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1.
Journal of Clinical Epidemiology ; 2023.
Article in English | ScienceDirect | ID: covidwho-2165508

ABSTRACT

Objective This article is part of a series on methods for living guidelines, consolidating practical experiences from developing living guidelines. It focuses on methods for identification, selection, and prioritisation of clinical questions for a living approach to guideline development. Study design and setting Members of the Australian Living Evidence Consortium (ALEC), the National Institute of Health and Care Excellence (NICE) and the US Grading of Recommendations, Assessment, Development and Evaluations (GRADE) Network, convened a working group. All members have expertise and practical experience in the development of living guidelines. We collated methods documents on prioritisation from each organisation's living guidelines, conducted interviews and held working group discussions. We consolidated these to form best-practice principles, which were then edited and agreed on by the working group members. Results We developed best-practice principles for 1) identification, 2) selection, and 3) prioritisation, of questions for a living approach to guideline development. Several different strategies for undertaking prioritising questions are explored. Conclusion The paper provides guidance for prioritising questions in living guidelines. Subsequent papers in this series explore consumer involvement, search decisions, and methods decisions, that are appropriate for questions with different priority levels.

2.
International Journal of Disaster Risk Reduction ; : 103504, 2022.
Article in English | ScienceDirect | ID: covidwho-2165367

ABSTRACT

Social vulnerability and society's resilience are two concepts frequently used to examine the capacity of social systems to prepare, absorb, and adapt to environmental hazards and shocks. With the emergence of the COVID-19 pandemic, the role of social vulnerability in dealing with risks has gained renewed attention. Assessing social vulnerability can help managers and planners prioritize budgets, develop prevention programs, and enhance risk preparedness. This study aimed to determine the association between social vulnerability and COVID-19 in the neighborhoods of Ahvaz, Iran. To assess the social vulnerability of Ahvaz neighborhoods, decision-making techniques (best-worst method and weighted aggregated sum product assessment method) and geographic information systems were applied. Moreover, to investigate the relationship between social vulnerability and COVID-19 cases, the Pearson correlation test was used. The results showed that the ‘20-meteri shahrdari' neighborhood has the highest level of social vulnerability, and the lowest level of social vulnerability among the neighborhoods of Ahvaz belongs to the neighborhood of ‘Shahrak Naft'. There is a low inverse association between the integrated index of social vulnerability and the incidence of COVID-19 per 1000 people in Ahvaz. By revealing the most important details at the neighborhood level and levels of vulnerability, the results can inform effective planning actions at the neighborhood level.

3.
Computers & Industrial Engineering ; : 108943, 2022.
Article in English | ScienceDirect | ID: covidwho-2165160

ABSTRACT

Aiming at the complex and changeable environment and the low public participation in emergency decision-making, this article proposes a method for the dynamic collaboration of the public and experts in large-scale group emergency decision-making (LSGEDM) based on social media data. First, sentiment analysis is carried out on text data from social media platforms to evaluate the quality of LSGEDM at both the attribute and comprehensive levels. Then, according to the decision-making quality at the attribute level, a method for the dynamic updating of attribute weights is proposed. Next, in the social network environment, the trust relationship between experts is dynamically updated based on the comprehensive quality of decision-making and the distance between the expert and group preferences, and expert weights are calculated by the improved PageRank algorithm. Finally, the effectiveness and superiority of the proposed method are verified via its application to the COVID-19 epidemic in China and a comparative analysis.

5.
Vaccines (Basel) ; 10(10)2022 Sep 28.
Article in English | MEDLINE | ID: covidwho-2163650

ABSTRACT

Despite the availability of safe and effective COVID-19 vaccines, vaccine acceptance has been low, particularly among parents. More information is needed on parental decision-making. We conducted a prospective cohort study from October 2021 to March 2022 among 334 parents in a large urban/suburban pediatric primary care network and linked longitudinal survey responses about attitudes and beliefs on vaccination, social norms, and access to vaccination services for COVID-19 to electronic health-record-derived vaccination outcomes for their eldest age-eligible children in June 2022. The odds of accepting two doses of COVID-19 vaccine for their child was higher in respondents who indicated the COVID-19 vaccine would be very safe (aOR [CI]: 2.69 [1.47-4.99], p = 0.001), as well as those who previously vaccinated their child against influenza (aOR [CI]: 4.07 [2.08-8.12], p < 0.001). The odds of vaccinating their child were lower for respondents who attended suburban vs. urban practices (aOR [CI]: 0.38 [0.21-0.67], p = 0.001). Parents in the cohort were active users of social media; the majority (78%) used their phone to check social media platforms at least once per day. Our findings suggest that healthcare providers and policymakers can focus on improving vaccination coverage among children living in suburban neighborhoods through targeted mobile-based messaging emphasizing safety to their parents.

6.
Socioecon Plann Sci ; : 101452, 2022 Oct 19.
Article in English | MEDLINE | ID: covidwho-2159810

ABSTRACT

Since human health greatly depends on a healthy and risk-free social environment, it is very important to have a concept to focus on improving epidemiology capacity and potential along with economic perspectives as a very influential factor in the future of societies. Through responsible behavior during an epidemic crisis, the health system units can be utilized as a suitable platform for sustainable development. This study employs the Best-Worst Method (BWM) in order to develop a system for identifying and ranking health system units with understanding the nature of the epidemic to help the World Health Organization (WHO) in recognizing the capabilities of resilient health system units. The purpose of this study is to identify and prioritize the resilient health system units for dealing with Coronavirus. The statistical population includes 215 health system units in the world and the opinions of twenty medical experts are also utilized as an informative sample to localize the conceptual model of the study and answer the research questionnaires. The resilient health system units of the world are identified and prioritized based on the statistics of "Total Cases", "Total Recovered", "Total Deaths", "Active Cases", "Serious", "Total Tests" and "Day of Infection". The present descriptive cross-sectional study is conducted on Worldometer data of COVID-19 during the period of 17 July 2020 at 8:33 GMT. According to the results, the factors of "Total Cases", "Total Deaths", "Serious", "Active Cases", "Total Recovered", "Total Tests" and "Day of Infection" are among the most effective ones, respectively, in order to have a successful and optimal performance during a crisis. The attention of health system units to the identified important factors can improve the performance of epidemiology system. The WHO should pay more attention to low-resilience health system units in terms of promoting the health culture in crisis management of common viruses. Considering the importance of providing health services as well as their significant effect on the efficiency of the world health system, especially in critical situations, resilience analysis with the possibility of comparison and ranking can be an important step to continuously improve the performance of health system units.

7.
Learn Health Syst ; : e10337, 2022 Sep 20.
Article in English | MEDLINE | ID: covidwho-2157868

ABSTRACT

Introduction: The persisting and evolving COVID-19 pandemic has made apparent that no singular policy of mitigation at a regional, national or global level has achieved satisfactory and universally acceptable results. In the United States, carefully planned and executed pandemic policies have been neither effective nor popular and COVID-19 risk management decisions have been relegated to individual citizens and communities. In this paper, we argue that a more effective approach is to equip and strengthen community coalitions to become local learning health communities (LLHCs) that use data over time to make adaptive decisions that can optimize the equity and well-being in their communities. Methods: We used data from the North Carolina (NC) county and zip code levels from May to August 2020 to demonstrate how a LLHC could use statistical process control (SPC) charts and simple statistical analysis to make local decisions about how to respond to COVID-19. Results: We found many patterns of COVID-19 progression at the local (county and zip code) levels during the same time period within the state that were completely different from the aggregate NC state level data used for policy making. Conclusions: Systematic approaches to learning from local data to support effective decisions have promise well beyond the current pandemic. These tools can help address other complex public health issues, and advance outcomes and equity. Building this capacity requires investment in data infrastructure and the strengthening of data competencies in community coalitions to better interpret data with limited need for advanced statistical expertise. Additional incentives that build trust, support data transparency, encourage truth-telling and promote meaningful teamwork are also critical. These must be carefully designed, contextually appropriate and multifaceted to motivate citizens to create and sustain an effective learning system that works for their communities.

8.
Oncol Ther ; 10(2): 421-440, 2022 Dec.
Article in English | MEDLINE | ID: covidwho-2149018

ABSTRACT

INTRODUCTION: Treatment decisions in older adults with acute myeloid leukemia (AML) are challenging, particularly for those who are not candidates for intensive chemotherapy (IC), and the trade-offs patients, their families and physicians consider when choosing a treatment option are not well understood. This qualitative research explored the value of extending survival and the treatment decision-making process from a multi-stakeholder perspective. METHODS: Overall, 28 patients with AML (≥ 65 years old, unsuitable for IC), 25 of their relatives and 10 independent physicians from the US, UK and Canada took part in one-on-one, 60-minute qualitative interviews. RESULTS: Across all stakeholders, improved health-related quality of life (HRQoL), extended survival and relief of AML symptoms were recognized as most important in AML treatment decision-making. However, extending survival in 'good health' was more important than extending survival alone, particularly because of the extra time it gives patients and their relatives together, and allows patients to achieve important goals. Patients' limited understanding of available treatment options, paired with incorrect perceptions of treatment side effects, impacted their involvement in the treatment decision-making process. Patients and physicians perceived physicians to have the most influence in the decision-making process despite their priorities not always aligning. CONCLUSION: These findings illustrate the importance of having structured discussions which explicitly assess patients' goals and their understanding and expectations of treatments and also the need for patient friendly resources about the lived experience of AML and available treatment options. These measures will help to ensure that patients are fully involved in the shared decision-making process.

9.
Front Vet Sci ; 9: 911026, 2022.
Article in English | MEDLINE | ID: covidwho-2148130

ABSTRACT

To provide students of veterinary medicine with the necessary day 1 competences, e-learning offerings are increasingly used in addition to classical teaching formats such as lectures. For example, virtual patients offer the possibility of case-based, computer-assisted learning. A concept to teach and test clinical decision-making is the key feature (KF) approach. KF questions consist of three to five critical points that are crucial for the case resolution. In the current study usage, learning success, usability and acceptance of KF cases as neurological virtual patients should be determined in comparison to the long cases format. Elective courses were offered in winter term 2019/20 and summer term 2020 and a total of 38 virtual patients with neurological diseases were presented in the KF format. Eight cases were provided with a new clinical decision-making application (Clinical Reasoning Tool) and contrasted with eight other cases without the tool. In addition to the evaluation of the learning analytics (e.g., processing times, success rates), an evaluation took place after course completion. After 229 course participations (168 individual students and additional 61 with repeated participation), 199 evaluation sheets were completed. The average processing time of a long case was 53 min, while that of a KF case 17 min. 78% of the long cases and 73% of KF cases were successfully completed. The average processing time of cases with Clinical Reasoning Tool was 19 min. The success rate was 58.3 vs. 60.3% for cases without the tool. In the survey, the long cases received a ranking (1 = very good, 6 = poor) of 2.4, while KF cases received a grade of 1.6, 134 of the respondents confirmed that the casework made them feel better prepared to secure a diagnosis in a real patient. Flexibility in learning (n = 93) and practical relevance (n = 65) were the most frequently listed positive aspects. Since KF cases are short and highlight only the most important features of a patient, 30% (n = 70) of respondents expressed the desire for more specialist information. KF cases are suitable for presenting a wide range of diseases and for training students' clinical decision-making skills. The Clinical Reasoning Tool can be used for better structuring and visualizing the reasoning process.

10.
Journal of Small Business Strategy ; 32(4):30-47, 2022.
Article in English | ProQuest Central | ID: covidwho-2164875

ABSTRACT

The goals of this study are to explore the use of the Management Control Systems (MCS) by SMEs' managers at the country level in order to identify the importance given to financial and nonfinancial measures, as well as key performance indicators. In this study, we use the behavioral accounting lens and adopt mixed methods approach to study the use of the MCS in Portuguese small to medium enterprises (SMEs): a correlational and a configurational analysis. Data was collected from a cross-sectional survey of 414 top managers of Portuguese SMEs across several industries. The results show that managers' perceptions of the importance given to financial measures is positively and significantly related to the importance given to several nonfinancial measures. We take an original approach by addressing the managers' perceptions to contribute to the understanding of Portuguese SMEs' use of tools for strategy implementation: the use of different MCS. Additionally, the study discovers alternative configurations of individual and organizational conditions that lead to the managers' perception of the importance given to financial and nonfinancial measures. This paper offers support for SMEs based on controlling strategy implementation by using MCS. The study's limitations regard a relatively low response rate to the questionnaire (4.56%), which may be justified because data was collected during the COVID-19 pandemic. We offer alternative configurations that generate the perception of managers about the importance of using financial and nonfinancial measures. Our results enlighten the use of such tools in support of strategic accomplishment.

11.
Journal of Pharmaceutical Negative Results ; 13(3):339-354, 2022.
Article in English | EMBASE | ID: covidwho-2164804

ABSTRACT

COVID-19 respiratory viral disease has changed the entire research communities' focus towards Diseases, Health Care, Treatment and related resources decision making and services. Fuzzy approach gives simplification and improvement in processing logic and speed applied to Data analytics and testing of algorithm for different business purposes may be future research domain. Significant COVID-19 analytics can help to classify and prioritize the resources the future consequences to take enhanced self-ruled decisions, to recognise and design pattern in data spread to design strategic policies for medical, health care units and stakeholders. Copyright © 2022 Wolters Kluwer Medknow Publications. All rights reserved.

12.
Scientific Papers of the University of Pardubice-Series D-Faculty of Economics and Administration ; 29(1), 2021.
Article in English | Web of Science | ID: covidwho-2164757

ABSTRACT

The emergence and spreading of COVID-19 pandemic were surprising and sudden. It caused the need for competent crisis management throughout the public administration to manage the initial stage of the crisis. The purpose of our research is to identify the connection between the competencies of crisis management in self-governments and employee performance, measured at the time of the initial stage of the crisis, by their feeling of satisfaction, safety and establishment of conditions for work. In this research report, we expect these variables to be connected via the sharing of information, teamwork and cognitive diversity of work teams. The research used the mediator model according to Baron and Kenny. Sobel's test was used to test the mediator effect. Regression analysis was used to verify the hypotheses. The ANOVA variance analysis was used to analyze multiple dependency. The level of significance was 5%. The research sample consisted of 207 managers in self-government organizations operating in Slovakia. The hypothesis on the dependency between the crisis management competencies and team performance during the initial stage of the crisis, facilitated by sharing of information, teamwork and cognitive diversity of crisis management, was confirmed.

13.
European Journal of Interdisciplinary Studies ; 14(2):1-23, 2022.
Article in English | ProQuest Central | ID: covidwho-2164563

ABSTRACT

In early 2020, many widespread restrictive measures were introduced worldwide in response to the COVID-19 pandemic. These measures entailed high socio-economic costs, which have been largely overlooked due to political motivations and the difficulty of their measurement. One of them is the negative impact of widespread restrictive measures on life expectancy due to the limited school attendance and the negative impact of restrictions on the population's health status. In this paper, we use our own structural model based on the trade-off analysis method. The research compares the lost years of life in the situation of the existence of restrictive measures and, on the contrary, the situation of a complete absence of these measures. We use data from the Czech Republic between February 2020 and October 2021. Our article concludes that the number of lost years of life is many times higher when widespread restrictive measures are implemented in all considered scenarios. These findings should be considered when making further decisions on applying widespread restrictive measures in the Czech Republic.

14.
Frontiers in Psychology ; 13, 2022.
Article in English | Web of Science | ID: covidwho-2163110

ABSTRACT

BackgroundWith the COVID-19 pandemic, healthcare professionals, especially nurses, are confronted with an intensified workload. The literature on compulsory citizenship behaviors and their consequences is still far from explaining the cognitive and emotional mechanisms that underlie this relationship. MethodsDrawing on the resource depletion theory, we unpack the mechanism by which compulsory citizenship behaviors influence moral disengagement with the mediation effects of anger toward the organization. We are reporting a cross-sectional survey of nurses (n = 294) in private and public hospitals in Istanbul, Turkey. The data analysis involved structural equation modeling and Bayesian mediation. ResultsThe study revealed that compulsory citizenship behaviors positively influenced anger toward the organization and moral disengagement. Further, anger toward the organization mediates the link between compulsory citizenship behaviors and moral disengagement. Likewise, the Bayesian mediation analysis indicated that the proportion mediated (PM), which ensures a prediction of the extent to which the pathway explains the total effect through the mediation effect, was 33.74%. ConclusionThe findings show that exposure to compulsory citizenship behaviors lead to negative emotional (anger toward to organization) and cognitive (moral disengagement) consequences in nurses. Practical implicationsHospital managers should not force nurses to display discretionary work tasks outside their job descriptions. Providing an organizational milieu where voluntarily extra-role behaviors are encouraged may help reduce nurses' moral disengagement and, in turn, ease their anger toward the organization.

15.
Abu Dhabi International Petroleum Exhibition and Conference 2022, ADIPEC 2022 ; 2022.
Article in English | Scopus | ID: covidwho-2162740

ABSTRACT

Oil and Gas industry is seeking new ways to improve efficiencies, reducing operating costs and increasing revenues in the current volatile market conditions. Data Science and all the new emerging technologies enable the discovery of new opportunities and digitalization is a vital element for making business more effective and efficient. While COVID19 has disrupted the world, ADNOC Onshore has recognized the importance of reskilling and empowering the future workforce through strategic enterprise data science and analytics program to achieve 2030 smart growth strategy. This paper talks about successful approach and enablers for development of in-house capability for transformation that lead to generating significant business value The digital transition can pose both challenges and opportunities in this transformation. ADNOC ONSHORE has developed an integrated framework to encourage and accelerate data science capabilities. This framework promotes a vision with collaborative, sustainable mechanisms to develop talent. It is not just the formal learning and additional professional qualification that make it possible to build this in house capability. There are five major areas are enabled this framework such as data science & analytics skills competency model, sustainable on-line collaborative learning program, organizational culture change, democratizing AI through open platform & a digital business model for performing real business problems/use case PoCs. Each area has a detailed program and execution strategy with a collaborative effort from technical and non-technical stakeholders. ADNOC ONSHORE has successfully implemented this framework and able to certify 20 employees as part of this program. The Data Science Competency Model identified and defined the skills required to be successful within the enterprise with a clear learning path and mentorship. The leadership played a pivotal role to encourage data driven decision making and predictive capabilities in addition to executive awareness to lead the change with clear performance indicators. By democratizing AI platform across upstream user community, six real business cases have been successfully developed with clear business value in subsurface and production workflows according to the defined digital business model. The successful business cases have improved efficiency by 75% in performing cement & corrosion log interpretation & well portfolio optimization. Data driven analytics have been evaluated in subsurface workflows such as infill location optimization, gas-lift candidate identification and they have complemented the existing techniques. The framework has been successfully extended to other group companies in ADNOC. The rapid growth of AI in business in the last five years presents an opportunity for oil and gas professionals for enhancing the skills and transformation. This paper talks about an integrated framework, learning path, democratizing AI, engagement of leadership, digital business model for business case evaluation by applying agile way of working and sustainable value creation. Copyright © 2022, Society of Petroleum Engineers.

16.
European Psychiatry ; 65(Supplement 1):S62, 2022.
Article in English | EMBASE | ID: covidwho-2162457

ABSTRACT

All healthcare had to rapidly adjust to covid-19;remote options were implemented at pace and unnecessary face to face contact minimised, with infection prevention and control taking primacy. Many research projects were suspended and some clinical researchers moved to frontline care. For psychiatric academic trainees, covid-19 affected recruitment, and risked delaying work on research degrees such as PhDs, potentially beyond the timeframe of a grant, leading to funding uncertainties. Those valuable casual conversations with senior colleagues in the cafe stopped and with many schools closed, parents had extra pressures on their time at home. In the UK the government prioritised "Urgent Public Health" (UPH) studies and took a co-ordinated approach to research approvals and recruitment strategies, contributing to the success of covid-19 platform trials such as RECOVERY. While initially only a minority of UPH studies were open to people with serious mental illnesses, now the effect of the pandemic on mental health has become a research priority. In parallel, service planners recognised the value of emergent research in informing decision-making creating de facto learning health systems. While covid-19 interrupted research as we knew it, it necessitated new ways of working, some of which will persist. These included an increase in remote data collection, allowing greater access to research opportunities for potential participants, along with more efficient research approval and evidence dissemination pathways.

17.
Journal of Function Spaces ; 2022, 2022.
Article in English | ProQuest Central | ID: covidwho-2162044

ABSTRACT

The purpose of aggregation methods is to convert a list of objects of a set into a single object of the same set usually by an n-arry function, so-called aggregation operator. The key features of this work are the aggregation operators, because they are based on a novel set called Fermatean cubic fuzzy set (F-CFS). F-CFS has greater spatial scope and can deal with more ambiguous situations where other fuzzy set extensions fail to support them. For this purpose, the notion of F-CFS is defined. F-CFS is the transformation of intuitionistic cubic fuzzy set (I-CFS), Pythagorean cubic fuzzy set (P-CFS), interval-valued cubic fuzzy set, and basic orthopair fuzzy set and is grounded on the constraint that "the cube of the supremum of membership plus nonmembership degree is ≤1”. We have analyzed some properties of Fermatean cubic fuzzy numbers (F-CFNs) as they are the alteration of basic properties of I-CFS and P-CFS. We also have defined the score and deviation degrees of F-CFNs. Moreover, the distance measuring function between two F-CFNs is defined which shows the space between two F-CFNs. Based on this notion, the aggregation operators namely Fermatean cubic fuzzy-weighted averaging operator (F-CFWA), Fermatean cubic fuzzy-weighted geometric operator (F-CFWG), Fermatean cubic fuzzy-ordered-weighted averaging operator (F-CFOWA), and Fermatean cubic fuzzy-ordered-weighted geometric operator (F-CFOWG) are developed. Furthermore, the notion is applied to multiattribute decision-making (MADM) problem in which we presented our objectives in the form of F-CFNs to show the effectiveness of the newly developed strategy.

18.
2nd International Conference on Engineering and Information Technology for Sustainable Industry, ICONETSI 2022 ; 2022.
Article in English | Scopus | ID: covidwho-2162021

ABSTRACT

COVID-19 pandemic has changed the economic weather and business performance in multiple streams. The uncertainty condition caused by the pandemic needs to be carefully taken care by all companies and organizations due to rapid consumer trend shifting and volatile market condition. The sales and marketing strategy needs to be carefully taken during organizational decision-making process to avoid further loss. PT XYZ as one of the leading consumer goods in beauty industry experiences the same condition and challenge reflected by down-trend in the organization KPI. This research aims to introduce and provide predictive data analytics tools for enhancing sales forecast by comparing Random Forest and Neural Network as part of machine learning methods also Vector Autoregression (VAR) as conventional statistical forecasting methodology. As the result of this research, neural network returns better evaluation for skin care and Vector Autoregression for makeup category. Meanwhile data visualization is found necessary to provide additional factual information, includes the external factor, to support knowledge management for better rational decision-making process. © 2022 ACM.

19.
Risk Anal ; 2022.
Article in English | PubMed | ID: covidwho-2161750

ABSTRACT

The COVID-19 pandemic presented serious risks to the health and financial wellbeing of millions of people across the world. While many individuals adapted to these challenges through a variety of prosocial and protective behaviors (e.g., social distancing, working from home), many others also engaged in dishonest behaviors (e.g., lying to obtain vaccines or furlough payments). Hence, the COVID-19 pandemic provided a unique context in which to obtain a better understanding of the relationship between risk and dishonesty. Across three preregistered studies, we assessed whether objective risk and perceived risk influenced the decision to behave dishonestly in order to gain access to vaccines and furlough payments during a pandemic. We also assessed the extent to which such dishonesty was deterred by the probability of the dishonesty being detected. We found that heightened health risk perceptions were positively related with lying to obtain a vaccine (Studies 1 and 2), but found no evidence of the same relationship between financial risk perceptions and lying to access furlough payments (Study 2). We also found that the probability of dishonesty being detected had a negative relationship with dishonest behavior (Study 3). In addition, across the three studies, we found that (i) dishonesty was consistently evident in approximately one-third of all of our samples, and (ii) greater dishonesty was associated with older age. We discuss how our findings could be utilized by policy makers to better deter and detect dishonest behaviors during future similar crises.

20.
4th International Conference on Pattern Analysis and Intelligent Systems, PAIS 2022 ; 2022.
Article in English | Scopus | ID: covidwho-2161479

ABSTRACT

Since the start of coronavirus pandemic (COVID-19), remote collaboration is increasingly becoming an important requirement in the healthcare sector. This is due to the fact that new information and communication technologies (ITC) can offer more flexibility in time and space. Therefore, we present in this paper a virtual environment that aims to support remote collaborative medical diagnosis. This proposal is mainly based on cognitive studies carried out in the medical field. Moreover, to support medical decision-making, we have integrated an intelligent system into our virtual environment using deep learning technologies. © 2022 IEEE.

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