324 research outputs found
Composite Dark Matter and Higgs
We investigate the possibility that Dark Matter arises as a composite state
of a fundamental confining dynamics, together with the Higgs boson. We focus on
the minimal SU(4)SU(4)/SU(4) model which has both a Dark Matter and a
Higgs candidates arising as pseudo-Nambu-Goldstone bosons. At the same time, a
simple underlying gauge-fermion theory can be defined providing an existence
proof of, and useful constraints on, the effective field theory description. We
focus on the parameter space where the Dark Matter candidate is mostly a gauge
singlet. We present a complete calculation of its relic abundance and find
preferred masses between 500 GeV to a few TeV. Direct Dark Matter detection
already probes part of the parameter space, ruling out masses above 1 TeV,
while Indirect Detection is relevant only if non-thermal production is assumed.
The prospects for detection of the odd composite scalars at the LHC are also
established.Comment: 54 pages, 10 figures; Typo fixed, figures improved, refs added et
Future prospects of mass-degenerate Higgs bosons in the -conserving two-Higgs-doublet model
The scenario of two mass-degenerate Higgs bosons within the general
two-Higgs-doublet model (2HDM) is revisited. We focus on the global picture
when two -even Higgs bosons of and are nearly mass-degenerate. A
global fit to the signal strength of the 125 GeV Higgs measured at the LHC is
performed. Based on the best-fit result of the 2HDM mixing angles
, theoretical constraints, charged and -odd Higgs boson
direct search constraints and the electroweak precision constraints are imposed
to the 2HDM parameter space. We present the signal predictions of the channels for the benchmark models at the LHC 14 TeV runs. We also
study the direct Higgs boson pair productions at the LHC, and the Z-associated
Higgs boson pair production search at the ILC 500 GeV runs, as well as the
indirect probes at the CEPC 250 GeV run. We find that the mass-degenerate Higgs
boson scenario in the Type-II 2HDM can be fully probed by these future
experimental searches.Comment: 31 pages, 9 figures, 5 tables, matches with the PRD published versio
Improved Performance of LiFe0.25Mn0.75PO4 by using Graphene and Fluorine- Doped Carbon Coating
Lithium transition metal phosphatesusually need modification of morphology and electron
conductivity for improving the electrochemical performance [1,2]. In this work, the electron
conductivity of LiFe0.25Mn0.75PO4 is increased by adopting graphene and F-doped carbon.The reductive graphene oxide and F-doped carbon coating LiFe0.25Mn0.75PO4 (LFMP/C-F/rGO) is synthesized by a simple ball milling method
What Can Online Doctor Reviews Tell Us? A Deep Learning Assisted Study of Telehealth Service
The present study develops a novel deep learning method which assists text mining of online doctor reviews to extract underlying sentiment scores. Those scores can be used to estimate a healthcare service quality model to investigate how the online doctor reviews impact the online doctor consultation demand. Based on the data from the largest online health platforms in China, our model results show that the underlying sentiment scores have statistically significant impacts on the demand of online doctor consultation. Theoretically, the present study constructs an innovative deep learning algorithm with a better performance than four widely used text mining methods, which can be applied to text mining of many online forums or social media texts. Empirically, our model results show what factors impact the health service quality and online doctor consultation demand, and following those factors, healthcare professionals can improve their service
Early Development of Graphical Literacy through Knowledge Building
This study examined growth in graphical literacy for students contributing to an online, multimedia, communal environment as they advanced their understanding of biology, history and optics. Their science and history studies started early in Grade 3 and continued to the end of Grade 4; students did not receive instruction in graphics production, nor were they required to produce graphics. Results show that students spontaneously produced graphics that advanced along seven dimensions, including effective representation of complex ideas, use of source information and captions, and aesthetic quality. On average, the scores for the seven dimensions were higher for Grade 4 students with two years of experience with Knowledge Building pedagogy and technology (Knowledge Forum®) than for Grade 6 students with one year of experience. The overall pattern of results suggests reciprocal enhancement of graphical, textual, digital, and scientific literacy, with students exceeding expectations by available norms, and performance enhanced through extended Knowledge Building experience
CartiMorph: a framework for automated knee articular cartilage morphometrics
We introduce CartiMorph, a framework for automated knee articular cartilage
morphometrics. It takes an image as input and generates quantitative metrics
for cartilage subregions, including the percentage of full-thickness cartilage
loss (FCL), mean thickness, surface area, and volume. CartiMorph leverages the
power of deep learning models for hierarchical image feature representation.
Deep learning models were trained and validated for tissue segmentation,
template construction, and template-to-image registration. We established
methods for surface-normal-based cartilage thickness mapping, FCL estimation,
and rule-based cartilage parcellation. Our cartilage thickness map showed less
error in thin and peripheral regions. We evaluated the effectiveness of the
adopted segmentation model by comparing the quantitative metrics obtained from
model segmentation and those from manual segmentation. The root-mean-squared
deviation of the FCL measurements was less than 8%, and strong correlations
were observed for the mean thickness (Pearson's correlation coefficient ), surface area () and volume () measurements. We compared our FCL measurements with those from a
previous study and found that our measurements deviated less from the ground
truths. We observed superior performance of the proposed rule-based cartilage
parcellation method compared with the atlas-based approach. CartiMorph has the
potential to promote imaging biomarkers discovery for knee osteoarthritis.Comment: To be published in Medical Image Analysi
Identification of random amplified polymorphic DNA (RAPD) marker of Ph-3 gene for late blight resistance in tomato
Late blight is a highly destructive disease of tomato worldwide. Host resistance is the most effective method for disease control. The application of molecular markers is an efficient way to identify host resistance for breeding programs. In this study, bulked segregant analysis (BSA) was used to search for random amplified polymorphic DNA (RAPD) markers linked to the late blight resistance gene Ph-3, using an F2 population (147 individuals) derived from a cross of tomato lines CLN2037 (resistant) and T2-03 (susceptible). Two hundred and thirty decamer primers with arbitrary sequences were chosen for polymerase chain reaction amplification. One RAPD marker CCPB272-03740 (primer sequence GGTCGATCTG) was found to be tightly linked to the resistance gene Ph-3 and was located 5.8 cm from the resistance gene. Marker CCPB272-03740 is the first marker of gene Ph-3 based on PCR reaction.Key words: Tomato, late blight, random amplified polymorphic DNA (RAPD) marker, gene Ph-3
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