  We present constraints on the parameters of the $\Lambda$CDM cosmological
model in the presence of massive neutrinos, using the one-dimensional
Ly$\alpha$ forest power spectrum obtained with the Baryon Oscillation
Spectroscopic Survey (BOSS) of the Sloan Digital Sky Survey (SDSS) by
Palanque-Delabrouille et al. (2013), complemented by additional cosmological
probes. The interpretation of the measured Ly$\alpha$ spectrum is done using a
second-order Taylor expansion of the simulated power spectrum. BOSS
  Ly$\alpha$ data alone provide better bounds than previous Ly$\alpha$ results,
but are still poorly constraining, especially for the sum of neutrino masses
$\sum m_\nu$, for which we obtain an upper bound of 1.1~eV (95\% CL), including
systematics for both data and simulations. Ly$\alpha$ constraints on
$\Lambda$CDM parameters and neutrino masses are compatible with CMB bounds from
the Planck collaboration. Interestingly, the combination of Ly$\alpha$ with CMB
data reduces the uncertainties significantly, due to very different directions
of degeneracy in parameter space, leading to the strongest cosmological bound
to date on the total neutrino mass, $\sum m_\nu < 0.15$~eV at 95\% CL (with a
best-fit in zero). Adding recent BAO results further tightens this constraint
to $\sum m_\nu < 0.14$~eV at 95\% CL. This bound is nearly independent of the
statistical approach used, and of the different combinations of CMB and BAO
data sets considered in this paper in addition to Ly$\alpha$. Given the
measured values of the two squared mass differences $\Delta m^2$, this result
tends to favor the normal hierarchy scenario against the inverted hierarchy
scenario for the masses of the active neutrino species.


  Interesting emergent behavior in quantum materials arises when the
interaction of electrons with the lattice leads to partial localization and
ordering of charge at low temperatures. The triangular lattice of some
transition metal dichalcogenides additionally presents an interesting case,
where spin order is frustrated, leading to an additional complex interplay of
interactions involving spin, charge and lattice degrees of freedom. Here we
present a study of local symmetry breaking of the lattice structure in the
layered dichalcogenide material 1T-TaS$_{2}$ using x-ray pair-distribution
function measurements. Remarkably, we observe symmetry-breaking polaronic
distortions of the lattice structure around individual localized electrons at
temperatures well above any of the known long-range ordered phases. These
characteristic polaronic signatures remain on cooling through the spin and
charge ordered states, eventually revealing a new transition near 50 K to a
state displaying partially restored symmetry and significant inter-layer
dimerization. The order parameter associated with the observed local atomic
displacements and symmetry-allowed polaron spin structure in the ground state
suggests that charge ordering is driven by the crystallization of polarons,
rather than conventional Fermi surface nesting. Symmetry analysis shows that
the distorted structure is consistent with a breakup of the QSL phase at low
temperature, concurrent with the disappearance of domains in the charge order.


  Comparing Bayesian neural networks (BNNs) with different widths is
challenging because, as the width increases, multiple model properties change
simultaneously, and, inference in the finite-width case is intractable. In this
work, we empirically compare finite- and infinite-width BNNs, and provide
quantitative and qualitative explanations for their performance difference. We
find that when the model is mis-specified, increasing width can hurt BNN
performance. In these cases, we provide evidence that finite-width BNNs
generalize better partially due to the properties of their frequency spectrum
that allows them to adapt under model mismatch.


  We give a new proof for a theorem of Ehrhart regarding the
quasi-polynomiality of the function that counts the number of integer points in
the integral dilates of a rational polytope. The proof involves a geometric
bijection, inclusion-exclusion, and recurrence relations, and we also prove
Ehrhart reciprocity using these methods.


  This paper discusses proof-theoretic semantics, the project of specifying the
meanings of the logical constants in terms of rules of inference governing
them. I concentrate on Michael Dummett's and Dag Prawitz' philosophical
motivations and give precise characterisations of the crucial notions of
harmony and stability, placed in the context of proving normalisation results
in systems of natural deduction. I point out a problem for defining the meaning
of negation in this framework and prospects for an account of the meanings of
modal operators in terms of rules of inference.


  Fast domain wall motion in systems with perpendicular magnetization is
necessary for many novel applications such as the racetrack memory, domain wall
logic devices and artificial synapses. The domain wall speed has been greatly
improved after the demonstration of current driven domain wall motion using the
spin transfer torque, and later achieved another leap due to the combined
effect of spin-Hall effect and Dzyaloshinskii-Moriya interaction (DMI).
However, only Neel wall can be effectively driven in the latter system. In this
paper, we show that both Bloch and Neel domain walls can be effectively moved
by exploiting the field-like torque with the out-of-plane spin polarization,
which can be generated in materials with reduced symmetry. In addition, we find
that the Neel wall and Bloch walls stabilized by the magnetostatic energy are
easily distorted by the spin-orbit torque and they then enter the Walker
breakdown region. External magnetic field and DMI are introduced to stabilize
the domain wall, and a very high domain wall velocity over 500 m/s is obtained
at a moderate current density of $2\times 10^{11} A/m^2$. In principle, this
mechanism can be used to drive any types of domain walls. This work thus
provides new degrees of freedom in the control of domain wall motion.


  Let T be a d-regular tree (d > 2) and A=Aut(T), its automorphism group. Let G
be a group generated by n independent Haar-random elements of A. We show that
almost surely, every nontrivial element of G has finitely many fixed points on
T.


  We study the electronic and magnetic structure of carbon and nitrogen
impurities and interstitials in rutile TiO${_2}$. To this end we perform
\textit{ab-initio} calculations of a 48-atom supercell employing the VASP code.
In order to obtain a realistic description of the electronic and magnetic
structure, exchange and correlation are treated with the HSE06 hybrid
functional. Both, atomic positions and cell dimensions are fully relaxed.
Substitutional carbon and nitrogen are found to have a magnetic moment of 2 and
1$\mu{_B}$, respectively, with a tendency for anti-ferromagnetic long range
order. For C/N on interstitial sites we find that carbon is non-magnetic while
nitrogen always possesses a magnetic moment of 1$\mu{_B}$. We find that these
interstitial positions are on a saddle point of the total energy. The stable
configuration is reached when both carbon and nitrogen form a C-O and N-O dimer
with a bond length close to the double bond for CO and NO. This result is in
agreement with earlier experimental investigations detecting such N-O entities
from XPS measurements. The frequencies of the symmetric stretching mode are
calculated for these dimers, which could provide a means for experimental
verification. For all configurations investigated both C and N states are found
inside the TiO${_2}$ gap. These new electronic states are discussed with
respect to tuning doped TiO${_2}$ for the application in photocatalysis


  A potentiostat is an essential piece of analytical equipment for studying
electrochemical devices and reactions. As the design of electrochemical devices
evolve applications for systems with multiple working electrodes have become
more common. These applications drive a need for low-cost multi-channel
potentiostat systems. We have developed a portable low-cost scalable system
with a modular design that can support 8 to 64 channels at a cost as low as \$8
per channel. This design can replace the functionality of commercial
potentiostats which cost upwards of \$10k for certain applications. Each
channel in the multi-channel potentiostat has an independent adjustable voltage
source with a built-in ammeter and switch, making the device flexible for
various configurations. The multi-channel potentiostat is designed for low
current applications (nA range), but its purpose can change by varying its
shunt resistor value. The system can either function as a standalone device or
remotely controlled. We demonstrate the functionality of this system for the
control of a 24-channel bioelectronic ion pump for open- and closed- loop
control of pH.


  We construct several new families of vacuum solutions that describe black
holes in uniformly accelerated motion. They generalize the C-metric to the case
where the energy density and tension of the strings that pull (or push) on the
black holes are independent parameters. These strings create large curvatures
near their axis and when they have infinite length they modify the asymptotic
properties of the spacetime, but we discuss how these features can be dealt
with physically, in particular in terms of `wiggly cosmic strings'. We comment
on possible extensions, and extract lessons for the problem of finding
higher-dimensional accelerating black hole solutions.


  The globalization of the Integrated Circuit (IC) market is attracting an
ever-growing number of partners, while remarkably lengthening the supply chain.
Thereby, security concerns, such as those imposed by functional Reverse
Engineering (RE), have become quintessential. RE leads to disclosure of
confidential information to competitors, potentially enabling the theft of
intellectual property. Traditional functional RE methods analyze a given
gate-level netlist through employing pattern matching towards reconstructing
the underlying basic blocks, and hence, reverse engineer the circuit's
function.
  In this work, we are the first to demonstrate that applying Approximate
Computing (AxC) principles to circuits significantly improves the resiliency
against RE. This is attributed to the increased complexity in the underlying
pattern-matching process. The resiliency remains effective even for Graph
Neural Networks (GNNs) that are presently one of the most powerful
state-of-the-art techniques in functional RE. Using AxC, we demonstrate a
substantial reduction in GNN average classification accuracy-- from 98% to a
mere 53%. To surmount the challenges introduced by AxC in RE, we propose the
highly promising AppGNN platform, which enables GNNs (still being trained on
exact circuits) to: (i) perform accurate classifications, and (ii) reverse
engineer the circuit functionality, notwithstanding the applied approximation
technique. AppGNN accomplishes this by implementing a novel graph-based node
sampling approach that mimics generic approximation methodologies, requiring
zero knowledge of the targeted approximation type.
  We perform an extensive evaluation and show that, using our method, we can
improve the classification accuracy from 53% to 81% when classifying
approximate adder circuits that have been generated using evolutionary
algorithms, which our method is oblivious of.


  We give equivalent and sufficient criteria for the automorphism group of a
complete toric variety, respectively a Gorenstein toric Fano variety, to be
reductive. In particular we show that the automorphism group of a Gorenstein
toric Fano variety is reductive, if the barycenter of the associated reflexive
polytope is zero. Furthermore a sharp bound on the dimension of the reductive
automorphism group of a complete toric variety is proven by studying the set of
Demazure roots.


  Phylogenetic inference can potentially result in a more accurate tree using
data from multiple loci. However, if the loci are incongruent--due to events
such as incomplete lineage sorting or horizontal gene transfer--it can be
misleading to infer a single tree. To address this, many previous contributions
have taken a mechanistic approach, by modelling specific processes.
Alternatively, one can cluster loci without assuming how these incongruencies
might arise. Such "process-agnostic" approaches typically infer a tree for each
locus and cluster these. There are, however, many possible combinations of tree
distance and clustering methods; their comparative performance in the context
of tree incongruence is largely unknown. Furthermore, because standard model
selection criteria such as AIC cannot be applied to problems with a variable
number of topologies, the issue of inferring the optimal number of clusters is
poorly understood. Here, we perform a large-scale simulation study of
phylogenetic distances and clustering methods to infer loci of common
evolutionary history. We observe that the best-performing combinations are
distances accounting for branch lengths followed by spectral clustering or
Ward's method. We also introduce two statistical tests to infer the optimal
number of clusters and show that they strongly outperform the silhouette
criterion, a general-purpose heuristic. We illustrate the usefulness of the
approach by (i) identifying errors in a previous phylogenetic analysis of yeast
species and (ii) identifying topological incongruence among newly sequenced
loci of the globeflower fly genus Chiastocheta. We release treeCl, a new
program to cluster genes of common evolutionary history (http://git.io/treeCl).


  Learning effective high-order feature interactions is very crucial in the CTR
prediction task. However, it is very time-consuming to calculate high-order
feature interactions with massive features in online e-commerce platforms. Most
existing methods manually design a maximal order and further filter out the
useless interactions from them. Although they reduce the high computational
costs caused by the exponential growth of high-order feature combinations, they
still suffer from the degradation of model capability due to the suboptimal
learning of the restricted feature orders. The solution to maintain the model
capability and meanwhile keep it efficient is a technical challenge, which has
not been adequately addressed. To address this issue, we propose an adaptive
feature interaction learning model, named as EulerNet, in which the feature
interactions are learned in a complex vector space by conducting space mapping
according to Euler's formula. EulerNet converts the exponential powers of
feature interactions into simple linear combinations of the modulus and phase
of the complex features, making it possible to adaptively learn the high-order
feature interactions in an efficient way. Furthermore, EulerNet incorporates
the implicit and explicit feature interactions into a unified architecture,
which achieves the mutual enhancement and largely boosts the model
capabilities. Such a network can be fully learned from data, with no need of
pre-designed form or order for feature interactions. Extensive experiments
conducted on three public datasets have demonstrated the effectiveness and
efficiency of our approach. Our code is available at:
https://github.com/RUCAIBox/EulerNet.


  We explore whether an ultrasoft fermionic mode exists at extremely high
temperature in Yukawa theory with massless fermion (coupling constant is g). We
find that the fermion propagator has a pole at \omega = \pm p/3-i\zeta, for
ultrasoft momentum p, where \zeta \sim g^4T ln 1/g, and the residue is Z \sim
g^2. It is shown that one needs to take into account the asymptotic masses and
the damping rate of hard particles to get a sensible result for such an
ultrasoft fermionic mode; possible vertex correction turns out unnecessary for
the scalar coupling in contrast to the gauge coupling.


  Is there an algorithm that takes a game in normal form as input, and outputs
a Nash equilibrium? If the payoffs are integers, the answer is yes, and lot of
work has been done in its computational complexity. If the payoffs are
permitted to be real numbers, the answer is no, for continuity reasons. It is
worthwhile to investigate the precise degree of non-computability (the
Weihrauch degree), since knowing the degree entails what other approaches are
available (eg, is there a randomized algorithm with positive success change?).
The two player case has already been fully classified, but the multiplayer case
remains open and is addressed here. Our approach involves classifying the
degree of finding roots of polynomials, and lifting this to systems of
polynomial inequalities via cylindrical algebraic decomposition.


  This letter confirms the existence of heat transfer enhancement (HTE) and
reduction (HTR) in turbulent natural convection with polymer additives. HTE and
HTR were numerically predicted by Benzi et al.(PRL, 104, 024502, 2010) in
homogenous turbulent convection, but experiments by Ahlers & Nikolaenko(PRL,
104, 034503, 2010) in turbulent natural convection observed HTR only. Using
direct numerical simulation of natural convection, the present study reconciles
earlier numerical and experimental work on the basis of the dominant role of
polymer length in the polymer dynamics in extensional flows.


  This publication is to present a summary of research (referred as Klabs -
http://www.kappalabs.org) carried out in author's Ph.D studies on topic of
application of Logic Programming as scripting language for virtual character
behavior control in First Person Shooter (FPS) games. The research goal is to
apply reasoning and knowledge representation techniques to create character
behavior, which results in increased players' engagement. An extended abstract
/ full version of a paper accepted to be presented at the Doctoral Consortium
of the 30th International Conference on Logic Programming (ICLP 2014), July
19-22, Vienna, Austria


  A modified linear sigma model that allows for $g_A = 1.26$ by addition of
vector and pseudovector $\pi N$ coupling terms was discussed by Bjorken and
Nauenberg and by Lee. In this extended linear sigma model the elastic $\pi $N
scattering amplitudes satisfy the relevant chiral low-energy theorems, such as
the Weinberg-Tomozawa relation for the isovector scattering length and in some
cases Adler's "consistency condition". The agreement of the isospin symmetric
$\pi N$ scattering length with experiment is substantially improved in this
extended sigma model as compared with the original one. We show that the
nucleon sigma term ($\Sigma_N$) in the linear- and the extended sigma models
with three different kinds of chiral symmetry breaking terms are identical.
Within the tree approximation the formal operator expression for the $\Sigma_N$
term and the value extracted from the $\pi N$ scattering matrix coincide. Large
values of $\Sigma_N$ are easily obtained without any $s\bar s$ content of the
nucleon. Using chiral rotations the Lagrangian of this extended sigma model
reproduces the lowest-order $\pi N$ chiral perturbation theory Lagrangian.


  In recent years traditional numerical methods for accurate weather prediction
have been increasingly challenged by deep learning methods. Numerous historical
datasets used for short and medium-range weather forecasts are typically
organized into a regular spatial grid structure. This arrangement closely
resembles images: each weather variable can be visualized as a map or, when
considering the temporal axis, as a video. Several classes of generative
models, comprising Generative Adversarial Networks, Variational Autoencoders,
or the recent Denoising Diffusion Models have largely proved their
applicability to the next-frame prediction problem, and is thus natural to test
their performance on the weather prediction benchmarks. Diffusion models are
particularly appealing in this context, due to the intrinsically probabilistic
nature of weather forecasting: what we are really interested to model is the
probability distribution of weather indicators, whose expected value is the
most likely prediction.
  In our study, we focus on a specific subset of the ERA-5 dataset, which
includes hourly data pertaining to Central Europe from the years 2016 to 2021.
Within this context, we examine the efficacy of diffusion models in handling
the task of precipitation nowcasting. Our work is conducted in comparison to
the performance of well-established U-Net models, as documented in the existing
literature. Our proposed approach of Generative Ensemble Diffusion (GED)
utilizes a diffusion model to generate a set of possible weather scenarios
which are then amalgamated into a probable prediction via the use of a
post-processing network. This approach, in comparison to recent deep learning
models, substantially outperformed them in terms of overall performance.


  We formulate fractional difference equations of Riemann-Liouville and Caputo
type in a functional analytical framework. Main results are existence of
solutions on Hilbert space-valued weighted sequence spaces and a condition for
stability of linear fractional difference equations. Using a functional
calculus, we relate the fractional sum to fractional powers of the operator $1
- \tau^{-1}$ with the right shift $\tau^{-1}$ on weighted sequence spaces.
Causality of the solution operator plays a crucial role for the description of
initial value problems.


  We determine the ring structure of the loop homology of some global quotient
orbifolds. We can compute by our theorem the loop homology ring with suitable
coefficients of the global quotient orbifolds of the form $[M/G]$ for $M$ being
some kinds of homogeneous manifolds, and $G$ being a finte subgroup of a path
connected topological group $\mathcal{G}$ acting on $M$. It is shown that these
homology rings split into the tensor product of the loop homology ring
$\mathbb{H}_{*}(LM)$ of the manifold $M$ and that of the classifying space of
the finite group, which coincides with the center of the group ring $Z(k[G])$.


  We study how the orientational correlations of DNA confined to nanochannels
depend on the channel diameter D by means of Monte Carlo simulations and a
mean-field theory. This theory describes DNA conformations in the
experimentally relevant regime where the Flory-de Gennes theory does not apply.
We show how local correlations determine the dependence of the end-to-end
distance of the DNA molecule upon D. Tapered nanochannels provide the necessary
resolution in D to study experimentally how the extension of confined DNA
molecules depends upon D. Our experimental and theoretical results are in
qualitative agreement.


  Using available multiwavelength data for the pulsars of different ages
detected in the optical range, we analyze the efficiencies of the conversion of
the pulsar spindown power \dot{E} into the observed non-thermal luminosity L in
different spectral domains. We find that these pulsars show significantly
non-monotonic dependencies of the optical and X-ray efficiencies (\eta =
L/\dot{E}) versus pulsar age with a pronounced minimum at the beginning of the
middle-age epoch and comparably higher efficiencies of younger and older
pulsars. In addition, we find a strong correlation between the optical and
2--10 keV X-ray luminosities of these pulsars that implies the same origin of
their nonthermal emission in both spectral domains.


  P. Kirchberger proved that, for a finite subset $X$ of $\mathbb{R}^{d}$ such
that each point in $X$ is painted with one of two colors, if every $d+2$ or
fewer points in $X$ can be separated along the colors, then all the points in
$X$ can be separated along the colors. In this paper, we show a more colorful
theorem.


  It is well known that the distribution of simple random walks on $\bf{Z}$
conditioned on returning to the origin after $2n$ steps does not depend on $p=
P(S_1 = 1)$, the probability of moving to the right. Moreover, conditioned on
$\{S_{2n}=0\}$ the maximal displacement $\max_{k\leq 2n} |S_k|$ converges in
distribution when scaled by $\sqrt{n}$ (diffusive scaling).
  We consider the analogous problem for transient random walks in random
environments on $\bf{Z}$. We show that under the quenched law $P_\omega$
(conditioned on the environment $\omega$), the maximal displacement of the
random walk when conditioned to return to the origin at time $2n$ is no longer
necessarily of the order $\sqrt{n}$. If the environment is nestling (both
positive and negative local drifts exist) then the maximal displacement
conditioned on returning to the origin at time $2n$ is of order
$n^{\kappa/(\kappa+1)}$, where the constant $\kappa>0$ depends on the law on
environment. On the other hand, if the environment is marginally nestling or
non-nestling (only non-negative local drifts) then the maximal displacement
conditioned on returning to the origin at time $2n$ is at least
$n^{1-\varepsilon}$ and at most $n/(\ln n)^{2-\varepsilon}$ for any
$\varepsilon>0$.
  As a consequence of our proofs, we obtain precise rates of decay for
$P_\omega(X_{2n}=0)$. In particular, for certain non-nestling environments we
show that $P_\omega(X_{2n}=0) = \exp\{-Cn -C'n/(\ln n)^2 + o(n/(\ln n)^2) \}$
with explicit constants $C,C'>0$.


  We discuss the ground-state phase diagram of the one-dimensional
Bose-Fermi-Hubbard model (BFHM) in the limit of fast fermions based on an
effective boson model. We give a detailed derivation of the effective model
with long-range RKKY-type interactions, discuss its range of validity and
provide a deeper insight into its implications. In particular we show that
integrating out the fast fermion degrees of freedom in a naive way results in
an ill-behaved effective Hamiltonian and a proper renormalization is required.
Based on the effective Hamiltonian, the phase diagram in the thermodynamic
limit is constructed by analytic means and is compared to numerical results
obtained by density matrix renormalization group (DMRG) techniques for the full
BFHM. The most prominent feature of the phase diagram, the existence of a phase
separation between Mott insulator (MI) and charge density wave (CDW) is
discussed in depth including boundary effects.


  A method for selecting a suitable subspace for discriminating signal
components through an oblique projection is proposed. The selection criterion
is based on the consistency principle introduced by M. Unser and A. Aldroubi
and extended by Y. Elder. An effective implementation of this principle for the
purpose of subspace selection is achieved by updating of the dual vectors
yielding the corresponding oblique projector.


  The aim of this study is to analyze the stability of Alfven Eigenmodes (AE)
in the China Fusion Engineering Test Reactor (CFETR) plasma for steady state
operations. The analysis is done using the gyro-fluid code FAR3d including the
effect of the acoustic modes, EP Finite Larmor radius damping effects and
multiple energetic particle populations. Two high poloidal beta scenarios are
studied with respect to the location of the internal transport barrier (ITB) at
r/a = 0.45 (case A) and r/a = 0.6 (case B). Both operation scenarios show a
narrow TAE gap between the inner-middle plasma region and a wide EAE gap all
along the plasma radius. The AE stability of CFETR plasmas improves if the ITB
is located inwards, case A, showing AEs with lower growth rates with respect to
the case B. The AEs growth rate is smaller in the case A because the modes are
located in the inner-middle plasma region where the stabilizing effect of the
magnetic shear is stronger with respect to the case B. Multiple EP populations
effects (NBI driven EP + alpha articles) are negligible for the case A,
although the simulations for the case B show a stabilizing effect of the NBI EP
on the n=1 BAE caused by alpha particles during the thermalization process. If
the FLR damping effects are included in the simulations, the growth rate of the
EAE/NAE decreases up to 70 %, particularly for n > 3 toroidal families. Low n
AEs (n<6) show the largest growth rates. On the other hand, high $n$ modes (n=6
to 15) are triggered in the frequency range of the NAE, strongly damped by the
FLR effects.


  Hyperspectral/multispectral imaging (HSI/MSI) contains rich information
clinical applications, such as 1) narrow band imaging for vascular
visualisation; 2) oxygen saturation for intraoperative perfusion monitoring and
clinical decision making [1]; 3) tissue classification and identification of
pathology [2]. The current systems which provide pixel-level HSI/MSI signal can
be generally divided into two types: spatial scanning and spectral scanning.
However, the trade-off between spatial/spectral resolution, the acquisition
time, and the hardware complexity hampers implementation in real-world
applications, especially intra-operatively. Acquiring high resolution images in
real-time is important for HSI/MSI in intra-operative imaging, to alleviate the
side effect caused by breathing, heartbeat, and other sources of motion.
Therefore, we developed an algorithm to recover a pixel-level MSI stack using
only the captured snapshot RGB images from a normal camera. We refer to this
technique as "super-spectral-resolution". The proposed method enables recovery
of pixel-level-dense MSI signals with 24 spectral bands at ~11 frames per
second (FPS) on a GPU. Multispectral data captured from porcine bowel and
sheep/rabbit uteri in vivo has been used for training, and the algorithm has
been validated using unseen in vivo animal experiments.


  We propose a model for a spatially modulated collective state of
superconducting cuprates in which the electronic properties vary locally in
space. In this model the regions of higher hole density (called stripes) are
described as Luttinger liquids and the regions of lower density
(antiferromagnetic ladders) as an interacting bosonic gas of d$_{x^2-y^2}$ hole
pairs. We show that the transition to the superconducting state is topological
and driven by decay processes among these elementary excitations in the
presence of vibrations.


  Elaborating on the observation that two-particle unitarity-cuts of scattering
amplitudes can be computed by applying Stokes' Theorem, we relate the Optical
Theorem to the Berry Phase, showing how the imaginary part of arbitrary
one-loop Feynman amplitudes can be interpreted as the flux of a complex 2-form.


  Extreme natural disasters can have devastating effects on both urban and
rural areas. In any disaster event, an initial response is the key to rescue
within 72 hours and prompt recovery. During the initial stage of disaster
response, it is important to quickly assess the damage over a wide area and
identify priority areas. Among machine learning algorithms, deep anomaly
detection is effective in detecting devastation features that are different
from everyday features. In addition, explainable computer vision applications
should justify the initial responses. In this paper, we propose an anomaly
detection application utilizing deeper fully convolutional data descriptions
(FCDDs), that enables the localization of devastation features and
visualization of damage-marked heatmaps. More specifically, we show numerous
training and test results for a dataset AIDER with the four disaster
categories: collapsed buildings, traffic incidents, fires, and flooded areas.
We also implement ablation studies of anomalous class imbalance and the data
scale competing against the normal class. Our experiments provide results of
high accuracies over 95% for F1. Furthermore, we found that the deeper FCDD
with a VGG16 backbone consistently outperformed other baselines CNN27,
ResNet101, and Inceptionv3. This study presents a new solution that offers a
disaster anomaly detection application for initial responses with higher
accuracy and devastation explainability, providing a novel contribution to the
prompt disaster recovery problem in the research area of anomaly scene
understanding. Finally, we discuss future works to improve more robust,
explainable applications for effective initial responses.


  The canonical polyadic decomposition (CPD) of a low rank tensor plays a major
role in data analysis and signal processing by allowing for unique recovery of
underlying factors. However, it is well known that the low rank CPD
approximation problem is ill-posed. That is, a tensor may fail to have a best
rank $R$ CPD approximation when $R>1$.
  This article gives deterministic bounds for the existence of best low rank
tensor approximations over $\mathbb{K}=\mathbb{R}$ or $\mathbb{K}=\mathbb{C}$.
More precisely, given a tensor $\mathcal{T} \in \mathbb{K}^{I \times I \times
I}$ of rank $R \leq I$, we compute the radius of a Frobenius norm ball centered
at $\mathcal{T}$ in which best $\mathbb{K}$-rank $R$ approximations are
guaranteed to exist. In addition we show that every $\mathbb{K}$-rank $R$
tensor inside of this ball has a unique canonical polyadic decomposition. This
neighborhood may be interpreted as a neighborhood of "mathematical truth" in
with CPD approximation and computation is well-posed.
  In pursuit of these bounds, we describe low rank tensor decomposition as a
``joint generalized eigenvalue" problem. Using this framework, we show that,
under mild assumptions, a low rank tensor which has rank strictly greater than
border rank is defective in the sense of algebraic and geometric multiplicities
for joint generalized eigenvalues. Bounds for existence of best low rank
approximations are then obtained by establishing perturbation theoretic results
for the joint generalized eigenvalue problem. In this way we establish a
connection between existence of best low rank approximations and the tensor
spectral norm. In addition we solve a "tensor Procrustes problem" which
examines orthogonal compressions for pairs of tensors.
  The main results of the article are illustrated by a variety of numerical
experiments.


  We develop a method to compute shakeup effects on photoluminescence in a
Wigner crystal from localized holes. Our method treats the lattice electrons
and the tunneling electron on an equal footing, and uses a quantum-mechanical
calculation of the collective modes that is realistic throughout the Brillouin
zone. We find that shakeup produces a series of sidebands that may be
identified with maxima in the collective mode density of states, and
definitively distinguishes the crystal state from a liquid state. We also find
a shift in the main luminescence peak, that is associated with lattice
relaxation in the vicinity of a vacancy.


  In this paper, we investigate the optimization problem of joint source and
relay beamforming matrices for a twoway amplify-and-forward (AF) multi-input
multi-output (MIMO) relay system. The system consisting of two source nodes and
two relay nodes is considered and the linear minimum meansquare- error (MMSE)
is employed at both receivers. We assume individual relay power constraints and
study an important design problem, a so-called determinant maximization (DM)
problem. Since this DM problem is nonconvex, we consider an efficient iterative
algorithm by using an MSE balancing result to obtain at least a locally optimal
solution. The proposed algorithm is developed based on QL, QR and Choleskey
decompositions which differ in the complexity and performance. Analytical and
simulation results show that the proposed algorithm can significantly reduce
computational complexity compared with their existing two-way relay systems and
have equivalent bit-error-rate (BER) performance to the singular value
decomposition (SVD) based on a regular block diagonal (RBD) scheme.


  In this paper, we prove that entropy degeneracy and entropy explosion happen
in the flow constructed by Ohno. We also construct a flow which has the only
one invariant and ergodic measure supporting at a fixed point. This flow is no
entropy explosion.


  The widespread popularity of social media has led to an increase in hateful,
abusive, and sexist language, motivating methods for the automatic detection of
such phenomena. The goal of the SemEval shared task \textit{Towards Explainable
Detection of Online Sexism} (EDOS 2023) is to detect sexism in English social
media posts (subtask A), and to categorize such posts into four coarse-grained
sexism categories (subtask B), and eleven fine-grained subcategories (subtask
C). In this paper, we present our submitted systems for all three subtasks,
based on a multi-task model that has been fine-tuned on a range of related
tasks and datasets before being fine-tuned on the specific EDOS subtasks. We
implement multi-task learning by formulating each task as binary pairwise text
classification, where the dataset and label descriptions are given along with
the input text. The results show clear improvements over a fine-tuned
DeBERTa-V3 serving as a baseline leading to $F_1$-scores of 85.9\% in subtask A
(rank 13/84), 64.8\% in subtask B (rank 19/69), and 44.9\% in subtask C
(26/63).


  Sixth-order boundary value problems (BVPs) arise in thin-film flows with a
surface that has elastic bending resistance. To solve such problems, we first
derive a complete set of odd and even orthonormal eigenfunctions -- resembling
trigonometric sines and cosines, as well as the so-called ``beam'' functions.
These functions intrinsically satisfy boundary conditions (BCs) of relevance to
thin-film flows, since they are the solutions of a self-adjoint sixth-order
Sturm--Liouville BVP with the same BCs. Next, we propose a Galerkin spectral
approach for sixth-order problems; namely the sought function as well as all
its derivatives and terms appearing in the differential equation are expanded
into an infinite series with respect to the derived complete orthonormal (CON)
set of eigenfunctions. The unknown coefficients in the series expansion are
determined by solving the algebraic system derived by taking successive inner
products with each member of the CON set of eigenfunctions. The proposed method
and its convergence are demonstrated by solving two model sixth-order BVPs.


  A universal framework for modeling composites and fabrics of micro- and
nanofibers, such as carbon nanotubes, carbon fibers and amyloid fibrils, is
presented. Within this framework, fibers are represented with chains of rigid
bodies, linked with elastic bonds. Elasticity of the bonds utilizes recently
developed enhanced vector model formalism. The type of interactions between
fibers is determined by their nature and physical length scale of the
simulation. The dynamics of fibers is computed using the modification of rigid
particle dynamics module of the waLBerla multiphysics framework. Our modeling
system demonstrates exceptionally high parallel performance combined with the
physical accuracy of the modeling. The efficiency of our approach is
demonstrated with illustrative mechanical test on a hypothetical carbon
nanotube textile.


  Classical and quantum statistical mechanics are cast here in the language of
projective geometry to provide a unified geometrical framework for statistical
physics. After reviewing the Hilbert space formulation of classical statistical
thermodynamics, we introduce projective geometry as a basis for analysing
probabilistic aspects of statistical physics. In particular, the specification
of a canonical polarity on $RP^{n}$ induces a Riemannian metric on the state
space of statistical mechanics. In the case of the canonical ensemble, we show
that equilibrium thermal states are determined by the Hamiltonian gradient flow
with respect to this metric. This flow is concisely characterised by the fact
that it induces a projective automorphism on the state manifold. The
measurement problem for thermal systems is studied by the introduction of the
concept of a random state. The general methodology is then extended to include
the quantum mechanical dynamics of equilibrium thermal states. In this case the
relevant state space is complex projective space, here regarded as a real
manifold endowed with the natural Fubini-Study metric. A distinguishing feature
of quantum thermal dynamics is the inherent multiplicity of thermal
trajectories in the state space, associated with the nonuniqueness of the
infinite temperature state. We are then led to formulate a geometric
characterisation of the standard KMS-relation often considered in the context
of $C^{*}$-algebras. The example of a quantum spin one-half particle in heat
bath is studied in detail.


  A new approach to suppress ion backflow in multi-GEM structures is suggested.
In this approach, the potential difference applied across the gap between two
adjacent GEMs is reversed compared to the standard configuration. In such a gap
structure, called Electric Gate, a signal transfer from the first to second GEM
is presumably provided by the small residual field still existing at small gate
voltages and connecting the holes of the two GEMs. On the other hand, ion
backflow between the GEMs turned out to be substantially reduced. We also
consider another configuration, called Photoelectric Gate, in which in addition
to the Electric Gate configuration, a CsI photocathode is deposited on the
second GEM. In the Photoelectric Gate, ion backflow through the gap is fully
suppressed and the signal transfer through the gap is provided by the
photoelectric mechanism due to either avalanche scintillations in the first GEM
or proportional scintillations in the electroluminescence gap replacing the
first GEM. The idea of the Electric Gate might find applications in the field
of TPC detectors and gas photomultipliers. The idea of the Photoelectric Gate
is more relevant in the field of two-phase avalanche detectors.


  The production of positive pions and neutrons by cosmic muons at underground
sites of various depths is investigated. We first test the equivalent photon
method in the particular case of $\Delta$ excitation by the muon. We find that
this method, when it neglects the momentum dependence of the transverse
response, reproduces remarkably well the theoretical muon cross-section. This
success has lead us to apply the method to higher energies, where it has not
been tested. We evaluate in this way the production of positive pions in liquid
scintillator from known photo-absorption cross-sections. At a shallow depth of
20 meters our estimate reproduces the measurement. As for the neutron emission,
we include the obvious sources, such as the giant-resonance excitation, the
quasi-deuteron process, the quasi- free pion production as well as neutrons
emitted following pion capture. Our evaluation underestimates the number of
neutrons produced and finds a too weak dependence on the depth. This suggests
that secondary neutron production is important at all depths.


  We consider the example from invariant theory concerning the conjugation
action of the general linear group on several copies of the $n \times n$
matrices, and examine a symmetric function which stably describes the Hilbert
series for the invariant ring with respect to the multigradation by degree. The
terms of this Hilbert series may be described as a sum of squares of
Littlewood-Richardson coefficients. A "principal specialization" of the
gradation is then related to the Hilbert series of the $\K$-invariant subring
in the $\GL_n$-harmonic polynomials, where $\K$ denotes a block diagonal
embedding of a product of general linear groups. We also consider other
specializations of this Hilbert series.


  Micro-photoluminescence spectroscopy at variable temperature, excitation
intensity and energy was performed on a single InAs/AlAs self-assembled quantum
dot. The exciton emission line (zero-phonon line, ZPL) exhibits a broad
sideband due to exciton-acoustic phonon coupling by the deformation potential
mechanism. Additionally, narrow low-energy sidebands at about 0.25 meV of the
ZPL are attributed to exciton-acoustic phonon piezoelectric coupling. In
lowering the excitation energy or intensity these bands gradually dominate the
emission spectrum of the quantum dot while the ZPL disappears. At high
excitation intensity the sidebands due to piezoelectric coupling decrease
strongly and the ZPL dominates the spectrum as a consequence of screening of
the piezoelectric coupling by the photocreated free carriers.


  The program Synarcher for synonym (and related terms) search in the text
corpus of special structure (Wikipedia) was developed. The results of the
search are presented in the form of graph. It is possible to explore the graph
and search for graph elements interactively. Adapted HITS algorithm for synonym
search, program architecture, and program work evaluation with test examples
are presented in the paper. The proposed algorithm can be applied to a query
expansion by synonyms (in a search engine) and a synonym dictionary forming.


  We used the Lyon-Fedder-Mobarry global magnetohydrodynamics model to study
the effects of the interplanetary magnetic field (IMF) IMF $\mathit{B}_{y}$
component on the coupling between the solar wind and magnetosphere-ionosphere
system. When the IMF reconnects with the terrestrial magnetic field with IMF
$\mathit{B}_{y}$ $\neq$ 0, flux transport is asymmetrically distributed between
the two hemispheres. We describe how $\mathit{B}_{y}$ is induced in the closed
magnetosphere on both the dayside and nightside and present the governing
equations. The magnetosphere imposes asymmetric forces on the ionosphere, and
the effects on the ionospheric flow are characterized by distorted convection
cell patterns, often referred to as "banana" and "orange" cell patterns. The
flux asymmetrically added to the lobes results in a non-uniform induced
$\mathit{B}_{y}$ in the closed magnetosphere. By including the dynamics of the
system, we introduce a mechanism that predicts asymmetric Birkeland currents at
conjugate foot points. Asymmetric Birkeland currents are created as a
consequence of $\textit {y}$ directed tension contained in the return flow.
Associated with these currents, we expect fast localized ionospheric azimuthal
flows present in one hemisphere but not necessarily in the other. We also
present current density measurements from Active Magnetosphere and Planetary
Electrodynamics Response Experiment that are consistent with this picture. We
argue that the induced $\mathit{B}_{y}$ produces asymmetrical Birkeland
currents as a consequence of asymmetric stress balance between the hemispheres.
Such an asymmetry will also lead to asymmetrical foot points and asymmetries in
the azimuthal flow in the ionosphere. These phenomena should therefore be
treated in a unified way.


  Mathematical notation makes up a large portion of STEM literature, yet
finding semantic representations for formulae remains a challenging problem.
Because mathematical notation is precise, and its meaning changes significantly
with small character shifts, the methods that work for natural text do not
necessarily work well for mathematical expressions. This work describes an
approach for representing mathematical expressions in a continuous vector
space. We use the encoder of a sequence-to-sequence architecture, trained on
visually different but mathematically equivalent expressions, to generate
vector representations (or embeddings). We compare this approach with a
structural approach that considers visual layout to embed an expression and
show that our proposed approach is better at capturing mathematical semantics.
Finally, to expedite future research, we publish a corpus of equivalent
transcendental and algebraic expression pairs.


  We present a calculation of the two-loop quark-squark-gluino contributions to
pseudoscalar Higgs boson production via gluon fusion in the MSSM. We regularize
the loop integrals using the Pauli-Villars method, and obtain explicit and
compact analytic results based on an expansion in the heavy particle masses.
Our results - valid when the pseudoscalar Higgs boson is lighter than squarks
and gluinos - can be easily implemented in computer codes for an efficient and
accurate determination of the pseudoscalar production cross section.


  Motivated by recent experimental implementations of artificial gauge fields
for gases of cold atoms, we study the scattering properties of particles that
are subjected to time-periodic Hamiltonians. Making use of Floquet theory, we
focus on translationally invariant situations in which the single-particle
dynamics can be described in terms of spatially extended Floquet-Bloch waves.
We develop a general formalism for the scattering of these Floquet-Bloch waves.
An important role is played by the conservation of Floquet quasi-energy, which
is defined only up to the addition of integer multiples of $\hbar\omega$ for a
Hamiltonian with period $T=2\pi/\omega$. We discuss the consequences of this
for the interpretation of "elastic" and "inelastic" scattering in cases of
physical interest. We illustrate our general results with applications to: the
scattering of a single particle in a Floquet-Bloch state from a static
potential; and, the scattering of two particles in Floquet-Bloch states through
their interparticle interaction. We analyse examples of these scattering
processes that are closely related to the schemes used to general artifical
gauge fields in cold-atom experiments, through optical dressing of internal
states, or through time-periodic modulations of tight-binding lattices. We show
that the effects of scattering cannot, in general, be understood by an
effective time-independent Hamiltonian, even in the limit $\omega \to \infty$
of rapid modulation. We discuss the relative sizes of the elastic scattering
(required to stablize many-body phases) and of the inelastic scattering
(leading to deleterious heating effects). In particular, we describe how
inelastic processes that can cause significant heating in current experimental
set-up can be switched off by additional confinement of transverse motion.


  Background: The electric giant-dipole resonance (GDR) is the most established
collective vibrational mode of excitation. A charge-exchange analog, however,
has been poorly studied in comparison with the spin (magnetic) dipole resonance
(SDR). Purpose: I investigate the role of deformation on the charge-exchange
dipole excitations and explore the generic features as an isovector mode of
excitation. Methods: The nuclear energy-density functional method is employed
for calculating the response functions based on the
Skyrme--Kohn--Sham--Bogoliubov method and the proton-neuton
quasiparticle-random-phase approximation. Results: The deformation splitting
into $K=0$ and $K=\pm 1$ components occurs in the charge-changing channels and
is proportional to the magnitude of deformation as is well known for the GDR.
For the SDR, however, a simple assertion based on geometry of a nucleus cannot
be applied for explaining the vibrational frequencies of each $K$-component. A
qualitative argument on the strength distributions for each component is given
based on the non-energy-weighted sum rules taking nuclear deformation into
account. The concentration of the electric dipole strengths in low energy and
below the giant resonance is found in neutron-rich unstable nuclei.
Conclusions: The deformation splitting occurs generically for the
charge-exchange dipole excitions as in the neutral channel. The analog pygmy
dipole resonance can emerge in deformed neutron-rich nuclei as well as in
spherical systems.


  We extend the definition of the recently introduced valence bond entanglement
entropy to arbitrary SU(2) wave functions of S=1/2 spin systems. Thanks to a
reformulation of this entanglement measure in terms of a projection, we are
able to compute it with various numerical techniques for frustrated spin
models. We provide extensive numerical data for the one-dimensional J1-J2 spin
chain where we are able to locate the quantum phase transition by using the
scaling of this entropy with the block size. We also systematically compare
with the scaling of the von Neumann entanglement entropy. We finally underline
that the valence-bond entropy definition does depend on the choice of
bipartition so that, for frustrated models, a "good" bipartition should be
chosen, for instance according to the Marshall sign.


  We consider the possibility that along the thermal history of the Universe,
dark matter (DM) would have been created from Standard Model particles, either
through a kinetic mixing portal to an extra U(1) gauge field, or through the
Higgs portal. Depending solely on the DM particle mass, on the portal and on
the DM hidden sector interaction, we show how the observed DM relic density can
be obtained. There are four possible freeze-in/reannihilation/freeze-out
regimes, which together result in a simple characteristic relic density phase
diagram, with the shape of a "Mesa". In the case of the kinetic mixing portal,
we show that, unlike other freeze-in scenarios discussed in the literature, the
freeze-in regime can be probed by forthcoming DM direct detection experiments.
These results are well representative {of} any scenario where a DM hidden
sector would be created out of the Standard Model {sector}.


  Classification may not be reliable for several reasons: noise in the data,
insufficient input information, overlapping distributions and sharp definition
of classes. Faced with several possibilities neural network may in such cases
still be useful if instead of a classification elimination of improbable
classes is done. Eliminators may be constructed using classifiers assigning new
cases to a pool of several classes instead of just one winning class.
Elimination may be done with the help of several classifiers using modified
error functions. A real life medical application of neural network is presented
illustrating the usefulness of elimination.


  Interlocking logics are at the core of critical systems controlling the
traffic within stations. In this paper, we consider a generic interlocking
logic, which can be instantiated to control a wide class of stations. We tackle
the problem of parameterized verification, i.e. prove that the logic satisfies
the required properties for all the relevant stations. We present a simplified
case study, where the interlocking logic is directly encoded in Dafny. Then, we
show how to automate the proof of an important safety requirement, by
integrating simple, template-based invariants and more complex invariants
obtained from a model checker for parameterized systems. Based on these
positive preliminary results, we outline how we intend to integrate the
approach by extending the IDE for the design of the interlocking logic.


  This paper is a survey about recent progress in measure rigidity and global
rigidity of Anosov actions, and celebrates the profound contributions by
Federico Rodriguez Hertz to rigidity in dynamical systems.


  To the Hubbard model on a square lattice we add an interaction, $W$, which
depends upon the square of a near-neighbor hopping. We use zero temperature
quantum Monte Carlo simulations on lattice sizes up to $16 \times 16$, to show
that at half-filling and constant value of the Hubbard repulsion, the
interaction $W$ triggers a quantum transition between an antiferromagnetic Mott
insulator and a $d_{x^2 -y^2}$ superconductor. With a combination of finite
temperature quantum Monte Carlo simulations and the Maximum Entropy method, we
study spin and charge degrees of freedom in the superconducting state. We give
numerical evidence for the occurrence of a finite temperature
Kosterlitz-Thouless transition to the $d_{x^2 -y^2}$ superconducting state.
Above and below the Kosterlitz-Thouless transition temperature, $T_{KT}$, we
compute the one-electron density of states, $N(\omega)$, the spin relaxation
rate $1/T_1$, as well as the imaginary and real part of the spin susceptibility
$\chi(\vec{q},\omega)$. The spin dynamics are characterized by the vanishing of
$1/T_1$ and divergence of $Re \chi(\vec{q} = (\pi,\pi), \omega = 0)$ in the low
temperature limit. As $T_{KT}$ is approached $N(\omega)$ develops a pseudo-gap
feature and below $T_{KT}$ $Im \chi(\vec{q} = (\pi,\pi), \omega)$ shows a peak
at finite frequency.


  A preliminary investigation of the anti-K N interaction is performed within a
chiral constituent quark model by solving the resonating group method (RGM)
equation. The model parameters are taken from our previous work, which gave a
satisfactory description of the S-, P-, D-, F-wave KN scattering phase shifts.
The channel-coupling between anti-K N, pi Lambda and pi Sigma is considered,
and the scattering phase shifts as well as the bound-state problem of anti-K N
are dynamically studied. The results show that the S-wave anti-K N interaction
in the isospin I=0 channel is attractive, and in the extended chiral SU(3)
quark model such an attraction can make for an anti-K N bound state, which
appears as a pi Sigma resonance in the coupled-channel calculation, while the
chiral SU(3) quark model cannot accommodate the existence of an anti-K N bound
state. It seems that the vector meson exchanges are necessary to be introduced
in the quark-quark interactions if one tries to explain the Lambda(1405) as an
anti-K N bound state or a pi Sigma - anti-K N resonance state.


  The Drell-Yan process for proton incident on nuclei is an excellent place for
deeply studying the parton propagation in a nucleus. By means of the nuclear
parton distributions determined only with lepton-nuclear deep inelastic
scattering experimental data and the analytic parameterization of quenching
weight based on BDMPS formalism, a phenomenological analysis of the nuclear
Drell-Yan differential cross section ratio as a function of Feynman variable is
performed from Fermilab E906 and E866 experimental data. With the nuclear
geometry effect on nuclear Drell-Yan process and the quark transport
coefficient as a constant, our predictions are in good agreement with the
experimental measurements. It is found that nuclear geometry effect has a
significant impact on the quark transport coefficient in cold nuclear matter.
It is necessary to consider the detailed nuclear geometry in studying the
nuclear Drell-Yan process. Our calculated results reveal that the difference in
the values of quark transport coefficient exists from E906 and E866
experiments. However, confirming the conclusion that the quark transport
coefficient depends on the target-quark momentum fraction, still need more
accurate experimental data on the Drell-Yan differential cross section ratio in
the future. Three models are proposed and discussed for the quark transport
coefficient as a function of the measurable kinematic variables. The quark
transport coefficient $\hat{q}$ is determined as a function of the Bjorken
variable $x_2$ and scale $Q^2$. It is hoped that the parametrization form of
quark transport coefficient in the cold nuclear medium can help to think about
the parton propagation mechanism in nuclear matter.


  Named Entity Recognition (NER) aims at locating and classifying named
entities in text. In some use cases of NER, including cases where detected
named entities are used in creating content recommendations, it is crucial to
have a reliable confidence level for the detected named entities. In this work
we study the problem of finding confidence levels for detected named entities.
We refer to this problem as Named Entity Sequence Classification (NESC). We
frame NESC as a binary classification problem and we use NER as well as
recurrent neural networks to find the probability of candidate named entity is
a real named entity. We apply this approach to Tweet texts and we show how we
could find named entities with high confidence levels from Tweets.


  We report the rf performance of a single-cell superconducting radiofrequency
cavity after low temperature baking in a nitrogen environment. A significant
increase in quality factor has been observed when the cavity was heat treated
in the temperature range of 120-160 {\deg}C with a nitrogen partial pressure of
~25 mTorr. This increase in quality factor as well as the Q-rise phenomenon
(anti-Q-slope) is similar to those previously obtained with high temperature
nitrogen doping as well as titanium doping. In this study, a cavity N2-treated
at 120 {\deg}C and at140 {\deg}C, showed no degradation in accelerating
gradient, however the accelerating gradient was degraded by 25 with a 160
{\deg}C N2 treatment. Sample coupons treated in the same conditions as the
cavity were analyzed by scanning electron microscope, x-ray photoelectron
spectroscopy and secondary ion mass spectroscopy revealed a complex surface
composition of Nb_2O5, NbO and NbN(1-x)Ox within the rf penetration depth.
Furthermore, magnetization measurements showed no significant change on bulk
superconducting properties.


  We study a simplified version of the Standard Electroweak Model and introduce
the concept of the physical gauge invariant effective potential in terms of
matrix elements of the Hamiltonian in physical states. This procedure allows an
unambiguous identification of the symmetry breaking order parameter and the
resulting effective potential as the energy in a constrained state. We
explicitly compute the physical effective potential at one loop order and
improve it using the RG. This construction allows us to extract a reliable,
gauge invariant bound on the Higgs mass by unambiguously obtaining the scale at
which new physics should emerge to preclude vacuum instability. Comparison is
made with popular gauge fixing procedures and an ``error'' estimate is provided
between the Landau gauge fixed and the gauge invariant results.


  Observation of resonance modes is the most straightforward way of studying
mechanical oscillations because these modes have maximum response to stimuli.
However, a deeper understanding of mechanical motion could be obtained by also
looking at modal responses at frequencies in between resonances. A common way
to do this is to force a mechanical object into oscillations and study its
off-resonance behaviour. In this paper, we present visualisation of the modal
response shapes for a mechanical drum driven off resonance. By using the
frequency modal analysis, we describe these shapes as a superposition of
resonance modes. We find that the spatial distribution of the oscillating
component of the driving force affects the modal weight or participation.
Moreover, we are able to infer the asymmetry of the drum by studying the
dependence of the resonance modes shapes on the frequency of the driving force.
Our results highlight that dynamic responses of any mechanical system are
mixtures of their resonance modes with various modal weights, further giving
credence to the universality of this phenomenon.


  The trend towards mobile devices usage has put more than ever the Web as a
ubiquitous platform where users perform all kind of tasks. In some cases, users
access the Web with 'native' mobile applications developed for well-known
sites, such as LinkedIn, Facebook, Twitter, etc. These native applications
might offer further (e.g. location-based) functionalities to their users in
comparison with their corresponding Web sites, because they were developed with
mobile features in mind. However, most Web applications have not this native
mobile counterpart and users access them using browsers in the mobile device.
Users might eventually want to add mobile features on these Web sites even
though those features were not supported originally. In this paper we present a
novel approach to allow end users to augment their preferred Web sites with
mobile features. This end-user approach is supported by a framework for mobile
Web augmentation that we describe in the paper. We also present a set of
supporting tools and a validation experiment with end users.


  We consider an asexual population under strong selection-weak mutation
conditions evolving on rugged fitness landscapes with many local fitness peaks.
Unlike the previous studies in which the initial fitness of the population is
assumed to be high, here we start the adaptation process with a low fitness
corresponding to a population in a stressful novel environment. For generic
fitness distributions, using an analytic argument we find that the average
number of steps to a local optimum varies logarithmically with the genotype
sequence length and increases as the correlations amongst genotypic fitnesses
increase. When the fitnesses are exponentially or uniformly distributed, using
an evolution equation for the distribution of population fitness, we
analytically calculate the fitness distribution of fixed beneficial mutations
and the walk length distribution.


  The weak $(1,1)$ boundedness of (local) Riesz transforms corresponding to a
large class of Schr\"{o}dinger operators on vector bundles is proved, mainly
assuming the generalized volume doubling condition, either Gaussian or
sub-Gaussian upper bounds for the heat kernel only in short time, and
derivative estimates of Bismut type for the corresponding semigroup.


  We show that a reflective/coreflective pair of full subcategories satisfies a
"maximal-normal"-type equivalence if and only if it is an associated pair in
the sense of Kelly and Lawvere.


  While general relativity possesses local Lorentz invariance, both canonical
quantum gravity and string theory suggest that Lorentz invariance may be broken
at high energies. Broken Lorentz invariance has also been postulated as an
explanation for astrophysical anomalies such as the missing GZK cutoff.
Therefore, we seek an effective field theory description of gravity where
Lorentz invariance is broken. We will construct a candidate theory and then
briefly discuss some of the implications.


  We complement previous functional renormalization group (fRG) studies of the
two-dimensional Hubbard model by mean-field calculations. The focus falls on
Van Hove filling and the the hopping amplitude t'/t=0.341. The fRG data suggest
a quantum critical point (QCP) in this region and in its vicinity a singular
fermionic self-energy, Im $\Sigma(\omega)/\omega \sim |\omega|^{-\gamma}$ with
$\gamma\approx 0.26$. Here we start a more detailed investigation of this QCP
using a bosonic formulation for the effective action, where the bosons couple
to the order parameter fields. To this end, we use the channel decomposition of
the fermionic effective action developed in [Phys. Rev. B 79, 195125 (2009)],
which allows to perform Hubbard-Stratonovich transformations for all relevant
order parameter fields at any given energy scale. We stop the flow at a scale
where the correlations of the order parameter field are already pronounced, but
the flow is still regular, and derive the effective boson theory. It contains
d-wave superconducting, magnetic, and density-density interactions. We analyze
the resulting phase diagram in the mean-field approximation. We show that the
singular fermionic self-energy suppresses gap formation both in the
superconducting and magnetic channel already at the mean-field level, thus
rounding a first-order transition (without self-energy) to a quantum phase
transition (with self-energy). We give a simple effective model that shows the
generality of this effect. In the two-dimensional Hubbard model, the effective
density-density interaction is peaked at a nonzero frequency, so that solving
the mean-field equations already involves a functional equation instead of
simply a matrix equation (on a technical level, similar to incommensurate
phases). Within a certain approximation, we show that such an interaction leads
to a short quasiparticle lifetime.


  We propose an explicit model, where an axionic domain wall dynamically
localizes a U(1)-component of a nonabelian gauge theory living in a 3+1
dimensional bulk. The effective theory on the wall is 2+1d Maxwell-Chern-Simons
theory with a compact U(1) gauge group. This setup allows us to understand all
key properties of MCS theory in terms of the dynamics of the underlying 3+1
dimensional gauge theory. Our findings can also shed some light on branes in
supersymmetric gluodynamics.


  Let R be a class of groups closed under taking semidirect products with
finite kernel and fully residually R-groups. We prove that R contains all
R-by-{finitely generated residually finite} groups. It follows that a
semidirect product of a finitely generated residually finite group with a
surjunctive group is surjunctive. This remained unknown even for direct
products of a surjunctive group with the integers Z.


  With potential relevance to biomechanics, an interesting problem in
statistical mechanics not previously solved is a binary mechanical model
system. Discrete chemical states of proteins are often associated with discrete
metastable structural states, such that with a change in state a protein acts
as a molecular switch. An ensemble of molecular switches that displace
compliant elements equilibrated with an external force, F, constitutes a binary
mechanical model system. As one in a series of publications developing this
model, here I consider the mechanical performance of this system. Four
processes naturally emerge from a transient analysis which are consistent with
the four phases observed in a muscle force transient.


  Online information has increased tremendously in today's age of Internet. As
a result, the need has arose to extract relevant content from the plethora of
available information. Researchers are widely using automatic text
summarization techniques for extracting useful and relevant information from
voluminous available information, it also enables users to obtain valuable
knowledge in a limited period of time with minimal effort. The summary obtained
from the automatic text summarization often faces the issues of diversity and
information coverage. Promising results are obtained for automatic text
summarization by the introduction of new techniques based on graph ranking of
sentences, clustering, and optimization. This research work proposes CoRank, a
two-stage sentence selection model involving clustering and then ranking of
sentences. The initial stage involves clustering of sentences using a novel
clustering algorithm, and later selection of salient sentences using CoRank
algorithm. The approach aims to cover two objectives: maximum coverage and
diversity, which is achieved by the extraction of main topics and sub-topics
from the original text. The performance of the CoRank is validated on DUC2001
and DUC 2002 data sets.


  We say that the polynomial sequence $(Q^{(\lambda)}_n)$ is a semiclassical
Sobolev polynomial sequence when it is orthogonal with respect to the inner
product $$ <p, r>_S=<{{\bf u}} ,{p\, r}> +\lambda <{{\bf u}}, {{\mathscr D}p
\,{\mathscr D}r}>, $$ where ${\bf u}$ is a semiclassical linear functional,
${\mathscr D}$ is the differential, the difference or the $q$--difference
operator, and $\lambda$ is a positive constant. In this paper we get algebraic
and differential/difference properties for such polynomials as well as
algebraic relations between them and the polynomial sequence orthogonal with
respect to the semiclassical functional $\bf u$. The main goal of this article
is to give a general approach to the study of the polynomials orthogonal with
respect to the above nonstandard inner product regardless of the type of
operator ${\mathscr D}$ considered. Finally, we illustrate our results by
applying them to some known families of Sobolev orthogonal polynomials as well
as to some new ones introduced in this paper for the first time.


  We identify and analyze statistical regularities and irregularities in the
recent order flow of different NASDAQ stocks, focusing on the positions where
orders are placed in the orderbook. This includes limit orders being placed
outside of the spread, inside the spread and (effective) market orders. We find
that limit order placement inside the spread is strongly determined by the
dynamics of the spread size. Most orders, however, arrive outside of the
spread. While for some stocks order placement on or next to the quotes is
dominating, deeper price levels are more important for other stocks. As market
orders are usually adjusted to the quote volume, the impact of market orders
depends on the orderbook structure, which we find to be quite diverse among the
analyzed stocks as a result of the way limit order placement takes place.


  This paper deals with the analytic derivation of a complete equation of state
(EOS) for solids from shock-wave data in the range of pressures and
temperatures, attained by detonation of chemical explosives. The caloric, the
thermal and the incomplete EOS are determined as well. An equation for the
shock temperature along the Hugoniot curve is derived also.


  Most communication systems use some form of feedback, often related to
channel state information. The common models used in analyses either assume
perfect channel state information at the receiver and/or noiseless state
feedback links. However, in practical systems, neither is the channel estimate
known perfectly at the receiver and nor is the feedback link perfect. In this
paper, we study the achievable diversity multiplexing tradeoff using i.i.d.
Gaussian codebooks, considering the errors in training the receiver and the
errors in the feedback link for FDD systems, where the forward and the feedback
are independent MIMO channels.
  Our key result is that the maximum diversity order with one-bit of feedback
information is identical to systems with more feedback bits. Thus,
asymptotically in $\mathsf{SNR}$, more than one bit of feedback does not
improve the system performance at constant rates. Furthermore, the one-bit
diversity-multiplexing performance is identical to the system which has perfect
channel state information at the receiver along with noiseless feedback link.
This achievability uses novel concepts of power controlled feedback and
training, which naturally surface when we consider imperfect channel estimation
and noisy feedback links. In the process of evaluating the proposed training
and feedback protocols, we find an asymptotic expression for the joint
probability of the $\mathsf{SNR}$ exponents of eigenvalues of the actual
channel and the estimated channel which may be of independent interest.


  It is well-known that a compact Riemannian spin manifold can be reconstructed
from its canonical spectral triple which consists of the algebra of smooth
functions, the Hilbert space of square integrable spinors and the Dirac
operator. It seems to be a folklore fact that the metric can be reconstructed
up to conformal equivalence if one replaces the Dirac operator D by sign(D). We
give a precise formulation and proof of this fact.


  The anisotropic Navier-Stokes system arises in geophysical fluid dynamics,
which is derived by changing $-\nu\D$ in the classical Navier-Stokes system to
$-(\nu_1\partial^2_1+\nu_2\partial^2_2+\nu_3\partial^2_3)$. Here
$\nu_1,\,\nu_2\,,\nu_3$ are the viscous coefficients, which can be different
from each other. This reflects that the fluid can behave differently in each
direction.
  The purpose of this paper is to derive some lower bound estimates on the
lifespan to such anisotropic Navier-Stokes system. We not only investigate the
case when $\nu_1,\,\nu_2\,,\nu_3$ are all positive, but also the more
sophisticated cases when one or two of them vanish. We find that in these lower
bound estimates, the weights of $\nu_1,\,\nu_2\,,\nu_3$ are not equal. A
detailed study of this problem can also help us to have a better understanding
of the nonlinear structure in the classical Navier-Stokes system.


  Classical mechanics is a singular theory in that real-energy classical
particles can never enter classically forbidden regions. However, if one
regulates classical mechanics by allowing the energy E of a particle to be
complex, the particle exhibits quantum-like behavior: Complex-energy classical
particles can travel between classically allowed regions separated by potential
barriers. When Im(E) -> 0, the classical tunneling probabilities persist.
Hence, one can interpret quantum tunneling as an anomaly. A numerical
comparison of complex classical tunneling probabilities with quantum tunneling
probabilities leads to the conjecture that as ReE increases, complex classical
tunneling probabilities approach the corresponding quantum probabilities. Thus,
this work attempts to generalize the Bohr correspondence principle from
classically allowed to classically forbidden regions.


  In this paper, we give the spinor wave equations of free and unfree photon,
which are the differential equation of space-time one order. For the free
photon, the spinor wave equations are covariant, and the spinors $\psi$ are
corresponding to the the reducibility representations $D^{10}+D^{01}$ and
$D^{10}+D^{01}+D^{1/2 1/2}$ of the proper Lorentz group.


  We study the full bosonic spectrum around giant and dual giant graviton
probes in exactly marginally deformed backgrounds. Considering supersymmetric
and non-supersymmetric three-parameter deformations of AdS_5 X S^5, we perform
a detailed analysis of small fluctuations for both the expanded D3-brane
configurations. In particular, we enhance the scalar spectra of frequencies
found in our previous paper hep-th/0609173 with the important contributions
brought by the gauge field fluctuations. The giant graviton case exhibits a
non-trivial coupling between scalar and vector modes driven by the deformation,
whose resolution yields to a universal correction of the undeformed spectrum.
On the other hand, dual giant vibrations turn out to be completely decoupled.
From our results one can also easily read the gauge field fluctuations in the
undeformed (dual) giant graviton scenario.


  A theorem of Pfister asserts that every $12$-dimensional quadratic form with
trivial discriminant and trivial Clifford invariant over a field of
characteristic different from $2$ decomposes as a tensor product of a binary
quadratic form and a $6$-dimensional quadratic form with trivial discriminant.
The main result of the paper extends Pfister's result to orthogonal
involutions: every central simple algebra of degree $12$ with orthogonal
involution of trivial discriminant and trivial Clifford invariant decomposes
into a tensor product of a quaternion algebra and a central simple algebra of
degree $6$ with orthogonal involutions. This decomposition is used to establish
a criterion for the existence of orthogonal involutions with trivial invariants
on algebras of degree $12$, and to calculate the $f_3$-invariant of the
involution if the algebra has index $2$.


  We show, either quantum mechanically or classically, that the variation of
the effective mass induced in a charged particle by the presence of an
ultra-strong electromagnetic field may lead to observable consequences. In
particular, we discuss how this effect may operate on electrons close to the
surface of a magnetar, a neutron star with a super-strong magnetic field of the
order of $10^{11}$ Tesla.


  Motivated by the recent experimental observations, we discuss the freeze-out
properties of the fireball created in central heavy ion collisions. We find
that the freeze-out conditions, like temperature, velocity gradient near center
of the fireball, are similar for different colliding systems and beam energies.
This means that the transverse flow is stronger in the collisions of heavy
nuclei than that of the light ones.


  This paper deals with an open problem posed by Jleli and Samet in \cite[\,
M.~Jleli and B.~Samet, On a new generalization of metric spaces, J. Fixed Point
Theory Appl, 20(3) 2018]{JS1}. In \cite[\, Remark 5.1]{JS1} They asked whether
the Cantor's intersection theorem can be extended to $\mathcal{F}$-metric
spaces or not. In this manuscript we give an affirmative answer to this open
question. We also show that the notions of compactness, totally boundedness in
the setting of $\mathcal{F}$-metric spaces are equivalent to that of usual
metric spaces.


  Synthetically created Cross-Lingual Summarisation (CLS) datasets are prone to
include document-summary pairs where the reference summary is unfaithful to the
corresponding document as it contains content not supported by the document
(i.e., hallucinated content). This low data quality misleads model learning and
obscures evaluation results. Automatic ways to assess hallucinations and
improve training have been proposed for monolingual summarisation,
predominantly in English. For CLS, we propose to use off-the-shelf
cross-lingual Natural Language Inference (X-NLI) to evaluate faithfulness of
reference and model generated summaries. Then, we study training approaches
that are aware of faithfulness issues in the training data and propose an
approach that uses unlikelihood loss to teach a model about unfaithful summary
sequences. Our results show that it is possible to train CLS models that yield
more faithful summaries while maintaining comparable or better informativess.


  As global supply chains and freight volumes grow, the U.S. faces escalating
transportation demands. The heavy reliance on road transport, coupled with the
underutilization of the railway system, results in congested highways,
prolonged transportation times, higher costs, and increased carbon emissions.
California's San Pedro Port Complex (SPPC), the nation's busiest, incurs a
significant share of these challenges. We utilize an agent-based simulation to
replicate real-world scenarios, focusing on the intricacies of interactions in
a modified intermodal inbound freight system for the SPPC. This involves
relocating container classification to potential warehouses in California,
Utah, Arizona, and Nevada, rather than exclusively at port areas. Our primary
aim is to evaluate the proposed system's efficiency, considering cost and
freight throughput, while also examining the effects of workforce shortages.
Computational analysis suggests that strategically installing intermodal
capabilities in select warehouses can reduce transportation costs, boost
throughput, and foster resour


  Efficient methods for generating samples of wave packet trajectories are
needed to build machine learning models for quantum dynamics. However,
simulating such data by direct integration of the time-dependent Schrodinger
equation can be demanding, especially when multiple spatial dimensions and
realistic potentials are involved. In this paper, we present a graphics
processor unit (GPU) implementation of the finite-difference time-domain (FDTD)
method for simulating the time-dependent Schrodinger equation. The performance
of our implementation is characterized in detail by simulating electron
diffraction from realistic material surfaces. On our hardware, our GPU
implementation achieves a roughly 350 times performance increase compared to a
serial CPU implementation. The suitability of our implementation for generating
samples of quantum dynamics data is also demonstrated by performing electron
diffraction simulations from multiple configurations of an organic thin film.
By studying how the structure of the data converges with sample sizes, we
acquire insights into the sample sizes required for machine learning purposes.


  In this paper we report the results of a thorough numerical study of the
motion of spinning particles in Kerr spacetime with different prescriptions. We
first evaluate the Mathisson-Papapetrou equations with two different spin
supplementary conditions, namely, the Tulczyjew and the Newton-Wigner, and make
a comparison of these two cases. We then use the Hamiltonian formalism given by
Barausse, Racine, and Buonanno in [Phys. Rev. D, 80, 104025 (2009)] to evolve
the orbits and compare them with the corresponding orbits provided by the
Mathisson-Papapetrou equations. We include a full description of how to treat
the issues arising in the numerical implementation.


  We determine the strong couplings of three mesons that involve, at least, one
$\eta_c$ or $J/\psi$ meson, within the framework of a constituent-quark model
by means of relativistic dispersion formulations. For strong couplings of
$J/\psi$ mesons to two charmed mesons, our approach leads to predictions
roughly twice as large as those arising from QCD sum rules.


  Vehicle safety is one of the most challenging aspect of future-generation
autonomous and semi-autonomous vehicles. Collision warning systems (CCWs), as a
proposed solution framework, can be relied as the main structure to address the
issues in this area. In this framework, information plays a very important
role. Each vehicle has access to its own information immediately. However,
another vehicle information is available through a wireless communication. Data
loss is very common issue for such communication approach. As a consequence,
CCW would suffer from providing late or false detection awareness. Robust
estimation of lost data is of this paper interest which its goal is to
reconstruct or estimate lost network data from previous available or estimated
data as close to actual values as possible under different rate of lost. In
this paper, we will investigate and evaluate three different algorithms
including constant velocity, constant acceleration and Kalman estimator for
this purpose. We make a comparison between their performance which reveals the
ability of them in term of accuracy and robustness for estimation and
prediction based on previous samples which at the end affects the quality of
CCW in awareness generation.


  Let $M$ denote the centered Hardy--Littlewood operator on $\mathbb{R}$. We
prove that \[ {\rm Var} (Mf)\le {\rm Var} (f) - \frac12\big|
|f(\infty)|-|f(-\infty)|\big| \] for piecewise constant functions $f$ with
nonzero and zero values alternating. The above inequality strengthens a recent
result of Bilz and Weigt proved for indicator functions of bounded variation
vanishing at $\pm\infty$. We conjecture that the inequality holds for all
functions of bounded variation, which is a stronger version of the known
conjecture ${\rm Var} (Mf)\le {\rm Var} (f)$. We also obtain the discrete
counterpart of our theorem, moreover proving a transference result on
equivalency between both settings that is of independent interest.


  Recently, square-net materials have attracted lots of attention for the Dirac
semimetal phase with negligible spin-orbit coupling (SOC) gap, e.g.
ZrSiS/LaSbTe and CaMnSb$_2$. In this paper, we demonstrate that the Jahn-Teller
effect enlarges the nontrivial SOC gap in the distorted structure, e.g. LaAsS
and SrZnSb$_2$. Its distorted $X$ square-net layer ($X=$ P, As, Sb, Bi)
resembles a quantum spin Hall (QSH) insulator. Since these QSH layers are
simply stacked in the $\hat{x}$ direction and weakly coupled, three-dimensional
QSH effect can be expected in these distorted materials, such as insulating
compounds CeAs$_{1+x}$Se$_{1-y}$ and EuCdSb$_2$. Our detailed calculations show
that it hosts two twisted nodal wires without SOC [each consists of two
noncontractible time-reversal symmetry- and inversion symmetry-protected nodal
lines touching at a fourfold degenerate point], while with SOC it becomes a
topological crystalline insulator with symmetry indicators $(000; 2)$ and
mirror Chern numbers $(0, 0)$. The nontrivial band topology is characterized by
a generalized spin Chern number $C_{s+}=2$ when there is a gap between two sets
of $\hat{s}_{x}$ eigenvalues. The nontrivial topology of these materials can be
well reproduced by our tight-binding model and the calculated spin Hall
conductivity is quantized to $\sigma^{x}_{yz} =
(\frac{\hbar}{e})\frac{G_xe^2}{\pi h}$ with $G_x$ a reciprocal lattice vector.


  While important properties of word vector representations have been studied
extensively, far less is known about the properties of sentence vector
representations. Word vectors are often evaluated by assessing to what degree
they exhibit regularities with regard to relationships of the sort considered
in word analogies. In this paper, we investigate to what extent commonly used
sentence vector representation spaces as well reflect certain kinds of
regularities. We propose a number of schemes to induce evaluation data, based
on lexical analogy data as well as semantic relationships between sentences.
Our experiments consider a wide range of sentence embedding methods, including
ones based on BERT-style contextual embeddings. We find that different models
differ substantially in their ability to reflect such regularities.


  After about two decades of the first observational papers confirming the
accelerated expansion of the universe, we are still facing the question whether
the cause of it is a rigid cosmological constant $\Lambda$-term or a mildly
evolving dynamical dark energy (DDE). While studies focusing mainly on CMB
measurements do not perceive signs of physics beyond the $\Lambda$CDM, in this
work we show that if we take a large string $SNIa+BAO+H(z)+LSS+CMB$ of modern
cosmological observations, in which not only the CMB but also a rich sample of
large scale structure formation data are included, one can extract $\sim
3.3\sigma$ signs of DDE using a simple XCDM parameterization. These signs can
be enhanced up to near $3.8\sigma$ in the context of the running vacuum model
(RVM), in which the vacuum energy density is in interaction with dark matter.
Recently the RVM has been shown to provide an efficient and economical solution
to the $\sigma_8$-tension, which is one of the intriguing phenomenological
problems that has not been possible to solve within the $\Lambda$CDM so far.
This fact contributes to strengthen the possibility that dynamical vacuum
energy, or in general DDE, could be presently favored by the observations.


  We present the results of analyzing the XMM-Newton data obtained in 2001
November 7 - 8. A flare is observed simultaneously in X-ray and UV together
with a quiescence. We find that during the flare event X-ray flux varies with
UV with no significant time lag, indicating a close correlation of flux
variation for X-ray and UV flares. An upper limit of the lag is estimated to be
\~1 min. From a timing analysis for X-ray data, we find that both pulsed and
unpulsed flux increase clearly as the flare advances in the entire energy band
0.15 - 10 keV. The net increase of pulsed flux to the quiescence is, however,
small and corresponds to about 3 - 4% of the increase in unpulsed flux,
confirming that a flux variation of flare in AE Aqr is dominated by unpulsed
X-rays. A spectral analysis reveals that the energy spectrum is similar to that
of the quiescence at the beginning of the flare, but the spectrum becomes
harder as the flare advances. Based on these results, we discuss the current
issues that need to be clarified, e.g., the possible flaring site and the mass
accretion problem of the white dwarf. We also discuss the flare properties
obtained in this study.


  Face liveness detection is an essential prerequisite for face recognition
applications. Previous face liveness detection methods usually train a binary
classifier to differentiate between a fake face and a real face before face
recognition. The client identity information is not utilized in previous face
liveness detection methods. However, in practical face recognition
applications, face spoofing attacks are always aimed at a specific client, and
the client identity information can provide useful clues for face liveness
detection. In this paper, we propose a face liveness detection method based on
the client identity using Siamese network. We detect face liveness after face
recognition instead of before face recognition, that is, we detect face
liveness with the client identity information. We train a Siamese network with
image pairs. Each image pair consists of two real face images or one real and
one fake face images. The face images in each pair come from a same client.
Given a test face image, the face image is firstly recognized by face
recognition system, then the real face image of the identified client is
retrieved to help the face liveness detection. Experiment results demonstrate
the effectiveness of our method.


  The fundamental question of how chirality affects the electronic coupling of
a nanotube to metal contacts is important for the application of nanotubes as
nanowires. We show that metallic-zigzag nanotubes are superior to armchair
nanotubes as nanowires, by modeling the metal-nanotube interface. More
specifically, we show that as a function of coupling strength, the total
electron transmission of armchair nanotubes increases and tends to be pinned
close to unity for a metal with Fermi wave vector close to that of gold. In
contrast, the total transmission of zigzag nanotubes increases to the maximum
possible value of two. The origin of these effects lies in the details of the
wave function, which is explained.


  Detailed account is given of the chirality scenario of experimental
spin-glass transitions. In this scenario, the spin glass order of weakly
anisotropic Heisenberg-like spin-glass magnets including canonical spin glasses
are essentially chirality driven. Recent numerical and experimental results are
discussed in conjunction with this scenario.


  A comparison is carried out among the star formation histories of early-type
galaxies (ETG) in fossil groups, clusters and low density environments.
Although they show similar evolutionary histories, a significant fraction of
the fossils are younger than their counterparts, suggesting that fossils can be
precursors of the isolated ETGs.


  With the shift towards on-device deep learning, ensuring a consistent
behavior of an AI service across diverse compute platforms becomes tremendously
important. Our work tackles the emergent problem of reducing predictive
inconsistencies arising as negative flips: test samples that are correctly
predicted by a less accurate model, but incorrectly by a more accurate one. We
introduce REGression constrained Neural Architecture Search (REG-NAS) to design
a family of highly accurate models that engender fewer negative flips. REG-NAS
consists of two components: (1) A novel architecture constraint that enables a
larger model to contain all the weights of the smaller one thus maximizing
weight sharing. This idea stems from our observation that larger weight sharing
among networks leads to similar sample-wise predictions and results in fewer
negative flips; (2) A novel search reward that incorporates both Top-1 accuracy
and negative flips in the architecture search metric. We demonstrate that
\regnas can successfully find desirable architectures with few negative flips
in three popular architecture search spaces. Compared to the existing
state-of-the-art approach, REG-NAS enables 33-48% relative reduction of
negative flips.


  Monopole and photon contributions to abelian Wilson loops are calculated
using Monte-Carlo simulations of finite-temperature $SU(2)$ QCD in the
maximally abelian gauge. Long monopole loops alone are responsible for the
behavior of the string tension in the confinement phase up to the critical
$\beta_c$. Short monopole loops and photons do not contribute to the string
tension. The abelian and the monopole spacial string tensions (both of which
agree with the normal ones for $\beta < \beta_c$) show a $g^{4}(T) T^2$ scaling
behavior in the deconfinement phase. The abelian spacial string tension is in
agreement with the full one even in the deconfinement phase.


  We present qualitative observations on the internal flow characteristics of
fluidic oscillator geometries commonly referred to as sweeping jets in active
flow control applications. This is part of the fluid dynamics videos.


  The zero-temperature random-field Ising model is solved analytically for
magnetisation vs external field for a bi-layered Bethe lattice. The mechanisms
of infinite avalanches which are observed for small values of disorder are
established. The effects of variable inter-layer interaction strengths on
infinite avalanches are investigated. The spin-field correlation length is
calculated and its critical behaviour is discussed. Direct Monte-Carlo
simulations of spin-flip dynamics are shown to support the analytical findings.
We find, paradoxically, that a reduction of the inter-layer bond strength can
cause a phase transition from a regime with continuous magnetisation reversal
to a regime where magnetisation exhibits a discontinuity associated with an
infinite avalanche. This effect is understood in terms of the proposed
mechanisms for the infinite avalanche.


  Reactor neutrinos have played a key role in understanding neutrino physics
since their discovery. The so-called reactor-anti-neutrino-anomaly RAA, a ~6.5
$\%$ deficit of the mean observed neutrino flux compared to the prediction
appeared recently. This anomaly could be interpreted by the existence of a
fourth, sterile, neutrino and this hypothesis is currently being tested by the
very short baseline experiment STEREO. The latter is installed at very short
distance (9 -11m) from the compact core of the ILL research reactor in
Grenoble-France and collecting data since November 2016. The ILL core is highly
enriched in ${}^{235}\textrm{U}$ and releases a nominal thermal power of 58.3
MW. The geometry of the STEREO detector, segmented into six identical cells
filled with Gd-loaded liquid scintillator, is designed for a direct test of a
new oscillation pattern in the L/E range around 1 m/MeV, relevant for the RAA.
First published results of STEREO have demonstrated the mitigation of the
background induced by the reactor and the cosmic-rays and a good energy
response. The data taking is now in progress with very stable conditions
favorable for an improved accuracy. We will present an overview of the
experiment and an update of the sterile neutrino analysis. A refined prediction
of the neutrino spectrum emitted by the ILL reactor is also presented.


  Let $f$ be an entire function and $L(f)$ a linear differential polynomial in
$f$ with constant coefficients. Suppose that $f$, $f'$, and $L(f)$ share a
meromorphic function $\alpha(z)$ that is a small function with respect to $f$.
A characterization of the possibilities that may arise was recently obtained by
Lahiri. However, one case leaves open many possibilities. We show that this
case has more structure than might have been expected, and that a more detailed
study of this case involves, among other things, Stirling numbers of the first
and second kinds. We prove that the function $\alpha$ must satisfy a linear
homogeneous differential equation with specific coefficients involving only
three free parameters, and then $f$ can be obtained from each solution.
Examples suggest that only rarely do single-valued solutions $\alpha(z)$ exist,
and even then they are not always small functions for $f$.