217 research outputs found
Bottom-Flavored Mono-Tau Tails at the LHC
We study the effective field theory sensitivity of an LHC analysis for the
final state with an associated b-jet. To illustrate the improvement
due to the b-tagging, we first recast the recent CMS analysis in the
channel, using an integrated luminosity of 35.9 fb at TeV,
and provide limits on all the dimension-six effective operators which
contribute to the process. The expected limits from the b-tagged analysis are
then derived and compared. We find an improvement of approximately
in the bounds for operators with a b quark. We also discuss in detail possible
angular observables to be used as a discriminator between dimension-six
operators with different Lorentz structure. Finally, we study the impact of
these limits on some simplified scenarios aimed at addressing the observed
deviations from the Standard Model in lepton flavor universality ratios of
semileptonic B-meson decays. In particular, we compare the collider limits on
those scenarios set by our analysis either with or without the b-tagging,
assuming an integrated luminosity of 300 fb, with relevant low-energy
flavor measurements.Comment: 41 pages, 13 figures. The complete chi-square function for our CMS
recast is shared in ancillary files. v2: references added, matches the
version to be published in JHE
Statistical Beamformer Exploiting Non-stationarity and Sparsity with Spatially Constrained ICA for Robust Speech Recognition
In this paper, we present a statistical beamforming algorithm as a
pre-processing step for robust automatic speech recognition (ASR). By modeling
the target speech as a non-stationary Laplacian distribution, a mask-based
statistical beamforming algorithm is proposed to exploit both its output and
masked input variance for robust estimation of the beamformer. In addition, we
also present a method for steering vector estimation (SVE) based on a noise
power ratio obtained from the target and noise outputs in independent component
analysis (ICA). To update the beamformer in the same ICA framework, we derive
ICA with distortionless and null constraints on target speech, which yields
beamformed speech at the target output and noises at the other outputs,
respectively. The demixing weights for the target output result in a
statistical beamformer with the weighted spatial covariance matrix (wSCM) using
a weighting function characterized by a source model. To enhance the SVE, the
strict null constraints imposed by the Lagrange multiplier methods are relaxed
by generalized penalties with weight parameters, while the strict
distortionless constraints are maintained. Furthermore, we derive an online
algorithm based on an optimization technique of recursive least squares (RLS)
for practical applications. Experimental results on various environments using
CHiME-4 and LibriCSS datasets demonstrate the effectiveness of the presented
algorithm compared to conventional beamforming and blind source extraction
(BSE) based on ICA on both batch and online processing.Comment: Accepted by TASL
Group Theoretic Approach to Fermion Production
We propose a universal group theoretic description of the fermion production
through any type of interaction to scalar or pseudo-scalar. Our group theoretic
approach relies on the group , corresponding to the freedom
in choosing representations of the gamma matrices in Clifford algebra, under
which a part of the Dirac spinor function transforms like a fundamental
representation. In terms of a new () vector constructed out
of spinor functions, we show that fermion production mechanism can be analogous
to the classical dynamics of a vector precessing with the angular velocity. In
our group theoretic approach, the equation of motion takes a universal form for
any system, and choosing a different type of interaction or a different basis
amounts to selecting the corresponding angular velocity. The expression of the
particle number density is greatly simplified, compared to the traditional
approach, and it provides us with a simple geometric interpretation of the
fermion production dynamics. For the purpose of the demonstration, we focus on
the fermion production through the derivative coupling to the pseudo-scalar.Comment: 25 pages, 4 figures, v3: version accepted to JHEP. New Section V
adde
A Cosmic Window on the Dark Axion Portal
Axions and dark photons are common in many extensions of the Standard Model.
The dark axion portal -- an axion coupling to the dark photon and photon -- can
significantly modify their phenomenology. We study the cosmological constraints
on the dark axion portal from Cosmic Microwave Background (CMB) bounds on the
energy density of dark radiation, . By computing the
axion-photon-dark photon collision terms and solving the Boltzmann equations
including their effects, we find that light axions are generally more
constrained by than from supernova cooling or collider
experiments. However, with dark photons at the MeV scale, a window of parameter
space is opened up above the supernova limits and below the experimental
exclusion, allowing for axion decay constants as low as GeV.
This region also modifies indirectly the neutrino energy density, thus relaxing
the cosmological upper bound on the sum of neutrino masses. Future CMB
measurements could detect a signal or close this open window on the dark axion
portal.Comment: 27 pages, 9 figure
NeXt-TDNN: Modernizing Multi-Scale Temporal Convolution Backbone for Speaker Verification
In speaker verification, ECAPA-TDNN has shown remarkable improvement by
utilizing one-dimensional(1D) Res2Net block and squeeze-and-excitation(SE)
module, along with multi-layer feature aggregation (MFA). Meanwhile, in vision
tasks, ConvNet structures have been modernized by referring to Transformer,
resulting in improved performance. In this paper, we present an improved block
design for TDNN in speaker verification. Inspired by recent ConvNet structures,
we replace the SE-Res2Net block in ECAPA-TDNN with a novel 1D two-step
multi-scale ConvNeXt block, which we call TS-ConvNeXt. The TS-ConvNeXt block is
constructed using two separated sub-modules: a temporal multi-scale convolution
(MSC) and a frame-wise feed-forward network (FFN). This two-step design allows
for flexible capturing of inter-frame and intra-frame contexts. Additionally,
we introduce global response normalization (GRN) for the FFN modules to enable
more selective feature propagation, similar to the SE module in ECAPA-TDNN.
Experimental results demonstrate that NeXt-TDNN, with a modernized backbone
block, significantly improved performance in speaker verification tasks while
reducing parameter size and inference time. We have released our code for
future studies.Comment: Accepted by ICASSP 202
Effects of epicatechin, a crosslinking agent, on human dental pulp cells cultured in collagen scaffolds
Objective The purpose of this study was to investigate the biological effects of epicatechin (ECN), a crosslinking agent, on human dental pulp cells (hDPCs) cultured in collagen scaffolds. Material and Method To evaluate the effects of ECN on the proliferation of hDPCs, cell counting was performed using optical and fluorescent microscopy. Measurements of alkaline phosphatase (ALP) activity, alizarin red staining, and real-time polymerase chain reactions were performed to assess odontogenic differentiation. The compressive strength and setting time of collagen scaffolds containing ECN were measured. Differential scanning calorimetry was performed to analyze the thermal behavior of collagen in the presence of ECN. Results Epicatechin increased ALP activity, mineralized nodule formation, and the mRNA expression of dentin sialophosphoprotein (DSPP), a specific odontogenic-related marker. Furthermore, ECN upregulated the expression of DSPP in hDPCs cultured in collagen scaffolds. Epicatechin activated the extracellular signal-regulated kinase (ERK) and the treatment with an ERK inhibitor (U0126) blocked the expression of DSPP. The compressive strength was increased and the setting time was shortened in a dose-dependent manner. The number of cells cultured in the ECN-treated collagen scaffolds was significantly increased compared to the cells in the untreated control group. Conclusions Our results revealed that ECN promoted the proliferation and differentiation of hDPCs. Furthermore, the differentiation was regulated by the ERK signaling pathway. Changes in mechanical properties are related to cell fate, including proliferation and differentiation. Therefore, our study suggests the ECN treatment might be desirable for dentin-pulp complex regeneration
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