251 research outputs found
Correction of High Vibration on a Vertical Turbine Deep Well Pump with a Dynamic Vibration Absorber
Case StudyA 100 horsepower, 180 foot deep vertical turbine pump called #12 Well Pump had a history of reoccurring high vibration despite multiple pump rebuilds and motor replacements. The problem was identified as a structural resonance of the motor and discharge head assembly. It was determined that a dynamic vibration absorber (DVA) would be the most effective solution. This case study presents the technique of diagnosing the resonance and the methodology of designing and calibrating a dynamic vibration absorber. Installation of the DVA reduced the overall vibration velocity amplitude by a factor of 16
Correction of High Vibration on a Vertical Turbine Deep Well Pump with a Dynamic Vibration Absorber
Case StudyA 100 horsepower, 180 foot deep vertical turbine pump called #12 Well Pump had a history of reoccurring high vibration despite multiple pump rebuilds and motor replacements. The problem was identified as a structural resonance of the motor and discharge head assembly. It was determined that a dynamic vibration absorber (DVA) would be the most effective solution. This case study presents the technique of diagnosing the resonance and the methodology of designing and calibrating a dynamic vibration absorber. Installation of the DVA reduced the overall vibration velocity amplitude by a factor of 16
Correction Of Chronic Thrust Bearing Failures On A Refrigeration Compressor
Case Studypg. 426-44
Subgenual activation and the finger of blame: individual differences and depression vulnerability.
BACKGROUND: Subgenual cingulate cortex (SCC) responses to self-blaming emotion-evoking stimuli were previously found in individuals prone to self-blame with and without a history of major depressive disorder (MDD). This suggested SCC activation reflects self-blaming emotions such as guilt, which are central to models of MDD vulnerability. METHOD: Here, we re-examined these hypotheses in an independent larger sample. A total of 109 medication-free participants (70 with remitted MDD and 39 healthy controls) underwent fMRI whilst judging self- and other-blaming emotion-evoking statements. They also completed validated questionnaires of proneness to self-blaming emotions including those related to internal (autonomy) and external (sociotropy) evaluation, which were subjected to factor analysis. RESULTS: An interaction between group (remitted MDD v. Control) and condition (self- v. other-blame) was observed in the right SCC (BA24). This was due to higher SCC signal for self-blame in remitted MDD and higher other-blame-selective activation in Control participants. Across the whole sample, extracted SCC activation cluster averages for self- v. other-blame were predicted by a regression model which included the reliable components derived from our factor analysis of measures of proneness to self-blaming emotions. Interestingly, this prediction was solely driven by autonomy/self-criticism, and adaptive guilt factors, with no effect of sociotropy/dependency. CONCLUSIONS: Despite confirming the prediction of SCC activation in self-blame-prone individuals and those vulnerable to MDD, our results suggest that SCC activation reflects blame irrespective of where it is directed rather than selective for self. We speculate that self-critical individuals have more extended SCC representations for blame in the context of self-agency
The many faces of fear:A synthesis of methodological variation in characterizing predation risk from carnivores
Predators affect prey by killing them directly (lethal effects) and by inducing costly antipredator behaviours in living prey (risk effects). Risk effects can strongly influence prey populations and cascade through trophic systems. A prerequisite for assessing risk effects is characterizing the spatiotemporal variation in predation risk. Risk effects research has experienced rapid growth in the last several decades. However, preliminary assessments of the resultant literature suggest that researchers characterize predation risk using a variety of techniques. The implications of this methodological variation for inference and comparability among studies have not been well recognized or formally synthesized. We couple a literature survey with a hierarchical framework, developed from established theory, to quantify the methodological variation in characterizing risk using carnivore-ungulate systems as a case study. Via this process, we documented 244 metrics of risk from 141 studies falling into at least 13 distinct subcategories within three broader categories. Both empirical and theoretical work suggest risk and its effects on prey constitute a complex, multi-dimensional process with expressions varying by spatiotemporal scale. Our survey suggests this multi-scale complexity is reflected in the literature as a whole but often underappreciated in any given study, which complicates comparability among studies and leads to an overemphasis on documenting the presence of risk effects rather than their mechanisms or scale of influence. We suggest risk metrics be placed in a more concrete conceptual framework to clarify inference surrounding risk effects and their cascading effects throughout ecosystems. We recommend studies (i) take a multi-scale approach to characterizing risk; (ii) explicitly consider 'true' predation risk (probability of predation per unit time); and (iii) use risk metrics that facilitate comparison among studies and the evaluation of multiple competing hypotheses. Addressing the pressing questions in risk effects research, including how, to what extent and on what scale they occur, requires leveraging the advantages of the many methods available to characterize risk while minimizing the confusion caused by variability in their application.The NSF Graduate Research Fellowship Program (RJM), the
Michigan State University MasterCard Foundation Scholars Program (ABM), CNPq-Brasil
(LA), and the University of Montana Boone and Crockett Program (JJM).http://onlinelibrary.wiley.com/journal/10.1111/(ISSN)1365-26562018-07-30cs2017Centre for Wildlife Managemen
The predictive value of the NICE "red traffic lights" in acutely ill children
Objective: Early recognition and treatment of febrile children with serious infections (SI) improves prognosis, however, early detection can be difficult. We aimed to validate the predictive rule-in value of the National Institute for Health and Clinical Excellence (NICE) most severe alarming signs or symptoms to identify SI in children. Design, Setting and Participants: The 16 most severe ("red") features of the NICE traffic light system were validated in seven different primary care and emergency department settings, including 6,260 children presenting with acute illness. Main Outcome Measures: We focussed on the individual predictive value of single red features for SI and their combinations. Results were presented as positive likelihood ratios, sensitivities and specificities. We categorised "general" and "disease-specific" red features. Changes in pre-test probability versus post-test probability for SI were visualised in Fagan nomograms. Results: Almost all red features had rule-in value for SI, but only four individual red features substantially raised the probability of SI in more than one dataset: "does not wake/stay awake", "reduced skin turgor", "non-blanching rash", and "focal neurological signs". The presence of ≥3 red features improved prediction of SI but still lacked strong rule-in value as likelihood ratios were below 5. Conclusions: The rule-in value of the most severe alarming signs or symptoms of the NICE traffic light system for identifying children with SI was limited, even when multiple red features were present. Our study highlights the importance of assessing the predictive value of alarming signs in clinical guidelines prior to widespread implementation in routine practice
Frontotemporal lobar degeneration and social behaviour:Dissociation between the knowledge of its consequences and its conceptual meaning
A longitudinal study combining the Double Diamond framework and Behavior Change Wheel to co-create a sedentary behavior intervention in police control rooms.
BackgroundPolice work can be sedentary and stressful, negatively impacting health and wellbeing. In a novel co-creation approach, we used the Behavior Change Wheel (BCW) and Double Diamond (DD) design framework to guide the collaborative design and development of a sedentary behavior intervention in the control rooms of two British police forces.MethodsMultiple stakeholders participated in four phases of research. In Phase 1, a literature review, focus groups (n = 20) and interviews (n = 10) were conducted to 'discover' the relationship between physical activity and wellbeing in the police. In Phase 2, a steering group consolidated Phase 1 findings to 'define' a specific behavior for intervention. Phases 3 and 4 'developed' the intervention across six workshops with control room workers and six steering group workshops.ResultsThe co-creation process identified contextual sedentary behavior as the target behavior, driven by behavioral regulation, social influence and social norms. The sedentary behavior intervention targeted these drivers and aimed to engage control room workers in short bursts of physical activity throughout their shifts. Key intervention features targeted involvement of staff in decision-making and embedding physical activity into work practices.ConclusionsThe BCW and DD can be combined to co-create evidence-based and participant-informed interventions and translate science into action
Concert recording 2013-03-31b
[Track 01]. Sweet Georgie fame / Blossom Dearie -- [Track 02]. Joy spring / Clifford Brown -- [Track 03]. Summer samba / Marcos Valle -- [Track 04]. Rhythm\u27ning / Thelonious Monk -- [Track 05]. One note samba / Antonio Carlos Jobim -- [Track 06]. In a sentimental mood / Duke Ellington -- [Track 07]. Recordame / Joe Henderson -- [Track 08]. Full house / Wes Montgomery -- [Track 09]. Cats and kittens / Peter Erskine -- [Track 10]. Primal prayer / Dan Haerle -- [Track 11]. Cookin\u27 Boox / Detroit Jackson
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