371 research outputs found
Social Media Attention Increases Article Visits: An Investigation on Article-Level Referral Data of PeerJ
In order to better understand the effect of social media in the dissemination
of scholarly articles, employing the daily updated referral data of 110 PeerJ
articles collected over a period of 345 days, we analyze the relationship
between social media attention and article visitors directed by social media.
Our results show that social media presence of PeerJ articles is high. About
68.18% of the papers receive at least one tweet from Twitter accounts other
than @PeerJ, the official account of the journal. Social media attention
increases the dissemination of scholarly articles. Altmetrics could not only
act as the complement of traditional citation measures but also play an
important role in increasing the article downloads and promoting the impacts of
scholarly articles. There also exists a significant correlation among the
online attention from different social media platforms. Articles with more
Facebook shares tend to get more tweets. The temporal trends show that social
attention comes immediately following publication but does not last long, so do
the social media directed article views
Hermite Positive Definite Solution of a Class of Matrix Equation
AbstractIn this paper, the Hermite positive definite solutions of the nonlinear matrix equation XS+A*X−tA=Q are discussed. A sufficient condition and two necessary and sufficient conditions for the existence of Hermite positive definite solutions for this equation are derived. The existence of minimal Hermite positive definite solution is also studied here, and an iterative method for obtaining the minimal Hermite positive definite solution is given
Detecting Early-warning signals in Time Series of Visits to Points of Interests to Examine Population Response to COVID -19 Pandemic
The objective of this paper is to examine population response to COVID-19 and
associated policy interventions through detecting early-warning signals in time
series of visits to points of interest (POIs). Complex systems, such as cities,
demonstrate early-warning signals when they approach phase transitions
responding to external perturbation, including crises, policy changes, and
human behavior changes. In urban systems, population visits to POIs represent a
state in the complex systems that are cities. These states may undergo phase
transitions due to population response to pandemic risks and intervention
policies. In this study, we conducted early-warning signal detection on
population visits to POIs to examine population response to pandemic risks. We
examined two early-warning signals, the increase of autocorrelation at-lag-1
and standard deviation, in time series of population visits to POIs in 17
metropolitan cities in the United States of America. The results show that: (1)
early-warning signals for population response to COVID-19 were detected between
February 14 and March 11, 2020 in 17 cities; (2) detected population response
had started prior to shelter-in-place orders in 17 cities; (3) early-warning
signals detected from the essential POIs visits appeared earlier than those
from non-essential POIs; and 4) longer time lags between detected population
response and shelter-in-place orders led to a less decrease in POI visits. The
results show the importance of detecting early-warning signals during crises in
cities as complex systems. Early-warning signals could provide important
insights regarding the timing and extent of population response to crises to
inform policy makers
Successive approximations for quasi-firmly type nonexpansive mappings
In this paper, two examples of quasi-firmly type
nonexpansive mappings are given to prove that the concept is different from nonexpansive mapping. Furthermore, it is studied to the convergence of the sequence of successive approximations for this class of mappings only when the super limit of iteration coefficients is less than . In particular, the Picard iteration of such a mapping converges to a fixed point of in a compact metric space
Describing Strong Correlation with Block-Correlated Coupled Cluster Theory
A block-correlated coupled cluster (BCCC) method based on the generalized
valence bond (GVB) wave function (GVB-BCCC in short) is proposed and
implemented at the ab initio level, which represents an attractive
multireference electronic structure method for strongly correlated systems. The
GVB-BCCC method is demonstrated to provide accurate descriptions for multiple
bond breaking in small molecules, although the GVB reference function is
qualitatively wrong for the studied processes. For a challenging prototype of
strongly correlated systems, tridecane with all 12 single C-C bonds at various
distances, our calculations have shown that the GVB-BCCC2b method can provide
highly comparable results as the density matrix renormalization group method
for potential energy surfaces along simultaneous dissociation of all C-C bonds
Effects of Population Co-location Reduction on Cross-county Transmission Risk of COVID-19 in the United States
The rapid spread of COVID-19 in the United States has imposed a major threat
to public health, the real economy, and human well-being. With the absence of
effective vaccines, the preventive actions of social distancing and travel
reduction are recognized as essential non-pharmacologic approaches to control
the spread of COVID-19. Prior studies demonstrated that human movement and
mobility drove the spatiotemporal distribution of COVID-19 in China. Little is
known, however, about the patterns and effects of co-location reduction on
cross-county transmission risk of COVID-19. This study utilizes Facebook
co-location data for all counties in the United States from March to early May
2020. The analysis examines the synchronicity and time lag between travel
reduction and pandemic growth trajectory to evaluate the efficacy of social
distancing in ceasing the population co-location probabilities, and
subsequently the growth in weekly new cases. The results show that the
mitigation effects of co-location reduction appear in the growth of weekly new
cases with one week of delay. Furthermore, significant segregation is found
among different county groups which are categorized based on numbers of cases.
The results suggest that within-group co-location probabilities remain stable,
and social distancing policies primarily resulted in reduced cross-group
co-location probabilities (due to travel reduction from counties with large
number of cases to counties with low numbers of cases). These findings could
have important practical implications for local governments to inform their
intervention measures for monitoring and reducing the spread of COVID-19, as
well as for adoption in future pandemics. Public policy, economic forecasting,
and epidemic modeling need to account for population co-location patterns in
evaluating transmission risk of COVID-19 across counties.Comment: 12 pages, 7 figure
Deformation rule of bored pile & steel support for deep foundation pit in sandy pebble geology
Regarding the whole excavation process of the support system of the Southwest Jiaotong University Station of Chengdu Metro Line 6 (the deep foundation pit bored pile + steel support and support system) as the engineering background, this paper studies the deformation rule of the deep foundation pit bored pile + steel support of the sandy pebble foundation. The deformation rule of this support system, the settlement rule of the ground surface outside the pit, and the rule of the uplift of the loose at the bottom of the pit are studied. A key analysis of the positive corner of the foundation pit is conducted, and the rationality of the optimization of the support scheme is evaluated. This paper provides effective guidance for the subsequent deep foundation pit construction and provides a reference for deep foundation pit construction
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