scholarly journals Novel Indicator to Ascertain the Status and Trend of COVID-19 Spread: Modeling Study (Preprint)

2020 ◽  
Author(s):  
Takashi Nakano ◽  
Yoichi Ikeda
Keyword(s):  
Early Stage ◽  
Logarithmic Derivative ◽  
Current Status ◽  
Difference Approximation ◽  
Time Interval ◽  
Cumulative Number ◽  
Infected People ◽  
Linear Decrease ◽  
Wide Range ◽  
The Status

BACKGROUND In the fight against the pandemic of COVID-19, it is important to ascertain the status and trend of the infection spread quickly and accurately. OBJECTIVE The purpose of our study is to formulate a new and simple indicator that represents the COVID-19 spread rate by using publicly available data. METHODS The new indicator <i>K</i> is a backward difference approximation of the logarithmic derivative of the cumulative number of cases with a time interval of 7 days. It is calculated as a ratio of the number of newly confirmed cases in a week to the total number of cases. RESULTS The analysis of the current status of COVID-19 spreading over countries showed an approximate linear decrease in the time evolution of the <i>K</i> value. The slope of the linear decrease differed from country to country. In addition, it was steeper for East and Southeast Asian countries than for European countries. The regional difference in the slope seems to reflect both social and immunological circumstances for each country. CONCLUSIONS The approximate linear decrease of the <i>K</i> value indicates that the COVID-19 spread does not grow exponentially but starts to attenuate from the early stage. The <i>K</i> trajectory in a wide range was successfully reproduced by a phenomenological model with the constant attenuation assumption, indicating that the total number of the infected people follows the Gompertz curve. Focusing on the change in the value of <i>K</i> will help to improve and refine epidemiological models of COVID-19.

scholarly journals Novel Indicator to Ascertain the Status and Trend of COVID-19 Spread: Modeling Study

10.2196/20144 ◽  
2020 ◽  
Vol 22 (11) ◽  
pp. e20144
Author(s):  
Takashi Nakano ◽  
Yoichi Ikeda
Keyword(s):  
Early Stage ◽  
Logarithmic Derivative ◽  
Current Status ◽  
Difference Approximation ◽  
Time Interval ◽  
Cumulative Number ◽  
K Value ◽  
Linear Decrease ◽  
Wide Range ◽  
The Status

Background In the fight against the pandemic of COVID-19, it is important to ascertain the status and trend of the infection spread quickly and accurately. Objective The purpose of our study is to formulate a new and simple indicator that represents the COVID-19 spread rate by using publicly available data. Methods The new indicator K is a backward difference approximation of the logarithmic derivative of the cumulative number of cases with a time interval of 7 days. It is calculated as a ratio of the number of newly confirmed cases in a week to the total number of cases. Results The analysis of the current status of COVID-19 spreading over countries showed an approximate linear decrease in the time evolution of the K value. The slope of the linear decrease differed from country to country. In addition, it was steeper for East and Southeast Asian countries than for European countries. The regional difference in the slope seems to reflect both social and immunological circumstances for each country. Conclusions The approximate linear decrease of the K value indicates that the COVID-19 spread does not grow exponentially but starts to attenuate from the early stage. The K trajectory in a wide range was successfully reproduced by a phenomenological model with the constant attenuation assumption, indicating that the total number of the infected people follows the Gompertz curve. Focusing on the change in the value of K will help to improve and refine epidemiological models of COVID-19.

Recombination-enhanced Dislocation Glides—The Current Status of Knowledge

2009 ◽  
Vol 1195 ◽  
Author(s):  
Koji Maeda
Keyword(s):  
Research Progress ◽  
Current Status ◽  
Bipolar Devices ◽  
Wide Range ◽  
Material Systems ◽  
The Status

AbstractTo update the status of knowledge on the recombination-enhanced dislocation glides (REDG) in semiconductors, which is one of the causes of serious degradation in bipolar devices, research progress achieved for the last decade has been surveyed. Rather than presenting a complete review over a wide range of material systems, a particular attention has been paid to the REDG effect in 4H-SiC for which a lot of information has been accumulated owing to extensive studies. Although the REDG effect exhibits features that could be interpreted in terms of the phonon-kick mechanism, conclusive proof is still lacking.

Recombination-enhanced Dislocation Glides—The Current Status of Knowledge

2009 ◽  
Vol 1195 ◽  
Author(s):  
Koji Maeda
Keyword(s):  
Research Progress ◽  
Current Status ◽  
Bipolar Devices ◽  
Wide Range ◽  
Material Systems ◽  
The Status

AbstractTo update the status of knowledge on the recombination-enhanced dislocation glides (REDG) in semiconductors, which is one of the causes of serious degradation in bipolar devices, research progress achieved for the last decade has been surveyed. Rather than presenting a complete review over a wide range of material systems, a particular attention has been paid to the REDG effect in 4H-SiC for which a lot of information has been accumulated owing to extensive studies. Although the REDG effect exhibits features that could be interpreted in terms of the phonon-kick mechanism, conclusive proof is still lacking.

scholarly journals Revisiting the configurationality issue in Old Icelandic

2021 ◽  
Author(s):  
Hannah Booth
Keyword(s):  
Word Order ◽  
Early Stage ◽  
Functional Grammar ◽  
Old Icelandic ◽  
Modern Language ◽  
Lexical Functional Grammar ◽  
Wide Range ◽  
The Status ◽  
Corpus Data

The status of Old Icelandic with respect to (argument) configurationality was subject to debate in the early 1990s (e.g. Faarlund 1990; Rögnvaldsson 1995) and remains unresolved. Since this work, further research on a wide range of languages has enhanced our understanding of configurationality, in particular within Lexical Functional Grammar (e.g. Austin & Bresnan 1996; Nordlinger 1998) and syntactically annotated Old Icelandic data are now available (Wallenberg et al. 2011). It is thus fitting to revisit the matter. In this paper, I show that allowing for argument configurationality as a gradient property, and also taking into account discourse configurationality (Kiss 1995) as a further gradient property, can neatly account for word order patterns in this early stage of Icelandic. Specifically, I show that corpus data supports part of the original claim in Faarlund (1990), that Old Icelandic lacks a VP-constituent, thus being somewhat less argument-configurational than the modern language. Furthermore, the observed word order patterns indicate a designated topic position in the postfinite domain, thus reflecting some degree of discourse configurationality at this early stage of the language.

scholarly journals Graphene-based biosensors

2018 ◽  
Vol 8 (3) ◽  
pp. 20160132 ◽  
Author(s):  
Sabine Szunerits ◽  
Rabah Boukherroub
Keyword(s):  
Biological Samples ◽  
Early Stage ◽  
Point Of Care ◽  
High Surface ◽  
Volume Ratio ◽  
Wide Range ◽  
The Status ◽  
Delays In Diagnosis ◽  
Short Time ◽  
Sensor Interfaces

Reliable data obtained from analysis of DNA, proteins, bacteria and other disease-related molecules or organisms in biological samples have become a fundamental and crucial part of human health diagnostics and therapy. The development of non-invasive tests that are rapid, sensitive, specific and simple would allow patient discomfort to be prevented, delays in diagnosis to be avoided and the status of a disease to be followed up. Bioanalysis is thus a progressive discipline for which the future holds many exciting opportunities. The use of biosensors for the early diagnosis of diseases has become widely accepted as a point-of-care diagnosis with appropriate specificity in a short time. To allow a reliable diagnosis of a disease at an early stage, highly sensitive biosensors are required as the corresponding biomarkers are generally expressed at very low concentrations. In the past 50 years, various biosensors have been researched and developed encompassing a wide range of applications. This contrasts the limited number of commercially available biosensors. When it comes to sensing of biomarkers with the required picomolar (pM) sensitivity for real-time sensing of biological samples, only a handful of sensing systems have been proposed, and these are often rather complex and costly. Lately, graphene-based materials have been considered as superior over other nanomaterials for the development of sensitive biosensors. The advantages of graphene-based sensor interfaces are numerous, including enhanced surface loading of the desired ligand due to the high surface-to-volume ratio, excellent conductivity and a small band gap that is beneficial for sensitive electrical and electrochemical read-outs, as well as tunable optical properties for optical read-outs such as fluorescence and plasmonics. In this paper, we review the advances made in recent years on graphene-based biosensors in the field of medical diagnosis.

scholarly journals Proinnovative Policy and the National Innovation System a case study from Poland

2014 ◽  
Vol 8 (1) ◽  
pp. 11-40
Author(s):  
Leszek Kwieciński
Keyword(s):  
Early Stage ◽  
Innovation System ◽  
Functional System ◽  
National Innovation System ◽  
Current Status ◽  
Public And Private ◽  
Holistic Management ◽  
Stage Of Development ◽  
Multi Stage ◽  
Wide Range

Abstract The article explores the main elements of the creation a proinnovation policy in Poland as a new case of public policy. It analyses the current status of proinnovation policy in Poland and the relationships implicit in the Polish National Innovation System. The findings support the conclusion that Polish proinnovation policy and the system through which it is enacted are at an early stage of development which is characteristic of co-called ‘catching-up’ countries. The findings show that there is a need for the strategic and holistic management of this type of sub-functional system to enable it to support SMEs in the development of their capacity for innovation. This should include a wide range of public and private institutions in the context of multi-stage governance.

scholarly journals Analysing and comparing the COVID-19 data: The closed cases of Hubei and South Korea, the dark March in Europe, the beginning of the outbreak in South America

2020 ◽  
Author(s):  
Stefano De Leo ◽  
Gabriel G. Maia ◽  
Leonardo Solidoro
Keyword(s):  
South America ◽  
South Korea ◽  
Early Stage ◽  
Spreading Rate ◽  
European Countries ◽  
Time Interval ◽  
Angular Coefficient ◽  
Infected People ◽  
Time Integral ◽  
Fitting Parameters

The present work is a statistical analysis of the COVID-19 pandemic. As the number of cases worldwide overtakes one million, data reveals closed outbreaks in Hubei and South Korea, with a new slight increase in the number of infected people in the latter. Both of these countries have reached a plateau in the number of Total Confirmed Cases per Million (TCCpM) residents, suggesting a trend to be followed by other affected regions. Using Hubei’s data as a basis of analysis, we have studied the spreading rate of COVID-19 and modelled the epidemic center for 10 European countries. We have also given the final TCCpM curves for Italy and Lombardia. The introduction of the α-factor allows us to analyse the different stages of the outbreak, compare the European countries amongst each other, and, finally, to confront the initial phase of the disease between Europe and South America.MethodsBy dividing the TCCpM curves in multiple sections spanning short time frames we were able to fit each section to a linear model. By pairing then the angular coefficient (α factor) of each section to the total number of confirmed infections at the center of the corresponding time interval, we have analysed how the spreading rate of Covid-19 changes as more people are infected. Also, by modelling the TCCpM curves with an asymmetrical time integral of a Normal Distribution, we were able to study, by fitting progressively larger data ensembles, how the fitting parameters change as more data becomes available.FindingsThe data analysis shows that the spreading rate of COVID-19 increases similarly for all countries in its early stage, but changes as the number of TCCpM in each country grows. Regarding the modelling of the TCCpM curves, we have found that the fitting parameters oscillate with time before reaching constant values. The estimation of such values allows the determination of better parameters for the model, which in turn leads to more trustworthy forecasts on the pandemic development.InterpretationThe analysis of the oscillating fitting parameters allows an early prediction of the TCC, epidemic center and standard deviation of the outbreak. The α factor and the recovered over confirmed cases ratio can be used to understand the pandemic development in each country and to compare the protective measures taken by local authorities and their impact on the spreading of the disease.FundingCNPq (grant number 2018/303911) and Fapesp (grant numebr 2019/06382-9).

Analysing and comparing the COVID-19 data: The closed cases of Hubei and South Korea, the dark March in Europe, the beginning of the outbreak in South America (Preprint)

2020 ◽  
Author(s):  
Stefano De Leo ◽  
Gabriel Gulak Maia ◽  
Leonardo Solidoro
Keyword(s):  
South America ◽  
South Korea ◽  
Early Stage ◽  
Spreading Rate ◽  
European Countries ◽  
Time Interval ◽  
Angular Coefficient ◽  
Infected People ◽  
Alpha Factor ◽  
Fitting Parameters

BACKGROUND The present work is a statistical analysis of the COVID-19 pandemic. As the number of cases worldwide overtakes one million, data reveals closed outbreaks in Hubei and South Korea, with a new slight increase in the number of infected people in the latter. Both of these countries have reached a plateau in the number of Total Confirmed Cases per Million (TCCpM) residents, suggesting a trend to be followed by other affected regions. OBJECTIVE Using Hubei's data as a basis of analysis, we have studied the spreading rate of COVID-19 and modelled the epidemic center for 10 European countries. We have also given the final TCCpM curves for Italy and Lombardia. The introduction of the $\boldsymbol{\alpha}$-factor allows us to analyse the different stages of the outbreak, compare the European countries amongst each other, and, finally, to confront the initial phase of the disease between Europe and South America. METHODS By dividing the TCCpM curves in multiple sections spanning short time frames we were able to fit each section to a linear model. By pairing then the angular coefficient ( factor) of each section to the total number of confirmed infections at the center of the corresponding time interval, we have analysed how the spreading rate of Covid-19 changes as more people are infected. Also, by modelling the TCCpM curves with an asymmetrical time integral of a Normal Distribution, we were able to study, by fitting progressively larger data ensembles, how the fitting parameters change as more data becomes available. RESULTS The data analysis shows that the spreading rate of COVID-19 increases similarly for all countries in its early stage, but changes as the number of TCCpM in each country grows. Regarding the modelling of the TCCpM curves, we have found that the fitting parameters oscillate with time before reaching constant values. The estimation of such values allows the determination of better parameters for the model, which in turn leads to more trustworthy forecasts on the pandemic development. CONCLUSIONS The analysis of the oscillating fitting parameters allows an early prediction of the TCC, epidemic center and standard deviation of the outbreak. The alpha factor and the recovered over confirmed cases ratio can be used to understand the pandemic development in each country and to compare the protective measures taken by local authorities and their impact on the spreading of the disease. INTERNATIONAL REGISTERED REPORT RR2-doi.org/10.1101/2020.04.06.20055327

scholarly journals Pattern analysis of risk situations using multi-sensor

2018 ◽  
Vol 7 (2.12) ◽  
pp. 50
Author(s):  
Chang Bae Noh ◽  
Miyang Cha
Keyword(s):  
Crime Prevention ◽  
Pattern Analysis ◽  
Early Stage ◽  
Integrated Management ◽  
Low Cost ◽  
Integrated Control ◽  
Human Resources Management ◽  
Current Status ◽  
High Tech ◽  
The Status

Background/Objectives: Existing crime prevention systems manually monitor risk situations using street lights, CCTVs, and security equipment. Since there are many areas where the workforce is held responsible, it is difficult to closely manage all systems due to work overload.Methods/Statistical analysis: The data of maps constructed and continuously updated through the system will allow more accurate predictions of crime and contribute to crime prevention strategies. Furthermore, replacing existing patrol manpower to unmanned drones will allow for more efficient human resources management as well as contribute to the crime prevention infrastructure, thereby minimizing the existence of blind spots in the current system.Findings: It is not easy to diffuse the initial situation in the case of an emergency through prompt notifications. Therefore, a low-cost, integrated management system is needed to prevent major accidents and to minimize damage by detecting crime and fire risks in the early stage. It will be easier to judge risks if we use the multi-sensor and pattern analysis algorithms proposed in this study. Occurrences of crime and fire have been rapidly rising with the quick pace of industrialization. This has resulted in an increase of unease among citizens as well as a rising demand for security and safety in residential environments. As the times change, it is necessary to develop advanced science technology that can predict crimes in order to construct crime preventing environments. The Risk Notification Service can promptly respond to the current status and situation of the user by forwarding the status to the administrator or guardian. Police activity can be strengthened by building a high-tech science and security system to monitor areas susceptible to crime in real-time.Improvements/Applications: This study looks into problems of the existing monitoring system and proposes an integrated control system for crime prevention. Keywords:Background/Objectives: Existing crime prevention systems manually monitor risk situations using street lights, CCTVs, and security equipment. Since there are many areas where the workforce is held responsible, it is difficult to closely manage all systems due to work overload.Methods/Statistical analysis: The data of maps constructed and continuously updated through the system will allow more accurate predictions of crime and contribute to crime prevention strategies. Furthermore, replacing existing patrol manpower to unmanned drones will allow for more efficient human resources management as well as contribute to the crime prevention infrastructure, thereby minimizing the existence of blind spots in the current system.Findings: It is not easy to diffuse the initial situation in the case of an emergency through prompt notifications. Therefore, a low-cost, integrated management system is needed to prevent major accidents and to minimize damage by detecting crime and fire risks in the early stage. It will be easier to judge risks if we use the multi-sensor and pattern analysis algorithms proposed in this study. Occurrences of crime and fire have been rapidly rising with the quick pace of industrialization. This has resulted in an increase of unease among citizens as well as a rising demand for security and safety in residential environments. As the times change, it is necessary to develop advanced science technology that can predict crimes in order to construct crime preventing environments. The Risk Notification Service can promptly respond to the current status and situation of the user by forwarding the status to the administrator or guardian. Police activity can be strengthened by building a high-tech science and security system to monitor areas susceptible to crime in real-time.Improvements/Applications: This study looks into problems of the existing monitoring system and proposes an integrated control system for crime prevention.  

scholarly journals Emergence of a new type of doctorate; professional doctorate

2018 ◽  
Vol 1 (1-2) ◽  
pp. 7-25
Author(s):  
Dan Potolea ◽  
Steliana Toma ◽  
Oana Monica Moșoiu
Keyword(s):  
Higher Education ◽  
Financial Support ◽  
Current Status ◽  
New Horizons ◽  
The Road ◽  
Wide Range ◽  
Professional Doctorate ◽  
The Status ◽  
New Type ◽  
Doctoral Programmes

Increasing number of students enrolled in doctoral programmes and the emergence of the new types of doctoral programmes across the world's universities as a response to various demands from a wide range of professional context has shown that professional doctorate has become a new challenge and opened new horizons in higher education. This article examines the road of the professional doctorate from beginning to current status and possible trends. The professional doctorate is examined in its relationship with the so-called traditional scientific doctorate. The paper focuses on some of the aspects that gives identity and legitimacy to this type of doctorate: programme aims, structure, content, duration, recruitment and admissions, students' motivation to enroll professional doctorate, status, financial support, standards, and thesis contributions. It also presents the status of the professional doctorate in Romania and some ideas as a basis for further examination of the professional doctorate.

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