scholarly journals Impact of Bursty Human Activity Patterns on the Popularity of Online Content

2012 ◽  
Vol 2012 ◽  
pp. 1-11 ◽  
Author(s):  
Qiang Yan ◽  
Lianren Wu
Keyword(s):  
Power Law ◽  
Activity Patterns ◽  
Temporal Analysis ◽  
Time Interval ◽  
Online Content ◽  
Power Law Decay ◽  
Content Popularity ◽  
Human Activity Patterns ◽  
The Impact ◽  
Statistical Results

The dynamics of online content popularity has attracted more and more researches in recent years. In this paper, we provide a quantitative, temporal analysis about the dynamics of online content popularity in a massive system: Sina Microblog. We use time-stamped data to investigate the impact of bursty human comment patterns on the popularity of online microblog news. Statistical results indicate that the number of news and comments exhibits an exponential growth. The strength of forwarding and comment is characterized by bursts, displaying fat-tailed distribution. In order to characterize the dynamics of popularity, we explore the distribution of the time intervalΔtbetween consecutive comment bursts and find that it also follows a power-law. Bursty patterns of human comment are responsible for the power-law decay of popularity. These results are well supported by both the theoretical analysis and empirical data.

scholarly journals Bacterial persistence is essential for susceptible cell survival in indirect resistance, mainly for lower cell densities

PLoS ONE ◽  
2021 ◽  
Vol 16 (9) ◽  
pp. e0246500
Author(s):  
João S. Rebelo ◽  
Célia P. F. Domingues ◽  
Francisca Monteiro ◽  
Teresa Nogueira ◽  
Francisco Dionisio
Keyword(s):  
Power Law ◽  
Initial Density ◽  
Toxic Substance ◽  
Power Law Distribution ◽  
Persister Cells ◽  
Experimental Conditions ◽  
Power Law Decay ◽  
Cell Densities ◽  
Antibiotic Degradation ◽  
The Impact

Antibiotic-susceptible bacteria may survive bactericidal antibiotics if other co-inhabiting bacteria detoxify the medium through antibiotic degradation or modification, a phenomenon denominated as indirect resistance. However, it is unclear how susceptible cells survive while the medium is still toxic. One explanation relies on the speed of detoxification, and another, non-exclusive explanation, relies on persistence, a state of bacterial dormancy where cells with low metabolic activity and growth rates are phenotypically tolerant to antibiotics and other cytotoxic substances. Here we simulated the fate of susceptible cells in laboratory experiments in the context of indirect resistance to understand whether persistence is necessary to explain the survival of susceptible cells. Depending on the strain and experimental conditions, the decay of persister populations may follow an exponential or a power-law distribution. Therefore, we studied the impact of both distributions in the simulations. Moreover, we studied the impact of considering that persister cells have a mechanism to sense the presence of a toxic substance–a mechanism that would enable cells to leave the dormant state when the medium becomes nontoxic. The simulations show that surviving susceptible cells under indirect resistance may originate both from persister and non-persister populations if the density of detoxifying cells is high. However, persistence was necessary when the initial density of detoxifying cells was low, although persister cells remained in that dormancy state for just a few hours. Finally, the results of our simulations are consistent both with exponential and power-law decay of the persistence population. Whether indirect resistance involves persistence should impact antibiotic treatments.

scholarly journals Superspreaders and lockdown timing explain the power law dynamics of COVID-19

2020 ◽  
Author(s):  
Alexei Vazquez
Keyword(s):  
Power Law ◽  
Disease Outbreaks ◽  
Growth Dynamics ◽  
Time Interval ◽  
Infectious Disease Outbreaks ◽  
First Case ◽  
Power Law Exponent ◽  
Containment Measures ◽  
The Impact ◽  
The Relationship

Infectious disease outbreaks are expected to grow exponentially in time when left unchecked. Containment measures such as lockdown and social distancing can drastically alter the growth dynamics of the outbreak. This is the case for the 2019-2020 COVID-19 outbreak, which is characterized by a power law growth. Strikingly however, the power law exponent is different across countries. Here I illustrate the relationship between these two extreme scenarios, exponential and power law growth, based on the impact of superspreaders and lockdown strategies to contain the outbreak. The theory predicts a relationship between the power law exponent and the time interval between the first case and lockdown that is validated by the observed COVID-19 data across different countries.

Uncovering urban mobility patterns and impact of spatial distribution of places on movements

2017 ◽  
Vol 28 (01) ◽  
pp. 1750004 ◽  
Author(s):  
Wang Chen ◽  
Qiang Gao ◽  
Hua-Gang Xiong
Keyword(s):  
Spatial Distribution ◽  
Power Law ◽  
Urban Areas ◽  
Large Scale ◽  
Length Distribution ◽  
Distribution Area ◽  
Urban Mobility ◽  
Mobility Patterns ◽  
Power Law Decay ◽  
The Impact

As an important component in varieties of practical applications, understanding human urban mobility patterns draws intensive attention from researchers. In this paper, we investigate the urban mobility patterns and the impact of spatial distribution of places on the patterns using the data from a popular location-based social network Whrrl which are unrestricted to transportation modes. A movement region is demarcated for each city, which better depicts the concentrated active area of residents in the city than the administrative region. We show that the trip lengths in urban areas follow the exponential law unlike the power law in large scale of space. We find that the cities with larger sizes of place distribution area generally have smaller exponents of trip length distribution, larger means and deviations of trip lengths, while there are no apparent relationships between place densities and trip lengths. To examine the findings, we construct series of synthetic cities based on the power-law decay of place density and simulate urban human movement by the rank-based model. The simulations validate our findings and imply that the exponential distribution of urban trips is a combined result of power-law decay of place density and rank-based mobility preference.

The impact of human activity patterns on asymptomatic infectious processes in complex networks

2012 ◽  
Vol 391 (14) ◽  
pp. 3718-3728 ◽  
Author(s):  
Mingjie Li ◽  
Mehmet A. Orgun ◽  
Jinghua Xiao ◽  
Weicai Zhong ◽  
Liyin Xue
Keyword(s):  
Complex Networks ◽  
Human Activity ◽  
Activity Patterns ◽  
Human Activity Patterns ◽  
The Impact

scholarly journals Time-to-Treatment in Oral Cancer: Causes and Implications for Survival

Cancers ◽  
2021 ◽  
Vol 13 (6) ◽  
pp. 1321
Author(s):  
Constanza Saka-Herrán ◽  
Enric Jané-Salas ◽  
Antoni Mari-Roig ◽  
Albert Estrugo-Devesa ◽  
José López-López
Keyword(s):  
Oral Cancer ◽  
Previous Treatment ◽  
Diagnostic Procedures ◽  
Original Data ◽  
Primary Treatment ◽  
Medical Attention ◽  
Time Interval ◽  
Pre Treatment ◽  
The Impact ◽  
Lack Of Knowledge

The purpose of this review was to identify and describe the causes that influence the time-intervals in the pathway of diagnosis and treatment of oral cancer and to assess its impact on prognosis and survival. The review was structured according to the recommendations of the Aarhus statement, considering original data from individual studies and systematic reviews that reported outcomes related to the patient, diagnostic and pre-treatment intervals. The patient interval is the major contributor to the total time-interval. Unawareness of signs and/or symptoms, denial and lack of knowledge about oral cancer are the major contributors to the process of seeking medical attention. The diagnostic interval is influenced by tumor factors, delays in referral due to higher number of consultations and previous treatment with different medicines or dental procedures and by professional factors such as experience and lack of knowledge related to the disease and diagnostic procedures. Patients with advanced stage disease, primary treatment with radiotherapy, treatment at an academic facility and transitions in care are associated with prolonged pre-treatment intervals. An emerging body of evidence supports the impact of prolonged pre-treatment and treatment intervals with poorer survival from oral cancer.

scholarly journals The Impact of Time Interval between Hepatic Resection and Liver Transplantation on Clinical Outcome in Patients with Hepatocellular Carcinoma

Cancers ◽  
2021 ◽  
Vol 13 (10) ◽  
pp. 2398
Author(s):  
Matteo Serenari ◽  
Enrico Prosperi ◽  
Marc-Antoine Allard ◽  
Michele Paterno ◽  
Nicolas Golse ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Liver Transplantation ◽  
Hepatic Resection ◽  
Primary Outcome ◽  
Polynomial Regression ◽  
Secondary Outcome ◽  
Time Interval ◽  
Comprehensive Complication Index ◽  
Fractional Polynomial ◽  
The Impact

Hepatic resection (HR) for hepatocellular carcinoma (HCC) may require secondary liver transplantation (SLT). However, a previous HR is supposed to worsen post-SLT outcomes. Data of patients treated by SLT between 2000 and 2018 at two tertiary referral centers were analyzed. The primary outcome of the study was to analyze the impact of HR on post-LT complications. A Comprehensive Complication Index ≥ 29.6 was chosen as cutoff. The secondary outcome was HCC-related death by means of competing-risk regression analysis. In the study period, 140 patients were included. Patients were transplanted in a median of 23 months after HR (IQR 14–41). Among all the features analyzed regarding the prior HR, only time interval between HR and SLT (time HR-SLT) was an independent predictor of severe complications after LT (OR = 0.98, p < 0.001). According to fractional polynomial regression, the probability of severe complications increased up to 15 months after HR (43%), then slowly decreased over time (OR = 0.88, p < 0.001). There was no significant association between HCC-related death and time HR-SLT at the multivariable competing risks regression model (SHR, 1.06; 95% CI: 0.69–1.62, p = 0.796). This study showed that time HR-SLT was key in predicting complications after LT, without affecting HCC-related death.

scholarly journals Analysing the impact of the COVID-19 outbreak on everyday travel behaviour in Germany and potential implications for future travel patterns

2021 ◽  
Vol 13 (1) ◽  
Author(s):  
Viktoriya Kolarova ◽  
Christine Eisenmann ◽  
Claudia Nobis ◽  
Christian Winkler ◽  
Barbara Lenz
Keyword(s):  
Public Transport ◽  
Online Survey ◽  
Adult Population ◽  
Activity Patterns ◽  
Age Groups ◽  
Travel Behaviour ◽  
German Population ◽  
Travel Patterns ◽  
Home Office ◽  
The Impact

Abstract Introduction The global Coronavirus (COVID-19) pandemic is having a great impact on all areas of the everyday life, including travel behaviour. Various measures that focus on restricting social contacts have been implemented in order to reduce the spread of the virus. Understanding how daily activities and travel behaviour change during such global crisis and the reasons behind is crucial for developing suitable strategies for similar future events and analysing potential mid- and long-term impacts. Methods In order to provide empirical insights into changes in travel behaviour during the first Coronavirus-related lockdown in 2020 for Germany, an online survey with a relative representative sample for the German population was conducted a week after the start of the nationwide contact ban. The data was analysed performing descriptive and inferential statistical analyses. Results and Discussion The results suggest in general an increase in car use and decrease in public transport use as well as more negative perception of public transport as a transport alternative during the pandemic. Regarding activity-related travel patterns, the findings show firstly, that the majority of people go less frequent shopping; simultaneously, an increase in online shopping can be seen and characteristics of this group were analysed. Secondly, half of the adult population still left their home for leisure or to run errands; young adults were more active than all other age groups. Thirdly, the majority of the working population still went to work; one out of four people worked in home-office. Lastly, potential implications for travel behaviour and activity patterns as well as policy measures are discussed.

scholarly journals Effect of the Assimilation Frequency of Radar Reflectivity on Rain Storm Prediction by Using WRF-3DVAR

2021 ◽  
Vol 13 (11) ◽  
pp. 2103
Author(s):  
Yuchen Liu ◽  
Jia Liu ◽  
Chuanzhe Li ◽  
Fuliang Yu ◽  
Wei Wang
Keyword(s):  
Data Assimilation ◽  
Northern China ◽  
Horizontal Resolution ◽  
Radar Reflectivity ◽  
Small Scale ◽  
Time Interval ◽  
Outer Domain ◽  
Storm Prediction ◽  
The Impact ◽  
Assimilation Time

An attempt was made to evaluate the impact of assimilating Doppler Weather Radar (DWR) reflectivity together with Global Telecommunication System (GTS) data in the three-dimensional variational data assimilation (3DVAR) system of the Weather Research Forecast (WRF) model on rain storm prediction in Daqinghe basin of northern China. The aim of this study was to explore the potential effects of data assimilation frequency and to evaluate the outputs from different domain resolutions in improving the meso-scale NWP rainfall products. In this study, four numerical experiments (no assimilation, 1 and 6 h assimilation time interval with DWR and GTS at 1 km horizontal resolution, 6 h assimilation time interval with radar reflectivity, and GTS data at 3 km horizontal resolution) are carried out to evaluate the impact of data assimilation on prediction of convective rain storms. The results show that the assimilation of radar reflectivity and GTS data collectively enhanced the performance of the WRF-3DVAR system over the Beijing-Tianjin-Hebei region of northern China. It is indicated by the experimental results that the rapid update assimilation has a positive impact on the prediction of the location, tendency, and development of rain storms associated with the study area. In order to explore the influence of data assimilation in the outer domain on the output of the inner domain, the rainfall outputs of 3 and 1 km resolution are compared. The results show that the data assimilation in the outer domain has a positive effect on the output of the inner domain. Since the 3DVAR system is able to analyze certain small-scale and convective-scale features through the incorporation of radar observations, hourly assimilation time interval does not always significantly improve precipitation forecasts because of the inaccurate radar reflectivity observations. Therefore, before data assimilation, the validity of assimilation data should be judged as far as possible in advance, which can not only improve the prediction accuracy, but also improve the assimilation efficiency.

scholarly journals Financing Growth through Remittances and Foreign Direct Investment: Evidences from Balkan Countries

2021 ◽  
Vol 14 (3) ◽  
pp. 117
Author(s):  
Esmeralda Jushi ◽  
Eglantina Hysa ◽  
Arjona Cela ◽  
Mirela Panait ◽  
Marian Catalin Voica
Keyword(s):  
Developing Economies ◽  
Central Banks ◽  
Sustainable Growth ◽  
Time Interval ◽  
Foreign Direct Investments ◽  
Factors Affecting ◽  
Balkan Countries ◽  
To Come ◽  
Sustainable Economic Growth ◽  
The Impact

The ultimate goal of central banks, worldwide, is to promote the foundations for sustainable economic growth. In the case of developing economies, in particular, such objective requires time, huge efforts, attention, and plenty of resources in order to be accomplished to the fullest degree. This paper thoroughly investigates key factors affecting Balkan countries’ economic development (as measured by gross domestic product (GDP) growth), focusing especially on the impact of remittances. The analysis was done over an 18-year time interval (2000–2017) and builds on 144 observations. The data figures were retrieved from the World Bank database while two dummies were created to test the impact of the last financial crisis (2008–2012). Econometric tools were employed to carry out a broad analysis on the interdependencies that exist and, in particular, to determine the role of remittance income on growth. The vector auto regressive model was estimated using EViews software, and was used to come up with relevant insights. Empirical findings suggest the following: population growth, remittances, and labor force participation are insignificant factors for sustainable growth. On the other hand, previous levels of GDP, trade, and foreign direct investments (FDIs) appear to be relevant for the predictor. This research provides up-to-date conclusions, which can be considered during the decision-making process of central banks, as well as by government policymakers.

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