The predictability of wind and virtual temperature profiles for flight and static test operations Final report, Jul. 1, 1965 - Mar. 31, 1966

Predictability of wind and virtual temperature profiles for flight and static test operation

Time-dependent depletion isotopics with MCNP-5 and SCALE-6.1

Thesis (S.M. and S.B.)--Massachusetts Institute of Technology, Dept. of Nuclear Science and Engineering, 2012.Cataloged from PDF version of thesis.Includes bibliographical references (p. 45).In order to operate a reactor safely and efficiently, computer simulations must be used to predict certain nuclear characteristics of the reactor. To determine how materials change in a fission power environment, a time-dependent depletion isotopic code must be used. Over the past several decades, the MIT Reactor (MITR) has taken many steps to prepare for its conversion from the use of highly enriched uranium (HEU) to low enriched uranium (LEU) in its fuel. Throughout this process, detailed neutronics simulations must be run to predict the characteristics of the reactor with its current HEU fuel, with potential forms of LEU fuel, and with combinations of the two. MCODE Version 3 is a linkage code that performs time-dependent burnup calculations by combining the Monte Carlo N-Particle transport code, MCNP, with the Oak Ridge Isotope Generation point depletion code, ORIGEN-S. MCNP provides reaction rates and neutron flux in user-specified irradiation material regions. COUPLE, a data-editing code included in the SCALE- 6.1 software package, uses these data from MCNP to update the cross section libraries, which ORIGEN then uses to perform nuclide depletion calculations in each irradiation zone. The MCNP model is then updated with the depleted material compositions, and the exchange is repeated. The MCNP/ORIGEN coupling utilizes an optional predictor-corrector capability. As a newer version of MCODE Version 2.2, MCODE-3 offers three major changes from its predecessor. The first is the incorporation of ORIGEN-S. MCODE-2 used a previous version of ORIGEN, which is no longer supported by ORNL. ORIGEN-S provides newer nuclear data as well as additional functionality and usability. Secondly, MCODE-3 uses COUPLE to create an entirely unique cross section library from the regionally averaged 238-group flux, which means every cross section value that MCODE-3 uses in its depletion is specific to the input model. MCODE-2 only updates a fraction of nuclides' cross sections, the rest default to a pre-compiled library. Finally, while MCODE-2.2 was written in ANSI C, MCODE-3's main function has been rewritten in the Python scripting language. MCODE's preproc, mcodeout, and mcnpxs programs have not been edited, and are thus still written in ANSI C. Benchmarking has indicated that while the evolution of most nuclides is similar to an MCODE-2 calculation, over many depletion steps some nuclides can diverge due to COUPLE's use of the 238-group flux.by Thomas P. Gerrity, III.S.M.and S.B

Reactions to uncertainty and the accuracy of diagnostic mammography.

BackgroundReactions to uncertainty in clinical medicine can affect decision making.ObjectiveTo assess the extent to which radiologists' reactions to uncertainty influence diagnostic mammography interpretation.DesignCross-sectional responses to a mailed survey assessed reactions to uncertainty using a well-validated instrument. Responses were linked to radiologists' diagnostic mammography interpretive performance obtained from three regional mammography registries.ParticipantsOne hundred thirty-two radiologists from New Hampshire, Colorado, and Washington.MeasurementMean scores and either standard errors or confidence intervals were used to assess physicians' reactions to uncertainty. Multivariable logistic regression models were fit via generalized estimating equations to assess the impact of uncertainty on diagnostic mammography interpretive performance while adjusting for potential confounders.ResultsWhen examining radiologists' interpretation of additional diagnostic mammograms (those after screening mammograms that detected abnormalities), a 5-point increase in the reactions to uncertainty score was associated with a 17% higher odds of having a positive mammogram given cancer was diagnosed during follow-up (sensitivity), a 6% lower odds of a negative mammogram given no cancer (specificity), a 4% lower odds (not significant) of a cancer diagnosis given a positive mammogram (positive predictive value [PPV]), and a 5% higher odds of having a positive mammogram (abnormal interpretation).ConclusionMammograms interpreted by radiologists who have more discomfort with uncertainty have higher likelihood of being recalled

Stress from Uncertainty from Graduation to Retirement—A Population-Based Study of Swiss Physicians

BACKGROUND: Uncertainty shapes many decisions made by physicians everyday. Uncertainty and physicians’ inability to handle it may result in substandard care and unexplained variations in patterns of care. OBJECTIVE: To describe socio-demographic and professional characteristics of reactions to uncertainty among physicians from all specialties, including physicians in training. DESIGN: Cross-sectional postal survey. PARTICIPANT: All physicians practicing in Geneva, Switzerland (n = 1,994). MEASUREMENT: Reaction to medical care uncertainty was measured with the Anxiety Due to Uncertainty and Concern About Bad Outcomes scales. The questionnaire also included items about professional characteristics and work-related satisfaction scales. RESULTS: After the first mailing and two reminders, 1,184 physicians responded to the survey. In univariate analysis, women, junior physicians, surgical specialists, generalist physicians, and physicians with lower workloads had higher scores in both scales. In multivariate models, sex, medical specialty, and workload remained significantly associated with both scales, whereas clinical experience remained associated only with concern about bad outcomes. Higher levels of anxiety due to uncertainty were associated with lower scores of work-related satisfaction, while higher levels of concern about bad outcomes were associated with lower satisfaction scores for patient care, personal rewards, professional relations, and general satisfaction, but not for work-related burden or satisfaction with income-prestige. The negative effect of anxiety due to uncertainty on work-related satisfaction was more important for physicians in training. CONCLUSION: Physicians’ reactions to uncertainty in medical care were associated with several dimensions of work-related satisfaction. Physicians in training experienced the greatest impact of anxiety due to uncertainty on their work-related satisfaction. Incorporating strategies to deal with uncertainty into residency training may be useful

A review of clinical decision-making: Models and current research

Aims and objectives: The aim of this paper was to review the current literature with respect to clinical decision-making models and the educational application of models to clinical practice. This was achieved by exploring the function and related research of the three available models of clinical decision making: information processing model, the intuitive-humanist model and the clinical decision making model. Background: Clinical decision-making is a unique process that involves the interplay between knowledge of pre-existing pathological conditions, explicit patient information, nursing care and experiential learning. Historically, two models of clinical decision making are recognised from the literature; the information processing model and the intuitive-humanist model. The usefulness and application of both models has been examined in relation the provision of nursing care and care related outcomes. More recently a third model of clinical decision making has been proposed. This new multidimensional model contains elements of the information processing model but also examines patient specific elements that are necessary for cue and pattern recognition. Design: Literature review Methods: Evaluation of the literature generated from MEDLINE, CINAHL, OVID, PUBMED and EBESCO systems and the Internet from 1980 – November 2005

The GAPS Experiment to Search for Dark Matter using Low-energy Antimatter

The GAPS experiment is designed to carry out a sensitive dark matter search by measuring low-energy cosmic ray antideuterons and antiprotons. GAPS will provide a new avenue to access a wide range of dark matter models and masses that is complementary to direct detection techniques, collider experiments and other indirect detection techniques. Well-motivated theories beyond the Standard Model contain viable dark matter candidates which could lead to a detectable signal of antideuterons resulting from the annihilation or decay of dark matter particles. The dark matter contribution to the antideuteron flux is believed to be especially large at low energies (E < 1 GeV), where the predicted flux from conventional astrophysical sources (i.e. from secondary interactions of cosmic rays) is very low. The GAPS low-energy antiproton search will provide stringent constraints on less than 10 GeV dark matter, will provide the best limits on primordial black hole evaporation on Galactic length scales, and will explore new discovery space in cosmic ray physics. Unlike other antimatter search experiments such as BESS and AMS that use magnetic spectrometers, GAPS detects antideuterons and antiprotons using an exotic atom technique. This technique, and its unique event topology, will give GAPS a nearly background-free detection capability that is critical in a rare-event search. GAPS is designed to carry out its science program using long-duration balloon flights in Antarctica. A prototype instrument was successfully flown from Taiki, Japan in 2012. GAPS has now been approved by NASA to proceed towards the full science instrument, with the possibility of a first long-duration balloon flight in late 2020. Here we motivate low-energy cosmic ray antimatter searches and discuss the current status of the GAPS experiment and the design of the payload.Comment: 8 pags, 3 figures, Proc. 35th International Cosmic Ray Conference (ICRC 2017), Busan, Kore

Validation and cultural adaptation of a German version of the Physicians' Reactions to Uncertainty scales

Contains fulltext : 51656.pdf ( ) (Open Access)BACKGROUND: The aim of the study was to examine the validity of a translated and culturally adapted version of the Physicians' Reaction to Uncertainty scales (PRU) in primary care physicians. METHODS: In a structured process, the original questionnaire was translated, culturally adapted and assessed after administering it to 93 GPs. Test-retest reliability was tested by sending the questionnaire to the GPs again after two weeks. RESULTS: The principal factor analysis confirmed the postulated four-factor structure underlying the 15 items. In contrast to the original version, item 5 achieved a higher loading on the 'concern about bad outcomes' scale. Consequently, we rearranged the scales. Good item-scale correlations were obtained, with Pearson's correlation coefficient ranging from 0.56-0.84. As regards the item-discriminant validity between the scales 'anxiety due to uncertainty' and 'concern about bad outcomes', partially high correlations (Pearson's correlation coefficient 0.02-0.69; p < 0.001) were found, indicating an overlap between both constructs. The assessment of internal consistency revealed satisfactory values; Cronbach's alpha of the rearranged version was 0.86 or higher for all scales. Test-retest-reliability, assessed by means of the intraclass-correlation-coefficient (ICC), exceeded 0.84, except for the 'reluctance to disclose mistakes to physicians' scale (ICC = 0.66). In this scale, some substantial floor effects occurred, with 29.3% of answers showing the lowest possible value. CONCLUSION: Dealing with uncertainty is an important issue in daily practice. The psychometric properties of the rearranged German version of the PRU are satisfying. The revealed floor effects do not limit the significance of the questionnaire. Thus, the German version of the PRU could contribute to the further evaluation of the impact of uncertainty in primary care physicians