A Two-Step Model of Pattern Acquisition: Application to Tsume-Go

AbstractAccurate and responsive non-invasive temperature measurements are enablers for process monitoring and plant optimization use cases in the context of Industry 4.0. If their performance is proven for large classes of applications, such measurement principles can replace traditional invasive measurements. In this paper we describe a two-step model to estimate the process temperature from a pipe surface temperature measurement. This static case model is compared to and enhanced by computational fluid dynamic (CFD) calculations to predict transient situations. The predictions of the approach are validated by means of controlled experiments in a laboratory environment. The experimental results demonstrate the efficacy of the model, the responsiveness of the pipe surface temperature, and that state of the art industrial non-invasive sensors can achieve the performance of invasive thermowells. The non-invasive sensors are then used to demonstrate the performance of the model in industrial applications for cooling fluids and steam.

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A Multi‐Step Model of Parkinson's Disease Pathogenesis

Movement Disorders ◽

10.1002/mds.28719 ◽

2021 ◽

Author(s):

Campbell Le Heron ◽

Michael MacAskill ◽

Deborah Mason ◽

John Dalrymple‐Alford ◽

Tim Anderson ◽

...

Keyword(s):

Parkinson’S Disease ◽

Parkinson's Disease ◽

Disease Pathogenesis ◽

Step Model

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Predicting drowning from sea and weather forecasts: development and validation of a model on surf beaches of southwestern France

Injury Prevention ◽

10.1136/injuryprev-2020-044092 ◽

2021 ◽

pp. injuryprev-2020-044092

Author(s):

Éric Tellier ◽

Bruno Simonnet ◽

Cédric Gil-Jardiné ◽

Marion Lerouge-Bailhache ◽

Bruno Castelle ◽

...

Keyword(s):

Regression Models ◽

Area Under The Curve ◽

Temperature Wave ◽

Medical Emergency ◽

Emergency Center ◽

Logistic Regression Models ◽

Weather Forecasts ◽

Step Model ◽

Daily Risk ◽

Development And Validation

ObjectiveTo predict the coast-wide risk of drowning along the surf beaches of Gironde, southwestern France.MethodsData on rescues and drownings were collected from the Medical Emergency Center of Gironde (SAMU 33). Seasonality, holidays, weekends, weather and metocean conditions were considered potentially predictive. Logistic regression models were fitted with data from 2011 to 2013 and used to predict 2015–2017 events employing weather and ocean forecasts.ResultsAir temperature, wave parameters, seasonality and holidays were associated with drownings. Prospective validation was performed on 617 days, covering 232 events (rescues and drownings) reported on 104 different days. The area under the curve (AUC) of the daily risk prediction model (combined with 3-day forecasts) was 0.82 (95% CI 0.79 to 0.86). The AUC of the 3-hour step model was 0.85 (95% CI 0.81 to 0.88).ConclusionsDrowning events along the Gironde surf coast can be anticipated up to 3 days in advance. Preventative messages and rescue preparations could be increased as the forecast risk increased, especially during the off-peak season, when the number of available rescuers is low.

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Fractional parabolic two-step model and its accurate numerical scheme for nanoscale heat conduction

Journal of Computational and Applied Mathematics ◽

10.1016/j.cam.2020.112812 ◽

2020 ◽

Vol 375 ◽

pp. 112812

Author(s):

Shujun Shen ◽

Weizhong Dai ◽

Jinfa Cheng

Keyword(s):

Heat Conduction ◽

Numerical Scheme ◽

Step Model

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Reaching the summit of discharge summaries: a quality improvement project

BMJ Open Quality ◽

10.1136/bmjoq-2020-001142 ◽

2021 ◽

Vol 10 (1) ◽

pp. e001142

Author(s):

Richard Thomas Richmond ◽

Isobel Joy McFadzean ◽

Pramodh Vallabhaneni

Keyword(s):

Quality Improvement ◽

Health And Safety ◽

Improve Patient Care ◽

Discharge Summary ◽

Shop Floor ◽

Junior Doctors ◽

Improvement Project ◽

Step Model ◽

Assessment Unit ◽

Discharge Summaries

BackgroundDischarge summaries need to be completed in a timely manner, to improve communication between primary and secondary care, and evidence suggests that delays in discharge summary completion can lead to patient harm.Following a hospital health and safety review due to the sheer backlog of notes in the doctor’s room and wards, urgent action had to be undertaken to improve the discharge summary completion process at our hospital’s paediatric assessment unit. It was felt that the process would best be carried out within a quality improvement (QI) project.MethodsKotter’s ‘eight-step model for change’ was implemented in this QI project with the aim to clear the existing backlog of pending discharge summaries and improve the timeliness of discharge summary completion from the hospital’s paediatric assessment unit. A minimum target of 10% improvement in the completion rate of discharge summaries was set as the primary goal of the project.ResultsFollowing the implementation of the QI processes, we were able to clear the backlog of discharge summaries within 9 months. We improved completion within 24 hours, from <10% to 84%, within 2 months. The success of our project lies in the sustainability of the change process; to date we have consistently achieved the target completion rates since the inception of the project. As a result of the project, we were able to modify the junior doctor rota to remove discharge summary duty slots and bolster workforce on the shop floor. This is still evident in November 2020, with consistently improved discharge summary rates.ConclusionQI projects when conducted successfully can be used to improve patient care, as well as reduce administrative burden on junior doctors. Our QI project is an example of how Kotter’s eight-step model for change can be applied to clinical practice.

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