9,428 research outputs found
Strong First Order EWPT and Strong Gravitational Waves in -symmetric Singlet Scalar Extension
The nature of electroweak (EW) phase transition (PT) is of great importance.
It may give a clue to the origin of baryon asymmetry if EWPT is strong first
order. Although it is second order within the standard model (SM), a great many
extensions of the SM are capable of altering the nature. Thus, gravitational
wave (GW), which is supposed to be relics of strong first order PT, is a good
complementary probe to new physics beyond SM (BSM). We in this paper elaborate
the patterns of strong first order EWPT in the next to simplest extension to
the SM Higgs sector, by introducing a -symmetric singlet scalar. We find
that, in the -symmetric limit, the tree level barrier could lead to strong
first order EWPT either via three or two-step PT. Moreover, they could produce
two sources of GW, despite of the undetectability from the first-step strong
first order PT for the near future GW experiments. But the other source with
significant supercooling which then gives rise to
almost can be wholly covered by future space-based GW interferometers such as
eLISA, DECIGO and BBO.Comment: references adde
Almost maximally broken permutation symmetry for neutrino mass matrix
Assuming three light neutrinos are Majorana particles, we propose mass matrix
ansatz for the charged leptons and Majorana neutrinos with family symmetry
broken into and , respectively. Each matrix has three
parameters, which are fixed by measured charged lepton masses, differences of
squared neutrino masses relevant to the solar and the atmospheric neutrino
puzzles, and the masses of three light Majorana neutrinos as a candidate for
hot dark matter with . The resulting neutrino mixing
is compatible with the data for the current upper limit, , of neutrino-less double beta decay experiments, and the current data
for various types of neutrino oscillation experiments. One solution of our
model predicts that oscillation probability
is about with , which may not be
accessible at CHORUS and other ongoing experiments.Comment: 9 pages, RevTex, no figure
New Avenues to Heavy Right-handed Neutrinos with Pair Production at Hadronic Colliders
In many models incorporating the type-I seesaw mechanism, the right-handed
neutrino () couples to heavy vector/scalar bosons and thereby has resonant
pair production. It barely receives attention thus far, however, it may provide
the best avenue to probe TeV scale without requiring anomalously large
mixing between and the active neutrino . In this paper we explore
the discovery prospects of (mainly heavy) pair production at the 14 TeV LHC
and future 100 TeV collider, based on the three signatures: 1) trilepton
from with the
leptonically/hadronically decaying ; 2) boosted di-Higgs boson plus MET from
; 3) a single boosted Higgs with
leptons and MET from . At the
100 TeV collider, we also consider the situation when the Higgs boson is over
boosted thus losing its jet substructure. Interpreting our tentative results in
the benchmark model, the local model, we find that the (multi-) TeV scale
can be probed at the (100) 14 TeV colliders.Comment: 34 pages, 8 figures, version to be published in Phys. Rev.
A simple modification of the maximal mixing scenario for three light neutrinos
We suggest a simple modification of the maximal mixing scenario (with
permutation symmetry) for three light neutrinos. Our neutrino mass matrix has
smaller permutation symmetry (), and
is consistent with all neutrino experiments except the Cl experiment.
The resulting mass eigenvalues for three neutrinos are for . Then these light neutrinos can account for
of the dark matter for . Our
model predicts the oscillation probability
in the range sensitive to the future experiments such as CHORUS and NOMAD.Comment: The title has been changed, to appear in Z. Phys.
SAIN: Self-Attentive Integration Network for Recommendation
With the growing importance of personalized recommendation, numerous
recommendation models have been proposed recently. Among them, Matrix
Factorization (MF) based models are the most widely used in the recommendation
field due to their high performance. However, MF based models suffer from cold
start problems where user-item interactions are sparse. To deal with this
problem, content based recommendation models which use the auxiliary attributes
of users and items have been proposed. Since these models use auxiliary
attributes, they are effective in cold start settings. However, most of the
proposed models are either unable to capture complex feature interactions or
not properly designed to combine user-item feedback information with content
information. In this paper, we propose Self-Attentive Integration Network
(SAIN) which is a model that effectively combines user-item feedback
information and auxiliary information for recommendation task. In SAIN, a
self-attention mechanism is used in the feature-level interaction layer to
effectively consider interactions between multiple features, while the
information integration layer adaptively combines content and feedback
information. The experimental results on two public datasets show that our
model outperforms the state-of-the-art models by 2.13%Comment: SIGIR 201
The Dual Roles of NF-kB Activation in Prx1+ Mesenchymal Cells in Health and Disease
Nuclear factor kappa-B (NF-kB) was discovered in 1986 and has since been studied extensively for its role as a master inflammatory transcription factor. As inflammation is critical for normal immune response but its chronic presence can be detrimental under pathological conditions, I sought to investigate the role of NF-kB in mesenchymal tissues under diabetic and homeostatic conditions. Aberrant activation of NF-kB and chronic inflammation have been documented in diabetic complications of kidney, eyes and cardiovascular system. Here I found that experimental type 1 diabetes caused hyperactivation of NF-kB in skeletal stem cells (SSCs) in the long bones of mice. Deletion of Ikkb, an activator of canonical NF-kB pathway, in Prx1+ (Paired Related Homeobox 1) SSCs prevented NF-kB activity and reversed the effect of diabetes on SSC apoptosis and anti-proliferation. In addition, it rescued the immuno-regulatory property of SSCs by transforming growth factor beta-1 (TGFb1), which in turn promoted macrophage polarization towards pro-resolving phenotype. These findings point to a detrimental role of NF-kB under pathologic condition such as type 1 diabetes. Surprisingly, I observed that NF-kB inactivation in Prx1+ cells caused hyper-inflammation and skin lesion that progressed with aging. The location of lesion was specific to ventral skin, consistent with the pattern of Prx1+ expression in mesenchyme derived from embryonic lateral plate mesoderm. Ikkb deletion in Col1a2Cre+ skin fibroblasts, but not Adipoq-Cre+ mature adipocytes, was sufficient to cause local inflammation but not in spleen or bone marrow. Single cell RNA sequencing analysis revealed an immune response that was characterized by an exaggerated inflammatory macrophage and type 2 T cell responses in the experimental animals. Furthermore, Prx1+ fibroblasts that had Ikkb deletion overexpressed CCL11 (also known as eotaxin-1), a potent chemoattractant for eosinophils. These results indicate Ikkb-NFkB activity in fibroblasts as an important contributor of immune homeostasis against an inflammatory response that mirrors the signs of atopic dermatitis. Thus, Ikkb-NFkB exhibits dual and opposing roles in Prx1+ mesenchymal cells where it is critical for homeostasis in dermal immunity, but it is detrimental in diabetic bone healing. These differential responses may be explained by the healthy or diseased status and/or by the niche-specific role of Prx1+ cells
Look at the First Sentence: Position Bias in Question Answering
Many extractive question answering models are trained to predict start and
end positions of answers. The choice of predicting answers as positions is
mainly due to its simplicity and effectiveness. In this study, we hypothesize
that when the distribution of the answer positions is highly skewed in the
training set (e.g., answers lie only in the k-th sentence of each passage), QA
models predicting answers as positions can learn spurious positional cues and
fail to give answers in different positions. We first illustrate this position
bias in popular extractive QA models such as BiDAF and BERT and thoroughly
examine how position bias propagates through each layer of BERT. To safely
deliver position information without position bias, we train models with
various de-biasing methods including entropy regularization and bias
ensembling. Among them, we found that using the prior distribution of answer
positions as a bias model is very effective at reducing position bias,
recovering the performance of BERT from 37.48% to 81.64% when trained on a
biased SQuAD dataset.Comment: 13 pages, EMNLP 202
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