655 research outputs found
Architecture Information Communication in Two OSS Projects: the Why, Who, When, and What
Architecture information is vital for Open Source Software (OSS) development,
and mailing list is one of the widely used channels for developers to share and
communicate architecture information. This work investigates the nature of
architecture information communication (i.e., why, who, when, and what) by OSS
developers via developer mailing lists. We employed a multiple case study
approach to extract and analyze the architecture information communication from
the developer mailing lists of two OSS projects, ArgoUML and Hibernate, during
their development life-cycle of over 18 years. Our main findings are: (a)
architecture negotiation and interpretation are the two main reasons (i.e.,
why) of architecture communication; (b) the amount of architecture information
communicated in developer mailing lists decreases after the first stable
release (i.e., when); (c) architecture communications centered around a few
core developers (i.e., who); (d) and the most frequently communicated
architecture elements (i.e., what) are Architecture Rationale and Architecture
Model. There are a few similarities of architecture communication between the
two OSS projects. Such similarities point to how OSS developers naturally
gravitate towards the four aspects of architecture communication in OSS
development.Comment: Preprint accepted for publication in Journal of Systems and Software,
202
Risk factors for surgical site infection of pilon fractures
OBJECTIVES: Pilon fracture is a complex injury that is often associated with severe soft tissue damage and high rates of surgical site infection. The goal of this study was to analyze and identify independent risk factors for surgical site infection among patients undergoing surgical fixation of a pilon fracture. METHODS: The medical records of all pilon fracture patients who underwent surgical fixation from January 2010 to October 2012 were reviewed to identify those who developed a surgical site infection. Then, we constructed univariate and multivariate logistic regressions to evaluate the independent associations of potential risk factors with surgical site infection in patients undergoing surgical fixation of a pilon fracture. RESULTS: A total of 519 patients were enrolled in the study from January 2010 to October 2012. A total of 12 of the 519 patients developed a surgical site infection, for an incidence of 2.3%. These patients were followed for 12 to 29 months, with an average follow-up period of 19.1 months. In the final regression model, open fracture, elevated postoperative glucose levels (≥125 mg/dL), and a surgery duration of more than 150 minutes were significant risk factors for surgical site infection following surgical fixation of a pilon fracture. CONCLUSIONS: Open fractures, elevated postoperative glucose levels (≥125 mg/dL), and a surgery duration of more than 150 minutes were related to an increased risk for surgical site infection following surgical fixation of a pilon fracture. Patients exhibiting the risk factors identified in this study should be counseled regarding the possible surgical site infection that may develop after surgical fixation
A computationally-efficient bound for the variance of measuring the orientation of single molecules
Modulating the polarization of excitation light, resolving the polarization of emitted fluorescence, and point spread function (PSF) engineering have been widely leveraged for measuring the orientation of single molecules. Typically, the performance of these techniques is optimized and quantified using the Cramér-Rao bound (CRB), which describes the best possible measurement variance of an unbiased estimator. However, CRB is a local measure and requires exhaustive sampling across the measurement space to fully characterize measurement precision. We develop a global variance upper bound (VUB) for fast quantification and comparison of orientation measurement techniques. Our VUB tightly bounds the diagonal elements of the CRB matrix from above; VUB overestimates the mean CRB by ~34%. However, compared to directly calculating the mean CRB over orientation space, we are able to calculate VUB ~1000 times faster
The spectrum of low- in heavy ion collisions in a fractal description
Transverse momentum spectrum of particles in hadron gas are affected by flow,
quantum and strong interaction effects. Previously, most models focus on only
one of the three effects but ignore others. The unconsidered effects are taken
into the fitted parameters. In this paper, we study the three effects together
from a new fractal angle by physical calculation instead of data fitting. Near
the critical temperature, the three effects induce and neighboring
meson to form a two-meson structure. We set up a two-particle fractal (TPF)
model to describe this structure. We propose that under the three effects,
- two-meson state, and two-quark states form a
self-similarity structure. With evolution, the two-meson structure
disintegrate. We introduce an influencing factor to describe the
flow, quantum and strong interaction effects and an escort factor to
describe the binding force and the three effects. By solving the probability
and entropy equations, we obtain the values of and at different
collision energies and centrality classes. By substituting the value of
into distribution function, we obtain the transverse momentum
spectrum of low- and find it in good agreement with experimental
data. We also analyze the evolution of with the temperature. It is
found that is larger than 1. This is because the three effects
decrease the number of microstates. We also find decreases with
decreasing the temperature. This is consistent with the fact that with the
system expansion, the influence of the three effects decrease.Comment: 9 pages, 3 figure
EmoSet: A Large-scale Visual Emotion Dataset with Rich Attributes
Visual Emotion Analysis (VEA) aims at predicting people's emotional responses
to visual stimuli. This is a promising, yet challenging, task in affective
computing, which has drawn increasing attention in recent years. Most of the
existing work in this area focuses on feature design, while little attention
has been paid to dataset construction. In this work, we introduce EmoSet, the
first large-scale visual emotion dataset annotated with rich attributes, which
is superior to existing datasets in four aspects: scale, annotation richness,
diversity, and data balance. EmoSet comprises 3.3 million images in total, with
118,102 of these images carefully labeled by human annotators, making it five
times larger than the largest existing dataset. EmoSet includes images from
social networks, as well as artistic images, and it is well balanced between
different emotion categories. Motivated by psychological studies, in addition
to emotion category, each image is also annotated with a set of describable
emotion attributes: brightness, colorfulness, scene type, object class, facial
expression, and human action, which can help understand visual emotions in a
precise and interpretable way. The relevance of these emotion attributes is
validated by analyzing the correlations between them and visual emotion, as
well as by designing an attribute module to help visual emotion recognition. We
believe EmoSet will bring some key insights and encourage further research in
visual emotion analysis and understanding. Project page:
https://vcc.tech/EmoSet.Comment: Accepted to ICCV2023, similar to the final versio
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