  Shape optimization based on surface gradients and the Hadarmard-form is
considered for a compressible viscous fluid. Special attention is given to the
difference between the 'function composition' approach involving local shape
derivatives and an alternate methodology based on the weak form of the state
equation. The resulting gradient expressions are found to be equal only if the
existence of a strong form solution is assumed. Surface shape derivatives based
on both formulations are implemented within a Discontinuous Galerkin flow
solver of variable order. The gradient expression stemming from the variational
approach is found to give superior accuracy when compared to finite
differences.


  We present measurements of time-dependent CP violation parameters in B0 -->
K0 PI0, B0 --> Ks Pi+ Pi- and B0 --> Ks K+ K- decays. The latter two are
extracted using time-dependent Dalitz plot analyses. These results are obtained
from a large data sample that contains 657 x 10^6 BBbar pairs collected at the
Upsilon(4S) resonance with the Belle detector at the KEKB asymmetric-energy
e+e- collider.


  In the past few years, Softmax has become a common component in neural
network frameworks. In this paper, a gradient decay hyperparameter is
introduced in Softmax to control the probability-dependent gradient decay rate
during training. By following the theoretical analysis and empirical results of
a variety of model architectures trained on MNIST, CIFAR-10/100 and SVHN, we
find that the generalization performance depends significantly on the gradient
decay rate as the confidence probability rises, i.e., the gradient decreases
convexly or concavely as the sample probability increases. Moreover,
optimization with the small gradient decay shows a similar curriculum learning
sequence where hard samples are in the spotlight only after easy samples are
convinced sufficiently, and well-separated samples gain a higher gradient to
reduce intra-class distance. Based on the analysis results, we can provide
evidence that the large margin Softmax will affect the local Lipschitz
constraint of the loss function by regulating the probability-dependent
gradient decay rate. This paper provides a new perspective and understanding of
the relationship among concepts of large margin Softmax, local Lipschitz
constraint and curriculum learning by analyzing the gradient decay rate.
Besides, we propose a warm-up strategy to dynamically adjust Softmax loss in
training, where the gradient decay rate increases from over-small to speed up
the convergence rate.


  Non-vanishing electromagnetic properties of the neutrinos have been predicted
by many theories beyond the Standard Model, and an enhanced neutrino magnetic
moment can have profound implications for fundamental physics. The XENON1T
experiment recently detected an excess of electron recoil events in the 1-7 keV
energy range, which can be compatible with solar neutrino magnetic moment
interaction at a most probable value of $\mu_{\nu} = 2.1 \times 10^{-11}
\mu_{\text{B}}$. However, tritium backgrounds and solar axion interaction in
this energy window are equally plausible causes. Upcoming multi-tonne noble
liquid detectors will test these scenarios more in depth, but will continue to
face similar ambiguity. We report a unique capability of future large liquid
scintillator detectors to help resolve the potential neutrino magnetic moment
scenario. With a liquid scintillator exposure of $O$(100) kton$\cdot$year, a
sensitivity of $\mu_{\nu} < 10^{-11} \mu_{\text{B}}$ can be reached at an
energy threshold greater than 40 keV, where no tritium or solar axion events
but only neutrino magnetic moment signal is still present.


  We define generalizations of the multiple elliptic gamma functions and the
multiple sine functions, labelled by rational cones in $\mathbb{R}^r$. For
$r=2,3$ we prove that the generalized multiple elliptic gamma functions enjoy a
modular property determined by the cone. This generalizes the modular
properties of the elliptic gamma function studied by Felder and Varchenko. The
generalized multiple sine enjoy a related infinite product representation,
generalizing the results of Narukawa for the ordinary multiple sine functions.


  We develop a theory on a topologically non-trivial manifold which leads to
different vacuum backgrounds at the field level. The different colors of the
same quark flavor live in different backgrounds generated by the action of the
torsion subgroup of H^2(M,2\pi Z) on H^2(M,2\pi Z) itself. This topological
separation leads to a quark confinement mechanism which does not apply to the
baryons as they turn out to live on the same vacuum state. The theory makes
some topological assumptions on the spacetime manifold which are compared with
the available data on the topology of the Universe.


  Three dimensional SU(2) Chern-Simons theory has been studied as a topological
field theory to provide a field theoretic description of knots and links in
three dimensions. A systematic method has been developed to obtain the
link-invariants within this field theoretic framework. The monodromy properties
of the correlators of the associated Wess-Zumino SU(2)$_k$ conformal field
theory on a two-dimensional sphere prove to be useful tools. The method is
simple enough to yield a whole variety of new knot invariants of which the
Jones polynomials are the simplest example.


  Balmer jump discontinuity of the peculiar star HD 215441 was measured on 14
continuous energy distributions obtained by S. J. Adelman at Kitt Peak National
and Palomar Observatories. The results show that the Balmer jump vary by about
0.05 dex over the cycle of the star. A comparison with new Kurucz model
atmospheres shown that the Balmer jump for the phase 0.5 corresponds to a 14750
K, log(g)=3.0 and for the phase 1.0 corresponds to a 15750 K, log(g)=3.0.


  In this paper, we execute the shift-splitting preconditioner for asymmetric
saddle point problems with its (1,2) block's transposition unequal to its (2,1)
block under the removed minus of its (2,1) block. The proposed preconditioner
is stemmed from the shift splitting (SS) iteration method for solving
asymmetric saddle point problems, which is convergent under suitable
conditions. The relaxed version of the shift-splitting preconditioner is
obtained as well. The spectral distributions of the related preconditioned
matrices are given. Numerical experiments from the Stokes problem are offered
to show the convergence performance of these two preconditioners.


  We present a detailed analysis of the Galaxy Stellar Mass Function of
galaxies up to z=2.5 as obtained from the VVDS. We estimate the stellar mass
from broad-band photometry using 2 different assumptions on the galaxy star
formation history and show that the addition of secondary bursts to a
continuous star formation history produces systematically higher (up to 40%)
stellar masses. At low redshift (z=0.2) we find a substantial population of
low-mass galaxies (<10^9 Msun) composed by faint blue galaxies (M_I-M_K=0.3).
In general the stellar mass function evolves slowly up to z=0.9 and more
significantly above this redshift. Conversely, a massive tail is present up to
z=2.5 and have extremely red colours (M_I-M_K=0.7-0.8). We find a decline with
redshift of the overall number density of galaxies for all masses (59+-5% for
M>10^8 Msun at z=1), and a mild mass-dependent average evolution
(`mass-downsizing'). In particular our data are consistent with mild/negligible
(<30%) evolution up to z=0.7 for massive galaxies (>6x10^10 Msun). For less
massive systems the no-evolution scenario is excluded. A large fraction (>=50%)
of massive galaxies have been already assembled and converted most of their gas
into stars at z=1, ruling out the `dry mergers' as the major mechanism of their
assembly history below z=1. This fraction decreases to 33% at z=2. Low-mass
systems have decreased continuously in number and mass density (by a factor up
to 4) from the present age to z=2, consistently with a prolonged mass assembly
also at z<1.


  Kernel-based approaches for sequence classification have been successfully
applied to a variety of domains, including the text categorization, image
classification, speech analysis, biological sequence analysis, time series and
music classification, where they show some of the most accurate results.
  Typical kernel functions for sequences in these domains (e.g., bag-of-words,
mismatch, or subsequence kernels) are restricted to {\em discrete univariate}
(i.e. one-dimensional) string data, such as sequences of words in the text
analysis, codeword sequences in the image analysis, or nucleotide or amino acid
sequences in the DNA and protein sequence analysis. However, original sequence
data are often of real-valued multivariate nature, i.e. are not univariate and
discrete as required by typical $k$-mer based sequence kernel functions.
  In this work, we consider the problem of the {\em multivariate} sequence
classification such as classification of multivariate music sequences, or
multidimensional protein sequence representations. To this end, we extend {\em
univariate} kernel functions typically used in sequence analysis and propose
efficient {\em multivariate} similarity kernel method (MVDFQ-SK) based on (1) a
direct feature quantization (DFQ) of each sequence dimension in the original
{\em real-valued} multivariate sequences and (2) applying novel multivariate
discrete kernel measures on these multivariate discrete DFQ sequence
representations to more accurately capture similarity relationships among
sequences and improve classification performance.
  Experiments using the proposed MVDFQ-SK kernel method show excellent
classification performance on three challenging music classification tasks as
well as protein sequence classification with significant 25-40% improvements
over univariate kernel methods and existing state-of-the-art sequence
classification methods.


  The projection onto the Light-Front of a Minkowski space
Faddeev-Bethe-Salpeter equation model truncated at the valence level is applied
to study the proton structure with constituent quarks. The dynamics of the
model has built-in: (i) a bound diquark brought by a contact interaction, and
(ii) the separation by \Lambda_QCD of the infrared and ultraviolet interaction
regions. The model parameters are fine tuned to reproduce the proton Dirac
electromagnetic form factor and mass. From that, the non-polarized longitudinal
and transverse momentum distributions were computed. The results for the
evolved non-polarized valence parton distributions suggest that: (i) the
explicit consideration of the spin degree of freedom of both quark and diquark
seems not relevant to it, and (ii) the comparison with the global fit from the
NNPDF4.0 calls for higher Fock components of the wave function beyond the
valence one.


  We demonstrate simultaneous center-of-mass cooling of two coupled
oscillators, consisting of a microsphere-cantilever and a tapered optical
fiber. Excitation of a whispering gallery mode (WGM) of the microsphere, via
the evanescent field of the taper, provides a transduction signal that
continuously monitors the relative motion between these two microgram objects
with a sensitivity of 3 pm. The cavity enhanced optical dipole force is used to
provide feedback damping on the motion of the micron-diameter taper, whereas a
piezo stack is used to damp the motion of the much larger (up to $180\,\mu$m in
diameter), heavier (up to $1.5\times 10^{-7}\,$kg) and stiffer
microsphere-cantilever. In each feedback scheme multiple mechanical modes of
each oscillator can be cooled, and mode temperatures below 10 K are reached for
the dominant mode, consistent with limits determined by the measurement noise
of our system. This represents stabilization on the picometer level and is the
first demonstration of using WGM resonances to cool the mechanical modes of
both the WGM resonator and its coupling waveguide.


  Let d_{k,n} and #_{k,n} denote the dimension and the degree of the
Grassmannian G_{k,n} of k-planes in projective n-space, respectively. For each
k between 1 and n-2 there are 2^{d_{k,n}} \cdot #_{k,n} (a priori complex)
k-planes in P^n tangent to d_{k,n} general quadratic hypersurfaces in P^n. We
show that this class of enumerative problem is fully real, i.e., for each k
between 1 and n-2 there exists a configuration of d_{k,n} real quadrics in
(affine) real space R^n so that all the mutually tangent k-flats are real.


  We study the low energy implications, especially the particle spectroscopy,
of SO(10) grand unification in which the SO(10) symmetry is broken to the
Standard Model gauge group with a single pair of (144+\bar144) dimensional
Higgs multiplet (unified Higgs sector). In this class of models, the asymptotic
relation Y_b \approx Y_\tau \approx Y_t/6 among the third generation quark and
lepton Yukawa couplings can be derived. This relation leads to the prediction
\tan\beta \approx 14, where \tan\beta is the well known MSSM parameter. We find
that this type of Yukawa coupling unification (YU) is realized only by
employing non-universal soft supersymmetry breaking terms, dictated by SO(10)
symmetry, for the gauginos. A 125 GeV Higgs boson mass is also found to be
consistent with YU at the \sim 5% level. Without imposing a constraint on the
relic abundance of dark matter in these models, the squark and slepton masses,
with the exception of the stop, exceed 2 TeV and the gluino is heavier than 1
TeV. We show that the neutralino in this model is an acceptable dark matter
candidate through the neutralino-stop coannihilation scenario, with the stop
quark being relatively light (\gtrsim 500 GeV).


  We open a new discussion of generalized canonical partition function in
standard statistical mechanics and apply it for the study of Bose-Einstein
condensation. We discuss the possible cases for the generalized canonical
partition function and arrives at a conclusion that the system of trapped bose
gas will not be existing at absolute zero. We analyse the present study with an
experimental result and point out the general difficulties in the analyses of
experimental observations, which can possibly suppress the effect of
generalized canonical partition function over standard canonical partition
function. We mention that the experimental studies with ideal condensates at
absolute zero with an unbiased approach towards the traditional Bose-Einstein
condensation theory can bring out the effect of generalized canonical partition
function.


  In this paper, we present a protocol for facilitating trust-less cross-chain
cryptocurrency transfers that preserve privacy of bridge withdrawals. We
leverage zero-knowledge primitives that are commonly used to design
cryptocurrency mixing protocols to provide similar functionality but across two
or more blockchains. To that end, we receive cryptocurrency mixing for free
through the bridge operations and de-scribe how to extend these protocols to
incentivise bridge transfers using past ideas. We describe how resulting
protocols lead to similar vampire style attacks coined in the Uniswap vs.
Sushiswap saga but across chains.


  Refractory epileptic patients can suffer a seizure at any moment. Seizure
prediction would substantially improve their lives. In this work, based on
scalp EEG and its transformation into images, the likelihood of an epileptic
seizure occurring at any moment is computed using an average of the softmax
layer output (the likelihood) of a CNN, instead of the output of the
classification layer. Results show that by analyzing the likelihood and
thresholding it, prediction has higher sensitivity or a lower FPR/h. The best
threshold for the likelihood was higher than 50% for 5 patients, and was lower
for the remaining 36. However, more testing is needed, especially in new
seizures, to better assess the real performance of this method. This work is a
proof of concept with a positive outlook.


  Let $g(x)$ be a fixed non-constant complex polynomial. It was conjectured by
Schinzel that if $g(h(x))$ has boundedly many terms, then $h(x)\in \C[x]$ must
also have boundedly many terms. Solving an older conjecture raised by R\'enyi
and by Erd\"os, Schinzel had proved this in the special cases $g(x)=x^d$;
however that method does not extend to the general case. Here we prove the full
Schinzel's conjecture (actually in sharper form) by a completely different
method. Simultaneously we establish an "algorithmic" parametric description of
the general decomposition $f(x)=g(h(x))$, where $f$ is a polynomial with a
given number of terms and $g,h$ are arbitrary polynomials. As a corollary, this
implies for instance that a polynomial with $l$ terms and given coefficients is
non-trivially decomposable if and only if the degree-vector lies in the union
of certain finitely many subgroups of $\Z^l$.


  We study the flow behaviour of a twist-bend nematic $(N_{TB})$ liquid
crystal. It shows three distinct shear stress ($\sigma$) responses in a certain
range of temperatures and shear rates ($\dot{\gamma}$). In Region-I,
$\sigma\sim\sqrt{\dot{\gamma}}$, in region-II, the stress shows a plateau,
characterised by a power law $\sigma\sim{\dot{\gamma}}^{\alpha}$, where
$\alpha\sim0.1-0.4$ and in region-III, $\sigma\sim\dot{\gamma}$. With
increasing shear rate, $\sigma$ changes continuously from region-I to II,
whereas it changes discontinuously with a hysteresis from region-II to III. In
the plateau (region-II), we observe a dynamic stress fluctuations, exhibiting
regular, periodic and quasiperiodic oscillations under the application of
steady shear. The observed spatiotemporal dynamics in our experiments are close
to those were predicted theoretically in sheared nematogenic fluids.


  We consider a re-sampling scheme for estimation of the population parameters
in the mixed effects nonlinear regression models of the type use for example in
clinical pharmacokinetics, say. We provide an estimation procedure which {\it
recycles}, via random weighting, the relevant two-stage parameters estimates to
construct consistent estimates of the sampling distribution of the various
estimates. We establish the asymptotic consistency and asymptotic normality of
the resampled estimates and demonstrate the applicability of the {\it
recycling} approach in a small simulation study and via example.


  Observational evidence of white dwarf planetary systems is dominated by the
remains of exo-asteroids through accreted metals, debris discs, and orbiting
planetesimals. However, exo-planets in these systems play crucial roles as
perturbing agents, and can themselves be perturbed close to the white dwarf
Roche radius. Here, we illustrate a procedure for computing the tidal
interaction between a white dwarf and a near-spherical solid planet. This
method determines the planet's inward and/or outward drift, and whether the
planet will reach the Roche radius and be destroyed. We avoid constant tidal
lag formulations and instead employ the self-consistent secular Darwin-Kaula
expansions from Bou\'{e} & Efroimsky (2019), which feature an arbitrary
frequency dependence on the quality functions. We adopt wide ranges of dynamic
viscosities and spin rates for the planet in order to straddle many possible
outcomes, and provide a foundation for the future study of individual systems
with known or assumed rheologies. We find that: (i) massive Super-Earths are
destroyed more readily than minor planets (such as the ones orbiting WD
1145+017 and SDSS J1228+1040), (ii) low-viscosity planets are destroyed more
easily than high-viscosity planets, and (iii) the boundary between survival and
destruction is likely to be fractal and chaotic.


  The identification and classification of political claims is an important
step in the analysis of political newspaper reports; however, resources for
this task are few and far between. This paper explores different strategies for
the cross-lingual projection of political claims analysis. We conduct
experiments on a German dataset, DebateNet2.0, covering the policy debate
sparked by the 2015 refugee crisis. Our evaluation involves two tasks (claim
identification and categorization), three languages (German, English, and
French) and two methods (machine translation -- the best method in our
experiments -- and multilingual embeddings).


  In this Rapid Communication, we investigate the universal properties of a
spin-polarized two-component Fermi gas in one dimension (1D) using Bethe
ansatz. We discuss the quantum phases and phase transitions by obtaining exact
results for the equation of state, the contact, the magnetic susceptibility and
the contact susceptibility, giving a precise understanding of the 1D analogue
of the Bose-Einstein condensation and Bardeen-Cooper-Schrieffer crossover in
three dimension (3D) and the associated universal magnetic properties. In
particular, we obtain the exact form of the magnetic susceptibility $\chi \sim
{1}/{\sqrt{T}}\exp(-\Delta/T)$ at low temperatures, where $\Delta$ is the
energy gap and $T$ is the temperature. Moreover, we establish exact upper and
lower bounds for the relation between polarization $P$ and the contact $C$ for
both repulsive and attractive Fermi gases. Our findings emphasize the role of
the pair fluctuations in strongly interacting 1D fermion systems that can shed
light on higher dimensions.


  We use a partially Gutzwiller projected BCS d-wave wavefunction with an
antiferromagentic weighting factor to study the ground state phase diagram of a
half filled Hubbard-Heisenberg model in a square lattice with nearest neighbor
hopping $t$ and a diagonal hopping $t'$. The calculations are carried out by
using variational Monte Carlo method which treats the Gutzwiller projection
explicitly. At large on-site Coulomb interaction $U$, the ground state is
antiferromagnetic. As $U$ decreases, the ground state becomes superconducting
and eventually metallic. The phase diagram is obtained by extensive
calculations. As compared to the strong effect of $U/t$, the phase boundaries
turn out to be less sensitive to $t'/t$. The result is consistent with the
phase diagram in layered organic conductors, and is compared to the earlier
mean field result based on the Gutzwiller approximation.


  We consider the well-posedness and numerical approximation of a
Hamilton--Jacobi equation on an evolving hypersurface in $\mathbb R^3$.
Definitions of viscosity sub- and supersolutions are extended in a natural way
to evolving hypersurfaces and provide uniqueness by comparison. An explicit in
time monotone numerical approximation is derived on evolving interpolating
triangulated surfaces. The scheme relies on a finite volume discretisation
which does not require acute triangles. The scheme is shown to be stable and
consistent leading to an existence proof via the proof of convergence. Finally
an error bound is proved of the same order as in the flat stationary case.


  In this paper, we prove some normality criteria concerning transitivity of
normality from one family of meromorphic functions to another which improve and
generalize some recent results. We also prove some value distribution results
for certain differential polynomials which lead to some normality criteria
involving sharing of holomorphic functions with certain differential
polynomials. As a consequence, a counterexample to the converse of the Bloch's
principle is also given.


  At the Large Hadron Collider (LHC), ATLAS and CMS collaborations observed
various decay modes of the light charged Higgs bosons produced by top
(anti)quark decays. In this paper, we are interested in the subsequent decay of
the light charged Higgs boson into a charm and a strange quark-antiquark pair
and into a tau and a tau-neutrino pair, separately, in the context of the
Georgi-Machacek model, which offers a large triplet vacuum expectation value
(vev) preserving custodial symmetry. We show that these experimental
observations constrain the triplet vev from above. We explore the model
parameter space consistent with the theoretical constraints, the latest Higgs
data and the experimental data for light charged Higgs decaying to $cs$ and
$\tau\nu_{\tau}$.


  The increasing complexity and high costs associated with modern processor
design have led to a surge in demand for processor design automation.
Instruction-tuned large language models (LLMs) have demonstrated remarkable
performance in automatically generating code for general-purpose programming
languages like Python. However, these methods fail on hardware description
languages (HDLs) like Verilog due to the scarcity of high-quality instruction
tuning data, as even advanced LLMs like GPT-3.5 exhibit limited performance on
Verilog generation. Regarding this issue, we observe that (1) Verilog code
collected from the real world has higher quality than those generated by LLMs.
(2) LLMs like GPT-3.5 excel in summarizing Verilog code rather than generating
it. Based on these observations, this paper introduces CodeV, a series of
open-source instruction-tuned Verilog generation LLMs. Instead of generating
descriptions first and then getting the corresponding code from advanced LLMs,
we prompt the LLM with Verilog code and let the LLM generate the corresponding
natural language description by multi-level summarization. Experimental results
show that CodeV relatively surpasses the previous open-source SOTA by 14.4%
(BetterV in VerilogEval) and 11.3% (RTLCoder in RTLLM) respectively, and also
relatively outperforms previous commercial SOTA GPT-4 by 22.1% in VerilogEval.


  We introduce DexGanGrasp, a dexterous grasping synthesis method that
generates and evaluates grasps with single view in real time. DexGanGrasp
comprises a Conditional Generative Adversarial Networks (cGANs)-based
DexGenerator to generate dexterous grasps and a discriminator-like DexEvalautor
to assess the stability of these grasps. Extensive simulation and real-world
expriments showcases the effectiveness of our proposed method, outperforming
the baseline FFHNet with an 18.57% higher success rate in real-world
evaluation. We further extend DexGanGrasp to DexAfford-Prompt, an
open-vocabulary affordance grounding pipeline for dexterous grasping leveraging
Multimodal Large Language Models (MLLMs) and Vision Language Models (VLMs), to
achieve task-oriented grasping with successful real-world deployments.


  This paper aims at reviewing and analysing the method of reflections. The
latter is an iterative procedure designed to linear boundary value problems set
in multiply connected domains. Being based on a decomposition of the domain
boundary, this method is particularly well-suited to numerical solvers relying
on integral representation formulas. For the parallel and sequential forms of
the method appearing in the literature, we propose a general abstract
formulation in a given Hilbert setting and interpret the procedure in terms of
subspace corrections. We then prove the unconditional convergence of the
sequential form and propose a modification of the parallel one that makes it
unconditionally converging. An alternative proof of convergence is provided in
a case which does not fit into the previous framework. We finally present some
numerical tests.


  In this paper we introduce a new clustering technique called Regularity
Clustering. This new technique is based on the practical variants of the two
constructive versions of the Regularity Lemma, a very useful tool in graph
theory. The lemma claims that every graph can be partitioned into pseudo-random
graphs. While the Regularity Lemma has become very important in proving
theoretical results, it has no direct practical applications so far. An
important reason for this lack of practical applications is that the graph
under consideration has to be astronomically large. This requirement makes its
application restrictive in practice where graphs typically are much smaller. In
this paper we propose modifications of the constructive versions of the
Regularity Lemma that work for smaller graphs as well. We call this the
Practical Regularity partitioning algorithm. The partition obtained by this is
used to build the reduced graph which can be viewed as a compressed
representation of the original graph. Then we apply a pairwise clustering
method such as spectral clustering on this reduced graph to get a clustering of
the original graph that we call Regularity Clustering. We present results of
using Regularity Clustering on a number of benchmark datasets and compare them
with standard clustering techniques, such as $k$-means and spectral clustering.
These empirical results are very encouraging. Thus in this paper we report an
attempt to harness the power of the Regularity Lemma for real-world
applications.


  Recent advancement on the knowledge of multifragmentation and phase
transition for hot nuclei is reported. It concerns i) the influence of radial
collective energy on fragment partitions and the derivation of general
properties of partitions in presence of such a collective energy, ii) a better
knowledge of freeze-out properties obtained by means of a simulation based on
all the available experimental information and iii) the quantitative study of
the bimodal behaviour of the heaviest fragment charge distribution for
fragmenting hot heavy quasi-projectiles which allows, for the first time, to
estimate the latent heat of the phase transition.


  We present Language-Image Value learning (LIV), a unified objective for
vision-language representation and reward learning from action-free videos with
text annotations. Exploiting a novel connection between dual reinforcement
learning and mutual information contrastive learning, the LIV objective trains
a multi-modal representation that implicitly encodes a universal value function
for tasks specified as language or image goals. We use LIV to pre-train the
first control-centric vision-language representation from large human video
datasets such as EpicKitchen. Given only a language or image goal, the
pre-trained LIV model can assign dense rewards to each frame in videos of
unseen robots or humans attempting that task in unseen environments. Further,
when some target domain-specific data is available, the same objective can be
used to fine-tune and improve LIV and even other pre-trained representations
for robotic control and reward specification in that domain. In our experiments
on several simulated and real-world robot environments, LIV models consistently
outperform the best prior input state representations for imitation learning,
as well as reward specification methods for policy synthesis. Our results
validate the advantages of joint vision-language representation and reward
learning within the unified, compact LIV framework.


  The first interstellar object, 1I/2017 U1 (`Oumuamua), exhibited several
unique properties, including an extreme aspect ratio, a lack of typical
cometary volatiles, and a deviation from a Keplerian trajectory. Several
authors have hypothesized that the non-gravitational acceleration was caused by
either cometary outgassing or radiation pressure. Here, we investigate the spin
dynamics of `Oumuamua under the action of high surface area fractional activity
and radiation pressure. We demonstrate that a series of transient jets that
migrate across the illuminated surface will not produce a secular increase in
the spin rate. We produce 3D tumbling simulations that approximate the dynamics
of a surface covering jet, and show that the resulting synthetic light curve
and periodogram are reasonably consistent with the observations. Moreover, we
demonstrate that radiation pressure also produces a steady spin-state. While
carbon monoxide (CO) has been dismissed as a possible accelerant because of its
non-detection in emission by $\textit{Spitzer}$, we show that outgassing from a
surface characterized by a modest covering fraction of CO ice can satisfy the
non-ballistic dynamics for a plausible range of assumed bulk densities and
surface albedos. $\textit{Spitzer}$ upper limits on CO emission are, however,
inconsistent with the CO production necessary to provide the acceleration.
Nonetheless, an ad hoc but physically plausible explanation is that the
activity level varied greatly during the time that the trajectory was
monitored. We reproduce the astrometric analysis presented in Micheli et al.
(2018), and verify that the non-gravitational acceleration was consistent with
stochastic changes in outgassing.


  Making use of the first- and second-order algorithms of supersymmetric
quantum mechanics (SUSY-QM), we construct quantum mechanical Hamiltonians whose
spectra are related to the zeroes of the Riemann Zeta function $\zeta(s)$.
Inspired by the model of Das and Kalauni (DK), which corresponds to this
function in the strip $0<Re[s]<1$, and taking the factorization energy equal to
zero, we use the wave function $|x|^{-S}$, $S\in\mathbb{C}$, as a seed solution
for our algorithms, obtaining XP-like operators. Thus, we construct SUSY-QM
partner Hamiltonians whose zero energy mode locates exactly the nontrivial
zeroes of $\zeta(s)$ along the critical line $Re[s]=1/2$ in the complex plane.
We further find that unlike the DK case, where the SUSY-QM partner potentials
correspond to free particles, our partner potentials belong to the family of
inverse squared distance potentials with complex couplings.


  The Dirac Hamiltonian $H^{\left(D\right)}$ for relativistic charged fermions
minimally coupled to (possibly time-dependent) electromagnetic fields is
transformed with a purpose-built flow equation method, so that the result of
that transformation is unitary equivalent to $H^{\left(D\right)}$ and granted
to strive towards a limiting value $H^{\left(NW\right)}$ commuting with the
Dirac $\beta$-matrix. Upon expansion of $H^{\left(NW\right)}$ to order
$\frac{v^2}{c^2}$ the nonrelativistic Hamiltonian $H^{\left(SP\right)}$ of
Schr\"odinger-Pauli quantum mechanics emerges as the leading order term adding
to the rest energy $mc^2$. All the relativistic corrections to
$H^{\left(SP\right)}$ are explicitly taken into account in the guise of a
Magnus type series expansion, the series coefficients generated to order
$\left(\frac{v^{2}}{c^{2}}\right)^{n}$ for $n\geq2$ comprising partial sums of
iterated commutators only. In the special case of static fields the equivalence
of the flow equation method with the well known energy-separating unitary
transformation of Eriksen is established on the basis of an exact solution of a
reverse flow equation transforming the $\beta$-matrix into the energy-sign
operator associated with $H^{\left(D\right)}$. That way the identity
$H^{\left(NW\right)}=\beta\sqrt{H^{\left(NW\right)}H^{\left(NW\right)}}$ is
established implying $H^{\left(NW\right)}$ being determined unambiguously.


  The comment is intended to answer the criticism presented on `Steady-state
fluctuations of a genetic feedback loop: an exact solution' [J. Chem. Phys.
{\bf 137}, 035104 (2012).] and provides the missing component for the complete
analytic solutions to the author's model.


  In this paper, by using the idea of linearizing maximal op-erators originated
by Charles Fefferman and the TT* method of Stein-Wainger, we establish a
weighted inequality for vector valued maximal Carleson type operators with
singular kernels proposed by Andersen and John on the weighted Lorentz spaces
with vector-valued functions.


  Fine-tuning pre-trained language models (LMs) is essential for enhancing
their capabilities. Existing techniques commonly fine-tune on input-output
pairs (e.g., instruction tuning) or with numerical rewards that gauge the
output quality (e.g., RLHF). We explore LMs' potential to learn from textual
interactions (LETI) that not only check their correctness with binary labels
but also pinpoint and explain errors in their outputs through textual feedback.
Our focus is the code generation task, where the model produces code based on
natural language instructions. This setting invites a natural and scalable way
to acquire textual feedback: the error messages and stack traces from code
execution using a Python interpreter. LETI iteratively fine-tunes the model,
using the LM objective, on a concatenation of natural language instructions,
LM-generated programs, and textual feedback. Prepended to this fine-tuning
text, a binary reward token is used to differentiate correct and buggy
solutions. LETI requires no ground-truth outputs for training and even
outperforms a fine-tuned baseline that does. LETI not only improves the
performance of LMs on a code generation dataset MBPP, but also generalizes to
other datasets. Trained on MBPP, it achieves comparable or better performance
than the base LMs on unseen problems in HumanEval. Furthermore, compared to
binary feedback, we observe that textual feedback leads to improved generation
quality and sample efficiency, achieving the same performance with fewer than
half of the gradient steps. LETI is equally applicable in natural language
tasks when they can be formulated as code generation, which we empirically
verified on event argument extraction.


  The energy spectrum of the cosmic microwave background (CMB) allows
constraining episodes of energy release in the early Universe. In this paper we
revisit and refine the computations of the cosmological thermalization problem.
For this purpose a new code, called CosmoTherm, was developed that allows
solving the coupled photon-electron Boltzmann equation in the expanding,
isotropic Universe for small spectral distortion in the CMB. We explicitly
compute the shape of the spectral distortions caused by energy release due to
(i) annihilating dark matter; (ii) decaying relict particles; (iii) dissipation
of acoustic waves; and (iv) quasi-instantaneous heating. We also demonstrate
that (v) the continuous interaction of CMB photons with adiabatically cooling
non-relativistic electrons and baryons causes a negative mu-type CMB spectral
distortion of DI_nu/I_nu ~ 10^{-8} in the GHz spectral band. We solve the
thermalization problem including improved approximations for the double Compton
and Bremsstrahlung emissivities, as well as the latest treatment of the
cosmological recombination process. At redshifts z <~ 10^3 the matter starts to
cool significantly below the temperature of the CMB so that at very low
frequencies free-free absorption alters the shape of primordial distortions
significantly. In addition, the cooling electrons down-scatter CMB photons
introducing a small late negative y-type distortion at high frequencies. We
also discuss our results in the light of the recently proposed CMB experiment
Pixie, for which CosmoTherm should allow detailed forecasting. Our current
computations show that for energy injection because of (ii) and (iv) Pixie
should allow to improve existing limits, while the CMB distortions caused by
the other processes seem to remain unobservable with the currently proposed
sensitivities and spectral bands of Pixie.


  Using the nonrelativistic QCD(NRQCD) factorization formalism, we calculate
the color-singlet cross sections for exclusive production processes
${e^++e^-\to J/\psi+\eta_c}$~ and ~$e^++e^-\to J/\psi + \chi_{cJ}$~$(J=0,1,2)$
at the center-of-mass energy $\sqrt{s}$=10.6 GeV. The cross sections are
estimated to be 5.5fb, 6.7fb, 1.1fb, and 1.6fb for $\eta_c, \chi_{c0},
\chi_{c1}$ and $\chi_{c2}$, respectively. The calculated $J/\psi+\eta_c$
production rate is smaller than the recent Belle data by about an order of
magnitude, which might indicate the failure of perturbative QCD calculation to
explain the double-charmonium production data. The complete
$\cal{O}$$(\alpha^2_{s})$ color-singlet cross section for ${e^++e^-\to
\chi_{c0}+ c\bar {c}}$ is calculated. In addition, we also evaluate the ratio
of exclusive to inclusive production cross sections. The ratio of
$J/\psi\eta_c$ production to $J/\psi c\bar{c}$ production could be consistent
with the experimental data.


  The study deals with a minimal energy problem in the presence of an external
field over noncompact classes of vector measures of infinite dimension in a
locally compact space. The components are positive measures (charges)
satisfying certain normalizing assumptions and supported by given closed sets
(plates) with the sign +1 or -1 prescribed such that oppositely signed sets are
mutually disjoint, and the interaction matrix for the charges corresponds to an
electrostatic interpretation of a condenser. For all positive definite kernels
satisfying Fuglede's condition of consistency between the weak* and strong
topologies, sufficient conditions for the existence of equilibrium measures are
established and properties of their uniqueness, vague compactness, and
continuity are studied. We also obtain variational inequalities for the
weighted equilibrium potentials, single out their characteristic properties,
and analyze continuity of the equilibrium constants.


  We study the correlation between the neutron skin development and the
low-energy dipole response associated with the pygmy dipole resonance (PDR) in
connection with the properties of symmetry energy. We perform our investigation
within a microscopic transport model based on the Landau-Vlasov kinetic
equation by employing three different equations of state in the isovector
sector. Together with the giant dipole resonance (GDR) for all studied systems,
we identify a PDR collective mode whose energy centroid is very well described
by the parametrization E_{PDR}=41 A^{-1/3}. A linear correlation between the
energy weighted sum rule (EWSR) associated to PDR and the neutron skin
thickness is evidenced. An increase of 15 MeVfm^2 of EWSR, in correspondence to
a change of 0.1fm of the neutron skin size, is obtained. We conjecture that
different nuclei having close neutron skin sizes will exhaust the same EWSR in
the pygmy region. This suggests that a precise experimental estimate of the
total EWSR exhausted by the PDR allows the determination of the neutron skin
size, constraining the slope parameter of the symmetry energy.


  Based on the obtained earlier experimental conductivity graphs at detonation
of five different high explosives, an analysis was performed which shows a
correlation between the carbon content and the conductivity magnitude. An
assumption was put forward that the conductivity in the whole detonation wave
is provided by the contact mechanism along conductive carbon nanostructures.


  In this paper we obtain uniform propagation estimates for systems of
interacting diffusions. We adopt a general model, satisfying various conditions
which ensure that the decay resulting from the internal dynamics term dominates
the interaction and noise terms. The result should have diverse applications,
particularly in neuroscience, and allows for models more elaborate than that of
Wilson and Cowan, not requiring the internal dynamics to be of linear decay.


  In Moving Horizon Estimation (MHE) the computed estimate is found by solving
a constrained finite-time optimal estimation problem in real-time at each
sample in a receding horizon fashion. The constrained estimation problem can be
solved by, e.g., interior-point (IP) or active-set (AS) methods, where the main
computational effort in both methods is known to be the computation of the
search direction, i.e., the Newton step. This is often done using generic
sparsity exploiting algorithms or serial Riccati recursions, but as parallel
hardware is becoming more commonly available the need for parallel algorithms
for computing the Newton step is increasing. In this paper a tailored,
non-iterative parallel algorithm for computing the Newton step using the
Riccati recursion is presented. The algorithm exploits the special structure of
the Karush-Kuhn-Tucker system for the optimal estimation problem. As a result
it is possible to obtain logarithmic complexity growth in the estimation
horizon length, which can be used to reduce the computation time for IP and AS
methods when applied to what is today considered as challenging estimation
problems. Promising numerical results have been obtained using an ANSI-C
implementation of the proposed algorithm running on true parallel hardware.
Beyond MHE, due to similarities in the problem structure, the algorithm can be
applied to various forms of on-line and off-line smoothing problems.


  The search problem of computing a \textit{leader-follower equilibrium} has
been widely investigated in the scientific literature in, almost exclusively,
the single-follower setting. Although the \textit{optimistic} and \
textit{pessimistic} versions of the problem are solved with different
methodologies, both cases allow for efficient, polynomial-time algorithms based
on linear programming. The situation is different with multiple followers,
where results are only sporadic and depend strictly on the nature of the
followers' game. In this paper, we investigate the setting of a normal-form
game with a single leader and multiple followers who, after observing the
leader's commitment, play a Nash equilibrium. The corresponding search problem,
both in the optimistic and pessimistic versions, is known to be not in
Poly-$\textsf{APX}$ unless $\textsf{P}=\textsf{NP}$ and exact algorithms are
known only for the optimistic case. We focus on the case where the followers
play in pure strategies under the assumption of pessimism. After casting this
search problem as a \italic{pessimistic bilevel programming problem}, we show
that, with two followers, the problem is $\textsf{NP}$-hard and, with three or
more followers, it is not in Poly-$\textsf{APX}$ unless
$\textsf{P}=\textsf{NP}$. We propose a single-level mathematical programming
reformulation which calls for the maximisation of a nonconcave quadratic
function over an unbounded nonconvex feasible region defined by linear and
quadratic constraints. Since, due to admitting a supremum but not a maximum,
only a restricted version of this formulation can be solved to optimality with
state-of-the-art methods, we propose an exact \textit{ad hoc} algorithm, which
we also embed within a branch-and-bound scheme, capable of computing the
supremum of the problem.


  At intermediate redshifts, many galaxies seem to be perturbed or suffering
from an interaction. Considering that disk galaxies may have formed and evolved
through minor mergers or through major mergers, it is important to understand
the mechanisms at play during each type of merger in order to be able to
establish the outcome of such an event. In some cases, only the use of both
morphological and kinematical information can disentangle the actual
configuration of an encounter at intermediate redshift.
  In this work, we present the morphological and kinematical analysis of a
system at z=0.74 in order to understand its configuration, interacting stage
and evolution. Using the integral field spectrograph GIRAFFE, long-slit
spectroscopy by FORS2 and direct optical images from the HST-ACS and ISAAC
near-infrared images, we disentangle the morphology of this system, its
star-formation history and its extended kinematics in order to propose a
possible configuration for the system. Numerical simulations are used to test
different interacting scenarii. We identify this system as a face-on disk
galaxy with a very bright bar in interaction with a smaller companion with a
mass ratio of 3:1. The relevance of kinematical information and the constraints
it imposes on the interpretation of the observations of distant galaxies is
particularly strengthened in this case.
  This object is amongst the best example on how one may misinterpret
morphology in the absence of kinematical information.


  Climate change continues to be a pressing issue that currently affects
society at-large. It is important that we as a society, including the Computer
Vision (CV) community take steps to limit our impact on the environment. In
this paper, we (a) analyze the effect of diminishing returns on CV methods, and
(b) propose a \textit{``NoFADE''}: a novel entropy-based metric to quantify
model--dataset--complexity relationships. We show that some CV tasks are
reaching saturation, while others are almost fully saturated. In this light,
NoFADE allows the CV community to compare models and datasets on a similar
basis, establishing an agnostic platform.


  Value-based methods play a fundamental role in Markov decision processes
(MDPs) and reinforcement learning (RL). In this paper, we present a unified
control-theoretic framework for analyzing valued-based methods such as value
computation (VC), value iteration (VI), and temporal difference (TD) learning
(with linear function approximation). Built upon an intrinsic connection
between value-based methods and dynamic systems, we can directly use existing
convex testing conditions in control theory to derive various convergence
results for the aforementioned value-based methods. These testing conditions
are convex programs in form of either linear programming (LP) or semidefinite
programming (SDP), and can be solved to construct Lyapunov functions in a
straightforward manner. Our analysis reveals some intriguing connections
between feedback control systems and RL algorithms. It is our hope that such
connections can inspire more work at the intersection of system/control theory
and RL.


  Starting from the functional representation of the Ablowitz-Kaup-Newell-Segur
(AKNS) and derivative nonlinear Schr\"odinger (DNLS) hierarchies and using the
chains of the Miura-like transformations we derive a set of B\"acklund
transformations that link solutions of these systems. It is shown that the
extended AKNS and DNLS hierarchies possess common set of tau-functions and
their connection with the Ablowitz-Ladik hierarchy is established. These
results are another manifestation of the already known fact that the AKNS and
DNLS hierarchies are closely related and can be viewed as particular cases of a
more general system.


  Exact theoretical results for the violation of time dependent
fluctuation-dissipation relations in driven dissipative systems are presented.
The ratio of correlation to delayed response in the stochastic model introduced
in [Phys. Rev. Lett. 93, 240601 (2004)] is shown to depend on measurement time.
The fluctuation temperature defined by this ratio differs both from the
temperature of the environment performing the driving, and from other effective
temperatures of the system, such as the average energy (or "granular
temperature"). General explanations are given for the time independence of
fluctuation temperature for simple measurements or long measurement times.


  In this paper, we introduce the concept of principal bundles on statistical
manifolds. After necessary preliminaries on information geometry and principal
bundles on manifolds, we study the $\alpha$-structure of frame bundles over
statistical manifolds with respect to $\alpha$-connections, by giving geometric
structures. The manifold of one-dimensional normal distributions appears in the
end as an application and a concrete example.


  We study the ground state phase diagram of a frustrated spin-1/2 four-leg
tube. Using a variety of complementary techniques, namely density matrix
renormalization group, exact diagonalization, Schwinger boson mean field
theory, quantum Monte-Carlo and series expansion, we explore the parameter
space of this model in the regime of all-antiferromagnetic exchange. In
contrast to unfrustrated four-leg tubes we uncover a rich phase diagram. Apart
from the Luttinger liquid fixed point in the limit of decoupled legs, this
comprises several gapped ground states, namely a plaquette, an incommensurate,
and an antiferromagnetic quasi spin-2 chain phase. The transitions between
these phases are analyzed in terms of total energy and static structure factor
calculations and are found to be of (weak) first order. Despite the absence of
long range order in the quantum case, remarkable similarities to the classical
phase diagram are uncovered, with the exception of the icommensurate regime,
which is strongly renormalized by quantum fluctuations. In the limit of large
leg exchange the tube exhibits a deconfinement cross-over from gapped magnon
like excitations to spinons.


  Closed bipartite quantum systems subject to fast local unitary control are
studied using quantum optimal control theory and a method of reduced control
systems based on the Schmidt decomposition. Particular focus is given to the
time-optimal generation of maximally entangled states and product states, as
well as to the problem of stabilizing quantum states with a certain amount of
entanglement. Explicit analytical solutions are given for general systems
consisting of two qubits (as well as for bosonic and fermionic analogues) and
also for a class of systems consisting of two coupled qutrits which is studied
using the Pontryagin Maximum Principle.


  We introduce a time-integrator to sample with high order of accuracy the
invariant distribution for a class of semilinear SPDEs driven by an additive
space-time noise. Combined with a postprocessor, the new method is a
modification with negligible overhead of the standard linearized implicit
Euler-Maruyama method. We first provide an analysis of the integrator when
applied for SDEs (finite dimension), where we prove that the method has order
$2$ for the approximation of the invariant distribution, instead of $1$. We
then perform a stability analysis of the integrator in the semilinear SPDE
context, and we prove in a linear case that a higher order of convergence is
achieved. Numerical experiments, including the semilinear heat equation driven
by space-time white noise, confirm the theoretical findings and illustrate the
efficiency of the approach.


  Recent advances in coreset methods have shown that a selection of
representative datapoints can replace massive volumes of data for Bayesian
inference, preserving the relevant statistical information and significantly
accelerating subsequent downstream tasks. Existing variational coreset
constructions rely on either selecting subsets of the observed datapoints, or
jointly performing approximate inference and optimizing pseudodata in the
observed space akin to inducing points methods in Gaussian Processes. So far,
both approaches are limited by complexities in evaluating their objectives for
general purpose models, and require generating samples from a typically
intractable posterior over the coreset throughout inference and testing. In
this work, we present a black-box variational inference framework for coresets
that overcomes these constraints and enables principled application of
variational coresets to intractable models, such as Bayesian neural networks.
We apply our techniques to supervised learning problems, and compare them with
existing approaches in the literature for data summarization and inference.


  The performances of commonly used electrocardiogram (ECG) diagnosis models
have recently improved with the introduction of deep learning (DL). However,
the impact of various combinations of multiple DL components and/or the role of
data augmentation techniques on the diagnosis have not been sufficiently
investigated. This study proposes an ensemble-based multi-view learning
approach with an ECG augmentation technique to achieve a higher performance
than traditional automatic 12-lead ECG diagnosis methods. The data analysis
results show that the proposed model reports an F1 score of 0.840, which
outperforms existing state-ofthe-art methods in the literature.


  First-principles calculation of the standard formation enthalpy, $\Delta
H_f^\circ$ (298K), in such large scale as required by chemical space
explorations, is amenable only with density functional approximations (DFAs)
and some composite wave function theories (cWFTs). Alas, the accuracies of
popular range-separated hybrid, `rung-4' DFAs, and cWFTs that offer the best
accuracy-vs.-cost trade-off have as yet been established only for datasets
predominantly comprising small molecules, hence, their transferability to
larger datasets remains vague. In this study, we present an extended benchmark
dataset of over 1600 values of $\Delta H_f^\circ$ for structurally and
electronically diverse molecules. We apply quartile-ranking based on
boundary-corrected kernel density estimation to filter outliers and arrive at
Probabilistically Pruned Enthalpies of 1694 compounds (PPE1694). For this
dataset, we rank the prediction accuracies of G4, G4(MP2), ccCA, CBS-QB3 and 23
popular DFAs using conventional and probabilistic error metrics. We discuss
systematic prediction errors and highlight the role an empirical higher-level
correction (HLC) plays in the G4(MP2) model. Furthermore, we comment on
uncertainties associated with the reference empirical data for atoms and the
systematic errors stemming from these that grow with the molecular size. We
believe these findings to aid in identifying meaningful application domains for
quantum thermochemical methods.


  Usually gradual and continuous changes in entities will lead to appear
events. But usually it is supposed that an event is occurred at once. In this
research an integrated framework called continuous occurrence theory (COT) is
presented to investigate respective path leading to occurrence of the events in
the real world. For this purpose initially fundamental concepts are defined.
Afterwards, the appropriate tools such as occurrence variables computations,
occurrence dependency function and occurrence model are introduced and
explained in a systematic manner. Indeed, COT provides the possibility to: (a)
monitor occurrence of events during time; (b) study background of the events;
(c) recognize the relevant issues of each event; and (d) understand how these
issues affect on the considered event. The developed framework (COT) provides
the necessary context to analyze accurately continual changes of the issues and
the relevant events in the various branches of science and business. Finally,
typical applications of COT and an applied modeling example of it have been
explained and a mathematical programming example is modeled in the occurrence
based environment.


  The PVLAS collaboration has obtained results that may be interpreted in terms
of a light axion-like particle, while the CAST collaboration has not found any
signal of such particles. Moreover, the PVLAS results are in gross
contradiction with astrophysical bounds. We develop a particle physics model
with two paraphotons and with a low energy scale in which these apparent
inconsistencies are circumvented.


  A statistical manifold is a pseudo-Riemannian manifold endowed with a Codazzi
structure.
  This structure plays an important role in Information Geometry and its
related fields, e.g., a statistical model admits this structure with the
Fisher-Rao metric.
  In practical application, however, the metric may be degenerate, and then
this geometric structure is not fully adapted.
  In the present paper, for such cases, we introduce the notice of
quasi-Codazzi structure which consists of a possibly degenerate metric (i.e.,
symmetric $(0,2)$-tensor) and a pair of coherent tangent bundles with affine
connections.
  This is thought of as an affine differential geometry of Lagrange subbundles
of para-Hermitian vector bundles and also as a submanifold theory of
para-Hermitian space-form.
  As a special case, the quasi-Codazzi structure with flat connections
coincides with the quasi-Hessian structure previously studied by
Nakajima-Ohmoto.
  The relation among our quasi-Codazzi structure, quasi-Hessian structure and
weak contrast functions generalizes the relation among Codazzi structure,
dually flat (i.e., Hessian) structure and contrast functions.


  We study the Bolker-Pacala-Dieckmann-Law (BPDL) model of population dynamics
in the regime of large population density. The BPDL model is a particle system
in which particles reproduce, move randomly in space, and compete with each
other locally. We rigorously prove global survival as well as a shape theorem
describing the asymptotic spread of the population, when the population density
is sufficiently large. In contrast to most previous studies, we allow the
competition kernel to have an arbitrary, even infinite range, whence the term
non-local competition. This makes the particle system non-monotone and of
infinite-range dependence, meaning that the usual comparison arguments break
down and have to be replaced by a more hands-on approach. Some ideas in the
proof are inspired by works on the non-local Fisher-KPP equation, but the
stochasticity of the model creates new difficulties.


  We study the rate of convergence to equilibrium of the solution of a
Fokker--Planck type equation introduced by one of the authors in 2006 to
describe opinion formation in a multi-agent system. The main feature of this
Fokker--Planck equation is the presence of a variable diffusion coefficient and
boundaries, which introduce new challenging mathematical problems in the study
of its long-time behavior.


  We present the discovery and early evolution of ASASSN-19bt, a tidal
disruption event (TDE) discovered by the All-Sky Automated Survey for
Supernovae (ASAS-SN) at a distance of $d\simeq115$ Mpc and the first TDE to be
detected by TESS. As the TDE is located in the TESS Continuous Viewing Zone,
our dataset includes 30-minute cadence observations starting on 2018 July 25,
and we precisely measure that the TDE begins to brighten $\sim8.3$ days before
its discovery. Our dataset also includes 18 epochs of Swift UVOT and XRT
observations, 2 epochs of XMM-Newton observations, 13 spectroscopic
observations, and ground data from the Las Cumbres Observatory telescope
network, spanning from 32 days before peak through 37 days after peak.
ASASSN-19bt thus has the most detailed pre-peak dataset for any TDE. The TESS
light curve indicates that the transient began to brighten on 2019 January 21.6
and that for the first 15 days its rise was consistent with a flux $\propto
t^2$ power-law model. The optical/UV emission is well-fit by a blackbody SED,
and ASASSN-19bt exhibits an early spike in its luminosity and temperature
roughly 32 rest-frame days before peak and spanning up to 14 days that has not
been seen in other TDEs, possibly because UV observations were not triggered
early enough to detect it. It peaked on 2019 March 04.9 at a luminosity of
$L\simeq1.3\times10^{44}$ ergs s$^{-1}$ and radiated $E\simeq3.2\times10^{50}$
ergs during the 41-day rise to peak. X-ray observations after peak indicate a
softening of the hard X-ray emission prior to peak, reminiscent of the
hard/soft states in X-ray binaries.


  The Higgs mode associated with amplitude fluctuations of the superconducting
gap in uniform superconductors usually is heavy, which makes its excitation and
detection difficult. We report on the existence of a gapless Higgs mode in the
Fulde-Ferrell-Larkin-Ovchinnikov states. This feature is originated from the
Goldstone mode associated with the translation symmetry breaking. The existence
of the gapless Higgs mode is demonstrated by using both a phenomenological
model and microscopic Bardeen-Cooper-Schrieffer (BCS) theory. The gapless Higgs
mode can avoid the decay into other low energy excitations, which renders it
stable and detectable.


  We present results from the first twelve months of operation of Radio Galaxy
Zoo, which upon completion will enable visual inspection of over 170,000 radio
sources to determine the host galaxy of the radio emission and the radio
morphology. Radio Galaxy Zoo uses $1.4\,$GHz radio images from both the Faint
Images of the Radio Sky at Twenty Centimeters (FIRST) and the Australia
Telescope Large Area Survey (ATLAS) in combination with mid-infrared images at
$3.4\,\mu$m from the {\it Wide-field Infrared Survey Explorer} (WISE) and at
$3.6\,\mu$m from the {\it Spitzer Space Telescope}. We present the early
analysis of the WISE mid-infrared colours of the host galaxies. For images in
which there is $>\,75\%$ consensus among the Radio Galaxy Zoo
cross-identifications, the project participants are as effective as the science
experts at identifying the host galaxies. The majority of the identified host
galaxies reside in the mid-infrared colour space dominated by elliptical
galaxies, quasi-stellar objects (QSOs), and luminous infrared radio galaxies
(LIRGs). We also find a distinct population of Radio Galaxy Zoo host galaxies
residing in a redder mid-infrared colour space consisting of star-forming
galaxies and/or dust-enhanced non star-forming galaxies consistent with a
scenario of merger-driven active galactic nuclei (AGN) formation. The
completion of the full Radio Galaxy Zoo project will measure the relative
populations of these hosts as a function of radio morphology and power while
providing an avenue for the identification of rare and extreme radio
structures. Currently, we are investigating candidates for radio galaxies with
extreme morphologies, such as giant radio galaxies, late-type host galaxies
with extended radio emission, and hybrid morphology radio sources.


  In this paper, a novel Snail Homing and Mating Search (SHMS) algorithm is
proposed. It is inspired from the biological behaviour of the snails. Snails
continuously travels to find food and a mate, leaving behind a trail of mucus
that serves as a guide for their return. Snails tend to navigate by following
the available trails on the ground and responding to cues from nearby shelter
homes. The proposed SHMS algorithm is investigated by solving several unimodal
and multimodal functions. The solutions are validated using standard
statistical tests such as two-sided and pairwise signed rank Wilcoxon test and
Friedman rank test. The solution obtained from the SHMS algorithm exhibited
superior robustness as well as search space exploration capabilities within the
less computational cost. The real-world application of SHMS algorithm is
successfully demonstrated in the engineering design domain by solving three
cases of design and economic optimization shell and tube heat exchanger
problem. The objective function value and other statistical results obtained
using SHMS algorithm are compared with other well-known metaheuristic
algorithms.


  We illustrate a technique for fitting lattice QCD correlators to sums of
exponentials that is significantly faster than traditional fitting methods ---
10--40 times faster for the realistic examples we present. Our examples are
drawn from a recent analysis of the Upsilon spectrum, and another recent
analysis of the D -> pi semileptonic form factor. For single correlators, we
show how to simplify traditional effective-mass analyses.


  We report new observations of the intermediate-frequency peaked BL Lacertae
object 3C 66A with the MAGIC telescopes. The data sample we use were taken in
2009 December and 2010 January, and comprises 2.3 hr of good quality data in
stereoscopic mode. In this period, we find a significant signal from the
direction of the blazar 3C 66A. The new MAGIC stereoscopic system is shown to
play an essential role for the separation between 3C 66A and the nearby radio
galaxy 3C 66B, which is at a distance of only $6^\prime$. The derived integral
flux above $100\eh{GeV}$ is 8.3% of Crab Nebula flux and the energy spectrum is
reproduced by a power law of photon index $3.64 \pm 0.39_{\rm stat} \pm
0.25_{\rm sys}$. Within errors, this is compatible with the one derived by
VERITAS in 2009. From the spectra corrected for absorption by the extragalactic
background light, we only find small differences between the four models that
we applied, and constrain the redshift of the blazar to $z < 0.68$.


  Since its inception six decades ago, astrobiology has diversified immensely
to encompass several scientific questions including the origin and evolution of
Terran life, the organic chemical composition of extraterrestrial objects, and
the concept of habitability, among others. The detection of life beyond Earth
forms the main goal of astrobiology, and a significant one for space
exploration in general. This goal has galvanized and connected with other
critical areas of investigation such as the analysis of meteorites and early
Earth geological and biological systems, materials gathered by sample-return
space missions, laboratory and computer simulations of extraterrestrial and
early Earth environmental chemistry, astronomical remote sensing, and in-situ
space exploration missions. Lately, scattered efforts are being undertaken
towards the R&D of the novel and as-yet-space-unproven life-detection
technologies capable of obtaining unambiguous evidence of extraterrestrial
life, even if it is significantly different from Terran life. As the suite of
space-proven payloads improves in breadth and sensitivity, this is an apt time
to examine the progress and future of life-detection technologies.


  Thermo-electric transport at the nano-scale is a rapidly developing topic, in
particular in superconductor-based hybrid devices. In this review paper, we
first discuss the fundamental principles of electronic cooling in mesoscopic
superconducting hybrid structures, the related limitations and applications. We
review recent work performed in Grenoble on the effects of Andreev reflection,
photonic heat transport, phonon cooling, as well as on an innovative
fabrication technique for powerful coolers.


  A survey that can cover the sky in optical bands over wide fields to faint
magnitudes with a fast cadence will enable many of the exciting science
opportunities of the next decade. The Large Synoptic Survey Telescope (LSST)
will have an effective aperture of 6.7 meters and an imaging camera with field
of view of 9.6 deg^2, and will be devoted to a ten-year imaging survey over
20,000 deg^2 south of +15 deg. Each pointing will be imaged 2000 times with
fifteen second exposures in six broad bands from 0.35 to 1.1 microns, to a
total point-source depth of r~27.5. The LSST Science Book describes the basic
parameters of the LSST hardware, software, and observing plans. The book
discusses educational and outreach opportunities, then goes on to describe a
broad range of science that LSST will revolutionize: mapping the inner and
outer Solar System, stellar populations in the Milky Way and nearby galaxies,
the structure of the Milky Way disk and halo and other objects in the Local
Volume, transient and variable objects both at low and high redshift, and the
properties of normal and active galaxies at low and high redshift. It then
turns to far-field cosmological topics, exploring properties of supernovae to
z~1, strong and weak lensing, the large-scale distribution of galaxies and
baryon oscillations, and how these different probes may be combined to
constrain cosmological models and the physics of dark energy.


  In this paper, we present a two-stream multi-task network for fashion
recognition. This task is challenging as fashion clothing always contain
multiple attributes, which need to be predicted simultaneously for real-time
industrial systems. To handle these challenges, we formulate fashion
recognition into a multi-task learning problem, including landmark detection,
category and attribute classifications, and solve it with the proposed deep
convolutional neural network. We design two knowledge sharing strategies which
enable information transfer between tasks and improve the overall performance.
The proposed model achieves state-of-the-art results on large-scale fashion
dataset comparing to the existing methods, which demonstrates its great
effectiveness and superiority for fashion recognition.


  We study a cosmological model composed of a dark energy fluid interacting
with a viscous matter fluid in a spatially flat Universe. The matter component
represents the baryon and dark matter and it is taken into account, through a
bulk viscosity, the irreversible process that the matter fluid undergoes
because of the accelerated expansion of the universe. The bulk viscous
coefficient is assumed to be proportional to the Hubble parameter. The
radiation component is also taken into account in the model. The model is
constrained using the type Ia supernova observations, the shift parameter of
the CMB, the acoustic peak of the BAO and the Hubble expansion rate, to
constrain the values of the barotropic index of dark energy and the bulk
viscous coefficient. It is found that the bulk viscosity is constrained to be
negligible (around zero) from the observations and that the barotropic index
for the dark energy to be negative and close to zero too, indicating a phantom
energy.


  In this paper we generalized the slave-particle technique to study the phase
diagram of the Hubbard model on honeycomb lattice which may contain charge
fluctuations. For large $U$, we have antiferromagnetic order phase. As we
decrease $U$ below $U_{c2}\simeq 3t$, the system undergoes a first order phase
transition into a gapped spin rotation invariant phase. Under a semiclassical
approximation of the slave-particle approach, we find that such phase breaks
the translation symmetry, the parity and the lattice rotation symmetry.
However, beyond the semiclassical approximation, a $Z_2$ spin liquid that does
not break any lattice symmetry is also possible.


  In quantum computing, the efficient optimization of Pauli string
decompositions is a crucial aspect for the compilation of quantum circuits for
many applications, such as chemistry simulations and quantum machine learning.
In this paper, we propose a novel algorithm for the synthesis of trotterized
time-evolution operators that results in circuits with significantly fewer
gates than previous solutions. Our synthesis procedure takes the qubit
connectivity of a target quantum computer into account. As a result, the
generated quantum circuit does not require routing, and no additional CNOT
gates are needed to run the resulting circuit on a target device. We compare
our algorithm against Paulihedral and TKET, and show a significant improvement
for randomized circuits and different molecular ansatzes. We also investigate
the Trotter error introduced by our ordering of the terms in the Hamiltonian
versus default ordering and the ordering from the baseline methods and conclude
that our method on average does not increase the Trotter error.


  Given a compact and complete metric space $X$ with several continuous
transformations $T_1, T_2, \ldots T_H: X \to X,$ we find sufficient conditions
for the existence of a point $x\in X$ such that $(x,x,\ldots,x)\in X^H$ has
dense orbit for the transformation $$\mathcal T:=T_1\times
T_2\times\cdots\times T_H.$$
  We use these conditions together with Liv\v{s}ic theorem, to obtain that for
$\alpha$-H\"older maps $f_1,f_2,\ldots,f_H: X\to \mathbb{R},$ the product
$\prod_{i=1}^H f_i(x_i)$ is a smooth coboundary with respect to $\mathcal T$ is
equivalent to the existence of a non-empty open subset $U \subset X$ such that
  $$\sup_{N} \sup_{x\in U}\left| \sum_{j=0}^{N} \prod_{i=1}^H f_i (T_i^{j} x)
\right| < \infty.$$


  Recent trends in Large Vision Language Models (LVLMs) research have been
increasingly focusing on advancing beyond general image understanding towards
more nuanced, object-level referential comprehension. In this paper, we present
and delve into the self-consistency capability of LVLMs, a crucial aspect that
reflects the models' ability to both generate informative captions for specific
objects and subsequently utilize these captions to accurately re-identify the
objects in a closed-loop process. This capability significantly mirrors the
precision and reliability of fine-grained visual-language understanding. Our
findings reveal that the self-consistency level of existing LVLMs falls short
of expectations, posing limitations on their practical applicability and
potential. To address this gap, we introduce a novel fine-tuning paradigm named
Self-Consistency Tuning (SC-Tune). It features the synergistic learning of a
cyclic describer-locator system. This paradigm is not only data-efficient but
also exhibits generalizability across multiple LVLMs. Through extensive
experiments, we demonstrate that SC-Tune significantly elevates performance
across a spectrum of object-level vision-language benchmarks and maintains
competitive or improved performance on image-level vision-language benchmarks.
Both our model and code will be publicly available at
https://github.com/ivattyue/SC-Tune.


  Context. Capella is among the few binary stars with two evolved giant
components. The hotter component is a chromospherically active star within the
Hertzsprung gap, while the cooler star is possibly helium-core burning. Aims.
The known inclination of the orbital plane from astrometry in combination with
precise radial velocities will allow very accurate masses to be determined for
the individual Capella stars. This will constrain their evolutionary stage and
possibly the role of the active star's magnetic field on the dynamical
evolution of the binary system. Methods. We obtained a total of 438
high-resolution \'echelle spectra during the years 2007-2010 and used the
measured velocities to recompute the orbital elements. Our double-lined orbital
solution yields average residuals of 64 m/s for the cool component and 297 m/s
for the more rapidly rotating hotter component. Results. The semi-amplitude of
the cool component is smaller by 0.045 km/s than the orbit determination of
Torres et al. from data taken during 1996-1999 but more precise by a factor of
5.5, while for the hotter component it is larger by 0.580 km/s and more precise
by a factor of 3.6. This corresponds to masses of 2.573\pm0.009 M_sun and
2.488\pm0.008 M_sun for the cool and hot component, respectively. Their
relative errors of 0.34% and 0.30% are about half of the values given in Torres
et al. for a combined literature- data solution but with absolute values
different by 4% and 2% for the two components, respectively. The mass ratio of
the system is therefore q = M_A/M_B = 0.9673 \pm 0.0020. Conclusions. Our orbit
is the most precise and also likely to be the most accurate ever obtained for
Capella.


  Babson and Steingr\'{\i}msson introduced generalized permutation patterns and
showed that most of the Mahonian statistics in the literature can be expressed
by the combination of generalized pattern functions. Particularly, they defined
a new Mahonian statistic in terms of generalized pattern functions, which is
denoted $stat$. Given a permutation $\pi$, let $des(\pi)$ denote the descent
number of $\pi$ and $maj(\pi)$ denote the major index of $\pi$. Babson and
Steingr\'{\i}msson conjectured that $(des,stat)$ and $(des,maj)$ are
equidistributed on $S_n$. Foata and Zeilberger settled this conjecture using
q-enumeration, generating functions and Maple packages ROTA and PERCY. Later,
Burstein provided a bijective proof of a refinement of this conjecture. In this
paper, we give a new bijective proof of this conjecture.


  Cosmological simulations predict more classical bulges than their
observational counterpart in the local Universe. Here, we quantify evolution of
the bulges since $z=0.1$ using photometric parameters of nearly 39,000 unbarred
disc galaxies from SDSS DR7 which are well represented by two components. We
adopted a combination of the S\'ersic index and Kormendy relation to separate
classical bulges and disc-like pseudo-bulges. We found that the fraction of
pseudo-bulges (classical bulges) smoothly increases (decreases) as the Universe
gets older. In the history of the Universe, there comes a point ($z \approx
0.016$) when classical bulges and pseudo-bulges become equal in number. The
fraction of pseudo-bulges rises with increasing bulge to disc half-light radius
ratio until R$_{\rm e}$/R$_{\rm hlr} \approx 0.6$ suggesting concentrated disc
is the most favourable place for pseudo-bulge formation. The mean ellipticity
of pseudo-bulges is always greater than that of classical bulges and it
decreases with decreasing redshift indicating that the bulges tend to be more
axisymmetric with evolution. Also, the massive bulges are progressing towards
axisymmetry at steeper rate than the low-mass bulges. There is no tight
correlation of bulge S\'ersic index evolution with other photometric properties
of the galaxy. Using the sample of multi-component fitting of $S^4G$ data and
$N-$body galaxy models, we have verified that our results are consistent or
even more pronounced with multi-component fitting and high-resolution
photometry.


  A brief summary of the hadronic calorimeter calibration systems and
performance results, in the ATLAS detector at the LHC is given.


  Let $\mathbf{Y}$ be the solution space of an $n$-layer cellular neural
network, and let $\mathbf{Y}^{(i)}$ and $\mathbf{Y}^{(j)}$ be the hidden
spaces, where $1 \leq i, j \leq n$. ($\mathbf{Y}^{(n)}$ is called the output
space.) The classification and the existence of factor maps between two hidden
spaces, that reaches the same topological entropies, are investigated in [Ban
et al., J.~Differential Equations \textbf{252}, 4563-4597, 2012]. This paper
elucidates the existence of factor maps between those hidden spaces carrying
distinct topological entropies. For either case, the Hausdorff dimension $\dim
\mathbf{Y}^{(i)}$ and $\dim \mathbf{Y}^{(j)}$ can be calculated. Furthermore,
the dimension of $\mathbf{Y}^{(i)}$ and $\mathbf{Y}^{(j)}$ are related upon the
factor map between them.


  Waves observed in the photosphere and chromosphere of sunspots show complex
dynamics and spatial patterns. The interpretation of high-resolution sunspot
wave observations requires modeling of three-dimensional non-linear wave
propagation and mode transformation in the sunspot upper layers in realistic
spot model atmospheres. Here we present the first results of such modeling. We
have developed a 3D non-linear numerical code specially designed to calculate
the response of magnetic structures in equilibrium to an arbitrary
perturbation. The code solves the 3D nonlinear MHD equations for perturbations;
it is stabilized by hyper-diffusivity terms and is fully parallelized. The
robustness of the code is demonstrated by a number of standard tests. We
analyze several simulations of a sunspot perturbed by pulses of different
periods at subphotospheric level, from short periods, introduced for academic
purposes, to longer and realistic periods of three and five minutes. We present
a detailed description of the three-dimensional mode transformation in a
non-trivial sunspot-like magnetic field configuration, including the conversion
between fast and slow magneto-acoustic waves and the Alfv\'en wave, by
calculation of the wave energy fluxes. Our main findings are the following: (1)
the conversion from acoustic to the Alfv\'en mode is only observed if the the
driving pulse is located out of the sunspot axis, but this conversion is
energetically inefficient; (2) as a consequence of the cut-off effects and
refraction of the fast magneto-acoustic mode, the energy of the evanescent
waves with periods around 5 minutes remains almost completely below the level
beta=1; (3) waves with frequencies above the cut-off propagate field-aligned to
the chromosphere and their power becomes dominating over that of evanescent
5-minute oscillations, in agreement with observations.


  The modified Ginzburg-Landau equations are used to study some fundamental
problems for the high temperature superconductors. The derivations of these
fundamental equations are summarized and the layered features of the sample
were taken into consideration and the relation between the coherence length and
the separation distance of the layers. The domain wall energy, the maximum
supercurrent and the parallel critical field of high temerature superconducting
thin film were evaluated. Comparison with previous works is given


  Accreting black holes are known to power relativistic jets, both in
stellar-mass binary systems and at the centres of galaxies. The power carried
away by the jets, and hence the feedback they provide to their surroundings,
depends strongly on their composition. Jets containing a baryonic component
should carry significantly more energy than electron-positron jets. While
energetic considerations and circular polarisation measurements have provided
conflicting circumstantial evidence for the presence or absence of baryons, the
only system in which baryons have been unequivocally detected in the jets is
the X-ray binary SS 433. Here we report the detection of Doppler-shifted X-ray
emission lines from a more typical black hole candidate X-ray binary,
4U1630-47, coincident with the reappearance of radio emission from the jets of
the source. We argue that these lines arise in a jet with velocity 0.66c,
thereby establishing the presence of baryons in the jet. Such baryonic jets are
more likely to be powered by the accretion disc rather than the spin of the
black hole, and if the baryons can be accelerated to relativistic speeds,
should be strong sources of gamma rays and neutrino emission.


  Recent X-ray and optical observations of the Perseus cluster indicate that
the viscous and conductive dissipation of sound waves is the mechanism
responsible for heating the intracluster medium and thus balancing radiative
cooling of cluster cores. We discuss this mechanism more generally and show how
the specific heating and cooling rates vary with temperature and radius. It
appears that the heating mechanism is most effective above 10^7K, which allows
for radiative cooling to proceed within normal galaxy formation but will stifle
the growth of very massive galaxies. The scaling of the wavelength of sound
waves with cluster temperature and feedback in the system are investigated.


  Magnetic field (H) effects on a correlated electron system with the
spin-state degree of freedom are examined. The effective Hamiltonian derived
from the two-orbital Hubbard model is analyzed by the mean-field approximation.
Applying H to the low-spin (LS) phase induces the excitonic insulating phase,
as well as the spin-state ordered phase where the LS and high-spin (HS) states
are ordered alternately. In the case where H is applied to the HS phase, a
reentrant transition for the HS phase appears. A rich variety of the phase
diagrams are attributed to the spin-state degree of freedom and their
combinations in the wave function as well as in the real-space configuration.


  Extending the classical notion of the spreading model, the $k$-spreading
models of a Banach space are introduced, for every $k\in\mathbb{N}$. The
definition, which is based on the $k$-sequences and plegma families, reveals a
new class of spreading sequences associated to a Banach space. Most of the
results of the classical theory are stated and proved in the higher order
setting. Moreover, new phenomena like the universality of the class of the
2-spreading models of $c_0$ and the composition property are established. As
consequence, a problem concerning the structure of the $k$-iterated spreading
models is solved.


  We consider the minimal coupling of two photons to neutral scalar and
pseudoscalar fields, as for instance in the case of the Higgs boson and axion,
respectively. In this framework, we analyze the photon dispersion relations in
the presence of static and homogeneous external magnetic and electric fields,
by taking into account the contribution of the imaginary part of the
scalar/pseudoscalar self-energy. We show that this contribution cannot be
neglected when it is of the same order as the photon-scalar/pseudoscalar mixing
term. In addition to the usual light-like photon propagation mode, with a
refraction index n > 1, a massive mode with mass of the order of the coupled
boson mass can be induced, provided that the external field is above a
particular critical value. Depending on the values of the external field,
photon energy, and mass of the scalar/pseudoscalar particle, the
scalar/pseudoscalar width could induce a sizeable rate of photon splitting in
two photons due to a strong resonant phenomenon. This effect has no practical
laboratory applications for the Higgs physics due to the very large critical
external magnetic or electric fields involved, for a photon energy of the order
of a TeV. However, it can have relevant consequences in the axion physics or in
any other scenario where light neutral scalar/pseudoscalar fields have minimal
coupling with two photons.


  Introductory and pedagogical treatmeant of the article : P. Broussous
"Distinction of the Steinberg representation", with an appendix by Fran\c{c}ois
Court\`es, IMRN 2014, no 11, 3140-3157. To appear in Proceedings of Chaire Jean
Morlet, Dipendra Prasad, Volker Heiermann Ed. 2017. Contains modified and
simplified proofs of loc. cit. This article is written in memory of
Fran\c{c}ois Court\`es who passed away in september 2016.


  Contemporary domain adaptive semantic segmentation aims to address data
annotation challenges by assuming that target domains are completely
unannotated. However, annotating a few target samples is usually very
manageable and worthwhile especially if it improves the adaptation performance
substantially. This paper presents SSDAS, a Semi-Supervised Domain Adaptive
image Segmentation network that employs a few labeled target samples as anchors
for adaptive and progressive feature alignment between labeled source samples
and unlabeled target samples. We position the few labeled target samples as
references that gauge the similarity between source and target features and
guide adaptive inter-domain alignment for learning more similar source
features. In addition, we replace the dissimilar source features by
high-confidence target features continuously during the iterative training
process, which achieves progressive intra-domain alignment between confident
and unconfident target features. Extensive experiments show the proposed SSDAS
greatly outperforms a number of baselines, i.e., UDA-based semantic
segmentation and SSDA-based image classification. In addition, SSDAS is
complementary and can be easily incorporated into UDA-based methods with
consistent improvements in domain adaptive semantic segmentation.


  Given a random matrix A with eigenvalues between -1 and 1, we analyze the
number of iterations needed to solve the linear equation (I-A)x=b with the
Neumann series iteration. We give sufficient conditions for convergence of an
upper bound of the iteration count in distribution. Specifically, our results
show that when the scaled extreme eigenvalues of A converge in distribution,
this scaled upper bound on the number of iterations will converge to the
reciprocal of the limiting distribution of the largest eigenvalue.


  We give formulas for the density of visible points of several families of
planar quasicrystals, which include the Ammann-Beenker point set and vertex
sets of some rhombic Penrose tilings. These densities are used in order to
calculate the limiting minimal normalised gap between the angles of visible
points in two families of planar quasicrystals, which include the
Ammann-Beenker point set and vertex sets of some rhombic Penrose tilings.


  The two-point correlation of the 4th (current) BATSE catalog (2494 objects)
is calculated. It is shown to be consistent with zero at nearly all angular
scales of interest. Assuming that GRBs trace the large scale structure in the
universe we calculate the angular correlation function for the standard CDM
(sCDM) model. It is shown to be $\le 10^{-4}$ at $\theta \simeq 5^\circ$ if the
BATSE catalog is assumed to be a volume-limited sample up to $z \simeq 1$.
Combined with the error analysis on the BATSE catalog this suggests that nearly
$10^5$ GRBs will be needed to make a positive detection of the two-point
angular correlation function at this angular scale.


  For fixed $r\geq 2$, we consider bootstrap percolation with threshold $r$ on
the Erd\H{o}s-R\'enyi graph ${\cal G}_{n,p}$. We identify a threshold for $p$
above which there is with high probability a set of size $r$ which can infect
the entire graph. This improves a result of Feige, Krivelevich and Reichman,
which gives bounds for this threshold, up to multiplicative constants.
  As an application of our results, we also obtain an upper bound for the
threshold for $K_4$-bootstrap percolation on ${\cal G}_{n,p}$, as studied by
Balogh, Bollob\'as and Morris. We conjecture that our bound is asymptotically
sharp.
  These thresholds are closely related to the survival probabilities of certain
time-varying branching processes, and we derive asymptotic formulae for these
survival probabilities which are of interest in their own right.


  In this work, we propose a family of single-node second-order boundary
schemes for the lattice Boltzmann method with general collision terms. The
construction of the schemes is quite universal and simple, it does not involve
concrete lattice Boltzmann models and uses the half-way bounce-back rule as a
central step. The constructed schemes are all second-order accurate if so is
the bounce-back rule. In addition, the proposed schemes have good stability
thanks to convex combinations. The accuracy and stability of several specific
schemes are numerically validated for multiple-relaxation-time models in both
2D and 3D.


  Predicting the evolution of expanding population is critical to control
biological threats such as invasive species and virus explosion. In this paper,
we consider a two species chemotaxis system of parabolic-parabolic-elliptic
type with Lotka-Volterra type competition terms and a free boundary. Such a
model with a free boundary describes the spreading of new or invasive species
subject to the influence of some chemical substances in an environment with a
free boundary representing the spreading front. We first find conditions on the
parameters which guarantee the global existence and boundedness of classical
solutions with nonnegative initial functions. Next, we investigate
vanishing-spreading dichotomy scenarios for positive solutions. It is shown
that the vanishing-spreading dichotomy in the generalized sense always occurs;
that the vanishing spreading dichotomy in the strong sense occurs when the
competition between two species is weak-weak competition; and that the
vanishing spreading dichotomy in the weak sense occurs when the competition
between two species is weak-strong competition.


  In this paper we prove a volume = multiplicity type theorem for epsilon
multiplicity. We show that epsilon multiplicity is a limit of Amao
multiplicities.


  We find three families of twisting maps of K^m with K^n. One of them is
related to truncated quiver algebras, the second one consists of deformations
of the first and the third one requires m=n and yields algebras isomorphic to
M_n(K). Using these families and some exceptional cases we construct all
twisting maps of K^3 with K^3.


  We present a method to measure the binary diffusion coefficient of mercury
atoms in a gas at room temperature and low pressure. It is based on the
measurement of the longitudinal spin relaxation of optically pumped mercury-199
atoms in a magnetic field gradient. We provide a consistent set of diffusion
coefficients for helium-3, helium-4, argon, krypton, xenon, nitrogen, carbon
dioxide, oxygen, and air.


  Since the discovery of the muon, particle physicists have carried out a
series of experiments aimed at measuring flavor violation in charged-lepton
interactions. To date, no such violation has been observed. The Mu2e experiment
at Fermilab will search for the charged lepton flavor violating process of
coherent muon-to-electron conversion in the presence of a nucleus with a
sensitivity four orders of magnitude beyond current limits. The experiment will
have a single event sensitivity of about $2.5\times10^{-17}$ while limiting the
total background to less than 0.5 events. One potential background is due to
cosmic-ray muons producing an electron that is indistinguishable from signal
within the Mu2e apparatus. The cosmic-ray-veto system of the Mu2e experiment is
tasked with vetoing cosmic-ray-induced backgrounds with high efficiency without
inducing significant dead time and while operating in a high-intensity
environment. In this note the challenges related to the high-radiation
environment that influence the design of the cosmic-ray-veto system will be
discussed.


  An articulation point in a network is a node whose removal disconnects the
network. Those nodes play key roles in ensuring connectivity of many real-world
networks, from infrastructure networks to protein interaction networks and
terrorist communication networks. Despite their fundamental importance, a
general framework of studying articulation points in complex networks is
lacking. Here we develop analytical tools to study key issues pertinent to
articulation points, e.g. the expected number of them and the network
vulnerability against their removal, in an arbitrary complex network. We find
that a greedy articulation point removal process provides us a novel
perspective on the organizational principles of complex networks. Moreover,
this process is associated with two fundamentally different types of
percolation transitions with a rich phase diagram. Our results shed light on
the design of more resilient infrastructure networks and the effective
destruction of terrorist communication networks.


  Numerous Knowledge Graphs (KGs) are being created to make Recommender Systems
(RSs) not only intelligent but also knowledgeable. Integrating a KG in the
recommendation process allows the underlying model to extract reasoning paths
between recommended products and already experienced products from the KG.
These paths can be leveraged to generate textual explanations to be provided to
the user for a given recommendation. However, the existing explainable
recommendation approaches based on KG merely optimize the selected reasoning
paths for product relevance, without considering any user-level property of the
paths for explanation. In this paper, we propose a series of quantitative
properties that monitor the quality of the reasoning paths from an explanation
perspective, based on recency, popularity, and diversity. We then combine in-
and post-processing approaches to optimize for both recommendation quality and
reasoning path quality. Experiments on three public data sets show that our
approaches significantly increase reasoning path quality according to the
proposed properties, while preserving recommendation quality. Source code, data
sets, and KGs are available at https://tinyurl.com/bdbfzr4n.


  NIKA is a dual-band camera operating with 315 frequency multiplexed LEKIDs
cooled at 100 mK. NIKA is designed to observe the sky in intensity and
polarisation at 150 and 260 GHz from the IRAM 30-m telescope. It is a
test-bench for the final NIKA2 camera. The incoming linear polarisation is
modulated at four times the mechanical rotation frequency by a warm rotating
multi-layer Half Wave Plate. Then, the signal is analysed by a wire grid and
finally absorbed by the LEKIDs. The small time constant (< 1ms ) of the LEKID
detectors combined with the modulation of the HWP enables the
quasi-simultaneous measurement of the three Stokes parameters I, Q, U,
representing linear polarisation. In this paper we present results of recent
observational campaigns demonstrating the good performance of NIKA in detecting
polarisation at mm wavelength.