369 research outputs found
Revealing the Disciplinary Landscape of Data Science Journals
The discipline, field, and practice of data science emerged to its current prominence in
the past several decades. New disciplines, fields, and practices often involve definitional and
scope challenges. This seems to be the case with data science. The research presented in this
poster is part of a broader investigation into the disciplinary or interdisciplinary characteristics of
data science. This work-in-progress poster reports the results of analyses of data science journals
in different subject areas to answer several questions including:
âą What is the population of journals that focus on topics of data science?
âą What disciplinary landscape of data science is revealed in the aims and scope statements
of these journals?
The unit of analysis in this research is at the journal level. Both quantitative and
qualitative approaches were used in the analysis of the aim and scope statements. The
quantitative approach used computational methods (e.g., Part-of-Speech Tagging, Word
Embedding) to identify keywords representing characteristics of the journal. The qualitative
approach used conceptual content analysis to reveal different patterns in terms of research types
and the scope of research of the journals.
Data science research and education are part of many library and information science
degree programs. The results of this research have the following benefits:
âą Researchers can understand disciplinary and research types published in the journals
when selecting a venue for submitting papers.
âą Educators and students can identify appropriate journal resources to support learning.
âą Librarians can use the results to assess collection development decisions regarding data
science journals
SPU-Net: Self-Supervised Point Cloud Upsampling by Coarse-to-Fine Reconstruction with Self-Projection Optimization
The task of point cloud upsampling aims to acquire dense and uniform point
sets from sparse and irregular point sets. Although significant progress has
been made with deep learning models, they require ground-truth dense point sets
as the supervision information, which can only trained on synthetic paired
training data and are not suitable for training under real-scanned sparse data.
However, it is expensive and tedious to obtain large scale paired sparse-dense
point sets for training from real scanned sparse data. To address this problem,
we propose a self-supervised point cloud upsampling network, named SPU-Net, to
capture the inherent upsampling patterns of points lying on the underlying
object surface. Specifically, we propose a coarse-to-fine reconstruction
framework, which contains two main components: point feature extraction and
point feature expansion, respectively. In the point feature extraction, we
integrate self-attention module with graph convolution network (GCN) to
simultaneously capture context information inside and among local regions. In
the point feature expansion, we introduce a hierarchically learnable folding
strategy to generate the upsampled point sets with learnable 2D grids.
Moreover, to further optimize the noisy points in the generated point sets, we
propose a novel self-projection optimization associated with uniform and
reconstruction terms, as a joint loss, to facilitate the self-supervised point
cloud upsampling. We conduct various experiments on both synthetic and
real-scanned datasets, and the results demonstrate that we achieve comparable
performance to the state-of-the-art supervised methods
Construction and Analysis of Ecological Security Patterns in the Southern Anhui Region of China from a Circuit Theory Perspective
Located in an important biodiversity conservation area in the Yangtze River Delta, the habitats of many species have been severely eroded because of human activities such as tourism development. There is no relevant species conservation plan in place in the region, and scientific guidance on ecosystem change and corridor construction is urgently needed. In this study, we first assess ecosystem service functions based on the InVEST model; then, we assess ecological sensitivity and identify landscape resistance surfaces by constructing ecosystem sensitivity indicators; finally, we construct ecological security patterns by combining landscape resistance surfaces and circuit theory identification. The main results are as follows: (1) The high value area of ecosystem services is located in the southwest, while the northeast part of the study area has lower ecosystem services, and there is a trade-off between the ecosystem services in the study area. (2) There are 38 ecological sources in southern Anhui, with a total area of more than 5742.79 km2, that are the basic guarantees of ecological security, mainly located in the northeast of the study area, and woodland and grassland are the most important components, accounting for 18.4% of the total study area. (3) The ecological security pattern in the study area consists of 63 ecological sources, 37 important corridors, and 26 potential corridors, of which there are 28 pinch point areas and 6 barrier point patches in the study area, mainly located within Huangshan City and Xuancheng City. We recommend that when implementing restoration and rehabilitation measures in the future, policy makers should give priority to pinch points and barrier areas.</p
Targeting histone deacetylase 3 (HDAC3) in the bone marrow microenvironment inhibits multiple myeloma proliferation by modulating exosomes and IL-6 trans-signaling
Multiple myeloma (MM) is an incurable cancer that derives pro-survival/proliferative signals from the bone marrow (BM) niche. Novel agents targeting not only cancer cells, but also the BM-niche have shown the greatest activity in MM. Histone deacetylases (HDACs) are therapeutic targets in MM and we previously showed that HDAC3 inhibition decreases MM proliferation both alone and in co-culture with bone marrow stromal cells (BMSC). In this study, we investigate the effects of HDAC3 targeting in BMSCs. Using both BMSC lines as well as patient-derived BMSCs, we show that HDAC3 expression in BMSCs can be induced by co-culture with MM cells. Knock-out (KO), knock-down (KD), and pharmacologic inhibition of HDAC3 in BMSCs results in decreased MM cell proliferation; including in autologous cultures of patient MM cells with BMSCs. We identified both quantitative and qualitative changes in exosomes and exosomal miRNA, as well as inhibition of IL-6 trans-signaling, as molecular mechanisms mediating anti-MM activity. Furthermore, we show that HDAC3-KD in BM endothelial cells decreases neoangiogenesis, consistent with a broad effect of HDAC3 targeting in the BM-niche. Our results therefore support the clinical development of HDAC3 inhibitors based not only on their direct anti-MM effects, but also their modulation of the BM microenvironment
Causal link between gut microbiota and four types of pancreatitis: a genetic association and bidirectional Mendelian randomization study
BackgroundA number of recent observational studies have indicated a correlation between the constitution of gut microbiota and the incidence of pancreatitis. Notwithstanding, observational studies are unreliable for inferring causality because of their susceptibility to confounding, bias, and reverse causality, the causal relationship between specific gut microbiota and pancreatitis is still unclear. Therefore, our study aimed to investigate the causal relationship between gut microbiota and four types of pancreatitis.MethodsAn investigative undertaking encompassing a genome-wide association study (GWAS) comprising 18,340 participants was undertaken with the aim of discerning genetic instrumental variables that exhibit associations with gut microbiota, The aggregated statistical data pertaining to acute pancreatitis (AP), alcohol-induced AP (AAP), chronic pancreatitis (CP), and alcohol-induced CP (ACP) were acquired from the FinnGen Consortium. The two-sample bidirectional Mendelian randomization (MR) approach was utilized. Utilizing the Inverse-Variance Weighted (IVW) technique as the cornerstone of our primary analysis. The Bonferroni analysis was used to correct for multiple testing, In addition, a number of sensitivity analysis methodologies, comprising the MR-Egger intercept test, the Cochranâs Q test, MR polymorphism residual and outlier (MR-PRESSO) test, and the leave-one-out test, were performed to evaluate the robustness of our findings.ResultsA total of 28 intestinal microflora were ascertained to exhibit significant associations with diverse outcomes of pancreatitis. Among them, Class Melainabacteria (OR = 1.801, 95% CI: 1.288â2.519, p = 0.008) has a strong causality with ACP after the Bonferroni-corrected test, in order to assess potential reverse causation effects, we used four types of pancreatitis as the exposure variable and scrutinized its impact on gut microbiota as the outcome variable, this analysis revealed associations between pancreatitis and 30 distinct types of gut microflora. The implementation of Cochranâs Q test revealed a lack of substantial heterogeneity among the various single nucleotide polymorphisms (SNP).ConclusionOur first systematic Mendelian randomization analysis provides evidence that multiple gut microbiota taxa may be causally associated with four types of pancreatitis disease. This discovery may contribute significant biomarkers conducive to the preliminary, non-invasive identification of Pancreatitis. Additionally, it could present viable targets for potential therapeutic interventions in the diseaseâs treatment
Thermal degradation of 2,2âČ,4,4âČ-tetrabromodiphenyl ether (BDE-47) over synthesized FeâAl composite oxide
Multidifferential study of identified charged hadron distributions in -tagged jets in proton-proton collisions at 13 TeV
Jet fragmentation functions are measured for the first time in proton-proton
collisions for charged pions, kaons, and protons within jets recoiling against
a boson. The charged-hadron distributions are studied longitudinally and
transversely to the jet direction for jets with transverse momentum 20 GeV and in the pseudorapidity range . The
data sample was collected with the LHCb experiment at a center-of-mass energy
of 13 TeV, corresponding to an integrated luminosity of 1.64 fb. Triple
differential distributions as a function of the hadron longitudinal momentum
fraction, hadron transverse momentum, and jet transverse momentum are also
measured for the first time. This helps constrain transverse-momentum-dependent
fragmentation functions. Differences in the shapes and magnitudes of the
measured distributions for the different hadron species provide insights into
the hadronization process for jets predominantly initiated by light quarks.Comment: All figures and tables, along with machine-readable versions and any
supplementary material and additional information, are available at
https://cern.ch/lhcbproject/Publications/p/LHCb-PAPER-2022-013.html (LHCb
public pages
Study of the decay
The decay is studied
in proton-proton collisions at a center-of-mass energy of TeV
using data corresponding to an integrated luminosity of 5
collected by the LHCb experiment. In the system, the
state observed at the BaBar and Belle experiments is
resolved into two narrower states, and ,
whose masses and widths are measured to be where the first uncertainties are statistical and the second
systematic. The results are consistent with a previous LHCb measurement using a
prompt sample. Evidence of a new
state is found with a local significance of , whose mass and width
are measured to be and , respectively. In addition, evidence of a new decay mode
is found with a significance of
. The relative branching fraction of with respect to the
decay is measured to be , where the first
uncertainty is statistical, the second systematic and the third originates from
the branching fractions of charm hadron decays.Comment: All figures and tables, along with any supplementary material and
additional information, are available at
https://cern.ch/lhcbproject/Publications/p/LHCb-PAPER-2022-028.html (LHCb
public pages
Measurement of the ratios of branching fractions and
The ratios of branching fractions
and are measured, assuming isospin symmetry, using a
sample of proton-proton collision data corresponding to 3.0 fb of
integrated luminosity recorded by the LHCb experiment during 2011 and 2012. The
tau lepton is identified in the decay mode
. The measured values are
and
, where the first uncertainty is
statistical and the second is systematic. The correlation between these
measurements is . Results are consistent with the current average
of these quantities and are at a combined 1.9 standard deviations from the
predictions based on lepton flavor universality in the Standard Model.Comment: All figures and tables, along with any supplementary material and
additional information, are available at
https://cern.ch/lhcbproject/Publications/p/LHCb-PAPER-2022-039.html (LHCb
public pages
Hate Speech and Counter Speech Detection: Conversational Context Does Matter
Hate speech is plaguing the cyberspace along with user-generated content.
This paper investigates the role of conversational context in the annotation
and detection of online hate and counter speech, where context is defined as
the preceding comment in a conversation thread. We created a context-aware
dataset for a 3-way classification task on Reddit comments: hate speech,
counter speech, or neutral. Our analyses indicate that context is critical to
identify hate and counter speech: human judgments change for most comments
depending on whether we show annotators the context. A linguistic analysis
draws insights into the language people use to express hate and counter speech.
Experimental results show that neural networks obtain significantly better
results if context is taken into account. We also present qualitative error
analyses shedding light into (a) when and why context is beneficial and (b) the
remaining errors made by our best model when context is taken into account.Comment: Accepted by NAACL 202
- âŠ