Increasing Ambient Temperature Reduces Emotional Well-Being

This study examines the impact of ambient temperature on emotional well-being in the U.S. population aged 18+. The U.S. is an interesting test case because of its resources, technology and variation in climate across different areas, which also allows us to examine whether adaptation to different climates could weaken or even eliminate the impact of heat on well-being. Using survey responses from 1.9 million Americans over the period from 2008 to 2013, we estimate the effect of temperature on well-being from exogenous day-to-day temperature variation within respondents’ area of residence and test whether this effect varies across areas with different climates. We find that increasing temperatures significantly reduce well-being. Compared to average daily temperatures in the 50–60 °F (10–16 °C) range, temperatures above 70 °F (21 °C) reduce positive emotions (e.g. joy, happiness), increase negative emotions (e.g. stress, anger), and increase fatigue (feeling tired, low energy). These effects are particularly strong among less educated and older Americans. However, there is no consistent evidence that heat effects on well-being differ across areas with mild and hot summers, suggesting limited variation in heat adaptation.

Assessment of turbulence model predictions for a centrifugal compressor simulation

Steady-state computational fluid dynamics (CFD) simulations are an essential tool in the design process of centrifugal compressors. Whilst global parameters, such as pressure ratio and efficiency, can be predicted with reasonable accuracy, the accurate prediction of detailed compressor flow fields is a much more significant challenge. Much of the inaccuracy is associated with the incorrect selection of turbulence model. The need for a quick turnaround in simulations during the design optimisation process, also demands that the turbulence model selected be robust and numerically stable with short simulation times.
In order to assess the accuracy of a number of turbulence model predictions, the current study used an exemplar open CFD test case, the centrifugal compressor ‘Radiver’, to compare the results of three eddy viscosity models and two Reynolds stress type models. The turbulence models investigated in this study were (i) Spalart-Allmaras (SA) model, (ii) the Shear Stress Transport (SST) model, (iii) a modification to the SST model denoted the SST-curvature correction (SST-CC), (iv) Reynolds stress model of Speziale, Sarkar and Gatski (RSM-SSG), and (v) the turbulence frequency formulated Reynolds stress model (RSM-ω). Each was found to be in good agreement with the experiments (below 2% discrepancy), with respect to total-to-total parameters at three different operating conditions. However, for the off-design conditions, local flow field differences were observed between the models, with the SA model showing particularly poor prediction of local flow structures. The SST-CC showed better prediction of curved rotating flows in the impeller. The RSM-ω was better for the wake and separated flow in the diffuser. The SST model showed reasonably stable, robust and time efficient capability to predict global and local flow features.

Enhancing the Manufacturing Knowledge of Undergraduate Engineering Students: A Case Study of a Design-Build-Test Challenge Involving Folding Bicycles

Many engineers currently in professional practice will have gained a degree level qualification which involved studying a curriculum heavy with mathematics and engineering science. While this knowledge is vital to the engineering design process so also is manufacturing knowledge, if the resulting designs are to be both technically and commercially viable.
The methodology advanced by the CDIO Initiative aims to improve engineering education by teaching in the context of Conceiving, Designing, Implementing and Operating products, processes or systems. A key element of this approach is the use of Design-Built-Test (DBT) projects as the core of an integrated curriculum. This approach facilitates the development of professional skills as well as the application of technical knowledge and skills developed in other parts of the degree programme. This approach also changes the role of lecturer to that of facilitator / coach in an active learning environment in which students gain concrete experiences that support their development.
The case study herein describes Mechanical Engineering undergraduate student involvement in the manufacture and assembly of concept and functional prototypes of a folding bicycle.

The O stars in the VLT-FLAMES Tarantula Survey

The VLT-FLAMES Tarantula Survey (VFTS) has secured mid-resolution spectra of over 300 O-type stars in the 30 Doradus region of the Large Magellanic Cloud. A homogeneous analysis of such a large sample requires automated techniques, an approach that will also be needed for the upcoming analysis of the Gaia surveys of the Northern and Southern Hemisphere supplementing the Gaia measurements. We point out the importance of Gaia for the study of O stars, summarize the O star science case of VFTS and present a test of the automated modeling technique using synthetically generated data. This method employs a genetic algorithm based optimization technique in combination with fastwind model atmospheres. The method is found to be robust and able to recover the main photospheric parameters accurately. Precise wind parameters can be obtained as well, however, as expected, for dwarf stars the rate of acceleration of the ow is poorly constrained.

Creating New Design-Build-Test Experiences as Outputs of Undergraduate Design-Build-Test Projects

This paper describes a methodology of using individual engineering undergraduate student projects as a means of effectively and efficiently developing new Design-Build-Test (DBT) learning experiences and challenges.
A key aspect of the rationale for this approach is that it benefits all parties. The student undertaking the individual project gets an authentic experience of producing a functional artefact, which has been the result of a design process that addresses conception, design, implementation and operation. The supervising faculty member benefits from live prototyping of new curriculum content and resources with a student who is at a similar level of knowledge and experience as the intended end users of the DBT outputs. The multiple students who ultimately undertake the DBT experiences / challenges benefit from the enhanced nature of a learning experience which has been “road tested” and optimised.
To demonstrate the methodology the paper will describe a case study example of an individual project completed in 2015. This resulted in a DBT design challenge with a theme of designing a catapult for throwing table tennis balls, the device being made from components laser cut from medium density fibreboard (MDF). Further three different modes of operation will be described which use the same resource materials but operate over different timescales and with different learning outcomes, from an icebreaker exercise focused on developing team dynamics through to full DBT where students get an opportunity to experience the full impact of their design decisions by competing against other students with a catapult they have designed and built themselves.

Implementing a structural continuity constraint and a halting method for the topology optimization of energy absorbers

This study investigates topology optimization of energy absorbing structures in which material damage is accounted for in the optimization process. The optimization objective is to design the lightest structures that are able to absorb the required mechanical energy. A structural continuity constraint check is introduced that is able to detect when no feasible load path remains in the finite element model, usually as a result of large scale fracture. This assures that designs do not fail when loaded under the conditions prescribed in the design requirements. This continuity constraint check is automated and requires no intervention from the analyst once the optimization process is initiated. Consequently, the optimization algorithm proceeds towards evolving an energy absorbing structure with the minimum structural mass that is not susceptible to global structural failure. A method is also introduced to determine when the optimization process should halt. The method identifies when the optimization method has plateaued and is no longer likely to provide improved designs if continued for further iterations. This provides the designer with a rational method to determine the necessary time to run the optimization and avoid wasting computational resources on unnecessary iterations. A case study is presented to demonstrate the use of this method.

Sepsis: the LightCycler SeptiFast Test MGRADE®, SepsiTest™ and IRIDICA BAC BSI assay for rapidly identifying bloodstream bacteria and fungi – a systematic review and economic evaluation

Background: Sepsis can lead to multiple organ failure and death. Timely and appropriate treatment can reduce in-hospital mortality and morbidity. Objectives: To determine the clinical effectiveness and cost-effectiveness of three tests [LightCycler SeptiFast Test MGRADE® (Roche Diagnostics, Risch-Rotkreuz, Switzerland); SepsiTest™ (Molzym Molecular Diagnostics, Bremen, Germany); and the IRIDICA BAC BSI assay (Abbott Diagnostics, Lake Forest, IL, USA)] for the rapid identification of bloodstream bacteria and fungi in patients with suspected sepsis compared with standard practice (blood culture with or without matrix-absorbed laser desorption/ionisation time-offlight mass spectrometry). Data sources: Thirteen electronic databases (including MEDLINE, EMBASE and The Cochrane Library) were searched from January 2006 to May 2015 and supplemented by hand-searching relevant articles. Review methods: A systematic review and meta-analysis of effectiveness studies were conducted. A review of published economic analyses was undertaken and a de novo health economic model was constructed. A decision tree was used to estimate the costs and quality-adjusted life-years (QALYs) associated with each test; all other parameters were estimated from published sources. The model was populated with evidence from the systematic review or individual studies, if this was considered more appropriate (base case 1). In a secondary analysis, estimates (based on experience and opinion) from seven clinicians regarding the benefits of earlier test results were sought (base case 2). A NHS and Personal Social Services perspective was taken, and costs and benefits were discounted at 3.5% per annum. Scenario analyses were used to assess uncertainty. Results: For the review of diagnostic test accuracy, 62 studies of varying methodological quality were included. A meta-analysis of 54 studies comparing SeptiFast with blood culture found that SeptiFast had an estimated summary specificity of 0.86 [95% credible interval (CrI) 0.84 to 0.89] and sensitivity of 0.65 (95% CrI 0.60 to 0.71). Four studies comparing SepsiTest with blood culture found that SepsiTest had an estimated summary specificity of 0.86 (95% CrI 0.78 to 0.92) and sensitivity of 0.48 (95% CrI 0.21 to 0.74), and four studies comparing IRIDICA with blood culture found that IRIDICA had an estimated summary specificity of 0.84 (95% CrI 0.71 to 0.92) and sensitivity of 0.81 (95% CrI 0.69 to 0.90). Owing to the deficiencies in study quality for all interventions, diagnostic accuracy data should be treated with caution. No randomised clinical trial evidence was identified that indicated that any of the tests significantly improved key patient outcomes, such as mortality or duration in an intensive care unit or hospital. Base case 1 estimated that none of the three tests provided a benefit to patients compared with standard practice and thus all tests were dominated. In contrast, in base case 2 it was estimated that all cost per QALY-gained values were below £20,000; the IRIDICA BAC BSI assay had the highest estimated incremental net benefit, but results from base case 2 should be treated with caution as these are not evidence based. Limitations: Robust data to accurately assess the clinical effectiveness and cost-effectiveness of the interventions are currently unavailable. Conclusions: The clinical effectiveness and cost-effectiveness of the interventions cannot be reliably determined with the current evidence base. Appropriate studies, which allow information from the tests to be implemented in clinical practice, are required.

Uses of Agent-Based Modeling for Health Communication: the TELL ME Case Study

Government communication is an important management tool during a public health crisis, but understanding its impact is difficult. Strategies may be adjusted in reaction to developments on the ground and it is challenging to evaluate the impact of communication separately from other crisis management activities. Agent-based modeling is a well-established research tool in social science to respond to similar challenges. However, there have been few such models in public health. We use the example of the TELL ME agent-based model to consider ways in which a non-predictive policy model can assist policy makers. This model concerns individuals' protective behaviors in response to an epidemic, and the communication that influences such behavior. Drawing on findings from stakeholder workshops and the results of the model itself, we suggest such a model can be useful: (i) as a teaching tool, (ii) to test theory, and (iii) to inform data collection. We also plot a path for development of similar models that could assist with communication planning for epidemics.