4. Towards a consensus on datasets and evaluation metrics for developing B-cell epitope prediction tools

    DEFF Research Database (Denmark)

    Greenbaum, Jason A.; Andersen, Pernille; Blythe, Martin

    2007-01-01

    and immunology communities. Improving the accuracy of B-cell epitope prediction methods depends on a community consensus on the data and metrics utilized to develop and evaluate such tools. A workshop, sponsored by the National Institute of Allergy and Infectious Disease (NIAID), was recently held in Washington...

  5. Users' experiences of an emergency department patient admission predictive tool: A qualitative evaluation.

    Science.gov (United States)

    Jessup, Melanie; Crilly, Julia; Boyle, Justin; Wallis, Marianne; Lind, James; Green, David; Fitzgerald, Gerard

    2016-09-01

    Emergency department overcrowding is an increasing issue impacting patients, staff and quality of care, resulting in poor patient and system outcomes. In order to facilitate better management of emergency department resources, a patient admission predictive tool was developed and implemented. Evaluation of the tool's accuracy and efficacy was complemented with a qualitative component that explicated the experiences of users and its impact upon their management strategies, and is the focus of this article. Semi-structured interviews were conducted with 15 pertinent users, including bed managers, after-hours managers, specialty department heads, nurse unit managers and hospital executives. Analysis realised dynamics of accuracy, facilitating communication and enabling group decision-making Users generally welcomed the enhanced potential to predict and plan following the incorporation of the patient admission predictive tool into their daily and weekly decision-making processes. They offered astute feedback with regard to their responses when faced with issues of capacity and communication. Participants reported an growing confidence in making informed decisions in a cultural context that is continually moving from reactive to proactive. This information will inform further patient admission predictive tool development specifically and implementation processes generally. © The Author(s) 2015.

  6. Development of a simple tool to predict the risk of postpartum diabetes in women with gestational diabetes mellitus.

    Science.gov (United States)

    Köhler, M; Ziegler, A G; Beyerlein, A

    2016-06-01

    Women with gestational diabetes mellitus (GDM) have an increased risk of diabetes postpartum. We developed a score to predict the long-term risk of postpartum diabetes using clinical and anamnestic variables recorded during or shortly after delivery. Data from 257 GDM women who were prospectively followed for diabetes outcome over 20 years of follow-up were used to develop and validate the risk score. Participants were divided into training and test sets. The risk score was calculated using Lasso Cox regression and divided into four risk categories, and its prediction performance was assessed in the test set. Postpartum diabetes developed in 110 women. The computed training set risk score of 5 × body mass index in early pregnancy (per kg/m(2)) + 132 if GDM was treated with insulin (otherwise 0) + 44 if the woman had a family history of diabetes (otherwise 0) - 35 if the woman lactated (otherwise 0) had R (2) values of 0.23, 0.25, and 0.33 at 5, 10, and 15 years postpartum, respectively, and a C-Index of 0.75. Application of the risk score in the test set resulted in observed risk of postpartum diabetes at 5 years of 11 % for low risk scores ≤140, 29 % for scores 141-220, 64 % for scores 221-300, and 80 % for scores >300. The derived risk score is easy to calculate, allows accurate prediction of GDM-related postpartum diabetes, and may thus be a useful prediction tool for clinicians and general practitioners.

  7. RDNAnalyzer: A tool for DNA secondary structure prediction and sequence analysis.

    Science.gov (United States)

    Afzal, Muhammad; Shahid, Ahmad Ali; Shehzadi, Abida; Nadeem, Shahid; Husnain, Tayyab

    2012-01-01

    RDNAnalyzer is an innovative computer based tool designed for DNA secondary structure prediction and sequence analysis. It can randomly generate the DNA sequence or user can upload the sequences of their own interest in RAW format. It uses and extends the Nussinov dynamic programming algorithm and has various application for the sequence analysis. It predicts the DNA secondary structure and base pairings. It also provides the tools for routinely performed sequence analysis by the biological scientists such as DNA replication, reverse compliment generation, transcription, translation, sequence specific information as total number of nucleotide bases, ATGC base contents along with their respective percentages and sequence cleaner. RDNAnalyzer is a unique tool developed in Microsoft Visual Studio 2008 using Microsoft Visual C# and Windows Presentation Foundation and provides user friendly environment for sequence analysis. It is freely available. http://www.cemb.edu.pk/sw.html RDNAnalyzer - Random DNA Analyser, GUI - Graphical user interface, XAML - Extensible Application Markup Language.

  8. Can we predict Acute Medical readmissions using the BOOST tool? A retrospective case note review.

    Science.gov (United States)

    Lee, Geraldine A; Freedman, Daniel; Beddoes, Penelope; Lyness, Emily; Nixon, Imogen; Srivastava, Vivek

    2016-01-01

    Readmissions within 30-days of hospital discharge are a problem. The aim was to determine if the Better Outcomes for Older Adults through Safe Transitions (BOOST) risk assessment tool was applicable within the UK. Patients over 65 readmitted were identified retrospectively via a casenote review. BOOST assessment was applied with 1 point for each risk factor. 324 patients were readmitted (mean age 77 years) with a median of 7 days between discharge and readmission. The median BOOST score was 3 (IQR 2-4) with polypharmacy evident in 88% and prior hospitalisation in 70%. The tool correctly predicted 90% of readmissions using two or more risk factors and 99.1% if one risk factor was included. The BOOST assessment tool appears appropriate in predicting readmissions however further analysis is required to determine its precision.

  9. Prefrontal Cortex Structure Predicts Training-Induced Improvements in Multitasking Performance.

    Science.gov (United States)

    Verghese, Ashika; Garner, K G; Mattingley, Jason B; Dux, Paul E

    2016-03-02

    The ability to perform multiple, concurrent tasks efficiently is a much-desired cognitive skill, but one that remains elusive due to the brain's inherent information-processing limitations. Multitasking performance can, however, be greatly improved through cognitive training (Van Selst et al., 1999, Dux et al., 2009). Previous studies have examined how patterns of brain activity change following training (for review, see Kelly and Garavan, 2005). Here, in a large-scale human behavioral and imaging study of 100 healthy adults, we tested whether multitasking training benefits, assessed using a standard dual-task paradigm, are associated with variability in brain structure. We found that the volume of the rostral part of the left dorsolateral prefrontal cortex (DLPFC) predicted an individual's response to training. Critically, this association was observed exclusively in a task-specific training group, and not in an active-training control group. Our findings reveal a link between DLPFC structure and an individual's propensity to gain from training on a task that taps the limits of cognitive control. Cognitive "brain" training is a rapidly growing, multibillion dollar industry (Hayden, 2012) that has been touted as the panacea for a variety of disorders that result in cognitive decline. A key process targeted by such training is "cognitive control." Here, we combined an established cognitive control measure, multitasking ability, with structural brain imaging in a sample of 100 participants. Our goal was to determine whether individual differences in brain structure predict the extent to which people derive measurable benefits from a cognitive training regime. Ours is the first study to identify a structural brain marker-volume of left hemisphere dorsolateral prefrontal cortex-associated with the magnitude of multitasking performance benefits induced by training at an individual level. Copyright © 2016 the authors 0270-6474/16/362638-08$15.00/0.

  10. A simple teaching tool for training the pelvic organ prolapse quantification system.

    Science.gov (United States)

    Geiss, Ingrid M; Riss, Paul A; Hanzal, Engelbert; Dungl, Andrea

    2007-09-01

    The pelvic organ prolapse quantification (POPQ) system is currently the most common and specific system describing different prolapse stages. Nevertheless, its use is not yet accepted worldwide in routine care. Our aim was to develop a simple teaching tool for the POPQ system capable of simulating different stages of uterovaginal prolapse for use in medical education with hands on training. We constructed a moveable and flexible tool with an inverted Santa Claus' cap, which simulated the vaginal cuff and the tassel at the end representing the cervix. A wooden embroidery frame fixed the cap and served as the hymen, the reference point for all measurements. Inside the cap, we sewed buttons to define the anatomic landmark points Aa and Ap located 3 cm distal from the frame. After explaining the device to the students, we used the three-by-three grid for recording the quantitative description of the pelvic organ support. First, each student had to demonstrate a specific prolapse with his cap device. Then, a prolapse was simulated on the cap, and the student had to take the relevant measurements and record them in the POPQ grid. The main training effect to understand the POPQ system seems to be the possibility for each trainee to simulate a three-dimensional prolapse with this flexible vagina model.

  11. The Analysis of User Behaviour of a Network Management Training Tool using a Neural Network

    Directory of Open Access Journals (Sweden)

    Helen Donelan

    2005-10-01

    Full Text Available A novel method for the analysis and interpretation of data that describes the interaction between trainee network managers and a network management training tool is presented. A simulation based approach is currently being used to train network managers, through the use of a simulated network. The motivation is to provide a tool for exposing trainees to a life like situation without disrupting a live network. The data logged by this system describes the detailed interaction between trainee network manager and simulated network. The work presented here provides an analysis of this interaction data that enables an assessment of the capabilities of the trainee network manager as well as an understanding of how the network management tasks are being approached. A neural network architecture is implemented in order to perform an exploratory data analysis of the interaction data. The neural network employs a novel form of continuous self-organisation to discover key features in the data and thus provide new insights into the learning and teaching strategies employed.

  12. International multicenter tool to predict the risk of nonsentinel node metastases in breast cancer

    DEFF Research Database (Denmark)

    Meretoja, Tuomo J; Leidenius, Marjut H K; Heikkilä, Päivi S

    2012-01-01

    predicting nonsentinel node involvement were identified in logistic regression analysis. A multivariable predictive model was developed and validated by area under the receiver operating characteristics curve (AUC), first internally in 500 additional patients and then externally in 1068 patients from other...... centers. All statistical tests were two-sided. Results Nine tumor- and sentinel node-specific variables were identified as statistically significant factors predicting nonsentinel node involvement in logistic regression analysis. A resulting predictive model applied to the internal validation series...... resulted in an AUC of 0.714 (95% confidence interval [CI] = 0.665 to 0.763). For the external validation series, the AUC was 0.719 (95% CI = 0.689 to 0.750). The model was well calibrated in the external validation series. Conclusions We present a novel, international, multicenter, predictive tool...

  13. Predicted Interval Plots (PIPS): A Graphical Tool for Data Monitoring of Clinical Trials.

    Science.gov (United States)

    Li, Lingling; Evans, Scott R; Uno, Hajime; Wei, L J

    2009-11-01

    Group sequential designs are often used in clinical trials to evaluate efficacy and/or futility. Many methods have been developed for different types of endpoints and scenarios. However, few of these methods convey information regarding effect sizes (e.g., treatment differences) and none uses prediction to convey information regarding potential effect size estimates and associated precision, with trial continuation. To address these limitations, Evans et al. (2007) proposed to use prediction and predicted intervals as a flexible and practical tool for quantitative monitoring of clinical trials. In this article, we reaffirm the importance and usefulness of this innovative approach and introduce a graphical summary, predicted interval plots (PIPS), to display the information obtained in the prediction process in a straightforward yet comprehensive manner. We outline the construction of PIPS and apply this method in two examples. The results and the interpretations of the PIPS are discussed.

  14. Running speed during training and percent body fat predict race time in recreational male marathoners

    OpenAIRE

    Knechtle, Beat; Barandun,; Knechtle,Patrizia; Klipstein,; Rüst,Christoph Alexander; Rosemann,Thomas; Lepers,Romuald

    2012-01-01

     Background: Recent studies have shown that personal best marathon time is a strong predictor of race time in male ultramarathoners. We aimed to determine variables predictive of marathon race time in recreational male marathoners by using the same characteristics of anthropometry and training as used for ultramarathoners.Methods: Anthropometric and training characteristics of 126 recreational male marathoners were bivariately and multivariately related to marathon race times.Results...

  15. The Smart Wheelchair: is it an appropriate mobility training tool for children with physical disabilities?

    Science.gov (United States)

    McGarry, Sarah; Moir, Lois; Girdler, Sonya

    2012-09-01

    To describe the impact of a mobility training program using the Smart Wheelchair on the driving skills and psychosocial outcomes of children with physical disabilities. A multiple case study design using mixed methods was used. Four children with physical disabilities were recruited through The Centre for Cerebral Palsy in Western Australia. The intervention was a 16 session Smart Wheelchair mobility training program. Data was collected using a quantitative driving skills assessment, field notes and qualitative parent interviews. Three out of four children gained independence in at least three driving skills or more, whilst one child was competent with verbal prompts. Three out of four mothers reported positive changes in their child's confidence, motivation and affect. The Smart Wheelchair has the ability to uncover learning potential and facilitate the recognition of abilities in children previously excluded from access to independent mobility. Given the significant limitation that restrictions in mobility pose to participation for children with physical disabilities, therapists must begin to understand the effectiveness of interventions such as the Smart Wheelchair. The descriptive findings of this study allow for future, more rigorous research, to be conducted on the effectiveness of the Smart Wheelchair as a mobility training tool.

  16. Memory self-efficacy predicts responsiveness to inductive reasoning training in older adults.

    Science.gov (United States)

    Payne, Brennan R; Jackson, Joshua J; Hill, Patrick L; Gao, Xuefei; Roberts, Brent W; Stine-Morrow, Elizabeth A L

    2012-01-01

    In the current study, we assessed the relationship between memory self-efficacy at pretest and responsiveness to inductive reasoning training in a sample of older adults. Participants completed a measure of self-efficacy assessing beliefs about memory capacity. Participants were then randomly assigned to a waitlist control group or an inductive reasoning training intervention. Latent change score models were used to examine the moderators of change in inductive reasoning. Inductive reasoning showed clear improvements in the training group compared with the control. Within the training group, initial memory capacity beliefs significantly predicted change in inductive reasoning such that those with higher levels of capacity beliefs showed greater responsiveness to the intervention. Further analyses revealed that self-efficacy had effects on how trainees allocated time to the training materials over the course of the intervention. Results indicate that self-referential beliefs about cognitive potential may be an important factor contributing to plasticity in adulthood.

  17. Predicting Antitumor Activity of Peptides by Consensus of Regression Models Trained on a Small Data Sample

    Directory of Open Access Journals (Sweden)

    Ivanka Jerić

    2011-11-01

    Full Text Available Predicting antitumor activity of compounds using regression models trained on a small number of compounds with measured biological activity is an ill-posed inverse problem. Yet, it occurs very often within the academic community. To counteract, up to some extent, overfitting problems caused by a small training data, we propose to use consensus of six regression models for prediction of biological activity of virtual library of compounds. The QSAR descriptors of 22 compounds related to the opioid growth factor (OGF, Tyr-Gly-Gly-Phe-Met with known antitumor activity were used to train regression models: the feed-forward artificial neural network, the k-nearest neighbor, sparseness constrained linear regression, the linear and nonlinear (with polynomial and Gaussian kernel support vector machine. Regression models were applied on a virtual library of 429 compounds that resulted in six lists with candidate compounds ranked by predicted antitumor activity. The highly ranked candidate compounds were synthesized, characterized and tested for an antiproliferative activity. Some of prepared peptides showed more pronounced activity compared with the native OGF; however, they were less active than highly ranked compounds selected previously by the radial basis function support vector machine (RBF SVM regression model. The ill-posedness of the related inverse problem causes unstable behavior of trained regression models on test data. These results point to high complexity of prediction based on the regression models trained on a small data sample.

  18. Using Bayesian Network as a tool for coastal storm flood impact prediction at Varna Bay (Bulgaria, Western Black Sea)

    Science.gov (United States)

    Valchev, Nikolay; Eftimova, Petya; Andreeva, Nataliya; Prodanov, Bogdan

    2017-04-01

    Coastal zone is among the fastest evolving areas worldwide. Ever increasing population inhabiting coastal settlements develops often conflicting economic and societal activities. The existing imbalance between the expansion of these activities, on one hand, and the potential to accommodate them in a sustainable manner, on the other, becomes a critical problem. Concurrently, coasts are affected by various hydro-meteorological phenomena such as storm surges, heavy seas, strong winds and flash floods, which intensities and occurrence frequency is likely to increase due to the climate change. This implies elaboration of tools capable of quick prediction of impact of those phenomena on the coast and providing solutions in terms of disaster risk reduction measures. One such tool is Bayesian network. Proposed paper describes the set-up of such network for Varna Bay (Bulgaria, Western Black Sea). It relates near-shore storm conditions to their onshore flood potential and ultimately to relevant impact as relative damage on coastal and manmade environment. Methodology for set-up and training of the Bayesian network was developed within RISC-KIT project (Resilience-Increasing Strategies for Coasts - toolKIT). Proposed BN reflects the interaction between boundary conditions, receptors, hazard, and consequences. Storm boundary conditions - maximum significant wave height and peak surge level, were determined on the basis of their historical and projected occurrence. The only hazard considered in this study is flooding characterized by maximum inundation depth. BN was trained with synthetic events created by combining estimated boundary conditions. Flood impact was modeled with the process-based morphodynamical model XBeach. Restaurants, sport and leisure facilities, administrative buildings, and car parks were introduced in the network as receptors. Consequences (impact) are estimated in terms of relative damage caused by given inundation depth. National depth

  19. Evaluation of insight training of ambulance drivers in Sweden using DART, a new e-learning tool.

    Science.gov (United States)

    Albertsson, Pontus; Sundström, Anna

    2011-12-01

    The aim of the study was to evaluate whether a new e-learning tool for insight training of ambulance drivers can have an effect on drivers' driving behaviors, perceived driving competence, competence to assess risks, self-reflection, and safety attitudes. A quasi-experimental study design, with participants nonrandomly assigned into a control and intervention group, was used. The intervention group participated in the insight-training course and the control group did not. Both groups completed a self- and peer assessment online questionnaire before and after the training. The main finding is that the ambulance drivers assessed themselves through the instruments after the training, with the e-learning tool Driver Access Recording Tool (DART), as safer drivers in the areas of speed adaptation, closing up, and overtaking. In the answers from the group-based evaluation, the ambulance drivers responded that they were more reflective/analytical, had increased their risk awareness, and had changed their driving behaviors. After insight training, the ambulance drivers in this study assessed themselves as safer drivers in several important areas, including speed adaptation, closing up, and overtaking. In future training of ambulance drivers there should be more focus on insight training instead of previous training focusing on maneuvering capabilities.

  20. A pilot of the use of Short Message Service (SMS) as a training tool ...

    African Journals Online (AJOL)

    In this setting, short in-service training interventions are a pragmatic attempt at improving ... education. A pragmatic approach to training these nurses is to provide in- service .... outcomes.1 The need for quality training interventions and trained ...

  1. Combining Results from Distinct MicroRNA Target Prediction Tools Enhances the Performance of Analyses

    Directory of Open Access Journals (Sweden)

    Arthur C. Oliveira

    2017-05-01

    Full Text Available Target prediction is generally the first step toward recognition of bona fide microRNA (miRNA-target interactions in living cells. Several target prediction tools are now available, which use distinct criteria and stringency to provide the best set of candidate targets for a single miRNA or a subset of miRNAs. However, there are many false-negative predictions, and consensus about the optimum strategy to select and use the output information provided by the target prediction tools is lacking. We compared the performance of four tools cited in literature—TargetScan (TS, miRanda-mirSVR (MR, Pita, and RNA22 (R22, and we determined the most effective approach for analyzing target prediction data (individual, union, or intersection. For this purpose, we calculated the sensitivity, specificity, precision, and correlation of these approaches using 10 miRNAs (miR-1-3p, miR-17-5p, miR-21-5p, miR-24-3p, miR-29a-3p, miR-34a-5p, miR-124-3p, miR-125b-5p, miR-145-5p, and miR-155-5p and 1,400 genes (700 validated and 700 non-validated as targets of these miRNAs. The four tools provided a subset of high-quality predictions and returned few false-positive predictions; however, they could not identify several known true targets. We demonstrate that union of TS/MR and TS/MR/R22 enhanced the quality of in silico prediction analysis of miRNA targets. We conclude that the union rather than the intersection of the aforementioned tools is the best strategy for maximizing performance while minimizing the loss of time and resources in subsequent in vivo and in vitro experiments for functional validation of miRNA-target interactions.

  2. Training in positivity for stroke? A qualitative study of acceptability of use of Positive Mental Training (PosMT) as a tool to assist stroke survivors with post-stroke psychological problems and in coping with rehabilitation.

    Science.gov (United States)

    Mavaddat, Nahal; Ross, Sheila; Dobbin, Alastair; Williams, Kate; Graffy, Jonathan; Mant, Jonathan

    2017-01-01

    Post-stroke psychological problems predict poor recovery, while positive affect enables patients to focus on rehabilitation and may improve functional outcomes. Positive Mental Training (PosMT), a guided self-help audio shows promise as a tool in promoting positivity, optimism and resilience. To assess acceptability of training in positivity with PosMT for prevention and management of post-stroke psychological problems and to help with coping with rehabilitation. A modified PosMT tool consisted of 12 audio tracks each lasting 18 minutes, one listened to every day for a week. Survivors and carers were asked to listen for 4 weeks, but could volunteer to listen for more. Interviews took place about experiences of the tool after 4 and 12 weeks. 10 stroke survivors and 5 carers from Stroke Support Groups in the UK. Three stroke survivors did not engage with the tool. The remainder reported positive physical and psychological benefits including improved relaxation, better sleep and reduced anxiety after four weeks. Survivors who completed the programme gained a positive outlook on the future, increased motivation, confidence and ability to cope with rehabilitation. No adverse effects were reported. The PosMT shows potential as a tool for coping with rehabilitation and overcoming post-stroke psychological problems including anxiety and depression.

  3. The use of machine learning and nonlinear statistical tools for ADME prediction.

    Science.gov (United States)

    Sakiyama, Yojiro

    2009-02-01

    Absorption, distribution, metabolism and excretion (ADME)-related failure of drug candidates is a major issue for the pharmaceutical industry today. Prediction of ADME by in silico tools has now become an inevitable paradigm to reduce cost and enhance efficiency in pharmaceutical research. Recently, machine learning as well as nonlinear statistical tools has been widely applied to predict routine ADME end points. To achieve accurate and reliable predictions, it would be a prerequisite to understand the concepts, mechanisms and limitations of these tools. Here, we have devised a small synthetic nonlinear data set to help understand the mechanism of machine learning by 2D-visualisation. We applied six new machine learning methods to four different data sets. The methods include Naive Bayes classifier, classification and regression tree, random forest, Gaussian process, support vector machine and k nearest neighbour. The results demonstrated that ensemble learning and kernel machine displayed greater accuracy of prediction than classical methods irrespective of the data set size. The importance of interaction with the engineering field is also addressed. The results described here provide insights into the mechanism of machine learning, which will enable appropriate usage in the future.

  4. Overcoming the barriers to patient-centred care: time, tools and training.

    Science.gov (United States)

    West, Elizabeth; Barron, David N; Reeves, Rachel

    2005-04-01

    To investigate whether nurses experience barriers to delivering high quality care in areas that are of particular concern to patients and to describe which aspects of care are most affected when nurses lack the required resources, such as time, tools and training to do their job. Patient surveys conducted in the National Health Service of the United Kingdom tend to show there is variation in the extent to which they are satisfied with care in a number of important areas, such as physical comfort, emotional support and the coordination of care. A sample of nurses working in 20 acute London hospitals was asked to complete a postal questionnaire based on a prototype employee survey developed in the United States and adapted by the authors for use in the United Kingdom. Staff in the human resources departments of participating hospitals mailed the questionnaires to nurses' home addresses. After two reminders, 2880 (out of 6160) useable responses were returned, giving a response rate of 47%. Nurses are aware that there are deficits in standards of care in areas that are particularly important to patients. The majority feel overworked (64%) and report that they do not have enough time to perform essential nursing tasks, such as addressing patients' anxieties, fears and concerns and giving patients and relatives information. Their work is often made more difficult by the lack of staff, space, equipment and cleanliness. They are often unable to control noise and temperature in clinical areas. Nurses in acute London hospitals are subject to high levels of aggressive behaviour, mainly from patients and their relatives, but also from other members of staff. More positively, high proportions of the nurses in our survey expressed the desire for further training, particularly in social and interpersonal aspects of care. This paper goes beyond reporting problems with the quality and safety of care to try to understand why patients do not always receive optimum care in areas that

  5. Rosetta Structure Prediction as a Tool for Solving Difficult Molecular Replacement Problems.

    Science.gov (United States)

    DiMaio, Frank

    2017-01-01

    Molecular replacement (MR), a method for solving the crystallographic phase problem using phases derived from a model of the target structure, has proven extremely valuable, accounting for the vast majority of structures solved by X-ray crystallography. However, when the resolution of data is low, or the starting model is very dissimilar to the target protein, solving structures via molecular replacement may be very challenging. In recent years, protein structure prediction methodology has emerged as a powerful tool in model building and model refinement for difficult molecular replacement problems. This chapter describes some of the tools available in Rosetta for model building and model refinement specifically geared toward difficult molecular replacement cases.

  6. Numerical tools to predict the environmental loads for offshore structures under extreme weather conditions

    Science.gov (United States)

    Wu, Yanling

    2018-05-01

    In this paper, the extreme waves were generated using the open source computational fluid dynamic (CFD) tools — OpenFOAM and Waves2FOAM — using linear and nonlinear NewWave input. They were used to conduct the numerical simulation of the wave impact process. Numerical tools based on first-order (with and without stretching) and second-order NewWave are investigated. The simulation to predict force loading for the offshore platform under the extreme weather condition is implemented and compared.

  7. The predictive accuracy of PREDICT: a personalized decision-making tool for Southeast Asian women with breast cancer.

    Science.gov (United States)

    Wong, Hoong-Seam; Subramaniam, Shridevi; Alias, Zarifah; Taib, Nur Aishah; Ho, Gwo-Fuang; Ng, Char-Hong; Yip, Cheng-Har; Verkooijen, Helena M; Hartman, Mikael; Bhoo-Pathy, Nirmala

    2015-02-01

    Web-based prognostication tools may provide a simple and economically feasible option to aid prognostication and selection of chemotherapy in early breast cancers. We validated PREDICT, a free online breast cancer prognostication and treatment benefit tool, in a resource-limited setting. All 1480 patients who underwent complete surgical treatment for stages I to III breast cancer from 1998 to 2006 were identified from the prospective breast cancer registry of University Malaya Medical Centre, Kuala Lumpur, Malaysia. Calibration was evaluated by comparing the model-predicted overall survival (OS) with patients' actual OS. Model discrimination was tested using receiver-operating characteristic (ROC) analysis. Median age at diagnosis was 50 years. The median tumor size at presentation was 3 cm and 54% of patients had lymph node-negative disease. About 55% of women had estrogen receptor-positive breast cancer. Overall, the model-predicted 5 and 10-year OS was 86.3% and 77.5%, respectively, whereas the observed 5 and 10-year OS was 87.6% (difference: -1.3%) and 74.2% (difference: 3.3%), respectively; P values for goodness-of-fit test were 0.18 and 0.12, respectively. The program was accurate in most subgroups of patients, but significantly overestimated survival in patients aged discrimination; areas under ROC curve were 0.78 (95% confidence interval [CI]: 0.74-0.81) and 0.73 (95% CI: 0.68-0.78) for 5 and 10-year OS, respectively. Based on its accurate performance in this study, PREDICT may be clinically useful in prognosticating women with breast cancer and personalizing breast cancer treatment in resource-limited settings.

  8. Training the Recurrent neural network by the Fuzzy Min-Max algorithm for fault prediction

    International Nuclear Information System (INIS)

    Zemouri, Ryad; Racoceanu, Daniel; Zerhouni, Noureddine; Minca, Eugenia; Filip, Florin

    2009-01-01

    In this paper, we present a training technique of a Recurrent Radial Basis Function neural network for fault prediction. We use the Fuzzy Min-Max technique to initialize the k-center of the RRBF neural network. The k-means algorithm is then applied to calculate the centers that minimize the mean square error of the prediction task. The performances of the k-means algorithm are then boosted by the Fuzzy Min-Max technique.

  9. A design tool for predicting the capillary transport characteristics of fuel cell diffusion media using an artificial neural network

    Science.gov (United States)

    Kumbur, E. C.; Sharp, K. V.; Mench, M. M.

    Developing a robust, intelligent design tool for multivariate optimization of multi-phase transport in fuel cell diffusion media (DM) is of utmost importance to develop advanced DM materials. This study explores the development of a DM design algorithm based on artificial neural network (ANN) that can be used as a powerful tool for predicting the capillary transport characteristics of fuel cell DM. Direct measurements of drainage capillary pressure-saturation curves of the differently engineered DMs (5, 10 and 20 wt.% PTFE) were performed at room temperature under three compressions (0, 0.6 and 1.4 MPa) [E.C. Kumbur, K.V. Sharp, M.M. Mench, J. Electrochem. Soc. 154(12) (2007) B1295-B1304; E.C. Kumbur, K.V. Sharp, M.M. Mench, J. Electrochem. Soc. 154(12) (2007) B1305-B1314; E.C. Kumbur, K.V. Sharp, M.M. Mench, J. Electrochem. Soc. 154(12) (2007) B1315-B1324]. The generated benchmark data were utilized to systematically train a three-layered ANN framework that processes the feed-forward error back propagation methodology. The designed ANN successfully predicts the measured capillary pressures within an average uncertainty of ±5.1% of the measured data, confirming that the present ANN model can be used as a design tool within the range of tested parameters. The ANN simulations reveal that tailoring the DM with high PTFE loading and applying high compression pressure lead to a higher capillary pressure, therefore promoting the liquid water transport within the pores of the DM. Any increase in hydrophobicity of the DM is found to amplify the compression effect, thus yielding a higher capillary pressure for the same saturation level and compression.

  10. The Prediction of Training Proficiency in Firefighters: A Study of Predictive Validity in Spain

    Directory of Open Access Journals (Sweden)

    Alfredo Berges

    2018-02-01

    Full Text Available The present study provides results of criterion validity in the selection of firefighters in Spain. The predictors were cognitive skills, job knowledge, and physical aptitudes, and the criterion was training proficiency. The process involves 639 candidates, but only 44 complete successfully the selection process. Our results support previous evidence showing that general cognitive ability is the best predictor of training proficiency, with an operational validity of .57. With respect to the other predictors, job knowledge presented an operational validity of .55 and physical tests of .49. In addition, multiple regression analysis showed that cognitive aptitude explains 33% of the variance, but when physical aptitudes are included the explained variance increases to 50%. If we also add job knowledge, explained variance increases to 55%. Our study offers recent results of criterion validity in a barely investigated job, gathered in a country other than the one where prior research had been carried out.

  11. Effect of standardized training on the reliability of the Cochrane risk of bias assessment tool: a study protocol.

    Science.gov (United States)

    da Costa, Bruno R; Resta, Nina M; Beckett, Brooke; Israel-Stahre, Nicholas; Diaz, Alison; Johnston, Bradley C; Egger, Matthias; Jüni, Peter; Armijo-Olivo, Susan

    2014-12-13

    The Cochrane risk of bias (RoB) tool has been widely embraced by the systematic review community, but several studies have reported that its reliability is low. We aim to investigate whether training of raters, including objective and standardized instructions on how to assess risk of bias, can improve the reliability of this tool. We describe the methods that will be used in this investigation and present an intensive standardized training package for risk of bias assessment that could be used by contributors to the Cochrane Collaboration and other reviewers. This is a pilot study. We will first perform a systematic literature review to identify randomized clinical trials (RCTs) that will be used for risk of bias assessment. Using the identified RCTs, we will then do a randomized experiment, where raters will be allocated to two different training schemes: minimal training and intensive standardized training. We will calculate the chance-corrected weighted Kappa with 95% confidence intervals to quantify within- and between-group Kappa agreement for each of the domains of the risk of bias tool. To calculate between-group Kappa agreement, we will use risk of bias assessments from pairs of raters after resolution of disagreements. Between-group Kappa agreement will quantify the agreement between the risk of bias assessment of raters in the training groups and the risk of bias assessment of experienced raters. To compare agreement of raters under different training conditions, we will calculate differences between Kappa values with 95% confidence intervals. This study will investigate whether the reliability of the risk of bias tool can be improved by training raters using standardized instructions for risk of bias assessment. One group of inexperienced raters will receive intensive training on risk of bias assessment and the other will receive minimal training. By including a control group with minimal training, we will attempt to mimic what many review authors

  12. Predictive analytics tools to adjust and monitor performance metrics for the ATLAS Production System

    CERN Document Server

    Barreiro Megino, Fernando Harald; The ATLAS collaboration

    2017-01-01

    Having information such as an estimation of the processing time or possibility of system outage (abnormal behaviour) helps to assist to monitor system performance and to predict its next state. The current cyber-infrastructure presents computing conditions in which contention for resources among high-priority data analysis happens routinely, that might lead to significant workload and data handling interruptions. The lack of the possibility to monitor and to predict the behaviour of the analysis process (its duration) and system’s state itself caused to focus on design of the built-in situational awareness analytic tools.

  13. Using open source computational tools for predicting human metabolic stability and additional absorption, distribution, metabolism, excretion, and toxicity properties.

    Science.gov (United States)

    Gupta, Rishi R; Gifford, Eric M; Liston, Ted; Waller, Chris L; Hohman, Moses; Bunin, Barry A; Ekins, Sean

    2010-11-01

    Ligand-based computational models could be more readily shared between researchers and organizations if they were generated with open source molecular descriptors [e.g., chemistry development kit (CDK)] and modeling algorithms, because this would negate the requirement for proprietary commercial software. We initially evaluated open source descriptors and model building algorithms using a training set of approximately 50,000 molecules and a test set of approximately 25,000 molecules with human liver microsomal metabolic stability data. A C5.0 decision tree model demonstrated that CDK descriptors together with a set of Smiles Arbitrary Target Specification (SMARTS) keys had good statistics [κ = 0.43, sensitivity = 0.57, specificity = 0.91, and positive predicted value (PPV) = 0.64], equivalent to those of models built with commercial Molecular Operating Environment 2D (MOE2D) and the same set of SMARTS keys (κ = 0.43, sensitivity = 0.58, specificity = 0.91, and PPV = 0.63). Extending the dataset to ∼193,000 molecules and generating a continuous model using Cubist with a combination of CDK and SMARTS keys or MOE2D and SMARTS keys confirmed this observation. When the continuous predictions and actual values were binned to get a categorical score we observed a similar κ statistic (0.42). The same combination of descriptor set and modeling method was applied to passive permeability and P-glycoprotein efflux data with similar model testing statistics. In summary, open source tools demonstrated predictive results comparable to those of commercial software with attendant cost savings. We discuss the advantages and disadvantages of open source descriptors and the opportunity for their use as a tool for organizations to share data precompetitively, avoiding repetition and assisting drug discovery.

  14. Development of nonlinear acoustic propagation analysis tool toward realization of loud noise environment prediction in aeronautics

    Energy Technology Data Exchange (ETDEWEB)

    Kanamori, Masashi, E-mail: kanamori.masashi@jaxa.jp; Takahashi, Takashi, E-mail: takahashi.takashi@jaxa.jp; Aoyama, Takashi, E-mail: aoyama.takashi@jaxa.jp [Japan Aerospace Exploration Agency, 7-44-1, Jindaijihigashi-machi, Chofu, Tokyo (Japan)

    2015-10-28

    Shown in this paper is an introduction of a prediction tool for the propagation of loud noise with the application to the aeronautics in mind. The tool, named SPnoise, is based on HOWARD approach, which can express almost exact multidimensionality of the diffraction effect at the cost of back scattering. This paper argues, in particular, the prediction of the effect of atmospheric turbulence on sonic boom as one of the important issues in aeronautics. Thanks to the simple and efficient modeling of the atmospheric turbulence, SPnoise successfully re-creates the feature of the effect, which often emerges in the region just behind the front and rear shock waves in the sonic boom signature.

  15. Providing access to risk prediction tools via the HL7 XML-formatted risk web service.

    Science.gov (United States)

    Chipman, Jonathan; Drohan, Brian; Blackford, Amanda; Parmigiani, Giovanni; Hughes, Kevin; Bosinoff, Phil

    2013-07-01

    Cancer risk prediction tools provide valuable information to clinicians but remain computationally challenging. Many clinics find that CaGene or HughesRiskApps fit their needs for easy- and ready-to-use software to obtain cancer risks; however, these resources may not fit all clinics' needs. The HughesRiskApps Group and BayesMendel Lab therefore developed a web service, called "Risk Service", which may be integrated into any client software to quickly obtain standardized and up-to-date risk predictions for BayesMendel tools (BRCAPRO, MMRpro, PancPRO, and MelaPRO), the Tyrer-Cuzick IBIS Breast Cancer Risk Evaluation Tool, and the Colorectal Cancer Risk Assessment Tool. Software clients that can convert their local structured data into the HL7 XML-formatted family and clinical patient history (Pedigree model) may integrate with the Risk Service. The Risk Service uses Apache Tomcat and Apache Axis2 technologies to provide an all Java web service. The software client sends HL7 XML information containing anonymized family and clinical history to a Dana-Farber Cancer Institute (DFCI) server, where it is parsed, interpreted, and processed by multiple risk tools. The Risk Service then formats the results into an HL7 style message and returns the risk predictions to the originating software client. Upon consent, users may allow DFCI to maintain the data for future research. The Risk Service implementation is exemplified through HughesRiskApps. The Risk Service broadens the availability of valuable, up-to-date cancer risk tools and allows clinics and researchers to integrate risk prediction tools into their own software interface designed for their needs. Each software package can collect risk data using its own interface, and display the results using its own interface, while using a central, up-to-date risk calculator. This allows users to choose from multiple interfaces while always getting the latest risk calculations. Consenting users contribute their data for future

  16. Multirule Based Diagnostic Approach for the Fog Predictions Using WRF Modelling Tool

    Directory of Open Access Journals (Sweden)

    Swagata Payra

    2014-01-01

    Full Text Available The prediction of fog onset remains difficult despite the progress in numerical weather prediction. It is a complex process and requires adequate representation of the local perturbations in weather prediction models. It mainly depends upon microphysical and mesoscale processes that act within the boundary layer. This study utilizes a multirule based diagnostic (MRD approach using postprocessing of the model simulations for fog predictions. The empiricism involved in this approach is mainly to bridge the gap between mesoscale and microscale variables, which are related to mechanism of the fog formation. Fog occurrence is a common phenomenon during winter season over Delhi, India, with the passage of the western disturbances across northwestern part of the country accompanied with significant amount of moisture. This study implements the above cited approach for the prediction of occurrences of fog and its onset time over Delhi. For this purpose, a high resolution weather research and forecasting (WRF model is used for fog simulations. The study involves depiction of model validation and postprocessing of the model simulations for MRD approach and its subsequent application to fog predictions. Through this approach model identified foggy and nonfoggy days successfully 94% of the time. Further, the onset of fog events is well captured within an accuracy of 30–90 minutes. This study demonstrates that the multirule based postprocessing approach is a useful and highly promising tool in improving the fog predictions.

  17. A prediction tool for real-time application in the disruption protection system at JET

    International Nuclear Information System (INIS)

    Cannas, B.; Fanni, A.; Sonato, P.; Zedda, M.K.

    2007-01-01

    A disruption prediction system, based on neural networks, is presented in this paper. The system is ideally suitable for on-line application in the disruption avoidance and/or mitigation scheme at the JET tokamak. A multi-layer perceptron (MLP) predictor module has been trained on nine plasma diagnostic signals extracted from 86 disruptive pulses, selected from four years of JET experiments in the pulse range 47830-57346 (from 1999 to 2002). The disruption class of the disruptive pulses is available. In particular, the selected pulses belong to four classes (density limit/high radiated power, internal transport barrier, mode lock and h-mode/l-mode). A self-organizing map has been used to select the samples of the pulses to train the MLP predictor module and to determine its target, increasing the prediction capability of the system. The prediction performance has been tested over 86 disruptive and 102 non-disruptive pulses. The test has been performed presenting to the network all the samples of each pulse sampled every 20 ms. The missed alarm rate and the false alarm rate of the predictor, up to 100 ms prior to the disruption time, are 23% and 1%, respectively. Recent plasma configurations might present features different from those observed in the experiments used in the training set. This 'novelty' can lead to incorrect behaviour of the predictor. To improve the robustness and reliability of the system, a novelty detection module has been integrated in the prediction system, increasing the system performance and resulting in a missed alarm rate reduced to 7% and a false alarm rate reduced to 0%

  18. Tools for Predicting Optical Damage on Inertial Confinement Fusion-Class Laser Systems

    International Nuclear Information System (INIS)

    Nostrand, M.C.; Carr, C.W.; Liao, Z.M.; Honig, J.; Spaeth, M.L.; Manes, K.R.; Johnson, M.A.; Adams, J.J.; Cross, D.A.; Negres, R.A.; Widmayer, C.C.; Williams, W.H.; Matthews, M.J.; Jancaitis, K.S.; Kegelmeyer, L.M.

    2010-01-01

    Operating a fusion-class laser to its full potential requires a balance of operating constraints. On the one hand, the total laser energy delivered must be high enough to give an acceptable probability for ignition success. On the other hand, the laser-induced optical damage levels must be low enough to be acceptably handled with the available infrastructure and budget for optics recycle. Our research goal was to develop the models, database structures, and algorithmic tools (which we collectively refer to as ''Loop Tools'') needed to successfully maintain this balance. Predictive models are needed to plan for and manage the impact of shot campaigns from proposal, to shot, and beyond, covering a time span of years. The cost of a proposed shot campaign must be determined from these models, and governance boards must decide, based on predictions, whether to incorporate a given campaign into the facility shot plan based upon available resources. Predictive models are often built on damage ''rules'' derived from small beam damage tests on small optics. These off-line studies vary the energy, pulse-shape and wavelength in order to understand how these variables influence the initiation of damage sites and how initiated damage sites can grow upon further exposure to UV light. It is essential to test these damage ''rules'' on full-scale optics exposed to the complex conditions of an integrated ICF-class laser system. Furthermore, monitoring damage of optics on an ICF-class laser system can help refine damage rules and aid in the development of new rules. Finally, we need to develop the algorithms and data base management tools for implementing these rules in the Loop Tools. The following highlights progress in the development of the loop tools and their implementation.

  19. Tools for Predicting Optical Damage on Inertial Confinement Fusion-Class Laser Systems

    Energy Technology Data Exchange (ETDEWEB)

    Nostrand, M C; Carr, C W; Liao, Z M; Honig, J; Spaeth, M L; Manes, K R; Johnson, M A; Adams, J J; Cross, D A; Negres, R A; Widmayer, C C; Williams, W H; Matthews, M J; Jancaitis, K S; Kegelmeyer, L M

    2010-12-20

    Operating a fusion-class laser to its full potential requires a balance of operating constraints. On the one hand, the total laser energy delivered must be high enough to give an acceptable probability for ignition success. On the other hand, the laser-induced optical damage levels must be low enough to be acceptably handled with the available infrastructure and budget for optics recycle. Our research goal was to develop the models, database structures, and algorithmic tools (which we collectively refer to as ''Loop Tools'') needed to successfully maintain this balance. Predictive models are needed to plan for and manage the impact of shot campaigns from proposal, to shot, and beyond, covering a time span of years. The cost of a proposed shot campaign must be determined from these models, and governance boards must decide, based on predictions, whether to incorporate a given campaign into the facility shot plan based upon available resources. Predictive models are often built on damage ''rules'' derived from small beam damage tests on small optics. These off-line studies vary the energy, pulse-shape and wavelength in order to understand how these variables influence the initiation of damage sites and how initiated damage sites can grow upon further exposure to UV light. It is essential to test these damage ''rules'' on full-scale optics exposed to the complex conditions of an integrated ICF-class laser system. Furthermore, monitoring damage of optics on an ICF-class laser system can help refine damage rules and aid in the development of new rules. Finally, we need to develop the algorithms and data base management tools for implementing these rules in the Loop Tools. The following highlights progress in the development of the loop tools and their implementation.

  20. Human Splicing Finder: an online bioinformatics tool to predict splicing signals

    OpenAIRE

    Desmet, Francois-Olivier; Hamroun, Dalil; Lalande, Marine; Collod-Beroud, Gwenaelle; Claustres, Mireille; Beroud, Christophe

    2009-01-01

    International audience; Thousands of mutations are identified yearly. Although many directly affect protein expression, an increasing proportion of mutations is now believed to influence mRNA splicing. They mostly affect existing splice sites, but synonymous, non-synonymous or nonsense mutations can also create or disrupt splice sites or auxiliary cis-splicing sequences. To facilitate the analysis of the different mutations, we designed Human Splicing Finder (HSF), a tool to predict the effec...

  1. A Discussion of Virtual Reality As a New Tool for Training Healthcare Professionals.

    Science.gov (United States)

    Fertleman, Caroline; Aubugeau-Williams, Phoebe; Sher, Carmel; Lim, Ai-Nee; Lumley, Sophie; Delacroix, Sylvie; Pan, Xueni

    2018-01-01

    Virtual reality technology is an exciting and emerging field with vast applications. Our study sets out the viewpoint that virtual reality software could be a new focus of direction in the development of training tools in medical education. We carried out a panel discussion at the Center for Behavior Change 3rd Annual Conference, prompted by the study, "The Responses of Medical General Practitioners to Unreasonable Patient Demand for Antibiotics--A Study of Medical Ethics Using Immersive Virtual Reality" (1). In Pan et al.'s study, 21 general practitioners (GPs) and GP trainees took part in a videoed, 15-min virtual reality scenario involving unnecessary patient demands for antibiotics. This paper was discussed in-depth at the Center for Behavior Change 3rd Annual Conference; the content of this paper is a culmination of findings and feedback from the panel discussion. The experts involved have backgrounds in virtual reality, general practice, medicines management, medical education and training, ethics, and philosophy. Virtual reality is an unexplored methodology to instigate positive behavioral change among clinicians where other methods have been unsuccessful, such as antimicrobial stewardship. There are several arguments in favor of use of virtual reality in medical education: it can be used for "difficult to simulate" scenarios and to standardize a scenario, for example, for use in exams. However, there are limitations to its usefulness because of the cost implications and the lack of evidence that it results in demonstrable behavior change.

  2. Sensory Integration Training Tool Design for Children with Autism Spectrum Disorder

    Directory of Open Access Journals (Sweden)

    Jiang Lijun

    2017-01-01

    Full Text Available This study aims to design a training tool for therapy of children with autism spectrum disorder (ASDs. Typically, ASDs pass through obstacle track several times with sandbags, which should be picked up from starting point and threw into a box at the end during sensory integration therapy. Counting the sandbags can help ASDs to have concept about the progress of mission. We redesign the counting box named “Skybox” which can help counting by playing sound after detect something throw in it. Aims to probe into the sound preference of two main subjects, an experiment with four kinds of sounds is conducted in this paper by using the method of paired comparisons. The result shows they like animals most, followed by human voice and nature sounds, and music instrument is the last. The material preference experiment shows two subjects like acrylic most, wood and paper are secondary while furry is the last. Skybox shortens their training time for 23.53%, 29.87% and 37.37% in three different projects. We consider that Skybox attracts ASDs therefore reduces their distraction and improves their performance in the usability test.

  3. Feasibility of adapting the fundamentals of laparoscopic surgery trainer box to endoscopic skills training tool.

    Science.gov (United States)

    Crespin, Oscar M; Okrainec, Allan; Kwong, Andrea V; Habaz, Ilay; Jimenez, Maria Carolina; Szasz, Peter; Weiss, Ethan; Gonzalez, Cecilia G; Mosko, Jeffrey D; Liu, Louis W C; Swanstrom, Lee L; Perretta, Silvana; Shlomovitz, Eran

    2018-06-01

    The fundamentals of laparoscopic surgery (FLS) training box is a validated tool, already accessible to surgical trainees to hone their laparoscopic skills. We aim to investigate the feasibility of adapting the FLS box for the practice and assessment of endoscopic skills. This would allow for a highly available, reusable, low-cost, mechanical trainer. The design and development process was based on a user-centered design, which is a combination of the design thinking method and cognitive task analysis. The process comprises four phases: empathy, cognitive, prototyping/adaptation, and end user testing. The underlying idea was to utilize as many of the existing components of FLS training to maintain simplicity and cost effectiveness while allowing for the practice of clinically relevant endoscopic skills. A sample size of 18 participants was calculated to be sufficient to detect performance differences between experts and trainees using a two tailed t test with alpha set at 0.05, standard deviation of 5.5, and a power of 80%. Adaptation to the FLS box included two fundamental attachments: a front panel with an insertion point for an endoscope and a shaft which provides additional support and limits movement of the scope. The panel also allows for mounting of retroflexion tasks. Six endoscopic tasks inspired by FLS were designed (two of which utilize existing FLS components). Pilot testing with 38 participants showed high user's satisfaction and demonstrated that the trainer was robust and reliable. Task performance times was able to discriminate between trainees and experts for all six tasks. A mechanical, reusable, low-cost adaptation of the FLS training box for endoscopic skills is feasible and has high user satisfaction. Preliminary testing shows that the simulator is able to discriminate between trainees and experts. Following further validation, this adaptation may act as a supplement to the FES program.

  4. NetH2pan: A Computational Tool to Guide MHC peptide prediction on Murine Tumors

    DEFF Research Database (Denmark)

    DeVette, Christa I; Andreatta, Massimo; Bardet, Wilfried

    2018-01-01

    With the advancement of personalized cancer immunotherapies, new tools are needed to identify tumor antigens and evaluate T-cell responses in model systems, specifically those that exhibit clinically relevant tumor progression. Key transgenic mouse models of breast cancer are generated and mainta......With the advancement of personalized cancer immunotherapies, new tools are needed to identify tumor antigens and evaluate T-cell responses in model systems, specifically those that exhibit clinically relevant tumor progression. Key transgenic mouse models of breast cancer are generated...... for evaluating antigen specificity in the murine FVB strain. Our study provides the first detailed molecular and immunoproteomic characterization of the FVB H-2q MHC Class I alleles, including >8500 unique peptide ligands, a multi-allele murine MHC peptide prediction tool, and in vivo validation of these data...

  5. A Business Analytics Software Tool for Monitoring and Predicting Radiology Throughput Performance.

    Science.gov (United States)

    Jones, Stephen; Cournane, Seán; Sheehy, Niall; Hederman, Lucy

    2016-12-01

    Business analytics (BA) is increasingly being utilised by radiology departments to analyse and present data. It encompasses statistical analysis, forecasting and predictive modelling and is used as an umbrella term for decision support and business intelligence systems. The primary aim of this study was to determine whether utilising BA technologies could contribute towards improved decision support and resource management within radiology departments. A set of information technology requirements were identified with key stakeholders, and a prototype BA software tool was designed, developed and implemented. A qualitative evaluation of the tool was carried out through a series of semi-structured interviews with key stakeholders. Feedback was collated, and emergent themes were identified. The results indicated that BA software applications can provide visibility of radiology performance data across all time horizons. The study demonstrated that the tool could potentially assist with improving operational efficiencies and management of radiology resources.

  6. Comparison of various tool wear prediction methods during end milling of metal matrix composite

    Science.gov (United States)

    Wiciak, Martyna; Twardowski, Paweł; Wojciechowski, Szymon

    2018-02-01

    In this paper, the problem of tool wear prediction during milling of hard-to-cut metal matrix composite Duralcan™ was presented. The conducted research involved the measurements of acceleration of vibrations during milling with constant cutting conditions, and evaluation of the flank wear. Subsequently, the analysis of vibrations in time and frequency domain, as well as the correlation of the obtained measures with the tool wear values were conducted. The validation of tool wear diagnosis in relation to selected diagnostic measures was carried out with the use of one variable and two variables regression models, as well as with the application of artificial neural networks (ANN). The comparative analysis of the obtained results enable.

  7. Predictive Function Control for Communication-Based Train Control (CBTC Systems

    Directory of Open Access Journals (Sweden)

    Bing Bu

    2013-01-01

    Full Text Available In Communication-Based Train Control (CBTC systems, random transmission delays and packet drops are inevitable in the wireless networks, which could result in unnecessary traction, brakes or even emergency brakes of trains, losses of line capacity and passenger dissatisfaction. This paper applies predictive function control technology with a mixed H2/∞ control approach to improve the control performances. The controller is in the state feedback form and satisfies the requirement of quadratic input and state constraints. A linear matrix inequality (LMI approach is developed to solve the control problem. The proposed method attenuates disturbances by incorporating H2/∞ into the control scheme. The control command from the automatic train operation (ATO is included in the reward function to optimize the train's running profile. The influence of transmission delays and packet drops is alleviated through improving the performances of the controller. Simulation results show that the method is effective to improve the performances and robustness of CBTC systems.

  8. Tools for Consumer Rights Protection in the Prediction of Electronic Virtual Market and Technological Changes

    Directory of Open Access Journals (Sweden)

    Mikuláš Gangur

    2014-05-01

    Full Text Available Electronic virtual markets can serve as an alternative tool for collecting information that is spread among numerous experts. This is the principal market functionality from the operators’ point of view. On the other hand it is profits that are the main interest of the market participants. What they expect from the market is liquidity as high as possible and the opportunity for unrestricted trading. Both the operator and the electronic market participant can be considered consumers of this particular market with reference to the requirements for the accuracy of its outputs but also for the market liquidity. Both the above mentioned groups of consumers (the operators and the participants themselves expect protection of their specific consumer rights, i.e. securing the two above mentioned functionalities of the market. These functionalities of the electronic market are, however, influenced by many factors, among others by participants’ activity. The article deals with the motivation tools that may improve the quality of the prediction market. In the prediction electronic virtual market there may be situations in which the commonly used tools for increasing business activities described in the published literature are not significantly effective. For such situations we suggest a new type of motivation incentive consisting in penalizing the individual market participants whose funds are not placed in the market. The functionality of the proposed motivation incentive is presented on the example of the existing data gained from the electronic virtual prediction market which is actively operated.

  9. Bigger Data, Collaborative Tools and the Future of Predictive Drug Discovery

    Science.gov (United States)

    Clark, Alex M.; Swamidass, S. Joshua; Litterman, Nadia; Williams, Antony J.

    2014-01-01

    Over the past decade we have seen a growth in the provision of chemistry data and cheminformatics tools as either free websites or software as a service (SaaS) commercial offerings. These have transformed how we find molecule-related data and use such tools in our research. There have also been efforts to improve collaboration between researchers either openly or through secure transactions using commercial tools. A major challenge in the future will be how such databases and software approaches handle larger amounts of data as it accumulates from high throughput screening and enables the user to draw insights, enable predictions and move projects forward. We now discuss how information from some drug discovery datasets can be made more accessible and how privacy of data should not overwhelm the desire to share it at an appropriate time with collaborators. We also discuss additional software tools that could be made available and provide our thoughts on the future of predictive drug discovery in this age of big data. We use some examples from our own research on neglected diseases, collaborations, mobile apps and algorithm development to illustrate these ideas. PMID:24943138

  10. iPat: intelligent prediction and association tool for genomic research.

    Science.gov (United States)

    Chen, Chunpeng James; Zhang, Zhiwu

    2018-06-01

    The ultimate goal of genomic research is to effectively predict phenotypes from genotypes so that medical management can improve human health and molecular breeding can increase agricultural production. Genomic prediction or selection (GS) plays a complementary role to genome-wide association studies (GWAS), which is the primary method to identify genes underlying phenotypes. Unfortunately, most computing tools cannot perform data analyses for both GWAS and GS. Furthermore, the majority of these tools are executed through a command-line interface (CLI), which requires programming skills. Non-programmers struggle to use them efficiently because of the steep learning curves and zero tolerance for data formats and mistakes when inputting keywords and parameters. To address these problems, this study developed a software package, named the Intelligent Prediction and Association Tool (iPat), with a user-friendly graphical user interface. With iPat, GWAS or GS can be performed using a pointing device to simply drag and/or click on graphical elements to specify input data files, choose input parameters and select analytical models. Models available to users include those implemented in third party CLI packages such as GAPIT, PLINK, FarmCPU, BLINK, rrBLUP and BGLR. Users can choose any data format and conduct analyses with any of these packages. File conversions are automatically conducted for specified input data and selected packages. A GWAS-assisted genomic prediction method was implemented to perform genomic prediction using any GWAS method such as FarmCPU. iPat was written in Java for adaptation to multiple operating systems including Windows, Mac and Linux. The iPat executable file, user manual, tutorials and example datasets are freely available at http://zzlab.net/iPat. zhiwu.zhang@wsu.edu.

  11. Improvements to executive function during exercise training predict maintenance of physical activity over the following year

    Directory of Open Access Journals (Sweden)

    John eBest

    2014-05-01

    Full Text Available Previous studies have shown that exercise training benefits cognitive, neural, and physical health markers in older adults. It is likely that these positive effects will diminish if participants return to sedentary lifestyles following training cessation. Theory posits that that the neurocognitive processes underlying self-regulation, namely executive function (EF, are important to maintaining positive health behaviors. Therefore, we examined whether better EF performance in older women would predict greater adherence to routine physical activity (PA over 1 year following a 12-month resistance exercise training randomized controlled trial. The study sample consisted of 125 community-dwelling women aged 65 to 75 years old. Our primary outcome measure was self-reported PA, as measured by the Physical Activity Scale for the Elderly (PASE, assessed on a monthly basis from month 13 to month 25. Executive function was assessed using the Stroop Test at baseline (month 0 and post-training (month 12. Latent growth curve analyses showed that, on average, PA decreased during the follow-up period but at a decelerating rate. Women who made greater improvements to EF during the training period showed better adherence to PA during the 1-year follow-up period (β = -.36, p .10. Overall, these findings suggest that improving EF plays an important role in whether older women maintain higher levels of PA following exercise training and that this association is only apparent after training when environmental support for PA is low.

  12. Model training across multiple breeding cycles significantly improves genomic prediction accuracy in rye (Secale cereale L.).

    Science.gov (United States)

    Auinger, Hans-Jürgen; Schönleben, Manfred; Lehermeier, Christina; Schmidt, Malthe; Korzun, Viktor; Geiger, Hartwig H; Piepho, Hans-Peter; Gordillo, Andres; Wilde, Peer; Bauer, Eva; Schön, Chris-Carolin

    2016-11-01

    Genomic prediction accuracy can be significantly increased by model calibration across multiple breeding cycles as long as selection cycles are connected by common ancestors. In hybrid rye breeding, application of genome-based prediction is expected to increase selection gain because of long selection cycles in population improvement and development of hybrid components. Essentially two prediction scenarios arise: (1) prediction of the genetic value of lines from the same breeding cycle in which model training is performed and (2) prediction of lines from subsequent cycles. It is the latter from which a reduction in cycle length and consequently the strongest impact on selection gain is expected. We empirically investigated genome-based prediction of grain yield, plant height and thousand kernel weight within and across four selection cycles of a hybrid rye breeding program. Prediction performance was assessed using genomic and pedigree-based best linear unbiased prediction (GBLUP and PBLUP). A total of 1040 S 2 lines were genotyped with 16 k SNPs and each year testcrosses of 260 S 2 lines were phenotyped in seven or eight locations. The performance gap between GBLUP and PBLUP increased significantly for all traits when model calibration was performed on aggregated data from several cycles. Prediction accuracies obtained from cross-validation were in the order of 0.70 for all traits when data from all cycles (N CS  = 832) were used for model training and exceeded within-cycle accuracies in all cases. As long as selection cycles are connected by a sufficient number of common ancestors and prediction accuracy has not reached a plateau when increasing sample size, aggregating data from several preceding cycles is recommended for predicting genetic values in subsequent cycles despite decreasing relatedness over time.

  13. Psychomotor testing predicts rate of skill acquisition for proficiency-based laparoscopic skills training.

    Science.gov (United States)

    Stefanidis, Dimitrios; Korndorffer, James R; Black, F William; Dunne, J Bruce; Sierra, Rafael; Touchard, Cheri L; Rice, David A; Markert, Ronald J; Kastl, Peter R; Scott, Daniel J

    2006-08-01

    Laparoscopic simulator training translates into improved operative performance. Proficiency-based curricula maximize efficiency by tailoring training to meet the needs of each individual; however, because rates of skill acquisition vary widely, such curricula may be difficult to implement. We hypothesized that psychomotor testing would predict baseline performance and training duration in a proficiency-based laparoscopic simulator curriculum. Residents (R1, n = 20) were enrolled in an IRB-approved prospective study at the beginning of the academic year. All completed the following: a background information survey, a battery of 12 innate ability measures (5 motor, and 7 visual-spatial), and baseline testing on 3 validated simulators (5 videotrainer [VT] tasks, 12 virtual reality [minimally invasive surgical trainer-virtual reality, MIST-VR] tasks, and 2 laparoscopic camera navigation [LCN] tasks). Participants trained to proficiency, and training duration and number of repetitions were recorded. Baseline test scores were correlated to skill acquisition rate. Cutoff scores for each predictive test were calculated based on a receiver operator curve, and their sensitivity and specificity were determined in identifying slow learners. Only the Cards Rotation test correlated with baseline simulator ability on VT and LCN. Curriculum implementation required 347 man-hours (6-person team) and 795,000 dollars of capital equipment. With an attendance rate of 75%, 19 of 20 residents (95%) completed the curriculum by the end of the academic year. To complete training, a median of 12 hours (range, 5.5-21), and 325 repetitions (range, 171-782) were required. Simulator score improvement was 50%. Training duration and repetitions correlated with prior video game and billiard exposure, grooved pegboard, finger tap, map planning, Rey Figure Immediate Recall score, and baseline performance on VT and LCN. The map planning cutoff score proved most specific in identifying slow learners

  14. Summary of Training Workshop on the Use of NASA tools for Coastal Resource Management in the Gulf of Mexico

    Energy Technology Data Exchange (ETDEWEB)

    Judd, Chaeli; Judd, Kathleen S.; Gulbransen, Thomas C.; Thom, Ronald M.

    2009-03-01

    A two-day training workshop was held in Xalapa, Mexico from March 10-11 2009 with the goal of training end users from the southern Gulf of Mexico states of Campeche and Veracruz in the use of tools to support coastal resource management decision-making. The workshop was held at the computer laboratory of the Institute de Ecologia, A.C. (INECOL). This report summarizes the results of that workshop and is a deliverable to our NASA client.

  15. Risk determination after an acute myocardial infarction: review of 3 clinical risk prediction tools.

    Science.gov (United States)

    Scruth, Elizabeth Ann; Page, Karen; Cheng, Eugene; Campbell, Michelle; Worrall-Carter, Linda

    2012-01-01

    The objective of the study was to provide comprehensive information for the clinical nurse specialist (CNS) on commonly used clinical prediction (risk assessment) tools used to estimate risk of a secondary cardiac or noncardiac event and mortality in patients undergoing primary percutaneous coronary intervention (PCI) for ST-elevation myocardial infarction (STEMI). The evolution and widespread adoption of primary PCI represent major advances in the treatment of acute myocardial infarction, specifically STEMI. The American College of Cardiology and the American Heart Association have recommended early risk stratification for patients presenting with acute coronary syndromes using several clinical risk scores to identify patients' mortality and secondary event risk after PCI. Clinical nurse specialists are integral to any performance improvement strategy. Their knowledge and understandings of clinical prediction tools will be essential in carrying out important assessment, identifying and managing risk in patients who have sustained a STEMI, and enhancing discharge education including counseling on medications and lifestyle changes. Over the past 2 decades, risk scores have been developed from clinical trials to facilitate risk assessment. There are several risk scores that can be used to determine in-hospital and short-term survival. This article critiques the most common tools: the Thrombolytic in Myocardial Infarction risk score, the Global Registry of Acute Coronary Events risk score, and the Controlled Abciximab and Device Investigation to Lower Late Angioplasty Complications risk score. The importance of incorporating risk screening assessment tools (that are important for clinical prediction models) to guide therapeutic management of patients cannot be underestimated. The ability to forecast secondary risk after a STEMI will assist in determining which patients would require the most aggressive level of treatment and monitoring postintervention including

  16. Getting nowhere fast: trade-off between speed and precision in training to execute image-guided hand-tool movements

    Directory of Open Access Journals (Sweden)

    Anil Ufuk Batmaz

    2016-11-01

    Full Text Available Abstract Background The speed and precision with which objects are moved by hand or hand-tool interaction under image guidance depend on a specific type of visual and spatial sensorimotor learning. Novices have to learn to optimally control what their hands are doing in a real-world environment while looking at an image representation of the scene on a video monitor. Previous research has shown slower task execution times and lower performance scores under image-guidance compared with situations of direct action viewing. The cognitive processes for overcoming this drawback by training are not yet understood. Methods We investigated the effects of training on the time and precision of direct view versus image guided object positioning on targets of a Real-world Action Field (RAF. Two men and two women had to learn to perform the task as swiftly and as precisely as possible with their dominant hand, using a tool or not and wearing a glove or not. Individuals were trained in sessions of mixed trial blocks with no feed-back. Results As predicted, image-guidance produced significantly slower times and lesser precision in all trainees and sessions compared with direct viewing. With training, all trainees get faster in all conditions, but only one of them gets reliably more precise in the image-guided conditions. Speed-accuracy trade-offs in the individual performance data show that the highest precision scores and steepest learning curve, for time and precision, were produced by the slowest starter. Fast starters produced consistently poorer precision scores in all sessions. The fastest starter showed no sign of stable precision learning, even after extended training. Conclusions Performance evolution towards optimal precision is compromised when novices start by going as fast as they can. The findings have direct implications for individual skill monitoring in training programmes for image-guided technology applications with human operators.

  17. Biodiversity in environmental assessment-current practice and tools for prediction

    International Nuclear Information System (INIS)

    Gontier, Mikael; Balfors, Berit; Moertberg, Ulla

    2006-01-01

    Habitat loss and fragmentation are major threats to biodiversity. Environmental impact assessment and strategic environmental assessment are essential instruments used in physical planning to address such problems. Yet there are no well-developed methods for quantifying and predicting impacts of fragmentation on biodiversity. In this study, a literature review was conducted on GIS-based ecological models that have potential as prediction tools for biodiversity assessment. Further, a review of environmental impact statements for road and railway projects from four European countries was performed, to study how impact prediction concerning biodiversity issues was addressed. The results of the study showed the existing gap between research in GIS-based ecological modelling and current practice in biodiversity assessment within environmental assessment

  18. The predictive and external validity of the STarT Back Tool in Danish primary care.

    Science.gov (United States)

    Morsø, Lars; Kent, Peter; Albert, Hanne B; Hill, Jonathan C; Kongsted, Alice; Manniche, Claus

    2013-08-01

    The STarT Back Tool (SBT) was recently translated into Danish and its concurrent validity described. This study tested the predictive validity of the Danish SBT. Danish primary care patients (n = 344) were compared to a UK cohort. SBT subgroup validity for predicting high activity limitation at 3 months' follow-up was assessed using descriptive proportions, relative risks, AUC and odds ratios. The SBT had a statistically similar predictive ability in Danish primary care as in UK primary care. Unadjusted relative risks for poor clinical outcome on activity limitation in the Danish cohort were 2.4 (1.7-3.4) for the medium-risk subgroup and 2.8 (1.8-3.8) for the high-risk subgroup versus 3.1 (2.5-3.9) and 4.5 (3.6-5.6) for the UK cohort. Adjusting for confounders appeared to explain the lower predictive ability of the Danish high-risk group. The Danish SBT distinguished between low- and medium-risk subgroups with a similar predictive ability of the UK SBT. That distinction is useful information for informing patients about their expected prognosis and may help guiding clinicians' choice of treatment. However, cross-cultural differences in the SBT psychosocial subscale may reduce the predictive ability of the high-risk subgroup in Danish primary care.

  19. A study on the effectiveness of task manager board game as a training tool in managing project

    Science.gov (United States)

    Yusof, Shahrul Azmi Mohd; Radzi, Shanizan Herman Md; Din, Sharifah Nadera Syed; Khalid, Nurhafizah

    2016-08-01

    Nowadays, games have become one of the useful tools in training. Many instructors choose to use games to enhance the way of delivering the subject. Failure to apply the suitable tool in training will lead to discouragement in learning and causing waste to the resources. An effective game will help the student understand the concept quickly. It can also help students to get involve in experiential learning where the student can manage and solve the problem as in the actual situation. This study will focus on the effectiveness of board game as a training tool for managing projects. This game has 4 tasks to be completed by students. They will be divided into a group of 4 or 5. Two methods are used in this study, pilot test, and post-test. These methods are chosen to analyze the effectiveness of using Task Manager Board Game as a teaching tool and the improvement of student's knowledge in project management. Three sub-components assessed were motivation, user experience and learning using case studies on Kirkpatrick's level one base on the perception of the students. The result indicated that the use of Task Manager board game as a training tool for managing project has a positive impact on students. It helps students to experience the situation of managing projects. It is one of the easiest ways for improving time management, human resources and communication skill.

  20. Effective e-Training: Using a Course Management System and e-Learning Tools to Train Library Employees

    Science.gov (United States)

    See, Andrew; Teetor, Travis Stephen

    2014-01-01

    In the summer of 2012, the University of Arizona Libraries implemented an online training program to effectively train Access Services staff and student employees at a large academic research library. This article discusses the program, which was built using a course management system (D2L) and various e-Learning software applications (Articulate…

  1. lncRScan-SVM: A Tool for Predicting Long Non-Coding RNAs Using Support Vector Machine.

    Science.gov (United States)

    Sun, Lei; Liu, Hui; Zhang, Lin; Meng, Jia

    2015-01-01

    Functional long non-coding RNAs (lncRNAs) have been bringing novel insight into biological study, however it is still not trivial to accurately distinguish the lncRNA transcripts (LNCTs) from the protein coding ones (PCTs). As various information and data about lncRNAs are preserved by previous studies, it is appealing to develop novel methods to identify the lncRNAs more accurately. Our method lncRScan-SVM aims at classifying PCTs and LNCTs using support vector machine (SVM). The gold-standard datasets for lncRScan-SVM model training, lncRNA prediction and method comparison were constructed according to the GENCODE gene annotations of human and mouse respectively. By integrating features derived from gene structure, transcript sequence, potential codon sequence and conservation, lncRScan-SVM outperforms other approaches, which is evaluated by several criteria such as sensitivity, specificity, accuracy, Matthews correlation coefficient (MCC) and area under curve (AUC). In addition, several known human lncRNA datasets were assessed using lncRScan-SVM. LncRScan-SVM is an efficient tool for predicting the lncRNAs, and it is quite useful for current lncRNA study.

  2. Utility of Eating Assessment Tool-10 in Predicting Aspiration in Patients with Unilateral Vocal Fold Paralysis.

    Science.gov (United States)

    Zuniga, Steven A; Ebersole, Barbara; Jamal, Nausheen

    2018-03-01

    Objective Examine the incidence of penetration/aspiration in patients with unilateral vocal fold immobility and investigate the relationship with self-reported perception of dysphagia. Study Design Case series with chart review. Setting Academic cancer center. Subjects and Methods Adult patients with unilateral vocal fold immobility diagnosed between 2014 and 2016 were reviewed. Patients were stratified into an aspiration group and a nonaspiration group using objective findings on flexible endoscopic evaluation of swallowing, as scored using Rosenbek's Penetration Aspiration Scale. Objective findings were compared to patient perception of dysphagia. Bivariate linear correlation analysis was performed to evaluate correlation between Eating Assessment Tool-10 scores and presence of aspiration. Tests of diagnostic accuracy were calculated to investigate the predictive value of Eating Assessment Tool-10 scores >9 on aspiration risk. Results Of the 35 patients with new-onset unilateral vocal fold immobility were evaluated, 25.7% (9/35) demonstrated tracheal aspiration. Mean ± SD Eating Assessment Tool-10 scores were 19.2 ± 13.7 for aspirators and 7.0 ± 7.8 for nonaspirators ( P = .016). A statistically significant correlation was demonstrated between increasing Eating Assessment Tool-10 scores and Penetration Aspiration Scale scores ( r = 0.511, P = .002). Diagnostic accuracy analysis for aspiration risk in patients with an Eating Assessment Tool-10 score >9 revealed a sensitivity of 77.8% and a specificity of 73.1%. Conclusion Patient perception of swallowing difficulty may have utility in predicting aspiration risk. An EAT-10 of >9 in patients with unilateral vocal fold immobility may portend up to a 5 times greater risk of aspiration. Routine swallow testing to assess for penetration/aspiration may be indicated in patients with unilateral vocal fold immobility.

  3. Predicting Workplace Transfer of Learning: A Study of Adult Learners Enrolled in a Continuing Professional Education Training Program

    Science.gov (United States)

    Nafukho, Fredrick Muyia; Alfred, Mary; Chakraborty, Misha; Johnson, Michelle; Cherrstrom, Catherine A.

    2017-01-01

    Purpose: The primary purpose of this study was to predict transfer of learning to workplace among adult learners enrolled in a continuing professional education (CPE) training program, specifically training courses offered through face-to-face, blended and online instruction formats. The study examined the predictive capacity of trainee…

  4. Exercise Black Skies 2008: Enhancing Live Training Through Virtual Preparation -- Part Two: An Evaluation of Tools and Techniques

    Science.gov (United States)

    2009-06-01

    visualisation tool. These tools are currently in use at the Surveillance and Control Training Unit (SACTU) in Williamtown, New South Wales, and the School...itself by facilitating the brevity and sharpness of learning points. The playback of video and audio was considered an extremely useful method of...The task assessor’s comments were supported by wall projections and audio replays of relevant mission segments that were controlled by an AAR

  5. Predicting complication risk in spine surgery: a prospective analysis of a novel risk assessment tool.

    Science.gov (United States)

    Veeravagu, Anand; Li, Amy; Swinney, Christian; Tian, Lu; Moraff, Adrienne; Azad, Tej D; Cheng, Ivan; Alamin, Todd; Hu, Serena S; Anderson, Robert L; Shuer, Lawrence; Desai, Atman; Park, Jon; Olshen, Richard A; Ratliff, John K

    2017-07-01

    OBJECTIVE The ability to assess the risk of adverse events based on known patient factors and comorbidities would provide more effective preoperative risk stratification. Present risk assessment in spine surgery is limited. An adverse event prediction tool was developed to predict the risk of complications after spine surgery and tested on a prospective patient cohort. METHODS The spinal Risk Assessment Tool (RAT), a novel instrument for the assessment of risk for patients undergoing spine surgery that was developed based on an administrative claims database, was prospectively applied to 246 patients undergoing 257 spinal procedures over a 3-month period. Prospectively collected data were used to compare the RAT to the Charlson Comorbidity Index (CCI) and the American College of Surgeons National Surgery Quality Improvement Program (ACS NSQIP) Surgical Risk Calculator. Study end point was occurrence and type of complication after spine surgery. RESULTS The authors identified 69 patients (73 procedures) who experienced a complication over the prospective study period. Cardiac complications were most common (10.2%). Receiver operating characteristic (ROC) curves were calculated to compare complication outcomes using the different assessment tools. Area under the curve (AUC) analysis showed comparable predictive accuracy between the RAT and the ACS NSQIP calculator (0.670 [95% CI 0.60-0.74] in RAT, 0.669 [95% CI 0.60-0.74] in NSQIP). The CCI was not accurate in predicting complication occurrence (0.55 [95% CI 0.48-0.62]). The RAT produced mean probabilities of 34.6% for patients who had a complication and 24% for patients who did not (p = 0.0003). The generated predicted values were stratified into low, medium, and high rates. For the RAT, the predicted complication rate was 10.1% in the low-risk group (observed rate 12.8%), 21.9% in the medium-risk group (observed 31.8%), and 49.7% in the high-risk group (observed 41.2%). The ACS NSQIP calculator consistently

  6. Perioperative Respiratory Adverse Events in Pediatric Ambulatory Anesthesia: Development and Validation of a Risk Prediction Tool.

    Science.gov (United States)

    Subramanyam, Rajeev; Yeramaneni, Samrat; Hossain, Mohamed Monir; Anneken, Amy M; Varughese, Anna M

    2016-05-01

    Perioperative respiratory adverse events (PRAEs) are the most common cause of serious adverse events in children receiving anesthesia. Our primary aim of this study was to develop and validate a risk prediction tool for the occurrence of PRAE from the onset of anesthesia induction until discharge from the postanesthesia care unit in children younger than 18 years undergoing elective ambulatory anesthesia for surgery and radiology. The incidence of PRAE was studied. We analyzed data from 19,059 patients from our department's quality improvement database. The predictor variables were age, sex, ASA physical status, morbid obesity, preexisting pulmonary disorder, preexisting neurologic disorder, and location of ambulatory anesthesia (surgery or radiology). Composite PRAE was defined as the presence of any 1 of the following events: intraoperative bronchospasm, intraoperative laryngospasm, postoperative apnea, postoperative laryngospasm, postoperative bronchospasm, or postoperative prolonged oxygen requirement. Development and validation of the risk prediction tool for PRAE were performed using a split sampling technique to split the database into 2 independent cohorts based on the year when the patient received ambulatory anesthesia for surgery and radiology using logistic regression. A risk score was developed based on the regression coefficients from the validation tool. The performance of the risk prediction tool was assessed by using tests of discrimination and calibration. The overall incidence of composite PRAE was 2.8%. The derivation cohort included 8904 patients, and the validation cohort included 10,155 patients. The risk of PRAE was 3.9% in the development cohort and 1.8% in the validation cohort. Age ≤ 3 years (versus >3 years), ASA physical status II or III (versus ASA physical status I), morbid obesity, preexisting pulmonary disorder, and surgery (versus radiology) significantly predicted the occurrence of PRAE in a multivariable logistic regression

  7. Developing site-specific interactive environmental management tools: An exciting method of communicating training, procedures, and other information

    Energy Technology Data Exchange (ETDEWEB)

    Jaeckels, J.M.

    1999-07-01

    Environmental managers are faced with numerous programs that must be communicated throughout their organizations. Among these are regulatory training programs, internal environmental policy, regulatory guidance/procedures and internal guidance/procedures. Traditional methods of delivering this type of information are typically confined to written materials and classroom training. There are many challenges faced by environmental managers with these traditional approaches including: determining if recipients of written plans or procedures are reading and comprehending the information; scheduling training sessions to reach all affected people across multiple schedules/shifts; and maintaining adequate training records. In addition, current trends toward performance-based or competency-based training requires a more consistent method of measuring and documenting performance. The use of interactive computer applications to present training or procedural information is a new and exciting tool for delivering environmental information to employees. Site-specific pictures, text, sound, and even video can be combined with multimedia software to create informative and highly interactive applications. Some of the applications that can be produced include integrated environmental training, educational pieces, and interactive environmental procedures. They can be executed from a CD-ROM, hard drive, network or a company Intranet. Collectively, the authors refer to these as interactive environmental management tools (IEMTs). This paper focuses on site-specific, interactive training as an example of an IEMT. Interactive training not only delivers a highly effective message, but can also be designed to focus on site-specific environmental issues that are unique to each company. Interactive training also lends itself well to automated record keeping functions and to reaching all affected employees.

  8. Feasibility of an Assessment Tool for Children's Competence to Consent to Predictive Genetic Testing: a Pilot Study.

    Science.gov (United States)

    Hein, Irma M; Troost, Pieter W; Lindeboom, Robert; Christiaans, Imke; Grisso, Thomas; van Goudoever, Johannes B; Lindauer, Ramón J L

    2015-12-01

    Knowledge on children's capacities to consent to medical treatment is limited. Also, age limits for asking children's consent vary considerably between countries. Decision-making on predictive genetic testing (PGT) is especially complicated, considering the ongoing ethical debate. In order to examine just age limits for alleged competence to consent in children, we evaluated feasibility of a standardized assessment tool, and investigated cutoff ages for children's competence to consent to PGT. We performed a pilot study, including 17 pediatric outpatients between 6 and 18 years at risk for an autosomal dominantly inherited cardiac disease, eligible for predictive genetic testing. The reference standard for competence was established by experts trained in the relevant criteria for competent decision-making. The MacArthur Competence Assessment Tool for Treatment (MacCAT-T) served as index test. Data analysis included raw agreement between competence classifications, difference in mean ages between children judged competent and judged incompetent, and estimation of cutoff ages for judgments of competence. Twelve (71 %) children were considered competent by the reference standard, and 16 (94 %) by the MacCAT-T, with an overall agreement of 76 %. The expert judgments disagreed in most cases, while the MacCAT-T judgments agreed in 65 %. Mean age of children judged incompetent was 9.3 years and of children judged competent 12.1 years (p = .035). With 90 % sensitivity, children younger than 10.0 years were judged incompetent, with 90 % specificity children older than 11.8 years were judged competent. Feasibility of the MacCAT-T in children is confirmed. Initial findings on age cutoffs are indicative for children between the age of 12 and 18 to be judged competent for involvement in the informed consent process. Future research on appropriate age-limits for children's alleged competence to consent is needed.

  9. Heart rate variability in prediction of individual adaptation to endurance training in recreational endurance runners.

    Science.gov (United States)

    Vesterinen, V; Häkkinen, K; Hynynen, E; Mikkola, J; Hokka, L; Nummela, A

    2013-03-01

    The aim of this study was to investigate whether nocturnal heart rate variability (HRV) can be used to predict changes in endurance performance during 28 weeks of endurance training. The training was divided into 14 weeks of basic training (BTP) and 14 weeks of intensive training periods (ITP). Endurance performance characteristics, nocturnal HRV, and serum hormone concentrations were measured before and after both training periods in 28 recreational endurance runners. During the study peak treadmill running speed (Vpeak ) improved by 7.5 ± 4.5%. No changes were observed in HRV indices after BTP, but after ITP, these indices increased significantly (HFP: 1.9%, P=0.026; TP: 1.7%, P=0.007). Significant correlations were observed between the change of Vpeak and HRV indices (TP: r=0.75, PHRV among recreational endurance runners, it seems that moderate- and high-intensity training are needed. This study showed that recreational endurance runners with a high HRV at baseline improved their endurance running performance after ITP more than runners with low baseline HRV. © 2011 John Wiley & Sons A/S.

  10. Development and Application of Predictive Tools for MHD Stability Limits in Tokamaks

    Energy Technology Data Exchange (ETDEWEB)

    Brennan, Dylan [Princeton Univ., NJ (United States); Miller, G. P. [Univ. of Tulsa, Tulsa, AZ (United States)

    2016-10-03

    This is a project to develop and apply analytic and computational tools to answer physics questions relevant to the onset of non-ideal magnetohydrodynamic (MHD) instabilities in toroidal magnetic confinement plasmas. The focused goal of the research is to develop predictive tools for these instabilities, including an inner layer solution algorithm, a resistive wall with control coils, and energetic particle effects. The production phase compares studies of instabilities in such systems using analytic techniques, PEST- III and NIMROD. Two important physics puzzles are targeted as guiding thrusts for the analyses. The first is to form an accurate description of the physics determining whether the resistive wall mode or a tearing mode will appear first as β is increased at low rotation and low error fields in DIII-D. The second is to understand the physical mechanism behind recent NIMROD results indicating strong damping and stabilization from energetic particle effects on linear resistive modes. The work seeks to develop a highly relevant predictive tool for ITER, advance the theoretical description of this physics in general, and analyze these instabilities in experiments such as ASDEX Upgrade, DIII-D, JET, JT-60U and NTSX. The awardee on this grant is the University of Tulsa. The research efforts are supervised principally by Dr. Brennan. Support is included for two graduate students, and a strong collaboration with Dr. John M. Finn of LANL. The work includes several ongoing collaborations with General Atomics, PPPL, and the NIMROD team, among others.

  11. Development and Application of Predictive Tools for MHD Stability Limits in Tokamaks

    International Nuclear Information System (INIS)

    Brennan, Dylan; Miller, G. P.

    2016-01-01

    This is a project to develop and apply analytic and computational tools to answer physics questions relevant to the onset of non-ideal magnetohydrodynamic (MHD) instabilities in toroidal magnetic confinement plasmas. The focused goal of the research is to develop predictive tools for these instabilities, including an inner layer solution algorithm, a resistive wall with control coils, and energetic particle effects. The production phase compares studies of instabilities in such systems using analytic techniques, PEST- III and NIMROD. Two important physics puzzles are targeted as guiding thrusts for the analyses. The first is to form an accurate description of the physics determining whether the resistive wall mode or a tearing mode will appear first as β is increased at low rotation and low error fields in DIII-D. The second is to understand the physical mechanism behind recent NIMROD results indicating strong damping and stabilization from energetic particle effects on linear resistive modes. The work seeks to develop a highly relevant predictive tool for ITER, advance the theoretical description of this physics in general, and analyze these instabilities in experiments such as ASDEX Upgrade, DIII-D, JET, JT-60U and NTSX. The awardee on this grant is the University of Tulsa. The research efforts are supervised principally by Dr. Brennan. Support is included for two graduate students, and a strong collaboration with Dr. John M. Finn of LANL. The work includes several ongoing collaborations with General Atomics, PPPL, and the NIMROD team, among others.

  12. A Multi-Center Prospective Derivation and Validation of a Clinical Prediction Tool for Severe Clostridium difficile Infection.

    LENUS (Irish Health Repository)

    Na, Xi

    2015-04-23

    Prediction of severe clinical outcomes in Clostridium difficile infection (CDI) is important to inform management decisions for optimum patient care. Currently, treatment recommendations for CDI vary based on disease severity but validated methods to predict severe disease are lacking. The aim of the study was to derive and validate a clinical prediction tool for severe outcomes in CDI.

  13. Structure Based Thermostability Prediction Models for Protein Single Point Mutations with Machine Learning Tools.

    Directory of Open Access Journals (Sweden)

    Lei Jia

    Full Text Available Thermostability issue of protein point mutations is a common occurrence in protein engineering. An application which predicts the thermostability of mutants can be helpful for guiding decision making process in protein design via mutagenesis. An in silico point mutation scanning method is frequently used to find "hot spots" in proteins for focused mutagenesis. ProTherm (http://gibk26.bio.kyutech.ac.jp/jouhou/Protherm/protherm.html is a public database that consists of thousands of protein mutants' experimentally measured thermostability. Two data sets based on two differently measured thermostability properties of protein single point mutations, namely the unfolding free energy change (ddG and melting temperature change (dTm were obtained from this database. Folding free energy change calculation from Rosetta, structural information of the point mutations as well as amino acid physical properties were obtained for building thermostability prediction models with informatics modeling tools. Five supervised machine learning methods (support vector machine, random forests, artificial neural network, naïve Bayes classifier, K nearest neighbor and partial least squares regression are used for building the prediction models. Binary and ternary classifications as well as regression models were built and evaluated. Data set redundancy and balancing, the reverse mutations technique, feature selection, and comparison to other published methods were discussed. Rosetta calculated folding free energy change ranked as the most influential features in all prediction models. Other descriptors also made significant contributions to increasing the accuracy of the prediction models.

  14. A Discussion of Virtual Reality As a New Tool for Training Healthcare Professionals

    Directory of Open Access Journals (Sweden)

    Caroline Fertleman

    2018-02-01

    Full Text Available BackgroundVirtual reality technology is an exciting and emerging field with vast applications. Our study sets out the viewpoint that virtual reality software could be a new focus of direction in the development of training tools in medical education. We carried out a panel discussion at the Center for Behavior Change 3rd Annual Conference, prompted by the study, “The Responses of Medical General Practitioners to Unreasonable Patient Demand for Antibiotics––A Study of Medical Ethics Using Immersive Virtual Reality” (1.MethodsIn Pan et al.’s study, 21 general practitioners (GPs and GP trainees took part in a videoed, 15-min virtual reality scenario involving unnecessary patient demands for antibiotics. This paper was discussed in-depth at the Center for Behavior Change 3rd Annual Conference; the content of this paper is a culmination of findings and feedback from the panel discussion. The experts involved have backgrounds in virtual reality, general practice, medicines management, medical education and training, ethics, and philosophy.ViewpointVirtual reality is an unexplored methodology to instigate positive behavioral change among clinicians where other methods have been unsuccessful, such as antimicrobial stewardship. There are several arguments in favor of use of virtual reality in medical education: it can be used for “difficult to simulate” scenarios and to standardize a scenario, for example, for use in exams. However, there are limitations to its usefulness because of the cost implications and the lack of evidence that it results in demonstrable behavior change.

  15. Development of a CME-associated geomagnetic storm intensity prediction tool

    Science.gov (United States)

    Wu, C. C.; DeHart, J. M.

    2015-12-01

    From 1995 to 2012, the Wind spacecraft recorded 168 magnetic cloud (MC) events. Among those events, 79 were found to have upstream shock waves and their source locations on the Sun were identified. Using a recipe of interplanetary magnetic field (IMF) Bz initial turning direction after shock (Wu et al., 1996, GRL), it is found that the north-south polarity of 66 (83.5%) out of the 79 events were accurately predicted. These events were tested and further analyzed, reaffirming that the Bz intial turning direction was accurate. The results also indicate that 37 of the 79 MCs originate from the north (of the Sun) averaged a Dst_min of -119 nT, whereas 42 of the MCs originating from the south (of the Sun) averaged -89 nT. In an effort to provide this research to others, a website was built that incorporated various tools and pictures to predict the intensity of the geomagnetic storms. The tool is capable of predicting geomagnetic storms with different ranges of Dst_min (from no-storm to gigantic storms). This work was supported by Naval Research Lab HBCU/MI Internship program and Chief of Naval Research.

  16. Calibration of Multiple In Silico Tools for Predicting Pathogenicity of Mismatch Repair Gene Missense Substitutions

    Science.gov (United States)

    Thompson, Bryony A.; Greenblatt, Marc S.; Vallee, Maxime P.; Herkert, Johanna C.; Tessereau, Chloe; Young, Erin L.; Adzhubey, Ivan A.; Li, Biao; Bell, Russell; Feng, Bingjian; Mooney, Sean D.; Radivojac, Predrag; Sunyaev, Shamil R.; Frebourg, Thierry; Hofstra, Robert M.W.; Sijmons, Rolf H.; Boucher, Ken; Thomas, Alun; Goldgar, David E.; Spurdle, Amanda B.; Tavtigian, Sean V.

    2015-01-01

    Classification of rare missense substitutions observed during genetic testing for patient management is a considerable problem in clinical genetics. The Bayesian integrated evaluation of unclassified variants is a solution originally developed for BRCA1/2. Here, we take a step toward an analogous system for the mismatch repair (MMR) genes (MLH1, MSH2, MSH6, and PMS2) that confer colon cancer susceptibility in Lynch syndrome by calibrating in silico tools to estimate prior probabilities of pathogenicity for MMR gene missense substitutions. A qualitative five-class classification system was developed and applied to 143 MMR missense variants. This identified 74 missense substitutions suitable for calibration. These substitutions were scored using six different in silico tools (Align-Grantham Variation Grantham Deviation, multivariate analysis of protein polymorphisms [MAPP], Mut-Pred, PolyPhen-2.1, Sorting Intolerant From Tolerant, and Xvar), using curated MMR multiple sequence alignments where possible. The output from each tool was calibrated by regression against the classifications of the 74 missense substitutions; these calibrated outputs are interpretable as prior probabilities of pathogenicity. MAPP was the most accurate tool and MAPP + PolyPhen-2.1 provided the best-combined model (R2 = 0.62 and area under receiver operating characteristic = 0.93). The MAPP + PolyPhen-2.1 output is sufficiently predictive to feed as a continuous variable into the quantitative Bayesian integrated evaluation for clinical classification of MMR gene missense substitutions. PMID:22949387

  17. Automated tool for virtual screening and pharmacology-based pathway prediction and analysis

    Directory of Open Access Journals (Sweden)

    Sugandh Kumar

    2017-10-01

    Full Text Available The virtual screening is an effective tool for the lead identification in drug discovery. However, there are limited numbers of crystal structures available as compared to the number of biological sequences which makes (Structure Based Drug Discovery SBDD a difficult choice. The current tool is an attempt to automate the protein structure modelling and automatic virtual screening followed by pharmacology-based prediction and analysis. Starting from sequence(s, this tool automates protein structure modelling, binding site identification, automated docking, ligand preparation, post docking analysis and identification of hits in the biological pathways that can be modulated by a group of ligands. This automation helps in the characterization of ligands selectivity and action of ligands on a complex biological molecular network as well as on individual receptor. The judicial combination of the ligands binding different receptors can be used to inhibit selective biological pathways in a disease. This tool also allows the user to systemically investigate network-dependent effects of a drug or drug candidate.

  18. Artificial neural network as the tool in prediction rheological features of raw minced meat.

    Science.gov (United States)

    Balejko, Jerzy A; Nowak, Zbigniew; Balejko, Edyta

    2012-01-01

    The aim of the study was to elaborate a method of modelling and forecasting rheological features which could be applied to raw minced meat at the stage of mixture preparation with a given ingredient composition. The investigated material contained pork and beef meat, pork fat, fat substitutes, ice and curing mixture in various proportions. Seven texture parameters were measured for each sample of raw minced meat. The data obtained were processed using the artificial neural network module in Statistica 9.0 software. The model that reached the lowest training error was a multi-layer perceptron MLP with three neural layers and architecture 7:7-11-7:7. Correlation coefficients between the experimental and calculated values in training, verification and testing subsets were similar and rather high (around 0.65) which indicated good network performance. High percentage of the total variance explained in PCA analysis (73.5%) indicated that the percentage composition of raw minced meat can be successfully used in the prediction of its rheological features. Statistical analysis of the results revealed, that artificial neural network model is able to predict rheological parameters and thus a complete texture profile of raw minced meat.

  19. Using "The Burns Suite" as a Novel High Fidelity Simulation Tool for Interprofessional and Teamwork Training.

    Science.gov (United States)

    Sadideen, Hazim; Wilson, David; Moiemen, Naiem; Kneebone, Roger

    2016-01-01

    Educational theory highlights the importance of contextualized simulation for effective learning. The authors recently published the concept of "The Burns Suite" (TBS) as a novel tool to advance the delivery of burns education for residents/clinicians. Effectively, TBS represents a low-cost, high-fidelity, portable, immersive simulation environment. Recently, simulation-based team training (SBTT) has been advocated as a means to improve interprofessional practice. The authors aimed to explore the role of TBS in SBTT. A realistic pediatric burn resuscitation scenario was designed based on "advanced trauma and life support" and "emergency management of severe burns" principles, refined utilizing expert opinion through cognitive task analysis. The focus of this analysis was on nontechnical and interpersonal skills of clinicians and nurses within the scenario, mirroring what happens in real life. Five-point Likert-type questionnaires were developed for face and content validity. Cronbach's alpha was calculated for scale reliability. Semistructured interviews captured responses for qualitative thematic analysis allowing for data triangulation. Twenty-two participants completed TBS resuscitation scenario. Mean face and content validity ratings were high (4.4 and 4.7 respectively; range 4-5). The internal consistency of questions was high. Qualitative data analysis revealed two new themes. Participants reported that the experience felt particularly authentic because the simulation had high psychological and social fidelity, and there was a demand for such a facility to be made available to improve nontechnical skills and interprofessional relations. TBS provides a realistic, novel tool for SBTT, addressing both nontechnical and interprofessional team skills. Recreating clinical challenge is crucial to optimize SBTT. With a better understanding of the theories underpinning simulation and interprofessional education, future simulation scenarios can be designed to provide

  20. Cardiovascular and Affective Outcomes of Active Gaming: Using the Nintendo Wii as a Cardiovascular Training Tool

    Science.gov (United States)

    Naugle, Keith E.; Naugle, Kelly M.; Wikstrom, Erik A.

    2014-01-01

    Naugle, KE, Naugle, KM, and Wikstrom, EA. Cardiovascular and affective outcomes of active gaming: Using the Nintendo Wii as a cardiovascular training tool. J Strength Cond Res 28(2): 443–451, 2014–Active-video gaming is purported to produce similar cardiovascular responses as aerobic fitness activities. This study compared the emotional and cardiovascular effects of Wii games with those of traditional exercise in college-aged adults with different exercise backgrounds. Specifically, the percentage of heart rate reserve, rate of perceived exertion (RPE), level of enjoyment, and Positive and Negative Affect Schedule scores were compared between subjects who reported exercising frequently at high intensities (high-intensity exerciser group: age = 20.18 years [0.87]; Height = 165.23 cm [9.97]; Mass = 62.37 kg [11.61]), N = 11 and those who exercise more often at lower intensities (low-intensity exercisers group: age = 20.72 years [1.19]; Height = 164.39 cm [8.05]; Mass = 68.04 kg [10.71]), N = 11. The subjects completed six 20-minute exercises sessions: treadmill walking, stationary cycling, and Wii's Tennis, Boxing, Cycling, and Step. The low-intensity exerciser group achieved a greater percentage of heart rate reserve (a) during traditional exercise compared with that during Wii boxing, (b) playing Wii boxing compared with that for Wii tennis, and (c) playing Wii boxing compared with that when the high-intensity exercisers group played any Wii games (p < 0.05). The RPE was greater for boxing and cycling compared with that for tennis and step (p < 0.05). Ratings of enjoyment and the increase in positive emotion were greater for boxing and for tennis compared with those for traditional exercises (p < 0.05). Results suggest that Wii boxing shows the greatest potential as a cardiovascular fitness tool among the Wii games, particularly for individuals who typically exercise at lower intensities. PMID:23660574

  1. A numerical tool for reproducing driver behaviour: experiments and predictive simulations.

    Science.gov (United States)

    Casucci, M; Marchitto, M; Cacciabue, P C

    2010-03-01

    This paper presents the simulation tool called SDDRIVE (Simple Simulation of Driver performance), which is the numerical computerised implementation of the theoretical architecture describing Driver-Vehicle-Environment (DVE) interactions, contained in Cacciabue and Carsten [Cacciabue, P.C., Carsten, O. A simple model of driver behaviour to sustain design and safety assessment of automated systems in automotive environments, 2010]. Following a brief description of the basic algorithms that simulate the performance of drivers, the paper presents and discusses a set of experiments carried out in a Virtual Reality full scale simulator for validating the simulation. Then the predictive potentiality of the tool is shown by discussing two case studies of DVE interactions, performed in the presence of different driver attitudes in similar traffic conditions.

  2. An Open-Source Web-Based Tool for Resource-Agnostic Interactive Translation Prediction

    Directory of Open Access Journals (Sweden)

    Daniel Torregrosa

    2014-09-01

    Full Text Available We present a web-based open-source tool for interactive translation prediction (ITP and describe its underlying architecture. ITP systems assist human translators by making context-based computer-generated suggestions as they type. Most of the ITP systems in literature are strongly coupled with a statistical machine translation system that is conveniently adapted to provide the suggestions. Our system, however, follows a resource-agnostic approach and suggestions are obtained from any unmodified black-box bilingual resource. This paper reviews our ITP method and describes the architecture of Forecat, a web tool, partly based on the recent technology of web components, that eases the use of our ITP approach in any web application requiring this kind of translation assistance. We also evaluate the performance of our method when using an unmodified Moses-based statistical machine translation system as the bilingual resource.

  3. Semi-structured interview is a reliable and feasible tool for selection of doctors for general practice specialist training

    DEFF Research Database (Denmark)

    Isaksen, Jesper; Hertel, Niels Thomas; Kjær, Niels Kristian

    2013-01-01

    In order to optimise the selection process for admission to specialist training in family medicine, we developed a new design for structured applications and selection interviews. The design contains semi-structured interviews, which combine individualised elements from the applications...... with standardised behaviour-based questions. This paper describes the design of the tool, and offers reflections concerning its acceptability, reliability and feasibility....

  4. Evaluation of an Automated Analysis Tool for Prostate Cancer Prediction Using Multiparametric Magnetic Resonance Imaging.

    Directory of Open Access Journals (Sweden)

    Matthias C Roethke

    Full Text Available To evaluate the diagnostic performance of an automated analysis tool for the assessment of prostate cancer based on multiparametric magnetic resonance imaging (mpMRI of the prostate.A fully automated analysis tool was used for a retrospective analysis of mpMRI sets (T2-weighted, T1-weighted dynamic contrast-enhanced, and diffusion-weighted sequences. The software provided a malignancy prediction value for each image pixel, defined as Malignancy Attention Index (MAI that can be depicted as a colour map overlay on the original images. The malignancy maps were compared to histopathology derived from a combination of MRI-targeted and systematic transperineal MRI/TRUS-fusion biopsies.In total, mpMRI data of 45 patients were evaluated. With a sensitivity of 85.7% (with 95% CI of 65.4-95.0, a specificity of 87.5% (with 95% CI of 69.0-95.7 and a diagnostic accuracy of 86.7% (with 95% CI of 73.8-93.8 for detection of prostate cancer, the automated analysis results corresponded well with the reported diagnostic accuracies by human readers based on the PI-RADS system in the current literature.The study revealed comparable diagnostic accuracies for the detection of prostate cancer of a user-independent MAI-based automated analysis tool and PI-RADS-scoring-based human reader analysis of mpMRI. Thus, the analysis tool could serve as a detection support system for less experienced readers. The results of the study also suggest the potential of MAI-based analysis for advanced lesion assessments, such as cancer extent and staging prediction.

  5. Effect of standardized training on the reliability of the Cochrane risk of bias assessment tool: a prospective study.

    Science.gov (United States)

    da Costa, Bruno R; Beckett, Brooke; Diaz, Alison; Resta, Nina M; Johnston, Bradley C; Egger, Matthias; Jüni, Peter; Armijo-Olivo, Susan

    2017-03-03

    The Cochrane risk of bias tool is commonly criticized for having a low reliability. We aimed to investigate whether training of raters, with objective and standardized instructions on how to assess risk of bias, can improve the reliability of the Cochrane risk of bias tool. In this pilot study, four raters inexperienced in risk of bias assessment were randomly allocated to minimal or intensive standardized training for risk of bias assessment of randomized trials of physical therapy treatments for patients with knee osteoarthritis pain. Two raters were experienced risk of bias assessors who served as reference. The primary outcome of our study was between-group reliability, defined as the agreement of the risk of bias assessments of inexperienced raters with the reference assessments of experienced raters. Consensus-based assessments were used for this purpose. The secondary outcome was within-group reliability, defined as the agreement of assessments within pairs of inexperienced raters. We calculated the chance-corrected weighted Kappa to quantify agreement within and between groups of raters for each of the domains of the risk of bias tool. A total of 56 trials were included in our analysis. The Kappa for the agreement of inexperienced raters with reference across items of the risk of bias tool ranged from 0.10 to 0.81 for the minimal training group and from 0.41 to 0.90 for the standardized training group. The Kappa values for the agreement within pairs of inexperienced raters across the items of the risk of bias tool ranged from 0 to 0.38 for the minimal training group and from 0.93 to 1 for the standardized training group. Between-group differences in Kappa for the agreement of inexperienced raters with reference always favored the standardized training group and was most pronounced for incomplete outcome data (difference in Kappa 0.52, p training on risk of bias assessment may significantly improve the reliability of the Cochrane risk of bias tool.

  6. In silico site-directed mutagenesis informs species-specific predictions of chemical susceptibility derived from the Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS) tool

    Science.gov (United States)

    The Sequence Alignment to Predict Across Species Susceptibility (SeqAPASS) tool was developed to address needs for rapid, cost effective methods of species extrapolation of chemical susceptibility. Specifically, the SeqAPASS tool compares the primary sequence (Level 1), functiona...

  7. TargetRNA: a tool for predicting targets of small RNA action in bacteria

    OpenAIRE

    Tjaden, Brian

    2008-01-01

    Many small RNA (sRNA) genes in bacteria act as posttranscriptional regulators of target messenger RNAs. Here, we present TargetRNA, a web tool for predicting mRNA targets of sRNA action in bacteria. TargetRNA takes as input a genomic sequence that may correspond to an sRNA gene. TargetRNA then uses a dynamic programming algorithm to search each annotated message in a specified genome for mRNAs that evince basepair-binding potential to the input sRNA sequence. Based on the calculated basepair-...

  8. Risk analysis for dengue suitability in Africa using the ArcGIS predictive analysis tools (PA tools).

    Science.gov (United States)

    Attaway, David F; Jacobsen, Kathryn H; Falconer, Allan; Manca, Germana; Waters, Nigel M

    2016-06-01

    Risk maps identifying suitable locations for infection transmission are important for public health planning. Data on dengue infection rates are not readily available in most places where the disease is known to occur. A newly available add-in to Esri's ArcGIS software package, the ArcGIS Predictive Analysis Toolset (PA Tools), was used to identify locations within Africa with environmental characteristics likely to be suitable for transmission of dengue virus. A more accurate, robust, and localized (1 km × 1 km) dengue risk map for Africa was created based on bioclimatic layers, elevation data, high-resolution population data, and other environmental factors that a search of the peer-reviewed literature showed to be associated with dengue risk. Variables related to temperature, precipitation, elevation, and population density were identified as good predictors of dengue suitability. Areas of high dengue suitability occur primarily within West Africa and parts of Central Africa and East Africa, but even in these regions the suitability is not homogenous. This risk mapping technique for an infection transmitted by Aedes mosquitoes draws on entomological, epidemiological, and geographic data. The method could be applied to other infectious diseases (such as Zika) in order to provide new insights for public health officials and others making decisions about where to increase disease surveillance activities and implement infection prevention and control efforts. The ability to map threats to human and animal health is important for tracking vectorborne and other emerging infectious diseases and modeling the likely impacts of climate change. Copyright © 2016 Elsevier B.V. All rights reserved.

  9. Fuzzy Constrained Predictive Optimal Control of High Speed Train with Actuator Dynamics

    Directory of Open Access Journals (Sweden)

    Xi Wang

    2016-01-01

    Full Text Available We investigate the problem of fuzzy constrained predictive optimal control of high speed train considering the effect of actuator dynamics. The dynamics feature of the high speed train is modeled as a cascade of cars connected by flexible couplers, and the formulation is mathematically transformed into a Takagi-Sugeno (T-S fuzzy model. The goal of this study is to design a state feedback control law at each decision step to enhance safety, comfort, and energy efficiency of high speed train subject to safety constraints on the control input. Based on Lyapunov stability theory, the problem of optimizing an upper bound on the cruise control cost function subject to input constraints is reduced to a convex optimization problem involving linear matrix inequalities (LMIs. Furthermore, we analyze the influences of second-order actuator dynamics on the fuzzy constrained predictive controller, which shows risk of potentially deteriorating the overall system. Employing backstepping method, an actuator compensator is proposed to accommodate for the influence of the actuator dynamics. The experimental results show that with the proposed approach high speed train can track the desired speed, the relative coupler displacement between the neighbouring cars is stable at the equilibrium state, and the influence of actuator dynamics is reduced, which demonstrate the validity and effectiveness of the proposed approaches.

  10. Towards Subject-Specific Strength Training Design through Predictive Use of Musculoskeletal Models

    Directory of Open Access Journals (Sweden)

    Michael Plüss

    2018-01-01

    Full Text Available Lower extremity dysfunction is often associated with hip muscle strength deficiencies. Detailed knowledge of the muscle forces generated in the hip under specific external loading conditions enables specific structures to be trained. The aim of this study was to find the most effective movement type and loading direction to enable the training of specific parts of the hip muscles using a standing posture and a pulley system. In a novel approach to release the predictive power of musculoskeletal modelling techniques based on inverse dynamics, flexion/extension and ab-/adduction movements were virtually created. To demonstrate the effectiveness of this approach, three hip orientations and an external loading force that was systematically rotated around the body were simulated using a state-of-the art OpenSim model in order to establish ideal designs for training of the anterior and posterior parts of the M. gluteus medius (GM. The external force direction as well as the hip orientation greatly influenced the muscle forces in the different parts of the GM. No setting was found for simultaneous training of the anterior and posterior parts with a muscle force higher than 50% of the maximum. Importantly, this study has demonstrated the use of musculoskeletal models as an approach to predict muscle force variations for different strength and rehabilitation exercise variations.

  11. 3D Cloud Field Prediction using A-Train Data and Machine Learning Techniques

    Science.gov (United States)

    Johnson, C. L.

    2017-12-01

    Validation of cloud process parameterizations used in global climate models (GCMs) would greatly benefit from observed 3D cloud fields at the size comparable to that of a GCM grid cell. For the highest resolution simulations, surface grid cells are on the order of 100 km by 100 km. CloudSat/CALIPSO data provides 1 km width of detailed vertical cloud fraction profile (CFP) and liquid and ice water content (LWC/IWC). This work utilizes four machine learning algorithms to create nonlinear regressions of CFP, LWC, and IWC data using radiances, surface type and location of measurement as predictors and applies the regression equations to off-track locations generating 3D cloud fields for 100 km by 100 km domains. The CERES-CloudSat-CALIPSO-MODIS (C3M) merged data set for February 2007 is used. Support Vector Machines, Artificial Neural Networks, Gaussian Processes and Decision Trees are trained on 1000 km of continuous C3M data. Accuracy is computed using existing vertical profiles that are excluded from the training data and occur within 100 km of the training data. Accuracy of the four algorithms is compared. Average accuracy for one day of predicted data is 86% for the most successful algorithm. The methodology for training the algorithms, determining valid prediction regions and applying the equations off-track is discussed. Predicted 3D cloud fields are provided as inputs to the Ed4 NASA LaRC Fu-Liou radiative transfer code and resulting TOA radiances compared to observed CERES/MODIS radiances. Differences in computed radiances using predicted profiles and observed radiances are compared.

  12. Tools and techniques for ageing predictions in nuclear reactors through condition monitoring

    International Nuclear Information System (INIS)

    Verma, R.M.P.

    1994-01-01

    To operate the nuclear reactors beyond their design predicted life is gaining importance because of huge replacement and decommissioning costs. But experience shows that nuclear plant safety and reliability may decline in the later years of plant life due to ageing degradation. Ageing of nuclear plant components, structures and systems, if unmitigated reduces their safety margins provided in the design and thus increases risks to public health and safety. These safety margins must be monitored throughout plant service life including any extended life. Condition monitoring of nuclear reactor components/equipment and systems can be done to study the effect of ageing, status of safety margins and effect of corrective and mitigating actions taken. The tools and techniques of condition monitoring are also important in failure trending, predictive maintenance, evaluation of scheduled maintenance, in mitigation of ageing, life extension and reliability studies. (author). 1 fig., 1 annexure

  13. Nonlinear Prediction As A Tool For Determining Parameters For Phase Space Reconstruction In Meteorology

    Science.gov (United States)

    Miksovsky, J.; Raidl, A.

    Time delays phase space reconstruction represents one of useful tools of nonlinear time series analysis, enabling number of applications. Its utilization requires the value of time delay to be known, as well as the value of embedding dimension. There are sev- eral methods how to estimate both these parameters. Typically, time delay is computed first, followed by embedding dimension. Our presented approach is slightly different - we reconstructed phase space for various combinations of mentioned parameters and used it for prediction by means of the nearest neighbours in the phase space. Then some measure of prediction's success was computed (correlation or RMSE, e.g.). The position of its global maximum (minimum) should indicate the suitable combination of time delay and embedding dimension. Several meteorological (particularly clima- tological) time series were used for the computations. We have also created a MS- Windows based program in order to implement this approach - its basic features will be presented as well.

  14. In 'big bang' major incidents do triage tools accurately predict clinical priority?: a systematic review of the literature.

    Science.gov (United States)

    Kilner, T M; Brace, S J; Cooke, M W; Stallard, N; Bleetman, A; Perkins, G D

    2011-05-01

    The term "big bang" major incidents is used to describe sudden, usually traumatic,catastrophic events, involving relatively large numbers of injured individuals, where demands on clinical services rapidly outstrip the available resources. Triage tools support the pre-hospital provider to prioritise which patients to treat and/or transport first based upon clinical need. The aim of this review is to identify existing triage tools and to determine the extent to which their reliability and validity have been assessed. A systematic review of the literature was conducted to identify and evaluate published data validating the efficacy of the triage tools. Studies using data from trauma patients that report on the derivation, validation and/or reliability of the specific pre-hospital triage tools were eligible for inclusion.Purely descriptive studies, reviews, exercises or reports (without supporting data) were excluded. The search yielded 1982 papers. After initial scrutiny of title and abstract, 181 papers were deemed potentially applicable and from these 11 were identified as relevant to this review (in first figure). There were two level of evidence one studies, three level of evidence two studies and six level of evidence three studies. The two level of evidence one studies were prospective validations of Clinical Decision Rules (CDR's) in children in South Africa, all the other studies were retrospective CDR derivation, validation or cohort studies. The quality of the papers was rated as good (n=3), fair (n=7), poor (n=1). There is limited evidence for the validity of existing triage tools in big bang major incidents.Where evidence does exist it focuses on sensitivity and specificity in relation to prediction of trauma death or severity of injury based on data from single or small number patient incidents. The Sacco system is unique in combining survivability modelling with the degree by which the system is overwhelmed in the triage decision system. The

  15. XBeach-G: a tool for predicting gravel barrier response to extreme storm conditions

    Science.gov (United States)

    Masselink, Gerd; Poate, Tim; McCall, Robert; Roelvink, Dano; Russell, Paul; Davidson, Mark

    2014-05-01

    Gravel beaches protect low-lying back-barrier regions from flooding during storm events and their importance to society is widely acknowledged. Unfortunately, breaching and extensive storm damage has occurred at many gravel sites and this is likely to increase as a result of sea-level rise and enhanced storminess due to climate change. Limited scientific guidance is currently available to provide beach managers with operational management tools to predict the response of gravel beaches to storms. The New Understanding and Prediction of Storm Impacts on Gravel beaches (NUPSIG) project aims to improve our understanding of storm impacts on gravel coastal environments and to develop a predictive capability by modelling these impacts. The NUPSIG project uses a 5-pronged approach to address its aim: (1) analyse hydrodynamic data collected during a proto-type laboratory experiment on a gravel beach; (2) collect hydrodynamic field data on a gravel beach under a range of conditions, including storm waves with wave heights up to 3 m; (3) measure swash dynamics and beach response on 10 gravel beaches during extreme wave conditions with wave heights in excess of 3 m; (4) use the data collected under 1-3 to develop and validate a numerical model to model hydrodynamics and morphological response of gravel beaches under storm conditions; and (5) develop a tool for end-users, based on the model formulated under (4), for predicting storm response of gravel beaches and barriers. The aim of this presentation is to present the key results of the NUPSIG project and introduce the end-user tool for predicting storm response on gravel beaches. The model is based on the numerical model XBeach, and different forcing scenarios (wave and tides), barrier configurations (dimensions) and sediment characteristics are easily uploaded for model simulations using a Graphics User Interface (GUI). The model can be used to determine the vulnerability of gravel barriers to storm events, but can also be

  16. Limitations of polyethylene glycol-induced precipitation as predictive tool for protein solubility during formulation development.

    Science.gov (United States)

    Hofmann, Melanie; Winzer, Matthias; Weber, Christian; Gieseler, Henning

    2018-05-01

    Polyethylene glycol (PEG)-induced protein precipitation is often used to extrapolate apparent protein solubility at specific formulation compositions. The procedure was used for several fields of application such as protein crystal growth but also protein formulation development. Nevertheless, most studies focused on applicability in protein crystal growth. In contrast, this study focuses on applicability of PEG-induced precipitation during high-concentration protein formulation development. In this study, solubility of three different model proteins was investigated over a broad range of pH. Solubility values predicted by PEG-induced precipitation were compared to real solubility behaviour determined by either turbidity or content measurements. Predicted solubility by PEG-induced precipitation was confirmed for an Fc fusion protein and a monoclonal antibody. In contrast, PEG-induced precipitation failed to predict solubility of a single-domain antibody construct. Applicability of PEG-induced precipitation as indicator of protein solubility during formulation development was found to be not valid for one of three model molecules. Under certain conditions, PEG-induced protein precipitation is not valid for prediction of real protein solubility behaviour. The procedure should be used carefully as tool for formulation development, and the results obtained should be validated by additional investigations. © 2017 Royal Pharmaceutical Society.

  17. Predictive tools for the evaluation of microbial effects on drugs during gastrointestinal passage.

    Science.gov (United States)

    Pieper, Ines A; Bertau, Martin

    2010-06-01

    Predicting drug metabolism after oral administration is highly complex, yet indispensable. Hitherto, drug metabolism mainly focuses on hepatic processes. In the intestine, drug molecules encounter the metabolic activity of microorganisms prior to absorption through the gut wall. Drug biotransformation through the gastrointestinal microflora has the potential to evoke serious problems because the metabolites formed may cause unexpected and undesired side effects in patients. Hence, in the course of drug development, the question has to be addressed if microbially formed metabolites are physiologically active, pharmaceutically active or even toxic. In order to provide answers to these questions and to keep the number of laboratory tests needed low, predictive tools - in vivo as well as in silico - are invaluable. This review gives an outline of the current state of the art in the field of predicting the drug biotransformation through the gastrointestinal microflora on several levels of modelling. A comprehensive review of the literature with a thorough discussion on assets and drawbacks of the different modelling approaches. The impact of the gastrointestinal drug biotransformation on patients' health will grow with increasing complexity of drug entities. Predicting metabolic fates of drugs by combining in vitro and in silico models provides invaluable information which will be suitable to particularly reduce in vivo studies.

  18. Evaluation of the efficacy of six nutritional screening tools to predict malnutrition in the elderly.

    Science.gov (United States)

    Poulia, Kalliopi-Anna; Yannakoulia, Mary; Karageorgou, Dimitra; Gamaletsou, Maria; Panagiotakos, Demosthenes B; Sipsas, Nikolaos V; Zampelas, Antonis

    2012-06-01

    Malnutrition in the elderly is a multifactorial problem, more prevalent in hospitals and care homes. The absence of a gold standard in evaluating nutritional risk led us to evaluate the efficacy of six nutritional screening tools used in the elderly. Two hundred forty eight elderly patients (129 men, 119 female women, aged 75.2 ± 8.5 years) were examined. Nutritional screening was performed on admission using the following tools: Nutritional Risk Index (NRI), Geriatric Nutritional Risk Index (GNRI), Subjective Global Assessment (SGA), Mini Nutritional Assessment - Screening Form (MNA-SF), Malnutrition Universal Screening Tool (MUST) and Nutritional Risk Screening 2002 (NRS 2002). A combined index for malnutrition was also calculated. Nutritional risk and/or malnutrition varied greatly, ranging from 47.2 to 97.6%, depending on the nutritional screening tool used. MUST was the most valid screening tool (validity coefficient = 0.766, CI 95%: 0.690-0.841), while SGA was in better agreement with the combined index (κ = 0.707, p = 0.000). NRS 2002 although was the highest in sensitivity (99.4%), it was the lowest in specificity (6.1%) and positive predictive value (68.2%). MUST seem to be the most valid in the evaluation of the risk for malnutrition in the elderly upon admission to the hospital. NRS 2002 was found to overestimate nutritional risk in the elderly. Copyright © 2011 Elsevier Ltd and European Society for Clinical Nutrition and Metabolism. All rights reserved.

  19. Exercise training raises daily activity stronger than predicted from exercise capacity in patients with COPD.

    Science.gov (United States)

    Behnke, Michaela; Wewel, Alexandra R; Kirsten, Detlef; Jörres, Rudolf A; Magnussen, Helgo

    2005-06-01

    The 6-min walking (6MWD) and 6-min treadmill distance (6MTD) are often used as measures of exercise performance in patients with COPD. The aim of our study was to assess their relationship to daily activity in the course of an exercise training program. Eighty-eight patients with stable COPD (71m/17f; mean +/- SD age, 60 +/-8 year; FEV1, 43+/-14% pred) were recruited, 66 of whom performed a hospital-based 10-day walking training, whereas 22 were treated as control. On day 16MTD, and on days 8 and 10, 6MTD and 6MWD were determined. In addition, patients used an accelerometer (TriTrac-R3D) to record 24 h-activity, whereby training sessions were excluded. In both groups there was a linear relationship (r > or = 0.84 and P daily activity did not markedly vary with exercise capacity under baseline conditions. Participation in a training program increased activity significantly stronger than predicted from the gain in exercise capacity. This underlines the importance of non-physiological, patient-centered factors associated with training in COPD.

  20. Habit strength is predicted by activity dynamics in goal-directed brain systems during training.

    Science.gov (United States)

    Zwosta, Katharina; Ruge, Hannes; Goschke, Thomas; Wolfensteller, Uta

    2018-01-15

    Previous neuroscientific research revealed insights into the brain networks supporting goal-directed and habitual behavior, respectively. However, it remains unclear how these contribute to inter-individual differences in habit strength which is relevant for understanding not only normal behavior but also more severe dysregulations between these types of action control, such as in addiction. In the present fMRI study, we trained subjects on approach and avoidance behavior for an extended period of time before testing the habit strength of the acquired stimulus-response associations. We found that stronger habits were associated with a stronger decrease in inferior parietal lobule activity for approach and avoidance behavior and weaker vmPFC activity at the end of training for avoidance behavior, areas associated with the anticipation of outcome identity and value. VmPFC in particular showed markedly different activity dynamics during the training of approach and avoidance behavior. Furthermore, while ongoing training was accompanied by increasing functional connectivity between posterior putamen and premotor cortex, consistent with previous assumptions about the neural basis of increasing habitualization, this was not predictive of later habit strength. Together, our findings suggest that inter-individual differences in habitual behavior are driven by differences in the persistent involvement of brain areas supporting goal-directed behavior during training. Copyright © 2017. Published by Elsevier Inc.

  1. A clinical risk stratification tool for predicting treatment resistance in major depressive disorder.

    Science.gov (United States)

    Perlis, Roy H

    2013-07-01

    Early identification of depressed individuals at high risk for treatment resistance could be helpful in selecting optimal setting and intensity of care. At present, validated tools to facilitate this risk stratification are rarely used in psychiatric practice. Data were drawn from the first two treatment levels of a multicenter antidepressant effectiveness study in major depressive disorder, the STAR*D (Sequenced Treatment Alternatives to Relieve Depression) cohort. This cohort was divided into training, testing, and validation subsets. Only clinical or sociodemographic variables available by or readily amenable to self-report were considered. Multivariate models were developed to discriminate individuals reaching remission with a first or second pharmacological treatment trial from those not reaching remission despite two trials. A logistic regression model achieved an area under the receiver operating characteristic curve exceeding .71 in training, testing, and validation cohorts and maintained good calibration across cohorts. Performance of three alternative models with machine learning approaches--a naïve Bayes classifier and a support vector machine, and a random forest model--was less consistent. Similar performance was observed between more and less severe depression, men and women, and primary versus specialty care sites. A web-based calculator was developed that implements this tool and provides graphical estimates of risk. Risk for treatment resistance among outpatients with major depressive disorder can be estimated with a simple model incorporating baseline sociodemographic and clinical features. Future studies should examine the performance of this model in other clinical populations and its utility in treatment selection or clinical trial design. Copyright © 2013 Society of Biological Psychiatry. Published by Elsevier Inc. All rights reserved.

  2. Novel inter and intra prediction tools under consideration for the emerging AV1 video codec

    Science.gov (United States)

    Joshi, Urvang; Mukherjee, Debargha; Han, Jingning; Chen, Yue; Parker, Sarah; Su, Hui; Chiang, Angie; Xu, Yaowu; Liu, Zoe; Wang, Yunqing; Bankoski, Jim; Wang, Chen; Keyder, Emil

    2017-09-01

    Google started the WebM Project in 2010 to develop open source, royalty- free video codecs designed specifically for media on the Web. The second generation codec released by the WebM project, VP9, is currently served by YouTube, and enjoys billions of views per day. Realizing the need for even greater compression efficiency to cope with the growing demand for video on the web, the WebM team embarked on an ambitious project to develop a next edition codec AV1, in a consortium of major tech companies called the Alliance for Open Media, that achieves at least a generational improvement in coding efficiency over VP9. In this paper, we focus primarily on new tools in AV1 that improve the prediction of pixel blocks before transforms, quantization and entropy coding are invoked. Specifically, we describe tools and coding modes that improve intra, inter and combined inter-intra prediction. Results are presented on standard test sets.

  3. DR2DI: a powerful computational tool for predicting novel drug-disease associations

    Science.gov (United States)

    Lu, Lu; Yu, Hua

    2018-05-01

    Finding the new related candidate diseases for known drugs provides an effective method for fast-speed and low-risk drug development. However, experimental identification of drug-disease associations is expensive and time-consuming. This motivates the need for developing in silico computational methods that can infer true drug-disease pairs with high confidence. In this study, we presented a novel and powerful computational tool, DR2DI, for accurately uncovering the potential associations between drugs and diseases using high-dimensional and heterogeneous omics data as information sources. Based on a unified and extended similarity kernel framework, DR2DI inferred the unknown relationships between drugs and diseases using Regularized Kernel Classifier. Importantly, DR2DI employed a semi-supervised and global learning algorithm which can be applied to uncover the diseases (drugs) associated with known and novel drugs (diseases). In silico global validation experiments showed that DR2DI significantly outperforms recent two approaches for predicting drug-disease associations. Detailed case studies further demonstrated that the therapeutic indications and side effects of drugs predicted by DR2DI could be validated by existing database records and literature, suggesting that DR2DI can be served as a useful bioinformatic tool for identifying the potential drug-disease associations and guiding drug repositioning. Our software and comparison codes are freely available at https://github.com/huayu1111/DR2DI.

  4. Controller Strategies for Automation Tool Use under Varying Levels of Trajectory Prediction Uncertainty

    Science.gov (United States)

    Morey, Susan; Prevot, Thomas; Mercer, Joey; Martin, Lynne; Bienert, Nancy; Cabrall, Christopher; Hunt, Sarah; Homola, Jeffrey; Kraut, Joshua

    2013-01-01

    A human-in-the-loop simulation was conducted to examine the effects of varying levels of trajectory prediction uncertainty on air traffic controller workload and performance, as well as how strategies and the use of decision support tools change in response. This paper focuses on the strategies employed by two controllers from separate teams who worked in parallel but independently under identical conditions (airspace, arrival traffic, tools) with the goal of ensuring schedule conformance and safe separation for a dense arrival flow in en route airspace. Despite differences in strategy and methods, both controllers achieved high levels of schedule conformance and safe separation. Overall, results show that trajectory uncertainties introduced by wind and aircraft performance prediction errors do not affect the controllers' ability to manage traffic. Controller strategies were fairly robust to changes in error, though strategies were affected by the amount of delay to absorb (scheduled time of arrival minus estimated time of arrival). Using the results and observations, this paper proposes an ability to dynamically customize the display of information including delay time based on observed error to better accommodate different strategies and objectives.

  5. The East London glaucoma prediction score: web-based validation of glaucoma risk screening tool

    Science.gov (United States)

    Stephen, Cook; Benjamin, Longo-Mbenza

    2013-01-01

    AIM It is difficult for Optometrists and General Practitioners to know which patients are at risk. The East London glaucoma prediction score (ELGPS) is a web based risk calculator that has been developed to determine Glaucoma risk at the time of screening. Multiple risk factors that are available in a low tech environment are assessed to provide a risk assessment. This is extremely useful in settings where access to specialist care is difficult. Use of the calculator is educational. It is a free web based service. Data capture is user specific. METHOD The scoring system is a web based questionnaire that captures and subsequently calculates the relative risk for the presence of Glaucoma at the time of screening. Three categories of patient are described: Unlikely to have Glaucoma; Glaucoma Suspect and Glaucoma. A case review methodology of patients with known diagnosis is employed to validate the calculator risk assessment. RESULTS Data from the patient records of 400 patients with an established diagnosis has been captured and used to validate the screening tool. The website reports that the calculated diagnosis correlates with the actual diagnosis 82% of the time. Biostatistics analysis showed: Sensitivity = 88%; Positive predictive value = 97%; Specificity = 75%. CONCLUSION Analysis of the first 400 patients validates the web based screening tool as being a good method of screening for the at risk population. The validation is ongoing. The web based format will allow a more widespread recruitment for different geographic, population and personnel variables. PMID:23550097

  6. DR2DI: a powerful computational tool for predicting novel drug-disease associations

    Science.gov (United States)

    Lu, Lu; Yu, Hua

    2018-04-01

    Finding the new related candidate diseases for known drugs provides an effective method for fast-speed and low-risk drug development. However, experimental identification of drug-disease associations is expensive and time-consuming. This motivates the need for developing in silico computational methods that can infer true drug-disease pairs with high confidence. In this study, we presented a novel and powerful computational tool, DR2DI, for accurately uncovering the potential associations between drugs and diseases using high-dimensional and heterogeneous omics data as information sources. Based on a unified and extended similarity kernel framework, DR2DI inferred the unknown relationships between drugs and diseases using Regularized Kernel Classifier. Importantly, DR2DI employed a semi-supervised and global learning algorithm which can be applied to uncover the diseases (drugs) associated with known and novel drugs (diseases). In silico global validation experiments showed that DR2DI significantly outperforms recent two approaches for predicting drug-disease associations. Detailed case studies further demonstrated that the therapeutic indications and side effects of drugs predicted by DR2DI could be validated by existing database records and literature, suggesting that DR2DI can be served as a useful bioinformatic tool for identifying the potential drug-disease associations and guiding drug repositioning. Our software and comparison codes are freely available at https://github.com/huayu1111/DR2DI.

  7. Student Training in the Use of an Online Synchronous Conferencing Tool

    Science.gov (United States)

    Heiser, Sarah; Stickler, Ursula; Furnborough, Concha

    2013-01-01

    With the increase of online language teaching the training needs of teachers have long been established and researched. However, the training needs of students have not yet been fully acknowledged. This paper focuses on learner training as preparation for language classes where online synchronous conferencing is used. It presents an action…

  8. On-Line Flutter Prediction Tool for Wind Tunnel Flutter Testing using Parameter Varying Estimation Methodology, Phase I

    Data.gov (United States)

    National Aeronautics and Space Administration — ZONA Technology, Inc. (ZONA) proposes to develop an on-line flutter prediction tool for wind tunnel model using the parameter varying estimation (PVE) technique to...

  9. Control room design and human factors using a virtual reality based tool for design, test and training

    International Nuclear Information System (INIS)

    Lirvall, Peter

    1998-02-01

    This report describes a user-centred approach to control room design adopted by IFE for the nuclear industry. The novelty of this approach is the development of a Control Room Philosophy, and the use of Virtual Reality (VR) technology as a tool in the design process, integrated with a specially developed Design Documentation System (DDS) and a process display prototyping tool PICASSO-3. The control room philosophy identifies all functional aspects of a control centre, to define the baseline principles and guidelines for the design. The use of VR technology enables end-users of the control room design (e.g. control room operators) to specify their preferred design of the new control room, and to replace the need for a physical mock-up to test and evaluate the proposed design. The DDS, integrated with the VR design tool, guides the control room operators, through a structured approach, to document the proposed design in a complete design specification. The VR tool, specially developed by IFE, is called the VR based Design, Test and Training tool (VR DTandT). It is not only intended to visualise the design, but also to test and evaluate the design. When the design is implemented, the same model is re-used as a VR based training simulator for operators. A special feature in the VR DTandT tool is that the verification and validation (VandV) tests, concerning human factors, are according to the regulative standards for nuclear control rooms

  10. TACO: a general-purpose tool for predicting cell-type-specific transcription factor dimers.

    Science.gov (United States)

    Jankowski, Aleksander; Prabhakar, Shyam; Tiuryn, Jerzy

    2014-03-19

    Cooperative binding of transcription factor (TF) dimers to DNA is increasingly recognized as a major contributor to binding specificity. However, it is likely that the set of known TF dimers is highly incomplete, given that they were discovered using ad hoc approaches, or through computational analyses of limited datasets. Here, we present TACO (Transcription factor Association from Complex Overrepresentation), a general-purpose standalone software tool that takes as input any genome-wide set of regulatory elements and predicts cell-type-specific TF dimers based on enrichment of motif complexes. TACO is the first tool that can accommodate motif complexes composed of overlapping motifs, a characteristic feature of many known TF dimers. Our method comprehensively outperforms existing tools when benchmarked on a reference set of 29 known dimers. We demonstrate the utility and consistency of TACO by applying it to 152 DNase-seq datasets and 94 ChIP-seq datasets. Based on these results, we uncover a general principle governing the structure of TF-TF-DNA ternary complexes, namely that the flexibility of the complex is correlated with, and most likely a consequence of, inter-motif spacing.

  11. PBPK Modeling - A Predictive, Eco-Friendly, Bio-Waiver Tool for Drug Research.

    Science.gov (United States)

    De, Baishakhi; Bhandari, Koushik; Mukherjee, Ranjan; Katakam, Prakash; Adiki, Shanta K; Gundamaraju, Rohit; Mitra, Analava

    2017-01-01

    The world has witnessed growing complexities in disease scenario influenced by the drastic changes in host-pathogen- environment triadic relation. Pharmaceutical R&Ds are in constant search of novel therapeutic entities to hasten transition of drug molecules from lab bench to patient bedside. Extensive animal studies and human pharmacokinetics are still the "gold standard" in investigational new drug research and bio-equivalency studies. Apart from cost, time and ethical issues on animal experimentation, burning questions arise relating to ecological disturbances, environmental hazards and biodiversity issues. Grave concerns arises when the adverse outcomes of continued studies on one particular disease on environment gives rise to several other pathogenic agents finally complicating the total scenario. Thus Pharma R&Ds face a challenge to develop bio-waiver protocols. Lead optimization, drug candidate selection with favorable pharmacokinetics and pharmacodynamics, toxicity assessment are vital steps in drug development. Simulation tools like Gastro Plus™, PK Sim®, SimCyp find applications for the purpose. Advanced technologies like organ-on-a chip or human-on-a chip where a 3D representation of human organs and systems can mimic the related processes and activities, thereby linking them to major features of human biology can be successfully incorporated in the drug development tool box. PBPK provides the State of Art to serve as an optional of animal experimentation. PBPK models can successfully bypass bio-equivalency studies, predict bioavailability, drug interactions and on hyphenation with in vitro-in vivo correlation can be extrapolated to humans thus serving as bio-waiver. PBPK can serve as an eco-friendly bio-waiver predictive tool in drug development. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  12. Unscented Kalman Filter-Trained Neural Networks for Slip Model Prediction

    Science.gov (United States)

    Li, Zhencai; Wang, Yang; Liu, Zhen

    2016-01-01

    The purpose of this work is to investigate the accurate trajectory tracking control of a wheeled mobile robot (WMR) based on the slip model prediction. Generally, a nonholonomic WMR may increase the slippage risk, when traveling on outdoor unstructured terrain (such as longitudinal and lateral slippage of wheels). In order to control a WMR stably and accurately under the effect of slippage, an unscented Kalman filter and neural networks (NNs) are applied to estimate the slip model in real time. This method exploits the model approximating capabilities of nonlinear state–space NN, and the unscented Kalman filter is used to train NN’s weights online. The slip parameters can be estimated and used to predict the time series of deviation velocity, which can be used to compensate control inputs of a WMR. The results of numerical simulation show that the desired trajectory tracking control can be performed by predicting the nonlinear slip model. PMID:27467703

  13. Predictive Engineering Tools for Injection-Molded Long-Carbon-Thermoplastic Composites: Weight and Cost Analyses

    Energy Technology Data Exchange (ETDEWEB)

    Nguyen, Ba Nghiep [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Fifield, Leonard S. [Pacific Northwest National Lab. (PNNL), Richland, WA (United States); Gandhi, Umesh N. [Toyota Research Inst. North America, Ann Arbor, MI (United States); Mori, Steven [MAGNA Exteriors and Interiors Corporation, Aurora, ON (Canada); Wollan, Eric J. [PlastiComp, Inc., Winona, MN (United States)

    2016-08-01

    This project proposed to integrate, optimize and validate the fiber orientation and length distribution models previously developed and implemented in the Autodesk Simulation Moldflow Insight (ASMI) package for injection-molded long-carbon-fiber thermoplastic composites into a cohesive prediction capability. The current effort focused on rendering the developed models more robust and efficient for automotive industry part design to enable weight savings and cost reduction. The project goal has been achieved by optimizing the developed models, improving and integrating their implementations in ASMI, and validating them for a complex 3D LCF thermoplastic automotive part (Figure 1). Both PP and PA66 were used as resin matrices. After validating ASMI predictions for fiber orientation and fiber length for this complex part against the corresponding measured data, in collaborations with Toyota and Magna PNNL developed a method using the predictive engineering tool to assess LCF/PA66 complex part design in terms of stiffness performance. Structural three-point bending analyses of the complex part and similar parts in steel were then performed for this purpose, and the team has then demonstrated the use of stiffness-based complex part design assessment to evaluate weight savings relative to the body system target (≥ 35%) set in Table 2 of DE-FOA-0000648 (AOI #1). In addition, starting from the part-to-part analysis, the PE tools enabled an estimated weight reduction for the vehicle body system using 50 wt% LCF/PA66 parts relative to the current steel system. Also, from this analysis an estimate of the manufacturing cost including the material cost for making the equivalent part in steel has been determined and compared to the costs for making the LCF/PA66 part to determine the cost per “saved” pound.

  14. MP3: a software tool for the prediction of pathogenic proteins in genomic and metagenomic data.

    Science.gov (United States)

    Gupta, Ankit; Kapil, Rohan; Dhakan, Darshan B; Sharma, Vineet K

    2014-01-01

    The identification of virulent proteins in any de-novo sequenced genome is useful in estimating its pathogenic ability and understanding the mechanism of pathogenesis. Similarly, the identification of such proteins could be valuable in comparing the metagenome of healthy and diseased individuals and estimating the proportion of pathogenic species. However, the common challenge in both the above tasks is the identification of virulent proteins since a significant proportion of genomic and metagenomic proteins are novel and yet unannotated. The currently available tools which carry out the identification of virulent proteins provide limited accuracy and cannot be used on large datasets. Therefore, we have developed an MP3 standalone tool and web server for the prediction of pathogenic proteins in both genomic and metagenomic datasets. MP3 is developed using an integrated Support Vector Machine (SVM) and Hidden Markov Model (HMM) approach to carry out highly fast, sensitive and accurate prediction of pathogenic proteins. It displayed Sensitivity, Specificity, MCC and accuracy values of 92%, 100%, 0.92 and 96%, respectively, on blind dataset constructed using complete proteins. On the two metagenomic blind datasets (Blind A: 51-100 amino acids and Blind B: 30-50 amino acids), it displayed Sensitivity, Specificity, MCC and accuracy values of 82.39%, 97.86%, 0.80 and 89.32% for Blind A and 71.60%, 94.48%, 0.67 and 81.86% for Blind B, respectively. In addition, the performance of MP3 was validated on selected bacterial genomic and real metagenomic datasets. To our knowledge, MP3 is the only program that specializes in fast and accurate identification of partial pathogenic proteins predicted from short (100-150 bp) metagenomic reads and also performs exceptionally well on complete protein sequences. MP3 is publicly available at http://metagenomics.iiserb.ac.in/mp3/index.php.

  15. Screening Tool for Early Postnatal Prediction of Retinopathy of Prematurity in Preterm Newborns (STEP-ROP).

    Science.gov (United States)

    Ricard, Caroline A; Dammann, Christiane E L; Dammann, Olaf

    2017-01-01

    Retinopathy of prematurity (ROP) is a disorder of the preterm newborn characterized by neurovascular disruption in the immature retina that may cause visual impairment and blindness. To develop a clinical screening tool for early postnatal prediction of ROP in preterm newborns based on risk information available within the first 48 h of postnatal life. Using data submitted to the Vermont Oxford Network (VON) between 1995 and 2015, we created logistic regression models based on infants born <28 completed weeks gestational age. We developed a model with 60% of the data and identified birth weight, gestational age, respiratory distress syndrome, non-Hispanic ethnicity, and multiple gestation as predictors of ROP. We tested the model in the remaining 40%, performed tenfold cross-validation, and tested the score in ELGAN study data. Of the 1,052 newborns in the VON database, 627 recorded an ROP status. Forty percent had no ROP, 40% had mild ROP (stages 1 and 2), and 20% had severe ROP (stages 3-5). We created a weighted score to predict any ROP based on the multivariable regression model. A cutoff score of 5 had the best sensitivity (95%, 95% CI 93-97), while maintaining a strong positive predictive value (63%, 95% CI 57-68). When applied to the ELGAN data, sensitivity was lower (72%, 95% CI 69-75), but PPV was higher (80%, 95% CI 77-83). STEP-ROP is a promising screening tool. It is easy to calculate, does not rely on extensive postnatal data collection, and can be calculated early after birth. Early ROP screening may help physicians limit patient exposure to additional risk factors, and may be useful for risk stratification in clinical trials aimed at reducing ROP. © 2017 S. Karger AG, Basel.

  16. Experimental and Mathematical Modeling for Prediction of Tool Wear on the Machining of Aluminium 6061 Alloy by High Speed Steel Tools

    Directory of Open Access Journals (Sweden)

    Okokpujie Imhade Princess

    2017-12-01

    Full Text Available In recent machining operation, tool life is one of the most demanding tasks in production process, especially in the automotive industry. The aim of this paper is to study tool wear on HSS in end milling of aluminium 6061 alloy. The experiments were carried out to investigate tool wear with the machined parameters and to developed mathematical model using response surface methodology. The various machining parameters selected for the experiment are spindle speed (N, feed rate (f, axial depth of cut (a and radial depth of cut (r. The experiment was designed using central composite design (CCD in which 31 samples were run on SIEG 3/10/0010 CNC end milling machine. After each experiment the cutting tool was measured using scanning electron microscope (SEM. The obtained optimum machining parameter combination are spindle speed of 2500 rpm, feed rate of 200 mm/min, axial depth of cut of 20 mm, and radial depth of cut 1.0mm was found out to achieved the minimum tool wear as 0.213 mm. The mathematical model developed predicted the tool wear with 99.7% which is within the acceptable accuracy range for tool wear prediction.

  17. Experimental and Mathematical Modeling for Prediction of Tool Wear on the Machining of Aluminium 6061 Alloy by High Speed Steel Tools

    Science.gov (United States)

    Okokpujie, Imhade Princess; Ikumapayi, Omolayo M.; Okonkwo, Ugochukwu C.; Salawu, Enesi Y.; Afolalu, Sunday A.; Dirisu, Joseph O.; Nwoke, Obinna N.; Ajayi, Oluseyi O.

    2017-12-01

    In recent machining operation, tool life is one of the most demanding tasks in production process, especially in the automotive industry. The aim of this paper is to study tool wear on HSS in end milling of aluminium 6061 alloy. The experiments were carried out to investigate tool wear with the machined parameters and to developed mathematical model using response surface methodology. The various machining parameters selected for the experiment are spindle speed (N), feed rate (f), axial depth of cut (a) and radial depth of cut (r). The experiment was designed using central composite design (CCD) in which 31 samples were run on SIEG 3/10/0010 CNC end milling machine. After each experiment the cutting tool was measured using scanning electron microscope (SEM). The obtained optimum machining parameter combination are spindle speed of 2500 rpm, feed rate of 200 mm/min, axial depth of cut of 20 mm, and radial depth of cut 1.0mm was found out to achieved the minimum tool wear as 0.213 mm. The mathematical model developed predicted the tool wear with 99.7% which is within the acceptable accuracy range for tool wear prediction.

  18. Integrating Cloud-Based Strategies and Tools in Face-to-Face Training Sessions to Increase the Impact of Professional Development

    Science.gov (United States)

    Gradel, Kathleen; Edson, Alden J.

    2012-01-01

    This article is based on the premise that face-to-face training can be augmented with cloud-based technology tools, to potentially extend viable training supports as higher education staff and faculty implement new content/skills in their jobs and classrooms. There are significant benefits to harnessing cloud-based tools that can facilitate both…

  19. Development of 1RM Prediction Equations for Bench Press in Moderately Trained Men.

    Science.gov (United States)

    Macht, Jordan W; Abel, Mark G; Mullineaux, David R; Yates, James W

    2016-10-01

    Macht, JW, Abel, MG, Mullineaux, DR, and Yates, JW. Development of 1RM prediction equations for bench press in moderately trained men. J Strength Cond Res 30(10): 2901-2906, 2016-There are a variety of established 1 repetition maximum (1RM) prediction equations, however, very few prediction equations use anthropometric characteristics exclusively or in part, to estimate 1RM strength. Therefore, the purpose of this study was to develop an original 1RM prediction equation for bench press using anthropometric and performance characteristics in moderately trained male subjects. Sixty male subjects (21.2 ± 2.4 years) completed a 1RM bench press and were randomly assigned a load to complete as many repetitions as possible. In addition, body composition, upper-body anthropometric characteristics, and handgrip strength were assessed. Regression analysis was used to develop a performance-based 1RM prediction equation: 1RM = 1.20 repetition weight + 2.19 repetitions to fatigue - 0.56 biacromial width (cm) + 9.6 (R = 0.99, standard error of estimate [SEE] = 3.5 kg). Regression analysis to develop a nonperformance-based 1RM prediction equation yielded: 1RM (kg) = 0.997 cross-sectional area (CSA) (cm) + 0.401 chest circumference (cm) - 0.385%fat - 0.185 arm length (cm) + 36.7 (R = 0.81, SEE = 13.0 kg). The performance prediction equations developed in this study had high validity coefficients, minimal mean bias, and small limits of agreement. The anthropometric equations had moderately high validity coefficient but larger limits of agreement. The practical applications of this study indicate that the inclusion of anthropometric characteristics and performance variables produce a valid prediction equation for 1RM strength. In addition, the CSA of the arm uses a simple nonperformance method of estimating the lifter's 1RM. This information may be used to predict the starting load for a lifter performing a 1RM prediction protocol or a 1RM testing protocol.

  20. Utilization of just-in-time training for nursing education using the LA Phonospirometry asthma tool.

    Science.gov (United States)

    Pade, Kathryn H; Seik-Ismail, Sophia T; Chang, Todd P; Wang, Vincent J

    2017-08-28

    Just-in-time training (JITT) has been used to teach and re-teach known medical techniques, but has not been used to teach novel techniques. We aimed to assess the performance retention of JITT on a novel asthma exacerbation severity assessment technique known as Los Angeles (LA) Phonospirometry. This was a prospective cohort study using a convenience sample of pediatric emergency department registered nurses (RNs) who were asked to watch a brief instructional digital video on LA Phonospirometry, and then asked to practice the technique on a research assistant (RA). A checklist was used to evaluate proficiency with the primary outcome being the number correct on the checklist. The secondary outcome included whether or not they could identify a common error demonstrated by the RA. RNs were re-tested after 4-6 months to assess skill retention. Forty RNs were enrolled in the study and six were lost to follow-up. The mean time from the first to second testing was 5.4 months ± 0.5 months. The mean score of the first part of the checklist on the initial testing was 4.6 ± 0.7 and on second testing was 3.8 ± 1.5 (p = 0.008). This represented a drop in scores and thus minimal knowledge decay of 18% (from 91% to 73%). The mean values for number of errors picked up for the first test and second test were 1.3 and 1.5, respectively (p = 0.2). JITT demonstrated feasibility as a rapid instructional tool for RNs, with a limited decay in cognitive knowledge surrounding the LA Phonospirometry technique.

  1. Toward competency-based curriculum: Application of workplace-based assessment tools in the National Saudi Arabian Anesthesia Training Program.

    Science.gov (United States)

    Boker, Ama

    2016-01-01

    The anesthesia training program of the Saudi Commission for health specialties has introduced a developed competency-based anesthesia residency program starting from 2015 with the utilization of the workplace-based assessment (WBA) tools, namely mini-clinical exercises (mini-CEX), direct observation of procedural skills (DOPS), and case-based discussion (CBD). This work aimed to describe the process of development of anesthesia-specific list of mini-CEX, DOPS, and CBD tools within the Saudi Arabian Anesthesia Training Programs. To introduce the main concepts of formative WBA tools and to develop anesthesia-specific applications for each of the selected WBA tools, four 1-day workshops were held at the level of major training committees at eastern (Dammam), western (Jeddah), and central (Riyadh) regions in the Kingdom were conducted. Sixty-seven faculties participated in these workshops. After conduction of the four workshops, the anesthesia-specific applications setting of mini-CEX, DOPS, and CBD tools among the 5-year levels were fully described. The level of the appropriate consultation skills was divided according to the case complexity adopted from the American Society of Anesthesiologists physical classification for adult and obstetric and pediatric patient as well as the type of the targeted anesthetic procedure. WBA anesthesia-specific lists of mini-CEX, DOPS, and CBD forms were easily incorporated first into guidelines to help the first stage of implementation of formative assessment in the Saudi Arabian Anesthesia Residency Program, and this can be helpful to replicate such program within other various training programs in Saudi Arabia and abroad.

  2. Sediment predictions in Wadi Al-Naft using soil water assessment tool

    Directory of Open Access Journals (Sweden)

    Alwan Imzahim Abdulkareem

    2018-01-01

    Full Text Available Sediment production is the amount of sediment in the unit area that is transported through the basin by water transfer over a specified period of time. The main aim of present study is to predict sediment yield of Wadi, Al-Naft watershed with 8820 Km2area, that is located in the North-East of Diyala Governorate in Iraq, using Soil-Water Assessment Tool, (SWAT and to predict the impact of land management and the input data including the land use, soil type, and soil texture maps which are obtained from Landsat-8 satellite image. Digital Elevation Model,(DEM with resolution (14 14 meter is used to delineate the watershed with the aid of model. Three Land-sat images were used to cover the study area which were mosaic processed and the study area masked- up from the mosaic, image. The area of study has been registries by Arc-GIS 10.2 and digitized the soil hydrologic group through assistant of Soil Plant Assistant Water Model, (SPAW which was progressed by USDA, Agricultural, Research Service, using the data of soil textural and organic matter from Food and Agriculture Organization (FAO, the available water content, saturated hydraulic conductivity, and bulk density. The results of average, sediment depth and the maximum upland sediment for simulation period (2010-2020 were predicted to be (1.7 mm, and (12.57 Mg/ha, respectively.

  3. A Tool for Predicting Regulatory Approval After Phase II Testing of New Oncology Compounds.

    Science.gov (United States)

    DiMasi, J A; Hermann, J C; Twyman, K; Kondru, R K; Stergiopoulos, S; Getz, K A; Rackoff, W

    2015-11-01

    We developed an algorithm (ANDI) for predicting regulatory marketing approval for new cancer drugs after phase II testing has been conducted, with the objective of providing a tool to improve drug portfolio decision-making. We examined 98 oncology drugs from the top 50 pharmaceutical companies (2006 sales) that first entered clinical development from 1999 to 2007, had been taken to at least phase II development, and had a known final outcome (research abandonment or regulatory marketing approval). Data on safety, efficacy, operational, market, and company characteristics were obtained from public sources. Logistic regression and machine-learning methods were used to provide an unbiased approach to assess overall predictability and to identify the most important individual predictors. We found that a simple four-factor model (activity, number of patients in the pivotal phase II trial, phase II duration, and a prevalence-related measure) had high sensitivity and specificity for predicting regulatory marketing approval. © 2015 American Society for Clinical Pharmacology and Therapeutics.

  4. Human Splicing Finder: an online bioinformatics tool to predict splicing signals.

    Science.gov (United States)

    Desmet, François-Olivier; Hamroun, Dalil; Lalande, Marine; Collod-Béroud, Gwenaëlle; Claustres, Mireille; Béroud, Christophe

    2009-05-01

    Thousands of mutations are identified yearly. Although many directly affect protein expression, an increasing proportion of mutations is now believed to influence mRNA splicing. They mostly affect existing splice sites, but synonymous, non-synonymous or nonsense mutations can also create or disrupt splice sites or auxiliary cis-splicing sequences. To facilitate the analysis of the different mutations, we designed Human Splicing Finder (HSF), a tool to predict the effects of mutations on splicing signals or to identify splicing motifs in any human sequence. It contains all available matrices for auxiliary sequence prediction as well as new ones for binding sites of the 9G8 and Tra2-beta Serine-Arginine proteins and the hnRNP A1 ribonucleoprotein. We also developed new Position Weight Matrices to assess the strength of 5' and 3' splice sites and branch points. We evaluated HSF efficiency using a set of 83 intronic and 35 exonic mutations known to result in splicing defects. We showed that the mutation effect was correctly predicted in almost all cases. HSF could thus represent a valuable resource for research, diagnostic and therapeutic (e.g. therapeutic exon skipping) purposes as well as for global studies, such as the GEN2PHEN European Project or the Human Variome Project.

  5. Advanced Online Survival Analysis Tool for Predictive Modelling in Clinical Data Science.

    Science.gov (United States)

    Montes-Torres, Julio; Subirats, José Luis; Ribelles, Nuria; Urda, Daniel; Franco, Leonardo; Alba, Emilio; Jerez, José Manuel

    2016-01-01

    One of the prevailing applications of machine learning is the use of predictive modelling in clinical survival analysis. In this work, we present our view of the current situation of computer tools for survival analysis, stressing the need of transferring the latest results in the field of machine learning to biomedical researchers. We propose a web based software for survival analysis called OSA (Online Survival Analysis), which has been developed as an open access and user friendly option to obtain discrete time, predictive survival models at individual level using machine learning techniques, and to perform standard survival analysis. OSA employs an Artificial Neural Network (ANN) based method to produce the predictive survival models. Additionally, the software can easily generate survival and hazard curves with multiple options to personalise the plots, obtain contingency tables from the uploaded data to perform different tests, and fit a Cox regression model from a number of predictor variables. In the Materials and Methods section, we depict the general architecture of the application and introduce the mathematical background of each of the implemented methods. The study concludes with examples of use showing the results obtained with public datasets.

  6. CaFE: a tool for binding affinity prediction using end-point free energy methods.

    Science.gov (United States)

    Liu, Hui; Hou, Tingjun

    2016-07-15

    Accurate prediction of binding free energy is of particular importance to computational biology and structure-based drug design. Among those methods for binding affinity predictions, the end-point approaches, such as MM/PBSA and LIE, have been widely used because they can achieve a good balance between prediction accuracy and computational cost. Here we present an easy-to-use pipeline tool named Calculation of Free Energy (CaFE) to conduct MM/PBSA and LIE calculations. Powered by the VMD and NAMD programs, CaFE is able to handle numerous static coordinate and molecular dynamics trajectory file formats generated by different molecular simulation packages and supports various force field parameters. CaFE source code and documentation are freely available under the GNU General Public License via GitHub at https://github.com/huiliucode/cafe_plugin It is a VMD plugin written in Tcl and the usage is platform-independent. tingjunhou@zju.edu.cn. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  7. Optical coherence tomography: a potential tool to predict premature rupture of fetal membranes.

    Science.gov (United States)

    Micili, Serap C; Valter, Markus; Oflaz, Hakan; Ozogul, Candan; Linder, Peter; Föckler, Nicole; Artmann, Gerhard M; Digel, Ilya; Artmann, Aysegul T

    2013-04-01

    A fundamental question addressed in this study was the feasibility of preterm birth prediction based on a noncontact investigation of fetal membranes in situ. Although the phenomena of preterm birth and the premature rupture of the fetal membrane are well known, currently, there are no diagnostic tools for their prediction. The aim of this study was to assess whether optical coherence tomography could be used for clinical investigations of high-risk pregnancies. The thickness of fetal membranes was measured in parallel by optical coherence tomography and histological techniques for the following types of birth: normal births, preterm births without premature ruptures and births at full term with premature rupture of membrane. Our study revealed that the membrane thickness correlates with the birth type. Normal births membranes were statistically significantly thicker than those belonging to the other two groups. Thus, in spite of almost equal duration of gestation of the normal births and the births at full term with premature rupture, the corresponding membrane thicknesses differed. This difference is possibly related to previously reported water accumulation in the membranes. The optical coherence tomography results were encouraging, suggesting that this technology could be used in future to predict and distinguish between different kinds of births.

  8. Screening Tool to Determine Risk of Having Muscle Dysmorphia Symptoms in Men Who Engage in Weight Training at a Gym.

    Science.gov (United States)

    Palazón-Bru, Antonio; Rizo-Baeza, María M; Martínez-Segura, Asier; Folgado-de la Rosa, David M; Gil-Guillén, Vicente F; Cortés-Castell, Ernesto

    2018-03-01

    Although 2 screening tests exist for having a high risk of muscle dysmorphia (MD) symptoms, they both require a long time to apply. Accordingly, we proposed the construction, validation, and implementation of such a test in a mobile application using easy-to-measure factors associated with MD. Cross-sectional observational study. Gyms in Alicante (Spain) during 2013 to 2014. One hundred forty-one men who engaged in weight training. The variables are as follows: age, educational level, income, buys own food, physical activity per week, daily meals, importance of nutrition, special nutrition, guilt about dietary nonadherence, supplements, and body mass index (BMI). A points system was constructed through a binary logistic regression model to predict a high risk of MD symptoms by testing all possible combinations of secondary variables (5035). The system was validated using bootstrapping and implemented in a mobile application. High risk of having MD symptoms (Muscle Appearance Satisfaction Scale). Of the 141 participants, 45 had a high risk of MD symptoms [31.9%, 95% confidence interval (CI), 24.2%-39.6%]. The logistic regression model combination providing the largest area under the receiver operating characteristic curve (0.76) included the following: age [odds ratio (OR) = 0.90; 95% CI, 0.84-0.97, P = 0.007], guilt about dietary nonadherence (OR = 2.46; 95% CI, 1.06-5.73, P = 0.037), energy supplements (OR = 3.60; 95% CI, 1.54-8.44, P = 0.003), and BMI (OR = 1.33, 95% CI, 1.12-1.57, P < 0.001). The points system was validated through 1000 bootstrap samples. A quick, easy-to-use, 4-factor test that could serve as a screening tool for a high risk of MD symptoms has been constructed, validated, and implemented in a mobile application.

  9. Soil and Water Assessment Tool model predictions of annual maximum pesticide concentrations in high vulnerability watersheds.

    Science.gov (United States)

    Winchell, Michael F; Peranginangin, Natalia; Srinivasan, Raghavan; Chen, Wenlin

    2018-05-01

    Recent national regulatory assessments of potential pesticide exposure of threatened and endangered species in aquatic habitats have led to increased need for watershed-scale predictions of pesticide concentrations in flowing water bodies. This study was conducted to assess the ability of the uncalibrated Soil and Water Assessment Tool (SWAT) to predict annual maximum pesticide concentrations in the flowing water bodies of highly vulnerable small- to medium-sized watersheds. The SWAT was applied to 27 watersheds, largely within the midwest corn belt of the United States, ranging from 20 to 386 km 2 , and evaluated using consistent input data sets and an uncalibrated parameterization approach. The watersheds were selected from the Atrazine Ecological Exposure Monitoring Program and the Heidelberg Tributary Loading Program, both of which contain high temporal resolution atrazine sampling data from watersheds with exceptionally high vulnerability to atrazine exposure. The model performance was assessed based upon predictions of annual maximum atrazine concentrations in 1-d and 60-d durations, predictions critical in pesticide-threatened and endangered species risk assessments when evaluating potential acute and chronic exposure to aquatic organisms. The simulation results showed that for nearly half of the watersheds simulated, the uncalibrated SWAT model was able to predict annual maximum pesticide concentrations within a narrow range of uncertainty resulting from atrazine application timing patterns. An uncalibrated model's predictive performance is essential for the assessment of pesticide exposure in flowing water bodies, the majority of which have insufficient monitoring data for direct calibration, even in data-rich countries. In situations in which SWAT over- or underpredicted the annual maximum concentrations, the magnitude of the over- or underprediction was commonly less than a factor of 2, indicating that the model and uncalibrated parameterization

  10. Prediction of a thermodynamic wave train from the monsoon to the Arctic following extreme rainfall events

    Science.gov (United States)

    Krishnamurti, T. N.; Kumar, Vinay

    2017-04-01

    This study addresses numerical prediction of atmospheric wave trains that provide a monsoonal link to the Arctic ice melt. The monsoonal link is one of several ways that heat is conveyed to the Arctic region. This study follows a detailed observational study on thermodynamic wave trains that are initiated by extreme rain events of the northern summer south Asian monsoon. These wave trains carry large values of heat content anomalies, heat transports and convergence of flux of heat. These features seem to be important candidates for the rapid melt scenario. This present study addresses numerical simulation of the extreme rains, over India and Pakistan, and the generation of thermodynamic wave trains, simulations of large heat content anomalies, heat transports along pathways and heat flux convergences, potential vorticity and the diabatic generation of potential vorticity. We compare model based simulation of many features such as precipitation, divergence and the divergent wind with those evaluated from the reanalysis fields. We have also examined the snow and ice cover data sets during and after these events. This modeling study supports our recent observational findings on the monsoonal link to the rapid Arctic ice melt of the Canadian Arctic. This numerical modeling suggests ways to interpret some recent episodes of rapid ice melts that may require a well-coordinated field experiment among atmosphere, ocean, ice and snow cover scientists. Such a well-coordinated study would sharpen our understanding of this one component of the ice melt, i.e. the monsoonal link, which appears to be fairly robust.

  11. Using Precept-Assist® to predict performance on the American Board of Family Medicine In-Training Examination.

    Science.gov (United States)

    Post, Robert E; Jamena, Gemma P; Gamble, James D

    2014-09-01

    Precept-Assist® (PA) is a computer-based program developed by the Virtua Family Medicine Residency where residents receive a score on a Likert-type scale from an attending for each precept based on their knowledge base. The purpose of this study was to attempt to validate this program for precepting family medicine residents. This was a validation study. PA and American Board of Family Medicine (ABFM) In-Training Exam (ITE) scores for all residents from a community-based family medicine residency between the years 2002 and 2011 were included (n=216). Pearson correlation coefficients were calculated between PA scores for the second quarter of the academic year (October 1 to December 31) and scores on the ITE. An ROC curve was also created to determine sensitivity and specificity for various PA scores in predicting residents scoring 500 or above on the ITE. The PA mean (SD) score was 5.18 (0.84) and the ITE mean (SD) score was 425.1 (87.6). The Pearson correlation coefficient between PA and ITE scores was 0.55, which is a moderately positive correlation. The AUC of the ROC curve was 0.783 (95% CI 0.704-0.859). A PA score of 5.5 (between the level of a PGY-2 and PGY-3) was 72% sensitive and 77% specific for scoring 500 or above on the ITE with a positive LR of 3.12. There is a significant correlation between PA scores and ABFM In-Training Exam scores. PA is a valid screening tool that can be used as a predictor for future performance in Family Medicine In-Training exams.

  12. Pediatric Eating Assessment Tool-10 as an indicator to predict aspiration in children with esophageal atresia.

    Science.gov (United States)

    Soyer, Tutku; Yalcin, Sule; Arslan, Selen Serel; Demir, Numan; Tanyel, Feridun Cahit

    2017-10-01

    Airway aspiration is a common problem in children with esophageal atresia (EA). Pediatric Eating Assessment Tool-10 (pEAT-10) is a self-administered questionnaire to evaluate dysphagia symptoms in children. A prospective study was performed to evaluate the validity of pEAT-10 to predict aspiration in children with EA. Patients with EA were evaluated for age, sex, type of atresia, presence of associated anomalies, type of esophageal repair, time of definitive treatment, and the beginning of oral feeding. Penetration-aspiration score (PAS) was evaluated with videofluoroscopy (VFS) and parents were surveyed for pEAT-10, dysphagia score (DS) and functional oral intake scale (FOIS). PAS scores greater than 7 were considered as risk of aspiration. EAT-10 values greater than 3 were assessed as abnormal. Higher DS scores shows dysphagia whereas higher FOIS shows better feeding abilities. Forty patients were included. Children with PAS greater than 7 were assessed as PAS+ group, and scores less than 7 were constituted as PAS- group. Demographic features and results of surgical treatments showed no difference between groups (p>0.05). The median values of PAS, pEAT-10 and DS scores were significantly higher in PAS+ group when compared to PAS- group (p<0.05). The sensitivity and specificity of pEAT-10 to predict aspiration were 88% and 77%, and the positive and negative predictive values were 22% and 11%, respectively. Type-C cases had better pEAT-10 and FOIS scores with respect to type-A cases, and both scores were statistically more reliable in primary repair than delayed repair (p<0.05). Among the postoperative complications, only leakage had impact on DS, pEAT-10, PAS and FOIS scores (p<0.05). The pEAT-10 is a valid, simple and reliable tool to predict aspiration in children. Patients with higher pEAT-10 scores should undergo detailed evaluation of deglutitive functions and assessment of risks of aspiration to improve safer feeding strategies. Level II (Development of

  13. Model predictive control as a tool for improving the process operation of MSW combustion plants

    International Nuclear Information System (INIS)

    Leskens, M.; Kessel, L.B.M. van; Bosgra, O.H.

    2005-01-01

    In this paper a feasibility study is presented on the application of the advanced control strategy called model predictive control (MPC) as a tool for obtaining improved process operation performance for municipal solid waste (MSW) combustion plants. The paper starts with a discussion of the operational objectives and control of such plants, from which a motivation follows for applying MPC to them. This is followed by a discussion on the basic idea behind this advanced control strategy. After that, an MPC-based combustion control system is proposed aimed at tackling a typical MSW combustion control problem and, using this proposed control system, an assessment is made of the improvement in performance that an MPC-based MSW combustion control system can provide in comparison to conventional MSW combustion control systems. This assessment is based on simulations using an experimentally obtained process and disturbance model of a real-life large-scale MSW combustion plant

  14. A model of integration among prediction tools: applied study to road freight transportation

    Directory of Open Access Journals (Sweden)

    Henrique Dias Blois

    Full Text Available Abstract This study has developed a scenery analysis model which has integrated decision-making tools on investments: prospective scenarios (Grumbach Method and systems dynamics (hard modeling, with the innovated multivariate analysis of experts. It was designed through analysis and simulation scenarios and showed which are the most striking events in the study object as well as highlighted the actions could redirect the future of the analyzed system. Moreover, predictions are likely to be developed through the generated scenarios. The model has been validated empirically with road freight transport data from state of Rio Grande do Sul, Brazil. The results showed that the model contributes to the analysis of investment because it identifies probabilities of events that impact on decision making, and identifies priorities for action, reducing uncertainties in the future. Moreover, it allows an interdisciplinary discussion that correlates different areas of knowledge, fundamental when you wish more consistency in creating scenarios.

  15. A low-dimensional tool for predicting force decomposition coefficients for varying inflow conditions

    KAUST Repository

    Ghommem, Mehdi; Akhtar, Imran; Hajj, M. R.

    2013-01-01

    We develop a low-dimensional tool to predict the effects of unsteadiness in the inflow on force coefficients acting on a circular cylinder using proper orthogonal decomposition (POD) modes from steady flow simulations. The approach is based on combining POD and linear stochastic estimator (LSE) techniques. We use POD to derive a reduced-order model (ROM) to reconstruct the velocity field. To overcome the difficulty of developing a ROM using Poisson's equation, we relate the pressure field to the velocity field through a mapping function based on LSE. The use of this approach to derive force decomposition coefficients (FDCs) under unsteady mean flow from basis functions of the steady flow is illustrated. For both steady and unsteady cases, the final outcome is a representation of the lift and drag coefficients in terms of velocity and pressure temporal coefficients. Such a representation could serve as the basis for implementing control strategies or conducting uncertainty quantification. Copyright © 2013 Inderscience Enterprises Ltd.

  16. Research-Based Monitoring, Prediction, and Analysis Tools of the Spacecraft Charging Environment for Spacecraft Users

    Science.gov (United States)

    Zheng, Yihua; Kuznetsova, Maria M.; Pulkkinen, Antti A.; Maddox, Marlo M.; Mays, Mona Leila

    2015-01-01

    The Space Weather Research Center (http://swrc. gsfc.nasa.gov) at NASA Goddard, part of the Community Coordinated Modeling Center (http://ccmc.gsfc.nasa.gov), is committed to providing research-based forecasts and notifications to address NASA's space weather needs, in addition to its critical role in space weather education. It provides a host of services including spacecraft anomaly resolution, historical impact analysis, real-time monitoring and forecasting, tailored space weather alerts and products, and weekly summaries and reports. In this paper, we focus on how (near) real-time data (both in space and on ground), in combination with modeling capabilities and an innovative dissemination system called the integrated Space Weather Analysis system (http://iswa.gsfc.nasa.gov), enable monitoring, analyzing, and predicting the spacecraft charging environment for spacecraft users. Relevant tools and resources are discussed.

  17. MODIFIED MALLAMPATI CLASSIFICATION SCORE- A SIMPLE TOOL FOR PREDICTING TOLERANCE IN UNSEDATED OESOPHAGOGASTRODUODENOSCOPY

    Directory of Open Access Journals (Sweden)

    Abishek Sasidharan

    2017-04-01

    Full Text Available BACKGROUND 40-47% of patients poorly tolerates esophagogastroduodenoscopy (EGD. Early identification of potentially intolerant patients improve procedural success and avoid patient discomfort. Modified Mallampati Classification (MMC score is a simple scoring system used to predict difficult tracheal intubation and laryngoscope insertion. As EGD involves the same level of patient discomfort during introduction, MMC may predict EGD tolerance. MATERIALS AND METHODS 100 patients with dyspeptic symptoms and no alarm features attending our department were recruited for unsedated EGD between January and July 2012. All patients had good performance status and underlying anxiety disorder was excluded. Based on MMC, patients placed into 4 classes- I: Soft palate, fauces, pillars and uvula visible. II: Soft palate, fauces and uvula visible. III: Soft palate and base of uvula visible. IV: Soft palate not visible. They were divided into good view (class I and II and poor view (class III and IV. EGD was performed by the same consultant and MMS status assessed by two independent trained personnel. All received 2 doses of topical pharyngeal spray containing 10% lidocaine hydrochloride. Outcome measurements were gag reflex, endoscopist’s assessment and patient feedback. RESULTS Of 100 patients, 52 were males. 58 in group A and 42 in group B. Gag reflex was present in 32.7% of good view group compared to 78.6% in poor view (p<0.001. From the endoscopist’s view, good tolerability observed in 72.4% of good view group compared to 21% in poor view (p<0.001. 74.1% patient reported satisfactory feedback in good view group compared to 19% in poor view group (p<0.001. CONCLUSION MMC is a good clinical indicator for predicting tolerance in unsedated EGD.

  18. Predicting risk and outcomes for frail older adults: an umbrella review of frailty screening tools

    Science.gov (United States)

    Apóstolo, João; Cooke, Richard; Bobrowicz-Campos, Elzbieta; Santana, Silvina; Marcucci, Maura; Cano, Antonio; Vollenbroek-Hutten, Miriam; Germini, Federico; Holland, Carol

    2017-01-01

    EXECUTIVE SUMMARY Background A scoping search identified systematic reviews on diagnostic accuracy and predictive ability of frailty measures in older adults. In most cases, research was confined to specific assessment measures related to a specific clinical model. Objectives To summarize the best available evidence from systematic reviews in relation to reliability, validity, diagnostic accuracy and predictive ability of frailty measures in older adults. Inclusion criteria Population Older adults aged 60 years or older recruited from community, primary care, long-term residential care and hospitals. Index test Available frailty measures in older adults. Reference test Cardiovascular Health Study phenotype model, the Canadian Study of Health and Aging cumulative deficit model, Comprehensive Geriatric Assessment or other reference tests. Diagnosis of interest Frailty defined as an age-related state of decreased physiological reserves characterized by an increased risk of poor clinical outcomes. Types of studies Quantitative systematic reviews. Search strategy A three-step search strategy was utilized to find systematic reviews, available in English, published between January 2001 and October 2015. Methodological quality Assessed by two independent reviewers using the Joanna Briggs Institute critical appraisal checklist for systematic reviews and research synthesis. Data extraction Two independent reviewers extracted data using the standardized data extraction tool designed for umbrella reviews. Data synthesis Data were only presented in a narrative form due to the heterogeneity of included reviews. Results Five reviews with a total of 227,381 participants were included in this umbrella review. Two reviews focused on reliability, validity and diagnostic accuracy; two examined predictive ability for adverse health outcomes; and one investigated validity, diagnostic accuracy and predictive ability. In total, 26 questionnaires and brief assessments and eight frailty

  19. External validation of approaches to prediction of falls during hospital rehabilitation stays and development of a new simpler tool

    Directory of Open Access Journals (Sweden)

    Angela Vratsistas-Curto

    2017-12-01

    Full Text Available Objectives: To test the external validity of 4 approaches to fall prediction in a rehabilitation setting (Predict_FIRST, Ontario Modified STRATIFY (OMS, physiotherapists’ judgement of fall risk (PT_Risk, and falls in the past year (Past_Falls, and to develop and test the validity of a simpler tool for fall prediction in rehabilitation (Predict_CM2. Participants: A total of 300 consecutively-admitted rehabilitation inpatients. Methods: Prospective inception cohort study. Falls during the rehabilitation stay were monitored. Potential predictors were extracted from medical records. Results: Forty-one patients (14% fell during their rehabilitation stay. The external validity, area under the receiver operating characteristic curve (AUC, for predicting future fallers was: 0.71 (95% confidence interval (95% CI: 0.61–0.81 for OMS (Total_Score; 0.66 (95% CI: 0.57–0.74 for Predict_FIRST; 0.65 (95% CI 0.57–0.73 for PT_Risk; and 0.52 for Past_Falls (95% CI: 0.46–0.60. A simple 3-item tool (Predict_CM2 was developed from the most predictive individual items (impaired mobility/transfer ability, impaired cognition, and male sex. The accuracy of Predict_CM2 was 0.73 (95% CI: 0.66–0.81, comparable to OMS (Total_Score (p = 0.52, significantly better than Predict_FIRST (p = 0.04, and Past_Falls (p < 0.001, and approaching significantly better than PT_Risk (p = 0.09. Conclusion: Predict_CM2 is a simpler screening tool with similar accuracy for predicting fallers in rehabilitation to OMS (Total_Score and better accuracy than Predict_FIRST or Past_Falls. External validation of Predict_CM2 is required.

  20. Application of the Streamflow Prediction Tool to Estimate Sediment Dredging Volumes in Texas Coastal Waterways

    Science.gov (United States)

    Yeates, E.; Dreaper, G.; Afshari, S.; Tavakoly, A. A.

    2017-12-01

    Over the past six fiscal years, the United States Army Corps of Engineers (USACE) has contracted an average of about a billion dollars per year for navigation channel dredging. To execute these funds effectively, USACE Districts must determine which navigation channels need to be dredged in a given year. Improving this prioritization process results in more efficient waterway maintenance. This study uses the Streamflow Prediction Tool, a runoff routing model based on global weather forecast ensembles, to estimate dredged volumes. This study establishes regional linear relationships between cumulative flow and dredged volumes over a long-term simulation covering 30 years (1985-2015), using drainage area and shoaling parameters. The study framework integrates the National Hydrography Dataset (NHDPlus Dataset) with parameters from the Corps Shoaling Analysis Tool (CSAT) and dredging record data from USACE District records. Results in the test cases of the Houston Ship Channel and the Sabine and Port Arthur Harbor waterways in Texas indicate positive correlation between the simulated streamflows and actual dredging records.

  1. Computational tools for genome-wide miRNA prediction and study

    KAUST Repository

    Malas, T.B.; Ravasi, Timothy

    2012-01-01

    MicroRNAs (miRNAs) are single-stranded non-coding RNA susually of 22 nucleotidesin length that play an important post-transcriptional regulation role in many organisms. MicroRNAs bind a seed sequence to the 3-untranslated region (UTR) region of the target messenger RNA (mRNA), inducing degradation or inhibition of translation and resulting in a reduction in the protein level. This regulatory mechanism is central to many biological processes and perturbation could lead to diseases such as cancer. Given the biological importance, of miRNAs, there is a great need to identify and study their targets and functions. However, miRNAs are very difficult to clone in the lab and this has hindered the identification of novel miRNAs. Next-generation sequencing coupled with new computational tools has recently evolved to help researchers efficiently identify large numbers of novel miRNAs. In this review, we describe recent miRNA prediction tools and discuss their priorities, advantages and disadvantages. Malas and Ravasi.

  2. Ecotoxicity on a stick: A novel analytical tool for predicting the ecotoxicity of petroleum contaminated samples

    International Nuclear Information System (INIS)

    Parkerton, T.F.; Stone, M.A.

    1995-01-01

    Hydrocarbons generally elicit toxicity via a nonpolar narcotic mechanism. Recent research suggests that chemicals acting by this mode invoke ecotoxicity when the molar concentration in organisms lipid exceeds a critical threshold. Since ecotoxicity of nonpolar narcotic mixtures appears to be additive, the ecotoxicity of hydrocarbon mixtures thus depends upon: (1) the partitioning of individual hydrocarbons comprising the mixture from the environment to lipids and (2) the total molar sum of the constituent hydrocarbons in lipids. These insights have led previous investigators to advance the concept of biomimetic extraction as a novel tool for assessing potential narcosis-type or baseline ecotoxicity in aqueous samples. Drawing from this earlier work, the authors have developed a method to quantify Bioavailable Petroleum Hydrocarbons (BPHS) in hydrocarbon-contaminated aqueous and soil/sediment samples. A sample is equilibrated with a solid phase microextraction (SPME) fiber that serves as a surrogate for organism lipids. The total moles of hydrocarbons that partition to the SPME fiber is then quantified using a simple GC/FID procedure. Research conducted to support the development and initial validation of this method will be presented. Results suggest that BPH analyses provide a promising, cost-effective approach for predicting the ecotoxicity of environmental samples contaminated with hydrocarbon mixtures. Consequently, BPH analyses may provide a valuable analytical screening tool for ecotoxicity assessment in product and effluent testing, environmental monitoring and site remediation applications

  3. Tool-life prediction under multi-cycle loading during metal forming: a feasibility study

    Directory of Open Access Journals (Sweden)

    Hu Yiran

    2015-01-01

    Full Text Available In the present research, the friction and wear behaviour of a hard coating were studied by using ball-on-disc tests to simulate the wear process of the coated tools for sheet metal forming process. The evolution of the friction coefficient followed a typical dual-plateau pattern, i.e. at the initial stage of sliding, the friction coefficient was relatively low, followed by a sharp increase due to the breakdown of the coatings after a certain number of cyclic dynamic loadings. This phenomenon was caused by the interactive response between the friction and wear from a coating tribo-system, which is often neglected by metal forming researchers, and constant friction coefficient values are normally used in the finite element (FE simulations to represent the complex tribological nature at the contact interfaces. Meanwhile, most of the current FE simulations consider single-cycle loading processes, whereas many metal-forming operations are conducted in a form of multi-cycle loading. Therefore, a novel friction/wear interactive friction model was developed to, simultaneously, characterise the evolutions of friction coefficient and the remaining thickness of the coating layer, to enable the wear life of coated tooling to be predicted. The friction model was then implemented into the FE simulation of a sheet metal forming process for feasibility study.

  4. Tool life prediction under multi-cycle loading conditions: A feasibility study

    Directory of Open Access Journals (Sweden)

    Yuan Xi

    2015-01-01

    Full Text Available In the present research, the friction and wear behaviour of a hard coating were studied by using ball-on-disc tests to simulate the wear process of the coated tools for sheet metal forming process. The evolution of the friction coefficient followed a typical dual-plateau pattern, i.e. at the initial stage of sliding, the friction coefficient was relatively low, followed by a sharp increase due to the breakdown of the coatings after a certain number of cyclic dynamic loadings. This phenomenon was caused by the interactive response between the friction and wear from a coating tribo-system, which has not been addressed so far by metal forming researchers, and constant friction coefficient values are normally used in the FE simulations to represent the complex tribological nature at the contact interfaces. Meanwhile, most of the current FE simulations are single cycle, whereas most sheet metal forming operations are conducted as multi-cycle. Therefore, a novel friction/wear interactive friction model was developed to, simultaneously, characterise the evolutions of friction coefficient and the remaining thickness of the coating layer, to enable the wear life of coated tooling to be predicted. The friction model was then implemented into the FE simulation of a sheet metal forming process for feasibility study.

  5. Computational tools for genome-wide miRNA prediction and study

    KAUST Repository

    Malas, T.B.

    2012-11-02

    MicroRNAs (miRNAs) are single-stranded non-coding RNA susually of 22 nucleotidesin length that play an important post-transcriptional regulation role in many organisms. MicroRNAs bind a seed sequence to the 3-untranslated region (UTR) region of the target messenger RNA (mRNA), inducing degradation or inhibition of translation and resulting in a reduction in the protein level. This regulatory mechanism is central to many biological processes and perturbation could lead to diseases such as cancer. Given the biological importance, of miRNAs, there is a great need to identify and study their targets and functions. However, miRNAs are very difficult to clone in the lab and this has hindered the identification of novel miRNAs. Next-generation sequencing coupled with new computational tools has recently evolved to help researchers efficiently identify large numbers of novel miRNAs. In this review, we describe recent miRNA prediction tools and discuss their priorities, advantages and disadvantages. Malas and Ravasi.

  6. ProBiS tools (algorithm, database, and web servers) for predicting and modeling of biologically interesting proteins.

    Science.gov (United States)

    Konc, Janez; Janežič, Dušanka

    2017-09-01

    ProBiS (Protein Binding Sites) Tools consist of algorithm, database, and web servers for prediction of binding sites and protein ligands based on the detection of structurally similar binding sites in the Protein Data Bank. In this article, we review the operations that ProBiS Tools perform, provide comments on the evolution of the tools, and give some implementation details. We review some of its applications to biologically interesting proteins. ProBiS Tools are freely available at http://probis.cmm.ki.si and http://probis.nih.gov. Copyright © 2017 Elsevier Ltd. All rights reserved.

  7. INFLUENCE OF DANCE TRAINING ON SACCULOCOLLIC PATHWAY: VESTIBULAR EVOKED MYOGENIC POTENTIALS (VEMP) AS AN OBJECTIVE TOOL

    OpenAIRE

    Swathi; Sathish Kumar

    2013-01-01

    ABSTRACT : Auditory system is shaped by experience and training. Training (s ensory experience) induces neurophysiologic changes & plasticity in normal hearing individuals, hearing loss patients, hearing aid users and cochlear implanted subjects. Not only speech stimulus, but music also brings about functional and structural organi zation of the brain in musician compared to non - musicians. The Vestibular evoked myogenic potentials (VEMP) are a biphasic in...

  8. Face, content, and construct validity of human placenta as a haptic training tool in neurointerventional surgery.

    Science.gov (United States)

    Ribeiro de Oliveira, Marcelo Magaldi; Nicolato, Arthur; Santos, Marcilea; Godinho, Joao Victor; Brito, Rafael; Alvarenga, Alexandre; Martins, Ana Luiza Valle; Prosdocimi, André; Trivelato, Felipe Padovani; Sabbagh, Abdulrahman J; Reis, Augusto Barbosa; Maestro, Rolando Del

    2016-05-01

    OBJECT The development of neurointerventional treatments of central nervous system disorders has resulted in the need for adequate training environments for novice interventionalists. Virtual simulators offer anatomical definition but lack adequate tactile feedback. Animal models, which provide more lifelike training, require an appropriate infrastructure base. The authors describe a training model for neurointerventional procedures using the human placenta (HP), which affords haptic training with significantly fewer resource requirements, and discuss its validation. METHODS Twelve HPs were prepared for simulated endovascular procedures. Training exercises performed by interventional neuroradiologists and novice fellows were placental angiography, stent placement, aneurysm coiling, and intravascular liquid embolic agent injection. RESULTS The endovascular training exercises proposed can be easily reproduced in the HP. Face, content, and construct validity were assessed by 6 neurointerventional radiologists and 6 novice fellows in interventional radiology. CONCLUSIONS The use of HP provides an inexpensive training model for the training of neurointerventionalists. Preliminary validation results show that this simulation model has face and content validity and has demonstrated construct validity for the interventions assessed in this study.

  9. Social Informatics: Natural Tools for Students' Information Training in The Conditions of Embodied and Mental Approaches Being Employed

    Directory of Open Access Journals (Sweden)

    Daria Barkhatova

    2017-09-01

    Full Text Available The relevance of the problem under study is due to the society's requirements for the quality information training of a personality which is oriented to forming the solid fundamental knowledge as well as to developing the cognitive capacities that are needed for solving mental tasks. With regard to this, the paper is aimed at finding out the opportunities of applying the natural tools in information training of students from the standpoints of embodied and mental approaches. The main idea of these is integrated studying of an object, beginning with learning it in an "embodied" way and finishing with abstract models formed in the human memory. The leading approach to the research is the integrated one taking into account the psychological and pedagogical, didactic and methodological constituents. It allows identifying the psychological and pedagogical conditions of application of natural tools as well as the possible ways of their use. The authors describe models of natural tools of computer science training in individual sections of the school course as the main results. The materials of the paper are of practical value in methods of teaching computer science to students at various stages of education.

  10. THE METHODICAL ASPECTS OF MAXIMA USING AS A TOOL FOR FUNDAMENTAL TRAINING OF BACHELORS OF COMPUTER SCIENCE

    Directory of Open Access Journals (Sweden)

    M. Shyshkina

    2014-07-01

    Full Text Available Within the formation of the information society, where the pace of scientific progress is rapidly growing, it is difficult to provide the training for immediate inclusion of the person into the production chain at a workplace or in an educational system. There is the way out and it is fundamentalization of informatics education. It is necessary to train the specialist so that he (she could be able to be adapted quickly to the changes occurring in the industry technological development; to give him knowledge, universal in nature, so as the expert may navigate quickly to resolve the professional tasks on this basis. The article describes the trends of systems of computer mathematics (SCM pedagogical use for teaching computer science disciplines. The general characteristics and conditions for effective use of the Maxima as a tool for fundamentalization of the bachelors learning process are outlined. The ways of informatics disciplines teaching methodology are revealed. The peculiarities of cloud based learning solutions are considered. The purpose of the article is the analysis of contemporary approaches to the use of systems of computer mathematics as a tool for fundamentalization of informatics disciplines training courses and identify methodological aspects of these systems application for the teaching of operations research as by the example of SCM Maxima. The object of investigation is the learning process of informatics bachelors with the use of SCM. The subject of investigation is the peculiarities of using the SCM Maxima as a learning tool for informatics courses support

  11. Plant training for induced defense against insect pests: a promising tool for integrated pest management in cotton.

    Science.gov (United States)

    Llandres, Ana L; Almohamad, Raki; Brévault, Thierry; Renou, Alain; Téréta, Idrissa; Jean, Janine; Goebel, François-Regis

    2018-04-17

    Enhancing cotton pest management using plant natural defenses has been described as a promising way to improve the management of crop pests. We here reviewed different studies on cotton growing systems to illustrate how an ancient technique called plant training, which includes plant topping and pruning, may contribute to this goal. Based on examples from cotton crops, we show how trained plants could be promoted to a state of enhanced defense that causes faster and more robust activation of their defense responses. We revisit agricultural benefits associated to this technique in cotton crops, with a focus on its potential as a supplementary tool for Integrated Pest Management (IPM). Particularly, we examine its role in mediating plant interactions with conspecific neighboring plants, pests and associated natural enemies. We propose a new IPM tool, plant training for induced defense, which involves inducing plant defense by artificial injuries. Experimental evidence from various studies shows that cotton training is a promising technique, particularly for smallholders, which can be used as part of an IPM program to significantly reduce insecticide use and to improve productivity in cotton farming. This article is protected by copyright. All rights reserved.

  12. Impact of sampling interval in training data acquisition on intrafractional predictive accuracy of indirect dynamic tumor-tracking radiotherapy.

    Science.gov (United States)

    Mukumoto, Nobutaka; Nakamura, Mitsuhiro; Akimoto, Mami; Miyabe, Yuki; Yokota, Kenji; Matsuo, Yukinori; Mizowaki, Takashi; Hiraoka, Masahiro

    2017-08-01

    To explore the effect of sampling interval of training data acquisition on the intrafractional prediction error of surrogate signal-based dynamic tumor-tracking using a gimbal-mounted linac. Twenty pairs of respiratory motions were acquired from 20 patients (ten lung, five liver, and five pancreatic cancer patients) who underwent dynamic tumor-tracking with the Vero4DRT. First, respiratory motions were acquired as training data for an initial construction of the prediction model before the irradiation. Next, additional respiratory motions were acquired for an update of the prediction model due to the change of the respiratory pattern during the irradiation. The time elapsed prior to the second acquisition of the respiratory motion was 12.6 ± 3.1 min. A four-axis moving phantom reproduced patients' three dimensional (3D) target motions and one dimensional surrogate motions. To predict the future internal target motion from the external surrogate motion, prediction models were constructed by minimizing residual prediction errors for training data acquired at 80 and 320 ms sampling intervals for 20 s, and at 500, 1,000, and 2,000 ms sampling intervals for 60 s using orthogonal kV x-ray imaging systems. The accuracies of prediction models trained with various sampling intervals were estimated based on training data with each sampling interval during the training process. The intrafractional prediction errors for various prediction models were then calculated on intrafractional monitoring images taken for 30 s at the constant sampling interval of a 500 ms fairly to evaluate the prediction accuracy for the same motion pattern. In addition, the first respiratory motion was used for the training and the second respiratory motion was used for the evaluation of the intrafractional prediction errors for the changed respiratory motion to evaluate the robustness of the prediction models. The training error of the prediction model was 1.7 ± 0.7 mm in 3D for all sampling

  13. "Best Case/Worst Case": Training Surgeons to Use a Novel Communication Tool for High-Risk Acute Surgical Problems.

    Science.gov (United States)

    Kruser, Jacqueline M; Taylor, Lauren J; Campbell, Toby C; Zelenski, Amy; Johnson, Sara K; Nabozny, Michael J; Steffens, Nicole M; Tucholka, Jennifer L; Kwekkeboom, Kris L; Schwarze, Margaret L

    2017-04-01

    Older adults often have surgery in the months preceding death, which can initiate postoperative treatments inconsistent with end-of-life values. "Best Case/Worst Case" (BC/WC) is a communication tool designed to promote goal-concordant care during discussions about high-risk surgery. The objective of this study was to evaluate a structured training program designed to teach surgeons how to use BC/WC. Twenty-five surgeons from one tertiary care hospital completed a two-hour training session followed by individual coaching. We audio-recorded surgeons using BC/WC with standardized patients and 20 hospitalized patients. Hospitalized patients and their families participated in an open-ended interview 30 to 120 days after enrollment. We used a checklist of 11 BC/WC elements to measure tool fidelity and surgeons completed the Practitioner Opinion Survey to measure acceptability of the tool. We used qualitative analysis to evaluate variability in tool content and to characterize patient and family perceptions of the tool. Surgeons completed a median of 10 of 11 BC/WC elements with both standardized and hospitalized patients (range 5-11). We found moderate variability in presentation of treatment options and description of outcomes. Three months after training, 79% of surgeons reported BC/WC is better than their usual approach and 71% endorsed active use of BC/WC in clinical practice. Patients and families found that BC/WC established expectations, provided clarity, and facilitated deliberation. Surgeons can learn to use BC/WC with older patients considering acute high-risk surgical interventions. Surgeons, patients, and family members endorse BC/WC as a strategy to support complex decision making. Copyright © 2017 American Academy of Hospice and Palliative Medicine. Published by Elsevier Inc. All rights reserved.

  14. IPMP Global Fit - A one-step direct data analysis tool for predictive microbiology.

    Science.gov (United States)

    Huang, Lihan

    2017-12-04

    The objective of this work is to develop and validate a unified optimization algorithm for performing one-step global regression analysis of isothermal growth and survival curves for determination of kinetic parameters in predictive microbiology. The algorithm is incorporated with user-friendly graphical interfaces (GUIs) to develop a data analysis tool, the USDA IPMP-Global Fit. The GUIs are designed to guide the users to easily navigate through the data analysis process and properly select the initial parameters for different combinations of mathematical models. The software is developed for one-step kinetic analysis to directly construct tertiary models by minimizing the global error between the experimental observations and mathematical models. The current version of the software is specifically designed for constructing tertiary models with time and temperature as the independent model parameters in the package. The software is tested with a total of 9 different combinations of primary and secondary models for growth and survival of various microorganisms. The results of data analysis show that this software provides accurate estimates of kinetic parameters. In addition, it can be used to improve the experimental design and data collection for more accurate estimation of kinetic parameters. IPMP-Global Fit can be used in combination with the regular USDA-IPMP for solving the inverse problems and developing tertiary models in predictive microbiology. Published by Elsevier B.V.

  15. Training algorithms evaluation for artificial neural network to temporal prediction of photovoltaic generation

    International Nuclear Information System (INIS)

    Arantes Monteiro, Raul Vitor; Caixeta Guimarães, Geraldo; Rocio Castillo, Madeleine; Matheus Moura, Fabrício Augusto; Tamashiro, Márcio Augusto

    2016-01-01

    Current energy policies are encouraging the connection of power generation based on low-polluting technologies, mainly those using renewable sources, to distribution networks. Hence, it becomes increasingly important to understand technical challenges, facing high penetration of PV systems at the grid, especially considering the effects of intermittence of this source on the power quality, reliability and stability of the electric distribution system. This fact can affect the distribution networks on which they are attached causing overvoltage, undervoltage and frequency oscillations. In order to predict these disturbs, artificial neural networks are used. This article aims to analyze 3 training algorithms used in artificial neural networks for temporal prediction of the generated active power thru photovoltaic panels. As a result it was concluded that the algorithm with the best performance among the 3 analyzed was the Levenberg-Marquadrt.

  16. Same admissions tools, different outcomes: a critical perspective on predictive validity in three undergraduate medical schools.

    Science.gov (United States)

    Edwards, Daniel; Friedman, Tim; Pearce, Jacob

    2013-12-27

    Admission to medical school is one of the most highly competitive entry points in higher education. Considerable investment is made by universities to develop selection processes that aim to identify the most appropriate candidates for their medical programs. This paper explores data from three undergraduate medical schools to offer a critical perspective of predictive validity in medical admissions. This study examined 650 undergraduate medical students from three Australian universities as they progressed through the initial years of medical school (accounting for approximately 25 per cent of all commencing undergraduate medical students in Australia in 2006 and 2007). Admissions criteria (aptitude test score based on UMAT, school result and interview score) were correlated with GPA over four years of study. Standard regression of each of the three admissions variables on GPA, for each institution at each year level was also conducted. Overall, the data found positive correlations between performance in medical school, school achievement and UMAT, but not interview. However, there were substantial differences between schools, across year levels, and within sections of UMAT exposed. Despite this, each admission variable was shown to add towards explaining course performance, net of other variables. The findings suggest the strength of multiple admissions tools in predicting outcomes of medical students. However, they also highlight the large differences in outcomes achieved by different schools, thus emphasising the pitfalls of generalising results from predictive validity studies without recognising the diverse ways in which they are designed and the variation in the institutional contexts in which they are administered. The assumption that high-positive correlations are desirable (or even expected) in these studies is also problematised.

  17. Landscape capability models as a tool to predict fine-scale forest bird occupancy and abundance

    Science.gov (United States)

    Loman, Zachary G.; DeLuca, William; Harrison, Daniel J.; Loftin, Cynthia S.; Rolek, Brian W.; Wood, Petra B.

    2018-01-01

    ContextSpecies-specific models of landscape capability (LC) can inform landscape conservation design. Landscape capability is “the ability of the landscape to provide the environment […] and the local resources […] needed for survival and reproduction […] in sufficient quantity, quality and accessibility to meet the life history requirements of individuals and local populations.” Landscape capability incorporates species’ life histories, ecologies, and distributions to model habitat for current and future landscapes and climates as a proactive strategy for conservation planning.ObjectivesWe tested the ability of a set of LC models to explain variation in point occupancy and abundance for seven bird species representative of spruce-fir, mixed conifer-hardwood, and riparian and wooded wetland macrohabitats.MethodsWe compiled point count data sets used for biological inventory, species monitoring, and field studies across the northeastern United States to create an independent validation data set. Our validation explicitly accounted for underestimation in validation data using joint distance and time removal sampling.ResultsBlackpoll warbler (Setophaga striata), wood thrush (Hylocichla mustelina), and Louisiana (Parkesia motacilla) and northern waterthrush (P. noveboracensis) models were validated as predicting variation in abundance, although this varied from not biologically meaningful (1%) to strongly meaningful (59%). We verified all seven species models [including ovenbird (Seiurus aurocapilla), blackburnian (Setophaga fusca) and cerulean warbler (Setophaga cerulea)], as all were positively related to occupancy data.ConclusionsLC models represent a useful tool for conservation planning owing to their predictive ability over a regional extent. As improved remote-sensed data become available, LC layers are updated, which will improve predictions.

  18. Extending the features of RBMK refuelling machine simulator with a training tool based on virtual reality

    International Nuclear Information System (INIS)

    Khoudiakov, M.; Slonimsky, V.; Mitrofanov, S.

    2004-01-01

    The paper describes a continuation of efforts of an international Russian - Norwegian joint team to improve operational safety during the refuelling process of an RBMK-type reactor by implementing a training simulator based on an innovative Virtual Reality (VR) approach. During the preceding 1st stage of the project a display-based simulator was extended with VR models of the real Refuelling Machine (RM) and its environment in order to improve both the learning process and operation's effectiveness. The simulator's challenge is to support the performance (operational activity) of RM operational staff firstly by helping them to develop basic knowledge and skills as well as to keep skilled staff in close touch with the complex machinery of the Refuelling Machine. During the 2nd stage of the joint project the functional scope of the VR-simulator was greatly enhanced - firstly, by connecting to the RBMK-unit full-scope simulator, and, secondly, by including a training program and simulator model upgrade. The present 3rd stage of the Project is primarily oriented towards the improvement of the training process for maintenance and operational personnel by means of a development of the Training Support Methodology and Courses (TSMC) to be based on Virtual Reality and enlarged functionality of 3D and process modelling. The TMSC development is based on Russian and International Regulatory Bodies requirements and recommendations. Design, development and creation of a specialised VR-based Training System for RM Maintenance Personnel are very important for the Russian RBMK plants. The main goal is to create a powerful, autonomous VR-based simulator for training technical maintenance personnel on the Refuelling Machine. VR based training is expected to improve the effect of training compared to the current training based on traditional methods using printed documentation. The LNPP management and the Regulatory Bodies supported this goal. The VR-based Training System should

  19. EdGCM: Research Tools for Training the Climate Change Generation

    Science.gov (United States)

    Chandler, M. A.; Sohl, L. E.; Zhou, J.; Sieber, R.

    2011-12-01

    Climate scientists employ complex computer simulations of the Earth's physical systems to prepare climate change forecasts, study the physical mechanisms of climate, and to test scientific hypotheses and computer parameterizations. The Intergovernmental Panel on Climate Change 4th Assessment Report (2007) demonstrates unequivocally that policy makers rely heavily on such Global Climate Models (GCMs) to assess the impacts of potential economic and emissions scenarios. However, true climate modeling capabilities are not disseminated to the majority of world governments or U.S. researchers - let alone to the educators who will be training the students who are about to be presented with a world full of climate change stakeholders. The goal is not entirely quixotic; in fact, by the mid-1990's prominent climate scientists were predicting with certainty that schools and politicians would "soon" be running GCMs on laptops [Randall, 1996]. For a variety of reasons this goal was never achieved (nor even really attempted). However, around the same time NASA and the National Science Foundation supported a small pilot project at Columbia University to show the potential of putting sophisticated computer climate models - not just "demos" or "toy models" - into the hands of non-specialists. The Educational Global Climate Modeling Project (EdGCM) gave users access to a real global climate model and provided them with the opportunity to experience the details of climate model setup, model operation, post-processing and scientific visualization. EdGCM was designed for use in both research and education - it is a full-blown research GCM, but the ultimate goal is to develop a capability to embed these crucial technologies across disciplines, networks, platforms, and even across academia and industry. With this capability in place we can begin training the skilled workforce that is necessary to deal with the multitude of climate impacts that will occur over the coming decades. To

  20. Cognitive training with and without additional physical activity in healthy older adults: cognitive effects, neurobiological mechanisms, and prediction of training success

    Directory of Open Access Journals (Sweden)

    Julia eRahe

    2015-10-01

    Full Text Available Data is inconsistent concerning the question whether cognitive-physical training (CPT yields stronger cognitive gains than cognitive training (CT. Effects of additional counseling, neurobiological mechanisms, and predictors have scarcely been studied. Healthy older adults were trained with CT (n=20, CPT (n=25, or CPT with counseling (CPT+C; n=23. Cognition, physical fitness, BDNF, IGF-1, and VEGF were assessed at pre- and posttest. No interaction effects were found except for one effect showing that CPT+C led to stronger gains in verbal fluency than CPT (p = .03. However, this superiority could not be assigned to additional physical training gains. Low baseline cognitive performance and BDNF, not carrying apoE4, gains in physical fitness and the moderation of gains in physical fitness x gains in BDNF predicted training success. Although all types of interventions seem successful to enhance cognition, our data do not support the hypotheses that CPT shows superior cognitive training gains compared to CT or that CPT+C adds merit to CPT. However, as CPT leads to additional gains in physical fitness which in turn is known to have positive impact on cognition in the long-term, CPT seems more beneficial. Training success can partly be predicted by neuropsychological, neurobiological, and genetic parameters.http://www.who.int/ictrp; ID: DRKS00005194

  1. Virtual Reality As a Training Tool to Treat Physical Inactivity in Children

    Science.gov (United States)

    Kiefer, Adam W.; Pincus, David; Richardson, Michael J.; Myer, Gregory D.

    2017-01-01

    Lack of adequate physical activity in children is an epidemic that can result in obesity and other poor health outcomes across the lifespan. Physical activity interventions focused on motor skill competence continue to be developed, but some interventions, such as neuromuscular training (NMT), may be limited in how early they can be implemented due to dependence on the child’s level of cognitive and perceptual-motor development. Early implementation of motor-rich activities that support motor skill development in children is critical for the development of healthy levels of physical activity that carry through into adulthood. Virtual reality (VR) training may be beneficial in this regard. VR training, when grounded in an information-based theory of perceptual-motor behavior that modifies the visual information in the virtual world, can promote early development of motor skills in youth akin to more natural, real-world development as opposed to strictly formalized training. This approach can be tailored to the individual child and training scenarios can increase in complexity as the child develops. Ultimately, training in VR may help serve as a precursor to “real-world” NMT, and once the child reaches the appropriate training age can also augment more complex NMT regimens performed outside of the virtual environment. PMID:29376045

  2. Virtual Reality As a Training Tool to Treat Physical Inactivity in Children

    Directory of Open Access Journals (Sweden)

    Adam W. Kiefer

    2017-12-01

    Full Text Available Lack of adequate physical activity in children is an epidemic that can result in obesity and other poor health outcomes across the lifespan. Physical activity interventions focused on motor skill competence continue to be developed, but some interventions, such as neuromuscular training (NMT, may be limited in how early they can be implemented due to dependence on the child’s level of cognitive and perceptual-motor development. Early implementation of motor-rich activities that support motor skill development in children is critical for the development of healthy levels of physical activity that carry through into adulthood. Virtual reality (VR training may be beneficial in this regard. VR training, when grounded in an information-based theory of perceptual-motor behavior that modifies the visual information in the virtual world, can promote early development of motor skills in youth akin to more natural, real-world development as opposed to strictly formalized training. This approach can be tailored to the individual child and training scenarios can increase in complexity as the child develops. Ultimately, training in VR may help serve as a precursor to “real-world” NMT, and once the child reaches the appropriate training age can also augment more complex NMT regimens performed outside of the virtual environment.

  3. Benefits for wind energy in electricity markets from using short term wind power prediction tools: a simulation study

    International Nuclear Information System (INIS)

    Usaola, J.; Ravelo, O.; Gonzalez, G.; Soto, F.; Davila, M.C.; Diaz-Guerra, B.

    2004-01-01

    One of the characteristics of wind energy, from the grid point of view, is its non-dispatchability, i.e. generation cannot be ordered, hence integration in electrical networks may be difficult. Short-term wind power prediction-tools could make this integration easier, either by their use by the grid System Operator, or by promoting the participation of wind farms in the electricity markets and using prediction tools to make their bids in the market. In this paper, the importance of a short-term wind power-prediction tool for the participation of wind energy systems in electricity markets is studied. Simulations, according to the current Spanish market rules, have been performed to the production of different wind farms, with different degrees of accuracy in the prediction tool. It may be concluded that income from participation in electricity markets is increased using a short-term wind power prediction-tool of average accuracy. This both marginally increases income and also reduces the impact on system operation with the improved forecasts. (author)

  4. The use of the "Objective Structured Assessment of Technical Skills" as an Assessment Tool Among Danish Vascular Surgeons in Training

    DEFF Research Database (Denmark)

    Lladó Grove, Gabriela; Langager Høgh, Annette; Nielsen, Judith

    2015-01-01

    OBJECTIVE: The concept of the Objective Structured Assessment of Technical Skills (OSATS) is to quantify surgical skills in an objective way and, thereby, produce an additional procedure-specific assessment tool. Since 2005, a 2-day practical course for upcoming specialist registrars in vascular...... surgery has been obligatory. The aim of this study is to describe the results from a tailored OSATS test as a tool for the evaluation of practical skills during an intensive training session in a simple simulator box for vascular anastomoses. METHOD: Between 2005 and 2013, we registered the OSATS scores......, or the experience with vascular anastomoses and outcomes. CONCLUSION: OSATS is a valuable tool for evaluating the advancement of technical skills during an intensive practical course in performing vascular anastomoses. (C) 2015 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights...

  5. Data Normalization to Accelerate Training for Linear Neural Net to Predict Tropical Cyclone Tracks

    Directory of Open Access Journals (Sweden)

    Jian Jin

    2015-01-01

    Full Text Available When pure linear neural network (PLNN is used to predict tropical cyclone tracks (TCTs in South China Sea, whether the data is normalized or not greatly affects the training process. In this paper, min.-max. method and normal distribution method, instead of standard normal distribution, are applied to TCT data before modeling. We propose the experimental schemes in which, with min.-max. method, the min.-max. value pair of each variable is mapped to (−1, 1 and (0, 1; with normal distribution method, each variable’s mean and standard deviation pair is set to (0, 1 and (100, 1. We present the following results: (1 data scaled to the similar intervals have similar effects, no matter the use of min.-max. or normal distribution method; (2 mapping data to around 0 gains much faster training speed than mapping them to the intervals far away from 0 or using unnormalized raw data, although all of them can approach the same lower level after certain steps from their training error curves. This could be useful to decide data normalization method when PLNN is used individually.

  6. Can we predict final outcome of internal medicine residents with in-training evaluation.

    Science.gov (United States)

    Chierakul, Nitipatana; Pongprasobchai, Supot; Boonyapisit, Kanokwan; Chinthammitr, Yingyong; Pithukpakorn, Manop; Maneesai, Adisak; Srivijitkamol, Apiradee; Koomanachai, Pornpan; Koolvisoot, Ajchara; Tanwandee, Tawesak; Shayakul, Chairat; Kachintorn, Udom

    2011-02-01

    To assess the predictive value of in-training evaluation for determining future success in the internal medicine board certifying examination. Ninety-seven internal medicine residents from Faculty of Medicine Siriraj Hospital who undertake the Thai Board examination during the academic year 2006-2008 were enrolled. Correlation between the scores during internal medicine rotation and final scores in board examination were then examined. Significant positive linear correlation was found between scores from both written and clinical parts of board certifying examination and scores from the first-year summative written and clinical examinations and also the second-year formative written examination (r = 0.43-0.68, p evaluation by attending staffs was less well correlated (r = 0.29-0.36) and the evaluation by nurses or medical students demonstrated inverse relationship (r = -0.2, p = 0.27 and r = -0.13, p = 0.48). Some methods of in-training evaluation can predict successful outcome of board certifying examination. Multisource assessments cannot well extrapolate some aspects of professional competences and qualities.

  7. Validity of a simple Internet-based outcome-prediction tool in patients with total hip replacement: a pilot study.

    Science.gov (United States)

    Stöckli, Cornel; Theiler, Robert; Sidelnikov, Eduard; Balsiger, Maria; Ferrari, Stephen M; Buchzig, Beatus; Uehlinger, Kurt; Riniker, Christoph; Bischoff-Ferrari, Heike A

    2014-04-01

    We developed a user-friendly Internet-based tool for patients undergoing total hip replacement (THR) due to osteoarthritis to predict their pain and function after surgery. In the first step, the key questions were identified by statistical modelling in a data set of 375 patients undergoing THR. Based on multiple regression, we identified the two most predictive WOMAC questions for pain and the three most predictive WOMAC questions for functional outcome, while controlling for comorbidity, body mass index, age, gender and specific comorbidities relevant to the outcome. In the second step, a pilot study was performed to validate the resulting tool against the full WOMAC questionnaire among 108 patients undergoing THR. The mean difference between observed (WOMAC) and model-predicted value was -1.1 points (95% confidence interval, CI -3.8, 1.5) for pain and -2.5 points (95% CI -5.3, 0.3) for function. The model-predicted value was within 20% of the observed value in 48% of cases for pain and in 57% of cases for function. The tool demonstrated moderate validity, but performed weakly for patients with extreme levels of pain and extreme functional limitations at 3 months post surgery. This may have been partly due to early complications after surgery. However, the outcome-prediction tool may be useful in helping patients to become better informed about the realistic outcome of their THR.

  8. Preliminary Evaluation of a Novel Simulation-Based Tool for Training Rapid Decision-Making Skills

    National Research Council Canada - National Science Library

    Christ, Richard E

    2006-01-01

    ...). SimFX is different from other desktop trainers in that it uses a discrete, outcome-driven simulation for training leader decision making rather than a simulation driven by inputs from the virtual operating environment...

  9. Human factors phase IV : risk analysis tool for new train control technology

    Science.gov (United States)

    2005-01-01

    This report covers the theoretical development of the safety state model for railroad operations. Using data from a train control technology experiment, experimental application of the model is demonstrated. A stochastic model of system behavior is d...

  10. Leningrad NPP full scope simulator - new generation tool for training and analysis

    International Nuclear Information System (INIS)

    Malkin, S.D.; Shalia, V.V.; Rakitin, I.D.; Khoudiakov, M.M.

    1999-01-01

    Recent developments of Russian Research Center 'Kurchatov Institute' are aimed at the soonest and minimum expenditure's creation of modern high-performance means for personnel's training and regular restraining and also at the development of means of modeling, safety analysis and operators' support with severe accidents to be included. In this view, the most elaborated one is the Training Support Center (TSC) created at the Leningrad NPP, Sosnovy Bor, Russia. To be applied in this center, GSE Systems of USA and RRC 'Kurchatov Institute' have jointly developed the Total Training System that incorporates full-scope simulator; analytical full-scope simulator, expert system, interactive system, psycho-physiological system; and training support programs. Mathematical models creating and special software development were the responsibility of RRC 'Kurchatov Institute', the hardware and general purpose software were the responsibility of GSE Systems. (author)

  11. The Commanders' Integrated Training Tool for the Close Combat Tactical Trainer 3: Final Prototype Development

    National Research Council Canada - National Science Library

    Flynn, Michael

    2001-01-01

    ...) for the Close Combat Tactical Trainer (CCTT), a system of armored vehicle manned-module simulators and workstations that allows units to train collective armor and infantry tasks at the platoon through battalion task force level...

  12. ONLINE PLATFORM AND TRAINING METHODOLOGY IN MOBIVET 2.0: THE OPTIMUM TOOL FOR SELF-DIRECTED LEARNERS AND TRAINERS IN VOCATIONAL EDUCATION AND TRAINING

    Directory of Open Access Journals (Sweden)

    Sorin IONITESCU

    2014-10-01

    Full Text Available The paper presents a summary of the activities and the results with an impact in vocational education and training from the implementation of the MOBIVET 2.0 project. The project envisaged that the future of teaching would rapidly vacate the classroom and become heavily involved in distance-learning using Multimedia/Internet. The revolution from the classroom lecturer’s “talk and chalk” to independent Mobile E-Learning requires a completely new and different didactical approach. Education process gets more focused on the availability and mobility needs of the students and more adapted to the changes in technology, as mobile devices become more versatile, software changes every few months and the wireless transfer rates increase. This process requires new teaching methodologies, training of trainers to keep them updated and validation of the best practices in the educational field. An online Learning Management System was implemented, a wide range of devices were used, ranging from desktop computers, to laptops, tablets and smartphones (with different Operating Systems, browsers and screen sizes and resolutions to develop and test a number of seven courses in different study areas. Teachers and students from vocational education and training (VET were assisted in the process and this lead to the development of a “VET Teachers manual in using Mobile Web 2.0 tools and applications in online training and tutoring”, an “online training and tutoring methodology” and a “self-evaluation methodology”, with step-by-step guidance for users. The technical testing and the piloting activities in the project revealed that by using mobile technologies in teaching, the availability of information increases and thus educational activities better serve their purpose for the students. Also, the use of laptops, smartphones and tablets was preferred by the participants over the desktop computers in a ratio of 3:1, thus emphasizing the need for

  13. The predictive validity of selection for entry into postgraduate training in general practice: evidence from three longitudinal studies.

    Science.gov (United States)

    Patterson, Fiona; Lievens, Filip; Kerrin, Máire; Munro, Neil; Irish, Bill

    2013-11-01

    The selection methodology for UK general practice is designed to accommodate several thousand applicants per year and targets six core attributes identified in a multi-method job-analysis study To evaluate the predictive validity of selection methods for entry into postgraduate training, comprising a clinical problem-solving test, a situational judgement test, and a selection centre. A three-part longitudinal predictive validity study of selection into training for UK general practice. In sample 1, participants were junior doctors applying for training in general practice (n = 6824). In sample 2, participants were GP registrars 1 year into training (n = 196). In sample 3, participants were GP registrars sitting the licensing examination after 3 years, at the end of training (n = 2292). The outcome measures include: assessor ratings of performance in a selection centre comprising job simulation exercises (sample 1); supervisor ratings of trainee job performance 1 year into training (sample 2); and licensing examination results, including an applied knowledge examination and a 12-station clinical skills objective structured clinical examination (OSCE; sample 3). Performance ratings at selection predicted subsequent supervisor ratings of job performance 1 year later. Selection results also significantly predicted performance on both the clinical skills OSCE and applied knowledge examination for licensing at the end of training. In combination, these longitudinal findings provide good evidence of the predictive validity of the selection methods, and are the first reported for entry into postgraduate training. Results show that the best predictor of work performance and training outcomes is a combination of a clinical problem-solving test, a situational judgement test, and a selection centre. Implications for selection methods for all postgraduate specialties are considered.

  14. The future of patient safety: Surgical trainees accept virtual reality as a new training tool

    Directory of Open Access Journals (Sweden)

    Vogelbach Peter

    2008-06-01

    Full Text Available Abstract Background The use of virtual reality (VR has gained increasing interest to acquire laparoscopic skills outside the operating theatre and thus increasing patients' safety. The aim of this study was to evaluate trainees' acceptance of VR for assessment and training during a skills course and at their institution. Methods All 735 surgical trainees of the International Gastrointestinal Surgery Workshop 2006–2008, held in Davos, Switzerland, were given a minimum of 45 minutes for VR training during the course. Participants' opinion on VR was analyzed with a standardized questionnaire. Results Fivehundred-twenty-seven participants (72% from 28 countries attended the VR sessions and answered the questionnaires. The possibility of using VR at the course was estimated as excellent or good in 68%, useful in 21%, reasonable in 9% and unsuitable or useless in 2%. If such VR simulators were available at their institution, most course participants would train at least one hour per week (46%, two or more hours (42% and only 12% wouldn't use VR. Similarly, 63% of the participants would accept to operate on patients only after VR training and 55% to have VR as part of their assessment. Conclusion Residents accept and appreciate VR simulation for surgical assessment and training. The majority of the trainees are motivated to regularly spend time for VR training if accessible.

  15. Effectiveness of Cooperative Learning Instructional Tools With Predict-Observe-Explain Strategy on the Topic of Cuboid and Cube Volume

    Science.gov (United States)

    Nurhuda; Lukito, A.; Masriyah

    2018-01-01

    This study aims to develop instructional tools and implement it to see the effectiveness. The method used in this research referred to Designing Effective Instruction. Experimental research with two-group pretest-posttest design method was conducted. The instructional tools have been developed is cooperative learning model with predict-observe-explain strategy on the topic of cuboid and cube volume which consist of lesson plans, POE tasks, and Tests. Instructional tools were of good quality by criteria of validity, practicality, and effectiveness. These instructional tools was very effective for teaching the volume of cuboid and cube. Cooperative instructional tool with predict-observe-explain (POE) strategy was good of quality because the teacher was easy to implement the steps of learning, students easy to understand the material and students’ learning outcomes completed classically. Learning by using this instructional tool was effective because learning activities were appropriate and students were very active. Students’ learning outcomes were completed classically and better than conventional learning. This study produced a good instructional tool and effectively used in learning. Therefore, these instructional tools can be used as an alternative to teach volume of cuboid and cube topics.

  16. "Score the Core" Web-based pathologist training tool improves the accuracy of breast cancer IHC4 scoring.

    Science.gov (United States)

    Engelberg, Jesse A; Retallack, Hanna; Balassanian, Ronald; Dowsett, Mitchell; Zabaglo, Lila; Ram, Arishneel A; Apple, Sophia K; Bishop, John W; Borowsky, Alexander D; Carpenter, Philip M; Chen, Yunn-Yi; Datnow, Brian; Elson, Sarah; Hasteh, Farnaz; Lin, Fritz; Moatamed, Neda A; Zhang, Yanhong; Cardiff, Robert D

    2015-11-01

    Hormone receptor status is an integral component of decision-making in breast cancer management. IHC4 score is an algorithm that combines hormone receptor, HER2, and Ki-67 status to provide a semiquantitative prognostic score for breast cancer. High accuracy and low interobserver variance are important to ensure the score is accurately calculated; however, few previous efforts have been made to measure or decrease interobserver variance. We developed a Web-based training tool, called "Score the Core" (STC) using tissue microarrays to train pathologists to visually score estrogen receptor (using the 300-point H score), progesterone receptor (percent positive), and Ki-67 (percent positive). STC used a reference score calculated from a reproducible manual counting method. Pathologists in the Athena Breast Health Network and pathology residents at associated institutions completed the exercise. By using STC, pathologists improved their estrogen receptor H score and progesterone receptor and Ki-67 proportion assessment and demonstrated a good correlation between pathologist and reference scores. In addition, we collected information about pathologist performance that allowed us to compare individual pathologists and measures of agreement. Pathologists' assessment of the proportion of positive cells was closer to the reference than their assessment of the relative intensity of positive cells. Careful training and assessment should be used to ensure the accuracy of breast biomarkers. This is particularly important as breast cancer diagnostics become increasingly quantitative and reproducible. Our training tool is a novel approach for pathologist training that can serve as an important component of ongoing quality assessment and can improve the accuracy of breast cancer prognostic biomarkers. Copyright © 2015 Elsevier Inc. All rights reserved.

  17. A Simple Evaluation Tool (ET-CET) Indicates Increase of Diagnostic Skills From Small Bowel Capsule Endoscopy Training Courses

    Science.gov (United States)

    Albert, J.G.; Humbla, O.; McAlindon, M.E.; Davison, C.; Seitz, U.; Fraser, C.; Hagenmüller, F.; Noetzel, E.; Spada, C.; Riccioni, M.E.; Barnert, J.; Filmann, N.; Keuchel, M.

    2015-01-01

    Abstract Small bowel capsule endoscopy (SBCE) has become a first line diagnostic tool. Several training courses with a similar format have been established in Europe; however, data on learning curve and training in SBCE remain sparse. Between 2008 and 2011, different basic SBCE training courses were organized internationally in UK (n = 2), Italy (n = 2), Germany (n = 2), Finland (n = 1), and nationally in Germany (n = 10), applying similar 8-hour curricula with 50% lectures and 50% hands-on training. The Given PillCam System was used in 12 courses, the Olympus EndoCapsule system in 5, respectively. A simple evaluation tool for capsule endoscopy training (ET-CET) was developed using 10 short SBCE videos including relevant lesions and normal or irrelevant findings. For each video, delegates were required to record a diagnosis (achievable total score from 0 to 10) and the clinical relevance (achievable total score 0 to 10). ET-CET was performed at baseline before the course and repeated, with videos in altered order, after the course. Two hundred ninety-four delegates (79.3% physicians, 16.3% nurses, 4.4% others) were included for baseline analysis, 268 completed the final evaluation. Forty percent had no previous experience in SBCE, 33% had performed 10 or less procedures. Median scores for correct diagnosis improved from 4.0 (IQR 3) to 7.0 (IQR 3) during the courses (P endoscopy may be useful before attending an SBCE course. PMID:26512623

  18. Tool Sequence Trends in Minimally Invasive Surgery: Statistical Analysis and Implications for Predictive Control of Multifunction Instruments

    Directory of Open Access Journals (Sweden)

    Carl A. Nelson

    2012-01-01

    Full Text Available This paper presents an analysis of 67 minimally invasive surgical procedures covering 11 different procedure types to determine patterns of tool use. A new graph-theoretic approach was taken to organize and analyze the data. Through grouping surgeries by type, trends of common tool changes were identified. Using the concept of signal/noise ratio, these trends were found to be statistically strong. The tool-use trends were used to generate tool placement patterns for modular (multi-tool, cartridge-type surgical tool systems, and the same 67 surgeries were numerically simulated to determine the optimality of these tool arrangements. The results indicate that aggregated tool-use data (by procedure type can be employed to predict tool-use sequences with good accuracy, and also indicate the potential for artificial intelligence as a means of preoperative and/or intraoperative planning. Furthermore, this suggests that the use of multifunction surgical tools can be optimized to streamline surgical workflow.

  19. Analysis of the uranium price predicted to 24 months, implementing neural networks and the Monte Carlo method like predictive tools

    International Nuclear Information System (INIS)

    Esquivel E, J.; Ramirez S, J. R.; Palacios H, J. C.

    2011-11-01

    The present work shows predicted prices of the uranium, using a neural network. The importance of predicting financial indexes of an energy resource, in this case, allows establishing budgetary measures, as well as the costs of the resource to medium period. The uranium is part of the main energy generating fuels and as such, its price rebounds in the financial analyses, due to this is appealed to predictive methods to obtain an outline referent to the financial behaviour that will have in a certain time. In this study, two methodologies are used for the prediction of the uranium price: the Monte Carlo method and the neural networks. These methods allow predicting the indexes of monthly costs, for a two years period, starting from the second bimonthly of 2011. For the prediction the uranium costs are used, registered from the year 2005. (Author)

  20. Augmenting Predictive Modeling Tools with Clinical Insights for Care Coordination Program Design and Implementation.

    Science.gov (United States)

    Johnson, Tracy L; Brewer, Daniel; Estacio, Raymond; Vlasimsky, Tara; Durfee, Michael J; Thompson, Kathy R; Everhart, Rachel M; Rinehart, Deborath J; Batal, Holly

    2015-01-01

    The Center for Medicare and Medicaid Innovation (CMMI) awarded Denver Health's (DH) integrated, safety net health care system $19.8 million to implement a "population health" approach into the delivery of primary care. This major practice transformation builds on the Patient Centered Medical Home (PCMH) and Wagner's Chronic Care Model (CCM) to achieve the "Triple Aim": improved health for populations, care to individuals, and lower per capita costs. This paper presents a case study of how DH integrated published predictive models and front-line clinical judgment to implement a clinically actionable, risk stratification of patients. This population segmentation approach was used to deploy enhanced care team staff resources and to tailor care-management services to patient need, especially for patients at high risk of avoidable hospitalization. Developing, implementing, and gaining clinical acceptance of the Health Information Technology (HIT) solution for patient risk stratification was a major grant objective. In addition to describing the Information Technology (IT) solution itself, we focus on the leadership and organizational processes that facilitated its multidisciplinary development and ongoing iterative refinement, including the following: team composition, target population definition, algorithm rule development, performance assessment, and clinical-workflow optimization. We provide examples of how dynamic business intelligence tools facilitated clinical accessibility for program design decisions by enabling real-time data views from a population perspective down to patient-specific variables. We conclude that population segmentation approaches that integrate clinical perspectives with predictive modeling results can better identify high opportunity patients amenable to medical home-based, enhanced care team interventions.

  1. Thermogravimetric analysis coupled with chemometrics as a powerful predictive tool for ß-thalassemia screening.

    Science.gov (United States)

    Risoluti, Roberta; Materazzi, Stefano; Sorrentino, Francesco; Maffei, Laura; Caprari, Patrizia

    2016-10-01

    β-Thalassemia is a hemoglobin genetic disorder characterized by the absence or reduced β-globin chain synthesis, one of the constituents of the adult hemoglobin tetramer. In this study the possibility of using thermogravimetric analysis (TGA) followed by chemometrics as a new approach for β-thalassemia detection is proposed. Blood samples from patients with β-thalassemia were analyzed by the TG7 thermobalance and the resulting curves were compared to those typical of healthy individuals. Principal Component Analysis (PCA) was used to evaluate the correlation between the hematological parameters and the thermogravimetric results. The thermogravimetric profiles of blood samples from β-thalassemia patients were clearly distinct from those of healthy individuals as result of the different quantities of water content and corpuscular fraction. The hematological overview showed significant decreases in the values of red blood cell indices and an increase in red cell distribution width value in thalassemia subjects when compared with those of healthy subjects. The implementation of a predictive model based on Partial Least Square Discriminant Analysis (PLS-DA) for β-thalassemia diagnosis, was performed and validated. This model permitted the discrimination of anemic patients and healthy individuals and was able to detect thalassemia in clinically heterogeneous patients as in the presence of δβ-thalassemia and β-thalassemia combined with Hb Lepore. TGA and Chemometrics are capable of predicting ß-thalassemia syndromes using only a few microliters of blood without any pretreatment and with an hour of analysis time. A fast, rapid and cost-effective diagnostic tool for the β-thalassemia screening is proposed. Copyright © 2016 Elsevier B.V. All rights reserved.

  2. Creating pharmacy staffing-to-demand models: predictive tools used at two institutions.

    Science.gov (United States)

    Krogh, Paul; Ernster, Jason; Knoer, Scott

    2012-09-15

    The creation and implementation of data-driven staffing-to-demand models at two institutions are described. Predictive workload tools provide a guideline for pharmacy managers to adjust staffing needs based on hospital volume metrics. At Abbott Northwestern Hospital, management worked with the department's staff and labor management committee to clearly outline the productivity monitoring system and the process for reducing hours. Reference charts describing the process for reducing hours and a form to track the hours of involuntary reductions for each employee were created to further enhance communication, explain the rationale behind the new process, and promote transparency. The University of Minnesota Medical Center-Fairview, found a strong correlation between measured pharmacy workload and an adjusted census formula. If the daily census and admission report indicate that the adjusted census will provide enough workload for the fully staffed department, no further action is needed. If the census report indicates the adjusted census is less than the breakeven point, staff members are asked to leave work, either voluntarily or involuntarily. The opposite holds true for days when the adjusted census is higher than the breakeven point, at which time additional staff are required to synchronize worked hours with predicted workload. Successful staffing-to- demand models were implemented in two hospital pharmacies. Financial savings, as indicated by decreased labor costs secondary to reduction of staffed shifts, were approximately $42,000 and $45,500 over a three-month period for Abbott Northwestern Hospital and the University of Minnesota Medical Center-Fairview, respectively. Maintenance of 100% productively allowed the departments to continue to replace vacant positions and avoid permanent staff reductions.

  3. Reverse alignment "mirror image" visualization as a laparoscopic training tool improves task performance.

    Science.gov (United States)

    Dunnican, Ward J; Singh, T Paul; Ata, Ashar; Bendana, Emma E; Conlee, Thomas D; Dolce, Charles J; Ramakrishnan, Rakesh

    2010-06-01

    Reverse alignment (mirror image) visualization is a disconcerting situation occasionally faced during laparoscopic operations. This occurs when the camera faces back at the surgeon in the opposite direction from which the surgeon's body and instruments are facing. Most surgeons will attempt to optimize trocar and camera placement to avoid this situation. The authors' objective was to determine whether the intentional use of reverse alignment visualization during laparoscopic training would improve performance. A standard box trainer was configured for reverse alignment, and 34 medical students and junior surgical residents were randomized to train with either forward alignment (DIRECT) or reverse alignment (MIRROR) visualization. Enrollees were tested on both modalities before and after a 4-week structured training program specific to their modality. Student's t test was used to determine differences in task performance between the 2 groups. Twenty-one participants completed the study (10 DIRECT, 11 MIRROR). There were no significant differences in performance time between DIRECT or MIRROR participants during forward or reverse alignment initial testing. At final testing, DIRECT participants had improved times only in forward alignment performance; they demonstrated no significant improvement in reverse alignment performance. MIRROR participants had significant time improvement in both forward and reverse alignment performance at final testing. Reverse alignment imaging for laparoscopic training improves task performance for both reverse alignment and forward alignment tasks. This may be translated into improved performance in the operating room when faced with reverse alignment situations. Minimal lab training can account for drastic adaptation to this environment.

  4. Semi-structured interview is a reliable and feasible tool for selection of doctors for general practice specialist training.

    Science.gov (United States)

    Isaksen, Jesper Hesselbjerg; Hertel, Niels Thomas; Kjær, Niels Kristian

    2013-09-01

    In order to optimise the selection process for admission to specialist training in family medicine, we developed a new design for structured applications and selection interviews. The design contains semi-structured interviews, which combine individualised elements from the applications with standardised behaviour-based questions. This paper describes the design of the tool, and offers reflections concerning its acceptability, reliability and feasibility. We used a combined quantitative and qualitative evaluation method. Ratings obtained by the applicants in two selection rounds were analysed for reliability and generalisability using the GENOVA programme. Applicants and assessors were randomly selected for individual semi-structured in-depth interviews. The qualitative data were analysed in accordance with the grounded theory method. Quantitative analysis yielded a high Cronbach's alpha of 0.97 for the first round and 0.90 for the second round, and a G coefficient of the first round of 0.74 and of the second round of 0.40. Qualitative analysis demonstrated high acceptability and fairness and it improved the assessors' judgment. Applicants reported concerns about loss of personality and some anxiety. The applicants' ability to reflect on their competences was important. The developed selection tool demonstrated an acceptable level of reliability, but only moderate generalisability. The users found that the tool provided a high degree of acceptability; it is a feasible and useful tool for -selection of doctors for specialist training if combined with work-based assessment. Studies on the benefits and drawbacks of this tool compared with other selection models are relevant. not relevant. not relevant.

  5. piRNA analysis framework from small RNA-Seq data by a novel cluster prediction tool - PILFER.

    Science.gov (United States)

    Ray, Rishav; Pandey, Priyanka

    2017-12-19

    With the increasing number of studies focusing on PIWI-interacting RNA (piRNAs), it is now pertinent to develop efficient tools dedicated towards piRNA analysis. We have developed a novel cluster prediction tool called PILFER (PIrna cLuster FindER), which can accurately predict piRNA clusters from small RNA sequencing data. PILFER is an open source, easy to use tool, and can be executed even on a personal computer with minimum resources. It uses a sliding-window mechanism by integrating the expression of the reads along with the spatial information to predict the piRNA clusters. We have additionally defined a piRNA analysis pipeline incorporating PILFER to detect and annotate piRNAs and their clusters from raw small RNA sequencing data and implemented it on publicly available data from healthy germline and somatic tissues. We compared PILFER with other existing piRNA cluster prediction tools and found it to be statistically more accurate and superior in many aspects such as the robustness of PILFER clusters is higher and memory efficiency is more. Overall, PILFER provides a fast and accurate solution to piRNA cluster prediction. Copyright © 2017 Elsevier Inc. All rights reserved.

  6. Predictive value of the korean academy of family medicine in-training examination for certifying examination.

    Science.gov (United States)

    Cho, Jung-Jin; Kim, Ji-Yong

    2011-09-01

    In-training examination (ITE) is a cognitive examination similar to the written test, but it is different from the Clinical Practice Examination of the Korean Academy of Family Medicine (KAFM) Certification Examination (CE). The objective of this is to estimate the positive predictive value of the KAFM-ITE for identifying residents at risk for poor performance on the three types of KAFM-CE. 372 residents who completed the KAFM-CE in 2011 were included. We compared the mean KAFM-CE scores with ITE experience. We evaluated the correlation and the positive predictive value (PPV) of ITE for the multiple choice question (MCQ) scores of 1st written test & 2nd slide examination, the total clinical practice examination scores, and the total sum of 2nd test. 275 out of 372 residents completed ITE. Those who completed ITE had significantly higher MCQ scores of 1st written test than those who did not. The correlation of ITE scores with 1st written MCQ (0.627) was found to be the highest among the other kinds of CE. The PPV of the ITE score for 1st written MCQ scores was 0.672. The PPV of the ITE score ranged from 0.376 to 0.502. The score of the KAFM ITE has acceptable positive predictive value that could be used as a part of comprehensive evaluation system for residents in cognitive field.

  7. Virtual reality and interactive 3D as effective tools for medical training.

    Science.gov (United States)

    Webb, George; Norcliffe, Alex; Cannings, Peter; Sharkey, Paul; Roberts, Dave

    2003-01-01

    CAVE-like displays allow a user to walk in to a virtual environment, and use natural movement to change the viewpoint of virtual objects which they can manipulate with a hand held device. This maps well to many surgical procedures offering strong potential for training and planning. These devices may be networked together allowing geographically remote users to share the interactive experience. This maps to the strong need for distance training and planning of surgeons. Our paper shows how the properties of a CAVE-Like facility can be maximised in order to provide an ideal environment for medical training. The implementation of a large 3D-eye is described. The resulting application is that of an eye that can be manipulated and examined by trainee medics under the guidance of a medical expert. The progression and effects of different ailments can be illustrated and corrective procedures, demonstrated.

  8. Moduli dynamics as a predictive tool for thermal maximally supersymmetric Yang-Mills at large N

    Energy Technology Data Exchange (ETDEWEB)

    Morita, Takeshi [Department of Physics, Shizuoka University,836 Ohya, Suruga-ku, Shizuoka 422-8529 (Japan); Department of Physics and Astronomy, University of Kentucky,Lexington, KY 40506 (United States); Shiba, Shotaro [Maskawa Institute for Science and Culture, Kyoto Sangyo University,Kamigamo-Motoyama, Kita-ku, Kyoto 603-8555 (Japan); Wiseman, Toby [Theoretical Physics Group, Blackett Laboratory, Imperial College,Exhibition Road, London SW7 2AZ (United Kingdom); Withers, Benjamin [Mathematical Sciences and STAG Research Centre, University of Southampton,Highfield, Southampton SO17 1BJ (United Kingdom)

    2015-07-09

    Maximally supersymmetric (p+1)-dimensional Yang-Mills theory at large N and finite temperature, with possibly compact spatial directions, has a rich phase structure. Strongly coupled phases may have holographic descriptions as black branes in various string duality frames, or there may be no gravity dual. In this paper we provide tools in the gauge theory which give a simple and unified picture of the various strongly coupled phases, and transitions between them. Building on our previous work we consider the effective theory describing the moduli of the gauge theory, which can be computed precisely when it is weakly coupled far out on the Coulomb branch. Whilst for perturbation theory naive extrapolation from weak coupling to strong gives little information, for this moduli theory naive extrapolation from its weakly to its strongly coupled regime appears to encode a surprising amount of information about the various strongly coupled phases. We argue it encodes not only the parametric form of thermodynamic quantities for these strongly coupled phases, but also certain transcendental factors with a geometric origin, and allows one to deduce transitions between the phases. We emphasise it also gives predictions for the behaviour of other observables in these phases.

  9. New tools and new ideas for HR practitioners. Structural and predictive validity of weighted satisfaction questionnaire

    Directory of Open Access Journals (Sweden)

    Lorenzo Revuelto Taboada

    2012-12-01

    Full Text Available One of the fundamental tasks for an Human Resource Management (HRM practitioner consists in designing a reward system that can be broadly understood and can influence the attitudes and, subsequently, the behavior of individuals to permit achievement of organizational objectives. To do so, appropriate tools are necessary to allow key actions to be identified in terms of motivating employees; thereby, avoiding opportunistic costs derived from allocating resources needed to close the gap in employee satisfaction, with regard to non-priority factors for workers in satisfying their own personal needs. This article, thus, presents a dual assessment scale consisting of 44 items, categorized into six dimensions, which firstly evaluates the importance of motivation and, secondly, the level of satisfaction with the current situation for each of the 44 factors considered. Using a sample of 801 individuals, we analyzedthe internal consistency, face validity, and predictive validity of the measuring scales, obtaining a series of results that were, to say the least, promising

  10. JASSA: a comprehensive tool for prediction of SUMOylation sites and SIMs.

    Science.gov (United States)

    Beauclair, Guillaume; Bridier-Nahmias, Antoine; Zagury, Jean-François; Saïb, Ali; Zamborlini, Alessia

    2015-11-01

    Post-translational modification by the Small Ubiquitin-like Modifier (SUMO) proteins, a process termed SUMOylation, is involved in many fundamental cellular processes. SUMO proteins are conjugated to a protein substrate, creating an interface for the recruitment of cofactors harboring SUMO-interacting motifs (SIMs). Mapping both SUMO-conjugation sites and SIMs is required to study the functional consequence of SUMOylation. To define the best candidate sites for experimental validation we designed JASSA, a Joint Analyzer of SUMOylation site and SIMs. JASSA is a predictor that uses a scoring system based on a Position Frequency Matrix derived from the alignment of experimental SUMOylation sites or SIMs. Compared with existing web-tools, JASSA displays on par or better performances. Novel features were implemented towards a better evaluation of the prediction, including identification of database hits matching the query sequence and representation of candidate sites within the secondary structural elements and/or the 3D fold of the protein of interest, retrievable from deposited PDB files. JASSA is freely accessible at http://www.jassa.fr/. Website is implemented in PHP and MySQL, with all major browsers supported. guillaume.beauclair@inserm.fr Supplementary data are available at Bioinformatics online. © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

  11. An Approach to Flooding Inundation Combining the Streamflow Prediction Tool (SPT) and Downscaled Soil Moisture

    Science.gov (United States)

    Cotterman, K. A.; Follum, M. L.; Pradhan, N. R.; Niemann, J. D.

    2017-12-01

    Flooding impacts numerous aspects of society, from localized flash floods to continental-scale flood events. Many numerical flood models focus solely on riverine flooding, with some capable of capturing both localized and continental-scale flood events. However, these models neglect flooding away from channels that are related to excessive ponding, typically found in areas with flat terrain and poorly draining soils. In order to obtain a holistic view of flooding, we combine flood results from the Streamflow Prediction Tool (SPT), a riverine flood model, with soil moisture downscaling techniques to determine if a better representation of flooding is obtained. This allows for a more holistic understanding of potential flood prone areas, increasing the opportunity for more accurate warnings and evacuations during flooding conditions. Thirty-five years of near-global historical streamflow is reconstructed with continental-scale flow routing of runoff from global land surface models. Elevation data was also obtained worldwide, to establish a relationship between topographic attributes and soil moisture patterns. Derived soil moisture data is validated against observed soil moisture, increasing confidence in the ability to accurately capture soil moisture patterns. Potential flooding situations can be examined worldwide, with this study focusing on the United States, Central America, and the Philippines.

  12. Predictive validity of the post-enrolment English language assessment tool for commencing undergraduate nursing students.

    Science.gov (United States)

    Glew, Paul J; Hillege, Sharon P; Salamonson, Yenna; Dixon, Kathleen; Good, Anthony; Lombardo, Lien

    2015-12-01

    Nursing students with English as an additional language (EAL) may underperform academically. The post-enrolment English language assessment (PELA) is used in literacy support, but its predictive validity in identifying those at risk of underperformance remains unknown. To validate a PELA, as a predictor of academic performance. Prospective survey design. The study was conducted at a university located in culturally and linguistically diverse areas of western Sydney, Australia. Commencing undergraduate nursing students who were Australian-born (n=1323, 49.6%) and born outside of Australia (n=1346, 50.4%) were recruited for this study. The 2669 (67% of 3957) participants provided consent and completed a first year nursing unit that focussed on developing literacy skills. Between 2010 and 2013, commencing students completed the PELA and English language acculturation scale (ELAS), a previously validated instrument. The grading levels of the PELA tool were: Level 1 (proficient), Level 2 (borderline), and Level 3 (poor, and requiring additional support). Participants with a PELA Level 2 or 3 were more likely to be: a) non-Australian-born (χ(2): 520.6, df: 2, pstudent (χ(2): 225.6, df: 2, pstudents who are at risk of academic underachievement. Crown Copyright © 2015. Published by Elsevier Ltd. All rights reserved.

  13. A low-dimensional tool for predicting force decomposition coefficients for varying inflow conditions

    KAUST Repository

    Ghommem, Mehdi

    2013-01-01

    We develop a low-dimensional tool to predict the effects of unsteadiness in the inflow on force coefficients acting on a circular cylinder using proper orthogonal decomposition (POD) modes from steady flow simulations. The approach is based on combining POD and linear stochastic estimator (LSE) techniques. We use POD to derive a reduced-order model (ROM) to reconstruct the velocity field. To overcome the difficulty of developing a ROM using Poisson\\'s equation, we relate the pressure field to the velocity field through a mapping function based on LSE. The use of this approach to derive force decomposition coefficients (FDCs) under unsteady mean flow from basis functions of the steady flow is illustrated. For both steady and unsteady cases, the final outcome is a representation of the lift and drag coefficients in terms of velocity and pressure temporal coefficients. Such a representation could serve as the basis for implementing control strategies or conducting uncertainty quantification. Copyright © 2013 Inderscience Enterprises Ltd.

  14. Moduli dynamics as a predictive tool for thermal maximally supersymmetric Yang-Mills at large N

    International Nuclear Information System (INIS)

    Morita, Takeshi; Shiba, Shotaro; Wiseman, Toby; Withers, Benjamin

    2015-01-01

    Maximally supersymmetric (p+1)-dimensional Yang-Mills theory at large N and finite temperature, with possibly compact spatial directions, has a rich phase structure. Strongly coupled phases may have holographic descriptions as black branes in various string duality frames, or there may be no gravity dual. In this paper we provide tools in the gauge theory which give a simple and unified picture of the various strongly coupled phases, and transitions between them. Building on our previous work we consider the effective theory describing the moduli of the gauge theory, which can be computed precisely when it is weakly coupled far out on the Coulomb branch. Whilst for perturbation theory naive extrapolation from weak coupling to strong gives little information, for this moduli theory naive extrapolation from its weakly to its strongly coupled regime appears to encode a surprising amount of information about the various strongly coupled phases. We argue it encodes not only the parametric form of thermodynamic quantities for these strongly coupled phases, but also certain transcendental factors with a geometric origin, and allows one to deduce transitions between the phases. We emphasise it also gives predictions for the behaviour of other observables in these phases.

  15. bTSSfinder: a novel tool for the prediction of promoters in Cyanobacteria andEscherichia coli

    KAUST Repository

    Shahmuradov, Ilham; Mohamad Razali, Rozaimi; Bougouffa, Salim; Radovanovic, Aleksandar; Bajic, Vladimir B.

    2016-01-01

    Results: Here, we introduce bTSSfinder, a novel tool that predicts putative promoters for five classes of σ factors in Cyanobacteria (σA, σC, σH, σG and σF) and for five classes of sigma factors in E. coli (σ70, σ38, σ32, σ28 and σ24). Comparing to currently available tools, bTSSfinder achieves higher accuracy (MCC=0.86, F1-score=0.93) compared to the next best tool with MCC=0.59, F1-score=0.79) and covers multiple classes of promoters.

  16. Dementia Population Risk Tool (DemPoRT): study protocol for a predictive algorithm assessing dementia risk in the community

    OpenAIRE

    Fisher, Stacey; Hsu, Amy; Mojaverian, Nassim; Taljaard, Monica; Huyer, Gregory; Manuel, Douglas G; Tanuseputro, Peter

    2017-01-01

    Introduction The burden of disease from dementia is a growing global concern as incidence increases dramatically with age, and average life expectancy has been increasing around the world. Planning for an ageing population requires reliable projections of dementia prevalence; however, existing population projections are simple and have poor predictive accuracy. The Dementia Population Risk Tool (DemPoRT) will predict incidence of dementia in the population setting using multivariable modellin...

  17. A multimedia - virtual reality based- tool for training in radiological protection

    International Nuclear Information System (INIS)

    Salve, R.; Castro, A.; Javier, Castelo; Francisco, Diaz; Francisco, Massana; Antonio, A. de; Herrero, P.

    2001-01-01

    This paper presents the work that has been carried out under the frame of the project PRVIR, promoted by DTN in co-operation with the UPM and Vandellos II NPP, as the pilot plant. The aim of the project is to make use of computer-based training in nuclear plants, taking advantage of multimedia resources and advanced computer graphics. The area that has been selected for this first training program is radiological protection fundamentals, and the end users of the program will be professionally exposed workers. The software can also be used for radiological protection concepts dissemination purposes. (author)

  18. A multimedia - virtual reality based- tool for training in radiological protection

    Energy Technology Data Exchange (ETDEWEB)

    Salve, R.; Castro, A. [DTN, Madrid (Spain); Antonio, A. de; Herrero, P. [UPM Facultad de Informatica, Madrid (Spain); Diaz, F.; Massana, F [Central Nuclear Vandellos 2, Tarragona (Spain)

    2001-07-01

    This paper presents the work that has been carried out under the frame of the project PRVIR, promoted by DTN in co-operation with the UPM and Vandellos II NPP, as the pilot plant. The aim of the project is to make use of computer-based training in nuclear plants, taking advantage of multimedia resources and advanced computer graphics. The area that has been selected for this first training program is radiological protection fundamentals, and the end users of the program will be professionally exposed workers. The software can also be used for radiological protection concepts dissemination purposes. (author)

  19. The hemorrhagic transformation index score: a prediction tool in middle cerebral artery ischemic stroke.

    Science.gov (United States)

    Kalinin, Mikhail N; Khasanova, Dina R; Ibatullin, Murat M

    2017-09-07

    We aimed to develop a tool, the hemorrhagic transformation (HT) index (HTI), to predict any HT within 14 days after middle cerebral artery (MCA) stroke onset regardless of the intravenous recombinant tissue plasminogen activator (IV rtPA) use. That is especially important in the light of missing evidence-based data concerning the timing of anticoagulant resumption after stroke in patients with atrial fibrillation (AF). We retrospectively analyzed 783 consecutive MCA stroke patients. Clinical and brain imaging data at admission were recorded. A follow-up period was 2 weeks after admission. The patients were divided into derivation (DC) and validation (VC) cohorts by generating Bernoulli variates with probability parameter 0.7. Univariate/multivariate logistic regression, and factor analysis were used to extract independent predictors. Validation was performed with internal consistency reliability and receiver operating characteristic (ROC) analysis. Bootstrapping was used to reduce bias. The HTI was composed of 4 items: Alberta Stroke Program Early CT score (ASPECTS), National Institutes of Health Stroke Scale (NIHSS), hyperdense MCA (HMCA) sign, and AF on electrocardiogram (ECG) at admission. According to the predicted probability (PP) range, scores were allocated to ASPECTS as follows: 10-7 = 0; 6-5 = 1; 4-3 = 2; 2-0 = 3; to NIHSS: 0-11 = 0; 12-17 = 1; 18-23 = 2; >23 = 3; to HMCA sign: yes = 1; to AF on ECG: yes = 1. The HTI score varied from 0 to 8. For each score, adjusted PP of any HT with 95% confidence intervals (CI) was as follows: 0 = 0.027 (0.011-0.042); 1 = 0.07 (0.043-0.098); 2 = 0.169 (0.125-0.213); 3 = 0.346 (0.275-0.417); 4 = 0.571 (0.474-0.668); 5 = 0.768 (0.676-0.861); 6 = 0.893 (0.829-0.957); 7 = 0.956 (0.92-0.992); 8 = 0.983 (0.965-1.0). The optimal cutpoint score to differentiate between HT-positive and negative groups was 2 (95% normal-based CI, 1-3) for the DC and VC alike. ROC area

  20. Does training novices to criteria and does rapid acquisition of skills on laparoscopic simulators have predictive validity or are we just playing video games?

    Science.gov (United States)

    Hogle, Nancy J; Widmann, Warren D; Ude, Aku O; Hardy, Mark A; Fowler, Dennis L

    2008-01-01

    To determine whether LapSim training (version 3.0; Surgical Science Ltd, Göteborg, Sweden) to criteria for novice PGY1 surgical residents had predictive validity for improvement in the performance of laparoscopic cholecystectomy. In all, 21 PGY1 residents performed laparoscopic cholecystectomies in pigs after minimal training; their performance was evaluated by skilled laparoscopic surgeons using the validated tool GOALS (global operative assessment of laparoscopic operative skills: depth perception, bimanual dexterity, efficiency, tissue handling, and overall competence). From the group, 10 residents trained to competency on the LapSim Basic Skills Programs (camera navigation, instrument navigation, coordination, grasping, lifting and grasping, cutting, and clip applying). All 21 PGY1 residents again performed laparoscopic cholecystectomies on pigs; their performance was again evaluated by skilled laparoscopic surgeons using GOALS. Additionally, we studied the rate of learning to determine whether the slow or fast learners on the LapSim performed equivalently when performing actual cholecystectomies in pigs. Finally, 6 categorical residents were tracked, and their clinical performance on all of the laparoscopic cholecystectomies in which they were "surgeon, junior" was prospectively evaluated using the GOALS criteria. We found a statistical improvement of depth perception in the operative performance of cholecystectomies in pigs in the group trained on the LapSim. In the other 4 domains, a trend toward improvement was observed. No correlation between being a fast learner and the ultimate skill was demonstrated in the clinical performance of laparoscopic cholecystectomies. We did find that the fast learners on LapSim all were past or current video game players ("gamers"); however, that background did not translate into better clinical performance. Using current criteria, we doubt that the time and effort spent training novice PGY1 Surgical Residents on the basic

  1. Performance of in silico prediction tools for the classification of rare BRCA1/2 missense variants in clinical diagnostics.

    Science.gov (United States)

    Ernst, Corinna; Hahnen, Eric; Engel, Christoph; Nothnagel, Michael; Weber, Jonas; Schmutzler, Rita K; Hauke, Jan

    2018-03-27

    The use of next-generation sequencing approaches in clinical diagnostics has led to a tremendous increase in data and a vast number of variants of uncertain significance that require interpretation. Therefore, prediction of the effects of missense mutations using in silico tools has become a frequently used approach. Aim of this study was to assess the reliability of in silico prediction as a basis for clinical decision making in the context of hereditary breast and/or ovarian cancer. We tested the performance of four prediction tools (Align-GVGD, SIFT, PolyPhen-2, MutationTaster2) using a set of 236 BRCA1/2 missense variants that had previously been classified by expert committees. However, a major pitfall in the creation of a reliable evaluation set for our purpose is the generally accepted classification of BRCA1/2 missense variants using the multifactorial likelihood model, which is partially based on Align-GVGD results. To overcome this drawback we identified 161 variants whose classification is independent of any previous in silico prediction. In addition to the performance as stand-alone tools we examined the sensitivity, specificity, accuracy and Matthews correlation coefficient (MCC) of combined approaches. PolyPhen-2 achieved the lowest sensitivity (0.67), specificity (0.67), accuracy (0.67) and MCC (0.39). Align-GVGD achieved the highest values of specificity (0.92), accuracy (0.92) and MCC (0.73), but was outperformed regarding its sensitivity (0.90) by SIFT (1.00) and MutationTaster2 (1.00). All tools suffered from poor specificities, resulting in an unacceptable proportion of false positive results in a clinical setting. This shortcoming could not be bypassed by combination of these tools. In the best case scenario, 138 families would be affected by the misclassification of neutral variants within the cohort of patients of the German Consortium for Hereditary Breast and Ovarian Cancer. We show that due to low specificities state-of-the-art in silico

  2. Link practical-oriented research and education: New training tools for a sustainable use of plant protection products.

    Science.gov (United States)

    Sacchettini, G; Calliera, M

    2017-02-01

    In the Horizon 2020 work programme 2016-17 it is stated that in 2010, 71% of European farm managers were operating on the basis of practical experience only. Education levels greatly vary depending on country, farm managers' age and gender, or farm structures, and this can hamper innovation. Transition towards a more sustainable agriculture requires a renewal and strengthening of the technical skills of all the actors involved and - as a consequence - of the educational system. The EU Directive on the sustainable use of pesticides (EU, 128/2009/EC) requires European Member States to develop training activities targeting occupational exposure to pesticides. The objective of this study is to develop new training tools for operators, addressing the new legal requirements and taking into account what is already available. For this reason, the outcomes of different European and national research projects developed by the Opera Research Centre were used, involving stakeholders in the decision making process, but also considering the real behaviours and perceptions of the final users. As a result, an e-learning tool able to build personalized training programmes, by collecting and integrating existing training material on Plant Protection Products use was developed, together with an e-learning course, with the aim to help operators, advisors and distributors to get prepared for their national certificate test. This work highlights the opportunity to create long-term added value through enhanced collaboration between educators and researchers, and identifies a common set of priorities that has to be taken into account in order to nudge the changes required to achieve a more sustainable use of pesticide and, more in general, sustainable development. Copyright © 2016 Elsevier B.V. All rights reserved.

  3. The Fatigue Life Prediction of Train Wheel Rims Containing Spherical Inclusions

    Science.gov (United States)

    Li, Yajie; Chen, Huanguo; Cai, Li; Chen, Pei; Qian, Jiacheng; Wu, Jianwei

    2018-03-01

    It is a common phenomenon that fatigue crack initiation occurs frequently in the inclusions of wheel rims. Research on the fatigue life of wheel rims with spherical inclusions is of great significance on the reliability of wheels. To find the danger point and working condition of a wheel, the stress state of the wheel rim with spherical inclusions was analyzed using the finite element method. Results revealed that curve conditions are dangerous. The critical plane method, based on the cumulative fatigue damage theory, was used to predict the fatigue life of the wheel rim and whether it contained spherical inclusions or not under curve conditions. It was found that the fatigue life of the wheel rim is significantly shorter when the wheel rim contains spherical inclusions. Analysis of the results can provide a theoretical basis and technical support for train operations and maintenance.

  4. Wilderness First Aid Training as a Tool for Improving Basic Medical Knowledge in South Sudan.

    Science.gov (United States)

    Katona, Lindsay B; Douglas, William S; Lena, Sean R; Ratner, Kyle G; Crothers, Daniel; Zondervan, Robert L; Radis, Charles D

    2015-12-01

    The challenges presented by traumatic injuries in low-resource communities are especially relevant in South Sudan. This study was conducted to assess whether a 3-day wilderness first aid (WFA) training course taught in South Sudan improved first aid knowledge. Stonehearth Open Learning Opportunities (SOLO) Schools designed the course to teach people with limited medical knowledge to use materials from their environment to provide life-saving care in the event of an emergency. A pre-test/post-test study design was used to assess first aid knowledge of 46 community members in Kit, South Sudan, according to a protocol approved by the University of New England Institutional Review Board. The course and assessments were administered in English and translated in real-time to Acholi and Arabic, the two primary languages spoken in the Kit region. Descriptive statistics, t-test, ANOVA, and correlation analyses were conducted. Results included a statistically significant improvement in first aid knowledge after the 3-day training course: t(38)=3.94; Pfirst of its kind in South Sudan, provides evidence that a WFA training course in South Sudan is efficacious. These findings suggest that similar training opportunities could be used in other parts of the world to improve basic medical knowledge in communities with limited access to medical resources and varying levels of education and professional experiences.

  5. Training in the working place: a tool for the improvement of the performance

    International Nuclear Information System (INIS)

    Hinestrosa, A.; Mazon, J. M.

    2011-01-01

    The qualification of the personnel of the nuclear plants, is not only related to the theoretical knowledge acquired during academic training or recycling courses received in the company, but it is also related to practical skills acquired during the incorporation to the workplace and prior work experience. Both knowledge and skills are essential for quality work.

  6. Virtual worlds are an innovative tool for medical device training in a simulated environment.

    Science.gov (United States)

    Patel, Vishal; Lee, Henry; Taylor, Dave; Aggarwal, Rajesh; Kinross, James; Darzi, Ara

    2012-01-01

    Medical infusion devices are an integral component within the delivery of healthcare management. The aim of this study was to develop a training simulation in the virtual world of Second Life for the management of adverse events associated with infusion devices. Forty nurses were subsequently recruited to participate within the simulation and assess its feasibility.

  7. Mental training as a tool in the neuroscientific study of brain and cognitive plasticity

    NARCIS (Netherlands)

    Slagter, H.A.; Davidson, R.J.; Lutz, A.

    2011-01-01

    Although the adult brain was once seen as a rather static organ, it is now clear that the organization of brain circuitry is constantly changing as a function of experience or learning. Yet, research also shows that learning is often specific to the trained stimuli and task, and does not improve

  8. Summer research training provides effective tools for underrepresented minorities to obtain doctoral level degrees

    Science.gov (United States)

    The ethnic, racial, and cultural diversity of the USA is not reflected in its healthcare and biomedical workforce. Undergraduate research programs are used to encourage underrepresented minorities to pursue training for biomedical careers, but there is limited published data on doctoral degree compl...

  9. Development of the Corrective Feedback Instrument: A Tool for Use in Counselor Training Groups.

    Science.gov (United States)

    Hulse-Killacky, Diana; Page, Betsy J.

    1994-01-01

    Presents an instrument for measuring emotional barriers that can inhibit giving, receiving, and exchanging corrective feedback in counselor training groups. Also assesses leader behaviors that can help group members address those barriers. Testing showed that the instrument can be used to identify group member concerns. (RJM)

  10. Web-based tree crown condition evaluation training tool for urban and community forestry

    Science.gov (United States)

    Neil Clark; Matthew Winn; Philip Araman

    2009-01-01

    Volunteers are getting involved more and more, particularly in monitoring applications within the context of urban and community forestry. Training numerous volunteers becomes a substantial task given the numbers of people, time available, and a multitude of other projects. Hundreds of different individuals may be involved in a single field season. These individuals...

  11. Student Service and SEM: Training as the Tool to Sharpen Your Competitive Edge

    Science.gov (United States)

    Leigh, Susan

    2014-01-01

    The Challenge: After years of investments on structures and systems that improve and integrate student transactional experiences, we discover that we have neglected to train our staff in customer service competencies that match student expectations. The Answer: Invest in your student service staff to ensure they possess the professional skills to…

  12. Evaluation of Procedural Simulation as a Training and Assessment Tool in General Surgery

    DEFF Research Database (Denmark)

    Bjerrum, Flemming; Strandbygaard, Jeanett; Rosthøj, Susanne

    2017-01-01

    BACKGROUND: Laparoscopic appendectomy is a commonly performed surgical procedure, but few training models have been described for it. We examined a virtual reality module for practising a laparoscopic appendectomy. METHODS: A prospective cohort study with the following 3 groups of surgeons (n = 45...

  13. Social-Psychological Training as a Tool to Foster Communicative Competency of Students Specialising in Management

    Directory of Open Access Journals (Sweden)

    Elena N.

    2018-03-01

    Full Text Available Introduction: communicative competency serves as the basis for individual development of students specialising in management as well as a factor of successful managerial career. The implementation of competency-oriented approach in education and modern requirements of the labour market provide for the relevance of fostering communicative competency including its psychological features such as communication knowledge and skills. The specific trait of the author’s approach in the research is a shift from psychological characteristics diagnosis of communicative competencies to their amelioration through social psychological training of students specialized in management. The aim of the research is to elaborate, verify and assess the training programme effectiveness in forming psychological traits of communicative competencies. The article might be of interest for trainers and high school staff, students, specialists in human resources departments of various organisations. Materials and Methods: the research includes the following steps: choosing the testees, selecting diagnostic methodology to identify the level of communication knowledge and skills, pre-testing, elaborating the training programme of communicative competency, getting feed-back from the testees on completing the programme, post-testing diagnostics, comparing the results of testing before and after the training, drawing conclusions. Results: the prospect of formation of students-managers’ preparedness to manage the dynamic correlation of communicative knowledge, abilities, and skills for future professional activity in management students is substantiated. As a result of diagnostics, better knowledge acquisition, higher values of indicators and higher level of development of communicative abilities were revealed. An original author’s approach was proposed. The distinctive feature of this method was the transition from the diagnostics of psychological characteristics of

  14. Prediction of composite fatigue life under variable amplitude loading using artificial neural network trained by genetic algorithm

    Science.gov (United States)

    Rohman, Muhamad Nur; Hidayat, Mas Irfan P.; Purniawan, Agung

    2018-04-01

    Neural networks (NN) have been widely used in application of fatigue life prediction. In the use of fatigue life prediction for polymeric-base composite, development of NN model is necessary with respect to the limited fatigue data and applicable to be used to predict the fatigue life under varying stress amplitudes in the different stress ratios. In the present paper, Multilayer-Perceptrons (MLP) model of neural network is developed, and Genetic Algorithm was employed to optimize the respective weights of NN for prediction of polymeric-base composite materials under variable amplitude loading. From the simulation result obtained with two different composite systems, named E-glass fabrics/epoxy (layups [(±45)/(0)2]S), and E-glass/polyester (layups [90/0/±45/0]S), NN model were trained with fatigue data from two different stress ratios, which represent limited fatigue data, can be used to predict another four and seven stress ratios respectively, with high accuracy of fatigue life prediction. The accuracy of NN prediction were quantified with the small value of mean square error (MSE). When using 33% from the total fatigue data for training, the NN model able to produce high accuracy for all stress ratios. When using less fatigue data during training (22% from the total fatigue data), the NN model still able to produce high coefficient of determination between the prediction result compared with obtained by experiment.

  15. Predicting Resident Performance from Preresidency Factors: A Systematic Review and Applicability to Neurosurgical Training.

    Science.gov (United States)

    Zuckerman, Scott L; Kelly, Patrick D; Dewan, Michael C; Morone, Peter J; Yengo-Kahn, Aaron M; Magarik, Jordan A; Baticulon, Ronnie E; Zusman, Edie E; Solomon, Gary S; Wellons, John C

    2018-02-01

    Neurosurgical educators strive to identify the best applicants, yet formal study of resident selection has proved difficult. We conducted a systematic review to answer the following question: What objective and subjective preresidency factors predict resident success? PubMed, ProQuest, Embase, and the CINAHL databases were queried from 1952 to 2015 for literature reporting the impact of preresidency factors (PRFs) on outcomes of residency success (RS), among neurosurgery and all surgical subspecialties. Due to heterogeneity of specialties and outcomes, a qualitative summary and heat map of significant findings were constructed. From 1489 studies, 21 articles met inclusion criteria, which evaluated 1276 resident applicants across five surgical subspecialties. No neurosurgical studies met the inclusion criteria. Common objective PRFs included standardized testing (76%), medical school performance (48%), and Alpha Omega Alpha (43%). Common subjective PRFs included aggregate rank scores (57%), letters of recommendation (38%), research (33%), interviews (19%), and athletic or musical talent (19%). Outcomes of RS included faculty evaluations, in-training/board exams, chief resident status, and research productivity. Among objective factors, standardized test scores correlated well with in-training/board examinations but poorly correlated with faculty evaluations. Among subjective factors, aggregate rank scores, letters of recommendation, and athletic or musical talent demonstrated moderate correlation with faculty evaluations. Standardized testing most strongly correlated with future examination performance but correlated poorly with faculty evaluations. Moderate predictors of faculty evaluations were aggregate rank scores, letters of recommendation, and athletic or musical talent. The ability to predict success of neurosurgical residents using an evidence-based approach is limited, and few factors have correlated with future resident performance. Given the importance of

  16. cortisol/cortisone ratio as a valid tool of training load monitoring

    Directory of Open Access Journals (Sweden)

    T Bouaziz

    2016-08-01

    Full Text Available The effectiveness of selected physiological and perceptual measures for monitoring training load and fatigue was studied in 16 male elite rugby sevens players during a 6-week intense training block (IT and 2-week tapering (TAP. Daily training load (TL and strain (TS as well as weekly total score of fatigue (TSF were quantified respectively by the session-rating of perceived exertion (RPE method and an 8-item questionnaire. Also, testing was performed and 24 h urinary cortisol (C, cortisone (Cn, adrenaline (A and noradrenalin (NA excretion was measured before (T0 and after the IT (T1 and after the TAP (T2. The TL, TS and TSF increased during the IT and decreased during the TAP, in conjunction with a significant drop and improvement, respectively, of performance standards during the two periods. At T1, C and Cn levels increased while A and NA levels decreased, resulting in a higher C/Cn ratio and lower A/NA ratio, respectively. At T2, both C/Cn and A/NA returned to baseline values. The changes in C/Cn ratio, after the 6-week IT, were more closely related to mean TL, TS and TSF (r=0.75-0.76 vs. r=0.48-0.58, p<0.01 and to changes in the majority of performance measures than to A/NA ratio. Only the changes in C/Cn ratio after the 2-week TAP were related to mean TL, TS and TSF (r=0.61-0.68, p<0.01. The changes in hormone levels, training strain and performance standards reflected the physical and mental stressors of training, with complete recovery, as indicated by physiological homeostasis, achieved after an appropriate tapering period.

  17. Use of Multimedia tools for Training in Radiation Protection for Interventional Radiology

    International Nuclear Information System (INIS)

    Guibelalde, E.; Vano, E.

    2003-01-01

    The European Commission has published and distributed cost free in the main European languages and interactive CD-ROM for Radiation Protection Training in Interventional Radiology (MARTIR project-Radiation Protection Series N. 119-EC 2002). The CD-ROM allows: a) To select different levels of training; b) To follow a training programme as a regular course (step by step) or looking only for the topics of interest; c) To do some auto evaluation multiple choice questions at the end of the different sections or topics; d) To perform a final examination at the end of the course and to have a certification with the total time dedicated to the training programme and the obtained score in final examination. During 2001 and 2002 the MARTIR material has been distributed for evaluation purpose to different experts and it has been used in different pilot courses. In this paper the experience of using this interactive CD-ROM is discussed. The University Complutense of Madrid offers an optional specific training on Radiation Protection for the students of Medicine during their clinical period (4th to 6th year). About 100 hundred students are enrolled per year, 10% of these students follow the MARTIR CD at home as a pilot course. All of them used the CD at Least during 40 hours, completed the low level step-by-step course and pass the exam (score over 75% for 60 multiple choice questions. 87% of the students after finishing the course stated that this education methodology was very suitable for them. (Author)

  18. Neuro-Fuzzy Prediction of Cooperation Interaction Profile of Flexible Road Train Based on Hybrid Automaton Modeling

    Directory of Open Access Journals (Sweden)

    Banjanovic-Mehmedovic Lejla

    2016-01-01

    Full Text Available Accurate prediction of traffic information is important in many applications in relation to Intelligent Transport systems (ITS, since it reduces the uncertainty of future traffic states and improves traffic mobility. There is a lot of research done in the field of traffic information predictions such as speed, flow and travel time. The most important research was done in the domain of cooperative intelligent transport system (C-ITS. The goal of this paper is to introduce the novel cooperation behaviour profile prediction through the example of flexible Road Trains useful road cooperation parameter, which contributes to the improvement of traffic mobility in Intelligent Transportation Systems. This paper presents an approach towards the control and cooperation behaviour modelling of vehicles in the flexible Road Train based on hybrid automaton and neuro-fuzzy (ANFIS prediction of cooperation profile of the flexible Road Train. Hybrid automaton takes into account complex dynamics of each vehicle as well as discrete cooperation approach. The ANFIS is a particular class of the ANN family with attractive estimation and learning potentials. In order to provide statistical analysis, RMSE (root mean square error, coefficient of determination (R2 and Pearson coefficient (r, were utilized. The study results suggest that ANFIS would be an efficient soft computing methodology, which could offer precise predictions of cooperative interactions between vehicles in Road Train, which is useful for prediction mobility in Intelligent Transport systems.

  19. ATLAS OpenData and OpenKey: using low tech computational tools for students training in High Energy Physics

    CERN Document Server

    Sanchez Pineda, Arturos; The ATLAS collaboration

    2018-01-01

    One of the big challenges in High Energy Physics development is the fact that many potential -and very valuable- students and young researchers live in countries where internet access and computational infrastructure are poor compared to institutions already participating. In order to accelerate the process, the ATLAS Open Data project releases useful and meaningful data and tools using standard and easy-to-deploy computational means, such as custom and light Linux Virtual Machines, open source technologies, web and desktop applications. The ATLAS Open Key, a simple USB pen, allows transporting all those resources around the globe. As simple as it sounds, this approach is helping to train students that are now PhD candidates and to integrate HEP educational programs at Master level in universities where did not exist before. The software tools and resources used will be presented, as well as results and stories, ideas and next steps of the ATLAS Open Data project.

  20. Prediction of the wear and evolution of cutting tools in a carbide / titanium-aluminum-vanadium machining tribosystem by volumetric tool wear characterization and modeling

    Science.gov (United States)

    Kuttolamadom, Mathew Abraham

    The objective of this research work is to create a comprehensive microstructural wear mechanism-based predictive model of tool wear in the tungsten carbide / Ti-6Al-4V machining tribosystem, and to develop a new topology characterization method for worn cutting tools in order to validate the model predictions. This is accomplished by blending first principle wear mechanism models using a weighting scheme derived from scanning electron microscopy (SEM) imaging and energy dispersive x-ray spectroscopy (EDS) analysis of tools worn under different operational conditions. In addition, the topology of worn tools is characterized through scanning by white light interferometry (WLI), and then application of an algorithm to stitch and solidify data sets to calculate the volume of the tool worn away. The methodology was to first combine and weight dominant microstructural wear mechanism models, to be able to effectively predict the tool volume worn away. Then, by developing a new metrology method for accurately quantifying the bulk-3D wear, the model-predicted wear was validated against worn tool volumes obtained from corresponding machining experiments. On analyzing worn crater faces using SEM/EDS, adhesion was found dominant at lower surface speeds, while dissolution wear dominated with increasing speeds -- this is in conformance with the lower relative surface speed requirement for micro welds to form and rupture, essentially defining the mechanical load limit of the tool material. It also conforms to the known dominance of high temperature-controlled wear mechanisms with increasing surface speed, which is known to exponentially increase temperatures especially when machining Ti-6Al-4V due to its low thermal conductivity. Thus, straight tungsten carbide wear when machining Ti-6Al-4V is mechanically-driven at low surface speeds and thermally-driven at high surface speeds. Further, at high surface speeds, craters were formed due to carbon diffusing to the tool surface and

  1. Ability of different screening tools to predict positive effect on nutritional intervention among the elderly in primary health care

    DEFF Research Database (Denmark)

    Beck, Anne Marie; Beermann, Tina; Kjær, Stine

    2013-01-01

    Routine identification of nutritional risk screening is paramount as the first stage in nutritional treatment of the elderly. The major focus of former validation studies of screening tools has been on the ability to predict undernutrition. The aim of this study was to validate Mini Nutritional A...

  2. Using exposure prediction tools to link exposure and dosimetry for risk-based decisions: A case study with phthalates

    Science.gov (United States)

    A few different exposure prediction tools were evaluated for use in the new in vitro-based safety assessment paradigm using di-2-ethylhexyl phthalate (DEHP) and dibutyl phthalate (DnBP) as case compounds. Daily intake of each phthalate was estimated using both high-throughput (HT...

  3.  Running speed during training and percent body fat predict race time in recreational male marathoners

    OpenAIRE

    Barandun U; Knechtle B; Knechtle P; Klipstein A; Rust CA; Rosemann T; Lepers R

    2012-01-01

     Background: Recent studies have shown that personal best marathon time is a strong predictor of race time in male ultramarathoners. We aimed to determine variables predictive of marathon race time in recreational male marathoners by using the same characteristics of anthropometry and training as used for ultramarathoners.Methods: Anthropometric and training characteristics of 126 recreational male marathoners were bivariately and multivariately related to marathon race times.Results...

  4. Assessment of Lightning Transients on a De-Iced Rotor Blade with Predictive Tools and Coaxial Return Measurements

    Science.gov (United States)

    Guillet, S.; Gosmain, A.; Ducoux, W.; Ponçon, M.; Fontaine, G.; Desseix, P.; Perraud, P.

    2012-05-01

    The increasing use of composite materials in aircrafts primary structures has led to different problematics in the field of safety of flight in lightning conditions. The consequences of this technological mutation, which occurs in a parallel context of extension of electrified critical functions, are addressed by aircraft manufacturers through the enhancement of their available assessment means of lightning transient. On the one hand, simulation tools, provided an accurate description of aircraft design, are today valuable assessment tools, in both predictive and operative terms. On the other hand, in-house test means allow confirmation and consolidation of design office hardening solutions. The combined use of predictive simulation tools and in- house test means offers an efficient and reliable support for all aircraft developments in their various life-time stages. The present paper provides PREFACE research project results that illustrate the above introduced strategy on the de-icing system of the NH90 composite main rotor blade.

  5. Prediction Of Tensile And Shear Strength Of Friction Surfaced Tool Steel Deposit By Using Artificial Neural Networks

    Science.gov (United States)

    Manzoor Hussain, M.; Pitchi Raju, V.; Kandasamy, J.; Govardhan, D.

    2018-04-01

    Friction surface treatment is well-established solid technology and is used for deposition, abrasion and corrosion protection coatings on rigid materials. This novel process has wide range of industrial applications, particularly in the field of reclamation and repair of damaged and worn engineering components. In this paper, we present the prediction of tensile and shear strength of friction surface treated tool steel using ANN for simulated results of friction surface treatment. This experiment was carried out to obtain tool steel coatings of low carbon steel parts by changing contribution process parame