scholarly journals A Two-Phase Stochastic Dynamic Model for COVID-19 Mid-Term Policy Recommendations in Greece: A Pathway towards Mass Vaccination

2021 ◽  
Vol 18 (5) ◽  
pp. 2497
Author(s):  
Nikolaos P. Rachaniotis ◽  
Thomas K. Dasaklis ◽  
Filippos Fotopoulos ◽  
Platon Tinios
Keyword(s):  
Dynamic Network ◽  
Mass Vaccination ◽  
Stochastic Dynamic ◽  
Second Phase ◽  
Retail Sector ◽  
Baseline Scenario ◽  
Two Phase ◽  
Vaccination Rates ◽  
First Results ◽  
Second Wave

From 7 November 2020, Greece adopted a second nationwide lockdown policy to mitigate the transmission of SARS-CoV-2 (the first took place from 23 March to 4 May 2020), just as the second wave of COVID-19 was advancing, as did other European countries. To secure the full benefits of mass vaccination, which started in early January 2021, it is of utmost importance to complement it with mid-term non-pharmaceutical interventions (NPIs). The objective was to minimize human losses and to limit social and economic costs. In this paper a two-phase stochastic dynamic network compartmental model (a pre-vaccination SEIR until 15 February 2021 and a post-vaccination SVEIR from 15 February 2021 to 30 June 2021) is developed. Three scenarios are assessed for the first phase: (a) A baseline scenario, which lifts the national lockdown and all NPIs in January 2021; (b) a “semi-lockdown” scenario with school opening, partial retail sector operation, universal mask wearing, and social distancing/teleworking in January 2021; and (c) a “rolling lockdown” scenario combining a partial lifting of measures in January 2021 followed by a third nationwide lockdown in February 2021. In the second phase three scenarios with different vaccination rates are assessed. Publicly available data along with some first results of the SHARE COVID-19 survey conducted in Greece are used as input. The results regarding the first phase indicate that the “semi-lockdown” scenario clearly outperforms the third lockdown scenario (5.7% less expected fatalities); the second phase is extremely sensitive on the availability of sufficient vaccine supplies and high vaccination rates.

scholarly journals A two-phase stochastic dynamic model for COVID-19 mid-term policy recommendations in Greece: a pathway towards mass vaccination

2021 ◽  
Author(s):  
Nikolaos P. Rachaniotis ◽  
Tomas K. Dasaklis ◽  
Filippos Fotopoulos ◽  
Platon Tinios
Keyword(s):  
Dynamic Network ◽  
Mass Vaccination ◽  
Stochastic Dynamic ◽  
Second Phase ◽  
Retail Sector ◽  
Baseline Scenario ◽  
Two Phase ◽  
Vaccination Rates ◽  
First Results ◽  
Second Wave

From November 7th, 2020, Greece adopted a second nationwide lockdown policy to mitigate the transmission of SARS-CoV-2 (the first took place from March 23rd till May 4th, 2020), just as the second wave of COVID-19 was advancing, as did other European countries. In the light of the very promising voluntary mass vaccination, which will start in January 2021, it is of utmost importance for the country to plan to complement vaccination with mid-term Non-Pharmaceutical Interventions (NPIs). The objective is to minimize human losses and to limit social and economic costs. In this paper a two-phase stochastic dynamic network compartmental model (a pre-vaccination SEIR until February 15th, 2021 and a post-vaccination SVEIR from February 15th, 2021 to June 30th, 2021) is developed. Three scenarios are assessed in the first phase: (a) a baseline scenario, which lifts the national lockdown and all NPIs on January 2021, (b) a 'semi-lockdown' scenario with school opening, partial retail sector operation, universal mask wearing and social distancing/teleworking on January 2021 and (c) a 'rolling lockdown' scenario combining a partial lifting of measures in January 2021 followed by a third imposed nationwide lockdown in February 2021. In the second phase three scenarios with different vaccination rates are assessed. Publicly available data along with some preliminary first results of the SHARE COVID-19 survey conducted in Greece are used as input. The results regarding the first phase indicate that the 'semi-lockdown' scenario outperforms the third lockdown scenario (5.7% less expected fatalities), whereas in the second phase it is of great importance to ensure a sufficient vaccine supply and high vaccination rates.

Tribological Behavior of Polymers Simulated by Molecular Dynamics

2004 ◽  
Vol 19 (3) ◽  
pp. 851-856 ◽  
Author(s):  
Witold Brostow ◽  
J. Adam Hinze ◽  
Ricardo Simões
Keyword(s):  
Molecular Dynamics ◽  
Liquid Crystalline ◽  
Tribological Behavior ◽  
Polymeric Materials ◽  
Scratch Resistance ◽  
Polymer Surfaces ◽  
Second Phase ◽  
Scratch Testing ◽  
Two Phase ◽  
First Results

Using molecular dynamics to simulate behavior of polymer surfaces during scratch testing, we report the first results of computer simulations of scratch behavior of noncrystals. A previously described procedure for creating realistic polymeric materials on the computer [W. Brostow, A.M. Cunha, and R. Simoes, Mater. Res. Innovat. 7, 19 (2003)] and used until now to simulate mechanical behavior of metals [S. Blonski, W. Brostow, and J. Kubat, Phys. Rev. B 49, 6494 (1994)] and one- and two-phase polymers [W. Brostow, A.M. Cunha, J. Quintanilla, and R. Simoes, Macromol. Theory Simul. 11, 308 (2002); W. Brostow, A.M. Cunha, and R. Simoes, Proc. Ann. Tech. Conf. Soc. Plastics Engrs. 60, 3105 (2002)] was applied. While experiments provide only the macroscopic penetration depth and the recovery (healing) depth, the simulations give the behavior of each macromolecular chain segment at each moment in time. We report results for one-phase polymers and also for systems with varying concentrations of a liquid crystalline (LC) second-phase that acts as a reinforcement. We relate the local structure to scratch resistance and recovery. The orientation of the chemical bonds is a major factor. The presence of a LC phase improves the tribological properties; however, the effect is not as significant as might have been expected.

A Comparison of Tem and Apfim to the Interpretation of Modulated Microstructures

1985 ◽  
Vol 43 ◽  
pp. 70-71
Author(s):  
M.G. Burke ◽  
M.K. Miller
Keyword(s):  
Low Temperature ◽  
Microstructural Characterization ◽  
Superlattice Reflection ◽  
High Volume ◽  
Atom Probe ◽  
Dark Field ◽  
Miscibility Gap ◽  
Second Phase ◽  
Two Phase ◽  
Probe Field

Interpretation of fine-scale microstructures containing high volume fractions of second phase is complex. In particular, microstructures developed through decomposition within low temperature miscibility gaps may be extremely fine. This paper compares the morphological interpretations of such complex microstructures by the high-resolution techniques of TEM and atom probe field-ion microscopy (APFIM).The Fe-25 at% Be alloy selected for this study was aged within the low temperature miscibility gap to form a <100> aligned two-phase microstructure. This triaxially modulated microstructure is composed of an Fe-rich ferrite phase and a B2-ordered Be-enriched phase. The microstructural characterization through conventional bright-field TEM is inadequate because of the many contributions to image contrast. The ordering reaction which accompanies spinodal decomposition in this alloy permits simplification of the image by the use of the centered dark field technique to image just one phase. A CDF image formed with a B2 superlattice reflection is shown in fig. 1. In this CDF micrograph, the the B2-ordered Be-enriched phase appears as bright regions in the darkly-imaging ferrite. By examining the specimen in a [001] orientation, the <100> nature of the modulations is evident.

THE DYNAMIC FRACTURE OF TWO PHASE ALLOYS WITH SECOND PHASE INCLUSIONS

1985 ◽  
Vol 46 (C5) ◽  
pp. C5-251-C5-255
Author(s):  
S. Pytel ◽  
L. Wojnar
Keyword(s):  
Dynamic Fracture ◽  
Second Phase ◽  
Two Phase

Behaviour of air injection nozzles in dissolved air flotation

1995 ◽  
Vol 31 (3-4) ◽  
pp. 25-35 ◽  
Author(s):  
E. M. Rykaart ◽  
J. Haarhoff
Keyword(s):  
Bubble Coalescence ◽  
Second Phase ◽  
Initial Growth ◽  
Two Phase ◽  
Dissolved Air Flotation ◽  
Nozzle Orifice ◽  
Pressure Release ◽  
Air Volume ◽  
Air Flotation ◽  
Dissolved Air

A simple two-phase conceptual model is postulated to explain the initial growth of microbubbles after pressure release in dissolved air flotation. During the first phase bubbles merely expand from existing nucleation centres as air precipitates from solution, without bubble coalescence. This phase ends when all excess air is transferred to the gas phase. During the second phase, the total air volume remains the same, but bubbles continue to grow due to bubble coalescence. This model is used to explain the results from experiments where three different nozzle variations were tested, namely a nozzle with an impinging surface immediately outside the nozzle orifice, a nozzle with a bend in the nozzle channel, and a nozzle with a tapering outlet immediately outside the nozzle orifice. From these experiments, it is inferred that the first phase of bubble growth is completed at approximately 1.7 ms after the start of pressure release.

scholarly journals A novel two-phase cycle algorithm for effective cyber intrusion detection in edge computing

2021 ◽  
Vol 2021 (1) ◽  
Author(s):  
Yiguang Gong ◽  
Yunping Liu ◽  
Chuanyang Yin
Keyword(s):  
Intrusion Detection ◽  
Optimal Parameter ◽  
Edge Computing ◽  
Cloud Services ◽  
Second Phase ◽  
Pareto Optimal ◽  
Two Phase ◽  
Multi Objective ◽  
Phase Cycle ◽  
Positive Rate

AbstractEdge computing extends traditional cloud services to the edge of the network, closer to users, and is suitable for network services with low latency requirements. With the rise of edge computing, its security issues have also received increasing attention. In this paper, a novel two-phase cycle algorithm is proposed for effective cyber intrusion detection in edge computing based on a multi-objective genetic algorithm (MOGA) and modified back-propagation neural network (MBPNN), namely TPC-MOGA-MBPNN. In the first phase, the MOGA is employed to build a multi-objective optimization model that tries to find the Pareto optimal parameter set for MBPNN. The Pareto optimal parameter set is applied for simultaneous minimization of the average false positive rate (Avg FPR), mean squared error (MSE) and negative average true positive rate (Avg TPR) in the dataset. In the second phase, some MBPNNs are created based on the parameter set obtained by MOGA and are trained to search for a more optimal parameter set locally. The parameter set obtained in the second phase is used as the input of the first phase, and the training process is repeated until the termination criteria are reached. A benchmark dataset, KDD cup 1999, is used to demonstrate and validate the performance of the proposed approach for intrusion detection. The proposed approach can discover a pool of MBPNN-based solutions. Combining these MBPNN solutions can significantly improve detection performance, and a GA is used to find the optimal MBPNN combination. The results show that the proposed approach achieves an accuracy of 98.81% and a detection rate of 98.23% and outperform most systems of previous works found in the literature. In addition, the proposed approach is a generalized classification approach that is applicable to the problem of any field having multiple conflicting objectives.

scholarly journals Three-Dimensional Analysis of the In Vivo Motion of Implantable Cardioverter Defibrillator Leads

2021 ◽  
Author(s):  
Tamas Szili-Torok ◽  
Jens Rump ◽  
Torsten Luther ◽  
Sing-Chien Yap
Keyword(s):  
Three Dimensional ◽  
Second Phase ◽  
Two Phase ◽  
Maximum Curvature ◽  
Phase Study ◽  
Absolute Curvature ◽  
Icd Leads ◽  
Lead Testing ◽  
Design And Testing

Abstract Better understanding of the lead curvature, movement and their spatial distribution may be beneficial in developing lead testing methods, guiding implantations and improving life expectancy of implanted leads. Objective The aim of this two-phase study was to develop and test a novel biplane cine-fluoroscopy-based method to evaluate input parameters for bending stress in leads based on their in vivo 3D motion using precisely determined spatial distributions of lead curvatures. Potential tensile, compressive or torque forces were not subjects of this study. Methods A method to measure lead curvature and curvature evolution was initially tested in a phantom study. In the second phase using this model 51 patients with implanted ICD leads were included. A biplane cine-fluoroscopy recording of the intracardiac region of the lead was performed. The lead centerline and its motion were reconstructed in 3D and used to define lead curvature and curvature changes. The maximum absolute curvature Cmax during a cardiac cycle, the maximum curvature amplitude Camp and the maximum curvature Cmax@amp at the location of Camp were calculated. These parameters can be used to characterize fatigue stress in a lead under cyclical bending. Results The medians of Camp and Cmax@amp were 0.18 cm−1 and 0.42 cm−1, respectively. The median location of Cmax was in the atrium whereas the median location of Camp occurred close to where the transit through the tricuspid valve can be assumed. Increased curvatures were found for higher slack grades. Conclusion Our results suggest that reconstruction of 3D ICD lead motion is feasible using biplane cine-fluoroscopy. Lead curvatures can be computed with high accuracy and the results can be implemented to improve lead design and testing.

scholarly journals A Decade in Trying to Increase Hand Hygiene—Finally Success

2020 ◽  
Vol 41 (S1) ◽  
pp. s93-s94
Author(s):  
Linda Huddleston ◽  
Sheila Bennett ◽  
Christopher Hermann
Keyword(s):  
Hand Hygiene ◽  
Hand Hygiene Compliance ◽  
Compliance Rate ◽  
Bloodstream Infections ◽  
Central Line ◽  
Second Phase ◽  
Two Phase ◽  
Hygiene Compliance ◽  
Tract Infections ◽  
The Voice

Background: Over the past 10 years, a rural health system has tried 10 different interventions to reduce hospital-associated infections (HAIs), and only 1 intervention has led to a reduction in HAIs. Reducing HAIs is a goal of nearly all hospitals, and improper hand hygiene is widely accepted as the main cause of HAIs. Even so, improving hand hygiene compliance is a challenge. Methods: Our facility implemented a two-phase longitudinal study to utilize an electronic hand hygiene reminder system to reduce HAIs. In the first phase, we implemented an intervention in 2 high-risk clinical units. The second phase of the study consisted of expanding the system to 3 additional clinical areas that had a lower incidence of HAIs. The hand hygiene baseline was established at 45% for these units prior to the voice reminder being turned on. Results: The system gathered baseline data prior to being turned on, and our average hand hygiene compliance rate was 49%. Once the voice reminder was turned on, hand hygiene improved nearly 35% within 6 months. During the first phase, there was a statistically significant 62% reduction in the average number of HAIs (catheter associated urinary tract infections (CAUTI), central-line–acquired bloodstream infections (CLABSIs), methicillin-resistant Staphylococcus aureus (MRSA), multidrug-resistant organisms (MDROs), and Clostridiodes difficile experienced in the preliminary units, comparing 12 months prior to 12 months after turning on the voice reminder. In the second phase, hand hygiene compliance increased to >65% in the following 6 months. During the second phase, all HAIs fell by a statistically significant 60%. This was determined by comparing the HAI rates 6 months prior to the voice reminder being turned on to 6 months after the voice reminder was turned on. Conclusions: The HAI data from both phases were aggregated, and there was a statistically significant reduction in MDROs by 90%, CAUTIs by 60%, and C. difficile by 64%. This resulted in annual savings >$1 million in direct costs of nonreimbursed HAIs.Funding: NoneDisclosures: None

CLIL as a pathway for cross-curricular and translingual classroom practices: A comparative quantitative study on Scottish and Spanish teachers’ views

2021 ◽  
pp. 136216882110324
Author(s):  
Xabier San Isidro
Keyword(s):  
Conceptual Framework ◽  
Quantitative Study ◽  
Classroom Practice ◽  
Classroom Practices ◽  
Research Tool ◽  
Second Phase ◽  
Integrated Learning ◽  
Two Phase ◽  
Pilot Testing ◽  
Final Questionnaire

Despite the numerous attempts to characterize Content and Language Integrated Learning (CLIL), the specialized literature has shown a dearth of cross-contextual studies on how stakeholders conceptualize classroom practice. This article presents the results of a two-phase comparative quantitative study on teachers’ views on CLIL design, implementation and results in two different contexts, Scotland ( n = 127) and Spain ( n = 186). The first phase focused on the creation, pilot-testing and validation of the research tool. The second phase consisted in administering the final questionnaire and analysing the results. The primary goals were (1) to ascertain whether practitioners’ perceptions on CLIL effects and classroom practices match the topics addressed by research; and (2) to analyse and compare teachers’ views in the two contexts. The study offers interesting insights into the main challenges in integrating language and content. Besides providing a conceptual framework for identifiable classroom practice, findings revealed that both cohorts shared broadly similar perceptions, although the Spanish respondents showed more positive views and significantly higher support for this approach.

scholarly journals XCOVNet: Chest X-ray Image Classification for COVID-19 Early Detection Using Convolutional Neural Networks

2021 ◽  
Author(s):  
Vishu Madaan ◽  
Aditya Roy ◽  
Charu Gupta ◽  
Prateek Agrawal ◽  
Anand Sharma ◽  
...  
Keyword(s):  
Image Classification ◽  
Second Phase ◽  
Two Phase ◽  
X Ray ◽  
The Neural Network ◽  
Rapid Spread ◽  
Chest X Ray ◽  
Polymerase Chain ◽  
Two Phases ◽  
Active Patients

AbstractCOVID-19 (also known as SARS-COV-2) pandemic has spread in the entire world. It is a contagious disease that easily spreads from one person in direct contact to another, classified by experts in five categories: asymptomatic, mild, moderate, severe, and critical. Already more than 66 million people got infected worldwide with more than 22 million active patients as of 5 December 2020 and the rate is accelerating. More than 1.5 million patients (approximately 2.5% of total reported cases) across the world lost their life. In many places, the COVID-19 detection takes place through reverse transcription polymerase chain reaction (RT-PCR) tests which may take longer than 48 h. This is one major reason of its severity and rapid spread. We propose in this paper a two-phase X-ray image classification called XCOVNet for early COVID-19 detection using convolutional neural Networks model. XCOVNet detects COVID-19 infections in chest X-ray patient images in two phases. The first phase pre-processes a dataset of 392 chest X-ray images of which half are COVID-19 positive and half are negative. The second phase trains and tunes the neural network model to achieve a 98.44% accuracy in patient classification.

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