60419 research outputs found
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Monitoring of transport infrastructure exposed to multiple hazards: a roadmap for building resilience
No full textMonitoring-enhanced resilience in transport management is emerging together with the new technologies and digital data, however have not been fully explored yet. Digital technologies have the potential to provide rapid resilience assessments in a quantifiable and engineered manner for transport infrastructure, which is exposed to multiple natural and human-induced hazards and diverse loads throughout their life-cycle. Physical damage and disruption of networks and interdependent systems may cause tremendous socioeconomic impact, affecting world economies and societies. Nowadays, transport infrastructure stakeholders have shifted the requirements in risk and resilience assessment. The expectation is that risk is estimated efficiently, almost in real-time with high accuracy, aiming at maximising the functionality and minimising losses. Nevertheless, no integrated framework exists for quantifying resilience to diverse hazards, based on structural and functionality monitoring (SHFM) data, and this is the main capability gap that this paper envisages filling. Monitoring systems have been used widely in transport infrastructure and have been studied extensively in the literature. Data can facilitate prognosis of the asset condition and the functionality of the network, informing computer-based asset and traffic models, which can assist in defining actionable performance indicators, for diagnosis and for defining risk and loss expediently and accurately. Evidence exists that SHFM is an enabler of resilience. However, strategies are absent in support of monitoring-based resilience assessment in transport infrastructure management. In response to the above challenge, this paper puts forward for the first time in the international literature, a roadmap for monitoring-based quantification of resilience for transport infrastructure, based on a comprehensive review of the current state-of-the-art. It is a holistic asset management roadmap, which identifies the interactions among the design, monitoring, risk assessment and quantification of resilience to multiple hazards. Monitoring is embraced as a vital component, providing expedient feedback for recovery measures, accelerating decision-making for adaptation of changing ecosystems and built environments, utilising emerging technologies, to continuously deliver safer and resilient transport infrastructure
How research can improve patient care and nurse wellbeing
No full textThis article, the first in a four-part series about using research evidence to inform the delivery of nursing care, discusses four studies that were funded following the two Francis inquiries into care failings at Mid Staffordshire NHS Foundation Trust. Each study evaluated an intervention method in an acute hospital setting that aimed to improve patient care and protect the wellbeing of nursing staff; these included a team-based practice development programme, a relational care training intervention for healthcare assistants, a regular bedside ward round (intentional rounding), and monthly group meetings during which staff discussed the emotional challenges of care. The remaining articles in this series will explore the results of the studies and how they can be applied to nursing care during, and after, the coronavirus pandemi
Transient Aero-Thermo-Mechanical Multidimensional Analysis of a High Pressure Turbine Assembly Through a Square Cycle
No full textBetter understanding and more accurate prediction of heat transfer and cooling flows in aero engine components in steady and transient operating regimes are essential to modern engine designs aiming at reduced cooling air consumption and improved engine efficiencies. This paper presents a simplified coupled transient analysis methodology that allows assessment of the aerothermal and thermomechanical responses of engine components together with cooling air mass flow, pressure and temperature distributions in an automatic fully integrated way. This is achieved by assembling a fluid network with contribution of components of different geometrical dimensions coupled to each other through dimensionally heterogeneous interfaces. More accurate local flow conditions, heat transfer and structural displacement are resolved on a smaller area of interest with multidimensional surface coupled CFD/FE codes. Contributions of the whole engine air-system are predicted with a faster mono dimensional flow network code. Matching conditions at the common interfaces are enforced at each time step exactly by employing an efficient iterative scheme. The coupled simulation is performed on an industrial high pressure turbine disk component run through a square cycle. Predictions are compared against the available experimental data. The paper proves the reliability and performance of the multidimensional coupling technique in a realistic industrial setting. The results underline the importance of including more physical details into transient thermal modelling of turbine engine components
Association between light exposure and metabolic syndrome in a rural Brazilian town
No full textContext
Metabolic syndrome (MetS) is a complex condition comprising a ‘clustering’ of components representing cardiometabolic risk factors for heart disease and diabetes; its prevalence rate is high and consequences serious. Evidence suggests that light exposure patterns and misalignment of circadian rhythms might contribute to MetS etiology by impacting energy metabolism and glucose regulation.
Objective
We hypothesised that individuals with MetS would show disrupted circadian and sleep parameters alongside differences in light exposure profiles. We investigated this using data from a cohort study in Brazil.
Methods
Data from 103 individuals from the Baependi Heart Cohort Study aged between 50 and 70 were analysed. Motor activity and light exposure were measured using wrist-worn actigraphy devices. Cardiometabolic data were used to calculate the number of MetS components present in each participant, and participants grouped as MetS/non-MetS according to standard guidelines. Between-group comparisons were made for the actigraphy measures; additionally, correlation analyses were conducted.
Results
Motor activity and circadian profiles showed no differences between groups. However, the MetS group presented lower light exposure during the day and higher light exposure at night. Correlation analyses, including all participants, showed that greater daytime light exposure and greater light exposure difference between day and night were associated with reduced MetS risk (a lower number of MetS components). Also, the light exposure difference between day and night correlated with body mass index across all participants.
Conclusions
The observed results suggest a direct association between light exposure and MetS which appears to not be attributable to disruptions in circadian activity rhythm nor to sleep parameters. This link between light exposure patterns and MetS risk could inform possible prevention strategies.</p
Heat exchanger network synthesis with detailed exchanger designs: Part 1. A discretized differential algebraic equation model for shell and tube heat exchanger design
No full textA new method for the detailed design of shell and tube heat exchangers is presented through the formulation of coupled differential heat equations, along with algebraic equations for design variables. Heat exchanger design components (tube passes, baffles, and shells) are used to discretize the differential equations and are solved simultaneously with the algebraic design equations. The coupled differential algebraic equation (DAE) system is suitable for numerical optimization as it replaces the nonsmooth log mean temperature difference (LMTD) term. Discrete decisions regarding the number of shells, fluid allocation, tube sizes, and number of baffles are determined by solving an LMTD‐based method iteratively. The resulting heat exchanger topology is then used to discretize the detailed DAE model, which is solved as a nonlinear programming model to obtain the detailed exchanger design by minimizing an economic objective function through varying the tube length. The DAE model also provides the stream temperature profiles inside the exchanger simultaneously with the detailed design. It is observed that the DAE model results are almost equal to the LMTD‐based design model for one‐shell heat exchangers with constant stream properties but shows significant differences when streams properties are allowed to vary with temperature or the number of shells are increased. The accuracy of the solutions and the required computational costs show that the model is well suited for solving heat exchanger network synthesis problems combined with detailed exchanger designs, which is demonstrated in Part 2 of the paper
Feasibility of Prehospital Rapid Sequence Intubation in the Cabin of an AW169 Helicopter
No full textObjective
Prehospital rapid sequence intubation (RSI) is an important aspect of prehospital care for helicopter emergency medical services (HEMS). This study examines the feasibility of in-aircraft (aircraft on the ground) RSI in different simulated settings.
Methods
Using an AW169 aircraft cabin simulator at Air Ambulance Kent Surrey Sussex, 3 clinical scenarios were devised. All required RSI in a “can intubate, can ventilate” (easy variant) and a “can't intubate, can't ventilate” scenario (difficult variant). Doctor-paramedic HEMS teams were video recorded, and elapsed times for prespecified end points were analyzed.
Results
Endotracheal intubation (ETI) was achieved fastest outside the simulator for the easy variant (median = 231 seconds, interquartile range = 28 seconds). Time to ETI was not significantly longer for in-aircraft RSI compared with RSI outside the aircraft, both in the easy (p = .14) and difficult variant (p = .50). Wearing helmets with noise distraction did not impact the time to intubation when compared with standard in-aircraft RSI, both in the easy (p = .28) and difficult variant (p = .24).
Conclusion
In-aircraft, on-the-ground RSI had no significant impact on the time to successful completion of ETI. Future studies should prospectively examine in-cabin RSI and explore the possibilities of in-flight RSI in civilian HEMS services.</p
Yolk-Shell structured NiCo@SiO₂ nanoreactor for CO₂ upgrading via reverse water-gas shift reaction
No full textThis work reports the successful and simplistic synthesis of highly uniform NiCo@SiO₂ yolk@shell catalysts, with their effectiveness towards CO₂ recycling investigated within the RWGS reaction. The engineered microstructure catalysts display high CO₂ conversion levels and a remarkable selectivity for CO as main reaction product across the whole examined temperatures. Interestingly, the selectivity is affected by Ni loading reflecting a close correlation catalytic performance/material structure-composition. Further to this behaviour, the designed nanoreactor exhibits considerable deactivation resistance and performance under reaction cycling conditions and appears to demonstrate the production of larger organic molecules after qualitative analysis of the product gas by mass spectrometry. These results demonstrate the effectiveness of the spatial confinement effect, imbued to the material from its advanced morphology, through its influence of deactivation resistance and control of reactive selectivity
BézierSketch: A generative model for scalable vector sketches
No full textThe study of neural generative models of human sketches is a fascinating contemporary modeling problem due to the links between sketch image generation and the human drawing process. The landmark SketchRNN provided breakthrough by sequentially generating sketches as a sequence of waypoints. However this leads to low-resolution image generation, and failure to model long sketches. In this paper we present B´ezierSketch, a novel generative model for fully vector sketches that are automatically scalable and high-resolution. To this end, we first introduce a novel inverse graphics approach to stroke embedding that trains an encoder to embed each stroke to its best fit B´ezier curve. This enables us to treat sketches as short sequences of paramaterized strokes and thus train a recurrent sketch generator with greater capacity for longer sketches, while producing scalable high-resolution results. We report qualitative and quantitative results on the Quick, Draw! benchmark
International Student Mobility Programs
No full textThis entry discusses programs that support, encourage or administer International Student Mobility (ISM). According to the definition from the Higher Education Funding Council for England (HEFCE, 2004), ISM is “any form of international mobility which takes place within a student’s programme of study in higher education”. ISM programs can refer to supporting outbound students (outward mobility) as well as incoming students from abroad (inward mobility). Students planning a spell abroad can either plan and organize their stay independently (as what are called free movers) or via a student exchange program.
This entry begins by providing an overview of patterns of student mobility, and then describes the role of student mobility programs. ISM includes both short-term study abroad visits as well as long-term study abroad stays for entire degree programs. This entry emphasizes study abroad as a part of a student’s higher education studies (often referred to as credit mobility), rather than completing an entire degree program abroad (degree mobility). In the following, the challenges of evaluating the effect of study abroad programs on subsequent outcomes are discussed. The introduction of the ERASMUS program is considered in light of research that has been undertaken using the launch and growth of the program as opportunities to examine and understand the effects of study abroad participation. The entry discusses the role of student exchanges on subsequent international mobility choices, as well as on subsequent labor market outcomes. It concludes by addressing some key open questions in this area. </p
Dynamic Scheduler Management Using Deep Learning
No full textThe ability to manage the distributed functionality of
large multi-vendor networks will be an important step
towards ultra-dense 5G networks. Managing distributed
scheduling functionality is particularly important, due to its influence over inter-cell interference and the lack of standardization for schedulers. In this paper, we formulate a method of managing distributed scheduling methods across a small cluster of cells by dynamically selecting schedulers to be implemented at each cell. We use deep reinforcement learning methods to identify suitable joint scheduling policies, based on the current state of the network observed from data already available in the RAN. Additionally, we also explore three methods of training the deep reinforcement learning based dynamic scheduler selection system. We compare the performance of these training methods in a simulated environment against each other, as well as homogeneous scheduler deployment scenarios, where each cell in the network uses the same type of scheduler. We show that, by using deep reinforcement learning, the dynamic scheduler selection system is able to identify scheduler distributions that increase the number of users that achieve their quality of service requirements in up to 77% of the simulated scenarios when compared to homogeneous scheduler deployment scenarios
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