scholarly journals TW-SIR: Time-window based SIR for COVID-19 forecasts

2020 ◽  
Author(s):  
Zhifang Liao ◽  
Peng Lan ◽  
Zhingning Liao ◽  
Yan Zhang ◽  
Shengzong Liu
Keyword(s):  
Real Time ◽  
Reproduction Number ◽  
Time Window ◽  
Data Sets ◽  
Machine Learning Method ◽  
The Real ◽  
Multiple Data ◽  
Multiple Data Sets ◽  
Time Changes ◽  
Epidemic Diseases

Abstract Since the outbreak of COVID-19, many COVID-19 research studies have proposed different models for predicting trend of COVID-19. Among them, the prediction model based on mathematical epidemiology (SIR) is the most widely used, but most of these models are adapted in special situations based on various assumptions. In order to reflect the real-time trend of the epidemic in the process of infection for different areas, different policies and different epidemic diseases, a general adapted time- window based SIR model is proposed, which is characterized by introducing a time window mechanism for dynamic data analysis and using machine learning method predicts the Basic reproduction number R0 and the exponential growth rate of the epidemic. Multiple data sets of epidemic diseases are analyzed, and the numerical results showed that the framework can effectively measure the real-time changes of the parameters during the epidemic, and error rate of predicting the number of COVID-19 infections in a single day is within 5%

scholarly journals TW-SIR: time-window based SIR for COVID-19 forecasts

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Zhifang Liao ◽  
Peng Lan ◽  
Zhining Liao ◽  
Yan Zhang ◽  
Shengzong Liu
Keyword(s):  
Prediction Model ◽  
Reproduction Number ◽  
Time Window ◽  
Machine Learning Method ◽  
Exponential Growth Rate ◽  
Learning Method ◽  
Mathematical Epidemiology ◽  
Dynamic Data ◽  
Time Changes ◽  
The Basic Reproduction Number

AbstractSince the outbreak of COVID-19, many COVID-19 research studies have proposed different models for predicting the trend of COVID-19. Among them, the prediction model based on mathematical epidemiology (SIR) is the most widely used, but most of these models are adapted in special situations based on various assumptions. In this study, a general adapted time-window based SIR prediction model is proposed, which is characterized by introducing a time window mechanism for dynamic data analysis and using machine learning method predicts the basic reproduction number and the exponential growth rate of the epidemic. We analyzed COVID-19 data from February to July 2020 in seven countries–––China, South Korea, Italy, Spain, Brazil, Germany and France, and the numerical results showed that the framework can effectively measure the real-time changes of the parameters during the epidemic, and error rate of predicting the number of COVID-19 infections in a single day is within 5%.

The development of nurses’ foundational values

2021 ◽  
pp. 096973302110032
Author(s):  
Sastrawan Sastrawan ◽  
Jennifer Weller-Newton ◽  
Gabrielle Brand ◽  
Gulzar Malik
Keyword(s):  
Professional Training ◽  
Reference Points ◽  
Constructivist Grounded Theory ◽  
Professional Values ◽  
Data Sets ◽  
Value System ◽  
Institutional Values ◽  
Multiple Data ◽  
Human Ethics ◽  
Multiple Data Sets

Background: In the ever-changing and complex healthcare environment, nurses encounter challenging situations that may involve a clash between their personal and professional values resulting in a profound impact on their practice. Nevertheless, there is a dearth of literature on how nurses develop their personal–professional values. Aim: The aim of this study was to understand how nurses develop their foundational values as the base for their value system. Research design: A constructivist grounded theory methodology was employed to collect multiple data sets, including face-to-face focus group and individual interviews, along with anecdote and reflective stories. Participants and research context: Fifty-four nurses working across various nursing settings in Indonesia were recruited to participate. Ethical considerations: Ethics approval was obtained from the Monash University Human Ethics Committee, project approval number 1553. Findings: Foundational values acquisition was achieved through family upbringing, professional nurse education and organisational/institutional values reinforcement. These values are framed through three reference points: religious lens, humanity perspective and professionalism. This framing results in a unique combination of personal–professional values that comprise nurses’ values system. Values are transferred to other nurses either in a formal or informal way as part of one’s professional responsibility and customary social interaction via telling and sharing in person or through social media. Discussion: Values and ethics are inherently interweaved during nursing practice. Ethical and moral values are part of professional training, but other values are often buried in a hidden curriculum, and attained and activated through interactions during nurses’ training. Conclusion: Developing a value system is a complex undertaking that involves basic social processes of attaining, enacting and socialising values. These processes encompass several intertwined entities such as the sources of values, the pool of foundational values, value perspectives and framings, initial value structures, and methods of value transference.

scholarly journals Evaluation of daily precipitation statistics and monsoon onset/retreat over western Sahel in multiple data sets

2014 ◽  
Vol 45 (5-6) ◽  
pp. 1325-1354 ◽  
Author(s):  
Emilia Paula Diaconescu ◽  
Philippe Gachon ◽  
John Scinocca ◽  
René Laprise
Keyword(s):  
Daily Precipitation ◽  
Monsoon Onset ◽  
Data Sets ◽  
Multiple Data ◽  
Western Sahel ◽  
Multiple Data Sets

Can earning much lead to doing good? Firm performance implications for corporate social responsibility

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Siyu Hou ◽  
Zhaoyang Guo ◽  
Chuangneng Cai ◽  
Xiaobo Jiao
Keyword(s):  
Corporate Social Responsibility ◽  
Firm Performance ◽  
Social Responsibility ◽  
State Ownership ◽  
Data Sets ◽  
Content Type ◽  
Multiple Data ◽  
Instrumental Variable Regression ◽  
Multiple Data Sets ◽  
Corporate Social

Purpose The purpose of this study is to examine the influence of firm performance on corporate social responsibility (CSR) and its possible moderating effect. Despite the significance of CSR, there remains an extensive debate about how it is affected by firm performance. Design/methodology/approach The conceptual model is mainly built on goal-setting theory. Based on archival data from multiple data sets on 1,650 companies, collected from 2010 to 2017, the hypotheses are tested using the two-stage instrumental variable regression method. Findings There is an inverted U-shaped relationship between firm performance and CSR that first increases and then decreases. In addition, considering the boundary conditions, state ownership makes the inverted U-shaped curve steeper, while high executive wage concentration makes the inverted U-shaped curve flatter. Research limitations/implications This study harmonizes the traditional contradictory findings of the influence of firm performance on CSR, that is, it supports a positive, negative or neutral relationship between the two. Originality/value This research provides a necessary structure for the CSR literature. By delving deeply into the relationship between firm performance and CSR, it enables scholars to better address the critical management question of whether earning more will lead to doing good.

Assimilation of multiple data sets with the ensemble Kalman filter to improve forecasts of forest carbon dynamics

2011 ◽  
Vol 21 (5) ◽  
pp. 1461-1473 ◽  
Author(s):  
Chao Gao ◽  
Han Wang ◽  
Ensheng Weng ◽  
S. Lakshmivarahan ◽  
Yanfen Zhang ◽  
...  
Keyword(s):  
Kalman Filter ◽  
Ensemble Kalman Filter ◽  
Carbon Dynamics ◽  
Forest Carbon ◽  
Data Sets ◽  
Multiple Data ◽  
Multiple Data Sets
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