  We present theoretical and experimental results exploring a half-Heusler
compound TmPdSb with unusual band order and metallic surface states. Typically,
the half-Heusler systems exhibit topological features in a semimetallic state,
and trivial ones in an insulating state. Topological properties of the most of
half-Heusler systems are related to the band inversion around the Fermi level,
similar to this observed in CdTe/HgTe systems. In the case of TmPdSb we
observed the gapped electronic band structure with ``band inversion'' in the
conductance band, while the slab-like system realized metallic surface states.
The bulk insulating nature of the compound was corroborated by means of
electrical transport measurements. The experimental data revealed several
features due to the presence of metallic surface states, such as linear
magnetoresistance and weak-antilocalization effect, characterized by enhanced
coherence length and a very large number of surface conductive channels. Our
findings reveal new features of the rare-earth half-Heusler.


  Chemo-dynamical models have been introduced in the late eighties and are a
generally accepted tool for understanding galaxy evolution. They have been
successfully applied to one-dimensional problems, e.g. the evolution of
non-rotating galaxies, and two-dimensional problems, e.g. the evolution of disk
galaxies. Recently, also three-dimensional chemo-dynamical models have become
available. In these models the dynamics of different components, i.e. dark
matter, stars and a multi-phase interstellar medium, are treated in a
self-consistent way and several processes allow for an exchange of matter,
energy and momentum between the components or different gas phases. Some
results of chemo-dynamical models and their comparison with observations of
chemical abundances or star formation histories will be reviewed.


  Automating radiology report generation can significantly alleviate
radiologists' workloads. Previous research has primarily focused on realizing
highly concise observations while neglecting the precise attributes that
determine the severity of diseases (e.g., small pleural effusion). Since
incorrect attributes will lead to imprecise radiology reports, strengthening
the generation process with precise attribute modeling becomes necessary.
Additionally, the temporal information contained in the historical records,
which is crucial in evaluating a patient's current condition (e.g., heart size
is unchanged), has also been largely disregarded. To address these issues, we
propose RECAP, which generates precise and accurate radiology reports via
dynamic disease progression reasoning. Specifically, RECAP first predicts the
observations and progressions (i.e., spatiotemporal information) given two
consecutive radiographs. It then combines the historical records,
spatiotemporal information, and radiographs for report generation, where a
disease progression graph and dynamic progression reasoning mechanism are
devised to accurately select the attributes of each observation and
progression. Extensive experiments on two publicly available datasets
demonstrate the effectiveness of our model.


  We present results from Chandra observations of SDSS J1004+4112, a strongly
lensed quasar system with a maximum image separation of 15". All four bright
images of the quasar, as well as resolved X-ray emission originating from the
lensing cluster, are clearly detected. The emission from the lensing cluster
extends out to approximately 1.5 arcmin. We measure the bolometric X-ray
luminosity and temperature of the lensing cluster to be 4.7e44 erg s^-1 and 6.4
keV, consistent with the luminosity-temperature relation for distant clusters.
The mass estimated from the X-ray observation shows excellent agreement with
the mass derived from gravitational lensing. The X-ray flux ratios of the
quasar images differ markedly from the optical flux ratios, and the combined
X-ray spectrum of the images possesses an unusually strong Fe Kalpha emission
line, both of which are indicative of microlensing.


  At the leading order, the low-energy effective field equations in string
theory admit solutions of the form of products of Minkowski spacetime and a
Ricci-flat Calabi-Yau space. The equations of motion receive corrections at
higher orders in \alpha', which imply that the Ricci-flat Calabi-Yau space is
modified. In an appropriate choice of scheme, the Calabi-Yau space remains
Kahler, but is no longer Ricci-flat. We discuss the nature of these corrections
at order {\alpha'}^3, and consider the deformations of all the known
cohomogeneity one non-compact Kahler metrics in six and eight dimensions. We do
this by deriving the first-order equations associated with the modified
Killing-spinor conditions, and we thereby obtain the modified supersymmetric
solutions. We also give a detailed discussion of the boundary terms for the
Euler complex in six and eight dimensions, and apply the results to all the
cohomogeneity one examples.


  For large scale applications, hybrid pixel detectors, in which sensor and
read-out IC are separate entities, constitute the state of the art in pixel
detector technology to date. They have been developed and start to be used as
tracking detectors and also imaging devices in radiography, autoradiography,
protein crystallography and in X-ray astronomy. A number of trends and
possibilities for future applications in these fields with improved
performance, less material, high read-out speed, large radiation tolerance, and
potential off-the-shelf availability have appeared and are momentarily matured.
Among them are monolithic or semi-monolithic approaches which do not require
complicated hybridization but come as single sensor/IC entities. Most of these
are presently still in the development phase waiting to be used as detectors in
experiments. The present state in pixel detector development including hybrid
and (semi-)monolithic pixel techniques and their suitability for particle
detection and for imaging, is reviewed.


  We demonstrate that an undoped two-dimensional carbon plane (graphene) whose
bulk is in the integer quantum Hall regime supports a non-chiral Luttinger
liquid at an armchair edge. This behavior arises due to the unusual dispersion
of the non-interacting edges states, causing a crossing of bands with different
valley and spin indices at the edge. We demonstrate that this stabilizes a
domain wall structure with a spontaneously ordered phase degree of freedom.
This coherent domain wall supports gapless charged excitations, and has a power
law tunneling $I-V$ with a non-integral exponent. In proximity to a bulk lead,
the edge may undergo a quantum phase transition between the Luttinger liquid
phase and a metallic state when the edge confinement is sufficiently strong
relative to the interaction energy scale.


  The complex structure of a surface generated by the two-dimensional dynamical
triangulation(DT) is determined by measuring the resistivity of the surface. It
is found that surfaces coupled to matter fields have well-defined complex
structures for cases when the matter central charges are less than or equal to
one, while they become unstable beyond c=1. A natural conjecture that fine
planar random network of resistors behave as a continuous sheet of constant
resistivity is justified numerically for c<1.


  We show that for a relatively light majoron ($\ll 100 $ eV) non-thermal
production from topological defects is an efficient production mechanism.
Taking the type I seesaw as benchmark scheme, we estimate the primordial
majoron abundance and determine the required parameter choices where it can
account for the observed cosmological dark matter. The latter is consistent
with the scale of unification. Possible direct detection of light majorons with
future experiments such as PTOLEMY and the formation of boson stars from the
majoron dark matter are also discussed.


  To prevent the spread of disinformation on Instagram, we need to study the
accounts and content of disinformation actors. However, due to their malicious
nature, Instagram often bans accounts that are responsible for spreading
disinformation, making these accounts inaccessible from the live web. The only
way we can study the content of banned accounts is through public web archives
such as the Internet Archive. However, there are many issues present with
archiving Instagram pages. Specifically, we focused on the issue that many
Wayback Machine Instagram mementos redirect to the Instagram login page. In
this study, we determined that mementos of Instagram account pages on the
Wayback Machine began redirecting to the Instagram login page in August 2019.
We also found that Instagram mementos on Archive.today, Arquivo.pt, and
Perma.cc are also not well archived in terms of quantity and quality. Moreover,
we were unsuccessful in all our attempts to archive Katy Perry's Instagram
account page on Archive.today, Arquivo.pt, and Conifer. Although in the
minority, replayable Instagram mementos exist in public archives and contain
valuable data for studying disinformation on Instagram. With that in mind, we
developed a Python script to web scrape Instagram mementos. As of August 2023,
the Python script can scrape Wayback Machine archives of Instagram account
pages between November 7, 2012 and June 8, 2018.


  Inference in Bayesian statistics involves the evaluation of marginal
likelihood integrals. We present algebraic algorithms for computing such
integrals exactly for discrete data of small sample size. Our methods apply to
both uniform priors and Dirichlet priors. The underlying statistical models are
mixtures of independent distributions, or, in geometric language, secant
varieties of Segre-Veronese varieties.


  Suppose that G is a finite group and x in G has prime order p > 3. Then x is
contained in the solvable radical of G if (and only if) <x,x^g> is solvable for
all g in G. If G is an almost simple group and x in G has prime order p > 3
then this implies that there exists g in G such that <x,x^g> is not solvable.
In fact, this is also true when p=3 with very few exceptions, which are
described explicitly.


  Glaucoma remains among the leading causes of blindness despite many treatment
options available today. Effective treatment requires early diagnosis, which is
difficult to achieve with existing imaging technologies that detect the already
inflicted irreversible posterior eye damage. One improved approach could be to
detect the changes in trabecular meshwork of the anterior eye that precede the
intraocular pressure buildup and vision loss. Here we report a device that
enables in vivo exploration of trabecular meshwork at cell resolution. The
instrument combines two orthogonal views: en face view of time-domain
full-field OCT for high-resolution and cross-sectional view of spectral-domain
OCT for aligning to the meshwork. The device resolves micron-level
corneoscleral and uveal pores, meshwork beams and internal elastic fibers,
ciliary body tendons and trabecular cell nuclei. Capable of detecting blockage
of trabecular pores, orthogonal view OCT presents a promising solution to the
long-standing problem of early glaucoma diagnosis. Future clinical adoption of
the device is facilitated by the compact footprint and broad functionality that
includes corneal imaging in healthy subjects and patients (with keratoconus,
Fuchs endothelial dystrophy) using the same design.


  Federated Learning (FL) is an approach to conduct machine learning without
centralizing training data in a single place, for reasons of privacy,
confidentiality or data volume. However, solving federated machine learning
problems raises issues above and beyond those of centralized machine learning.
These issues include setting up communication infrastructure between parties,
coordinating the learning process, integrating party results, understanding the
characteristics of the training data sets of different participating parties,
handling data heterogeneity, and operating with the absence of a verification
data set.
  IBM Federated Learning provides infrastructure and coordination for federated
learning. Data scientists can design and run federated learning jobs based on
existing, centralized machine learning models and can provide high-level
instructions on how to run the federation. The framework applies to both Deep
Neural Networks as well as ``traditional'' approaches for the most common
machine learning libraries. {\proj} enables data scientists to expand their
scope from centralized to federated machine learning, minimizing the learning
curve at the outset while also providing the flexibility to deploy to different
compute environments and design custom fusion algorithms.


  Graphene is a very promising test-bed for the field of electron quantum
optics. However, a fully tunable and coherent electronic beam splitter is still
missing. We report the demonstration of electronic beam splitters in graphene
that couple quantum Hall edge channels having opposite valley polarizations.
The electronic transmission of our beam splitters can be tuned from zero to
near unity. By independently setting the beam splitters at the two corners of a
graphene PN junction to intermediate transmissions, we realize a fully tunable
electronic Mach-Zehnder interferometer. This tunability allows us to
unambiguously identify the quantum interferences due to the Mach-Zehnder
interferometer, and to study their dependence with the beam-splitter
transmission and the interferometer bias voltage. The comparison with
conventional semiconductor interferometers points towards universal processes
driving the quantum decoherence in those two different 2D systems, with
graphene being much more robust to their effect.


  Rejoinder of "Estimating the historical and future probabilities of large
terrorist events" by Aaron Clauset and Ryan Woodard [arXiv:1209.0089].


  Jupiter's atmosphere has been observed to be depleted in helium (Yatm~0.24),
suggesting active helium sedimentation in the interior. This is accounted for
in standard Jupiter structure and evolution models through the assumption of an
outer, He-depleted envelope that is separated from the He-enriched deep
interior by a sharp boundary. Here we aim to develop a model for Jupiter's
inhomogeneous thermal evolution that relies on a more self-consistent
description of the internal profiles of He abundance, temperature, and heat
flux. We make use of recent numerical simulations on H/He demixing, and on
layered (LDD) and oscillatory (ODD) double diffusive convection, and assume an
idealized planet model composed of a H/He envelope and a massive core. A
general framework for the construction of interior models with He rain is
described. Despite, or perhaps because of, our simplifications made we find
that self-consistent models are rare. For instance, no model for ODD convection
is found. We modify the H/He phase diagram of Lorenzen et al. to reproduce
Jupiter's atmospheric helium abundance and examine evolution models as a
function of the LDD layer height, from those that prolong Jupiter's cooling
time to those that actually shorten it. Resulting models that meet the
luminosity constraint have layer heights of about 0.1-1 km, corresponding to
~10,-20,000 layers in the rain zone between ~1 and 3-4.5 Mbars. Present
limitations and directions for future work are discussed, such as the formation
and sinking of He droplets.


  Stability and attractor property of free-floating axisymmetric magnetic
bubbles in high-conductivity plasmas is (tentatively, numerically)
demonstrated. The existence of compact non-singular axisymmetric magnetic
equilibria is proved. Being attractors, the solitary magnetic bubbles should
exist in nature.


  In the context of the standard model of particles, the weak interaction of
cosmic microwave background (CMB) and cosmic neutrino background (C$\nu$B), can
generate non-vanishing TB and EB power spectra in the order of one loop forward
scattering, in the presence of scalar perturbation, which is in contrast with
the standard scenario cosmology. Comparing our results with the current
experimental data may provide, significant information about the nature of
C$\nu$B, including CMB-C$\nu$B forward scattering for TB, TE, and EB power
spectra. To this end, different cases were studied, including Majorana C$\nu$B
and Dirac C$\nu$B. On the other hand, it was shown that the mean opacity due to
cosmic neutrino background could behave as an anisotropic birefringent medium
and change the linear polarization rotation angle. Considering the
contributions from neutrino and anti-neutrino forward scattering with CMB
photons (in the case of Dirac neutrino), we introduce relative neutrino and
anti-neutrino density asymmetry ($\delta_\nu=\frac{\Delta
n_\nu}{n_\nu}=\frac{n_\nu-n_{\bar{\nu}}}{n_\nu}$). Then, using the cosmic
birefringence angle reported by the Planck data release
$\beta=0.30^\circ\pm0.11^\circ$ ($68\%C.L.$), some constraints can be put on
$\delta_\nu$. Also, the value of cosmic birefringence due to Majorana C$\nu$B
medium is estimated at about $\beta|_\nu\simeq0.2$ rad. In this respect, since
Majorana neutrino and anti-neutrino are exactly the same, both CB contributions
will be added together. However, this value is at least two orders larger than
the cosmic birefringence angle reported by the Planck data release,
$\beta=0.30^\circ\pm0.11^\circ$ ($68\%C.L.$).


  We study the black hole interiors in holographic Weyl semimetals and
holographic nodal line semimetals. We find that the black hole singularities
are of Kasner form. In the topologically nontrivial phase at low temperature,
both the Kasner exponents of the metric fields and the proper time from the
horizon to the singularity are almost constant, likely reflecting the
topological nature of the topological semimetals. We also find some specific
behaviors inside the horizon in each holographic semimetal model.


  We derive logarithmically enhanced two-loop virtual electroweak corrections
for arbitrary fermion-scattering processes at the TeV scale. This extends
results previously obtained for massless fermion scattering to processes that
involve also bottom and top quarks. The contributions resulting from soft,
collinear, and ultraviolet singularities in the complete electroweak Standard
Model are explicitly extracted from two-loop diagrams to
next-to-leading-logarithmic accuracy including all effects associated with
symmetry breaking and Yukawa interactions.


  In the era of the Internet of Things (IoT), the retrieval of relevant medical
information has become essential for efficient clinical decision-making. This
paper introduces MedFusionRank, a novel approach to zero-shot medical
information retrieval (MIR) that combines the strengths of pre-trained language
models and statistical methods while addressing their limitations. The proposed
approach leverages a pre-trained BERT-style model to extract compact yet
informative keywords. These keywords are then enriched with domain knowledge by
linking them to conceptual entities within a medical knowledge graph.
Experimental evaluations on medical datasets demonstrate MedFusion Rank's
superior performance over existing methods, with promising results with a
variety of evaluation metrics. MedFusionRank demonstrates efficacy in
retrieving relevant information, even from short or single-term queries.


  We performed electron energy-loss spectroscopy studies in transmission in
order to obtain insight into the electronic properties of potassium
intercalated coronene, a recently discovered superconductor with a rather high
transition temperature of about 15\,K. A comparison of the loss function of
undoped and potassium intercalated coronene shows the appearance of several new
peaks in the optical gap upon potassium addition. Furthermore, our core level
excitation data clearly signal filling of the conduction bands with electrons.


  It is usually thought that a single equation of state (EoS) model "correctly"
represents cores of all compact stars. Here we emphasize that two families of
compact stars, viz., neutron stars and strange stars, can coexist in nature,
and that neutron stars can get converted to strange stars through the
nucleation process of quark matter in the stellar center. From our fully
general relativistic numerical computations of the structures of fast-spinning
compact stars, known as millisecond pulsars, we find that such a stellar
conversion causes a simultaneous spin-up and decrease in gravitational mass of
these stars. This is a new type of millisecond pulsar evolution through a new
mechanism, which gives rise to relatively lower mass compact stars with higher
spin rates. This could have implication for the observed mass and spin
distributions of millisecond pulsars. Such a stellar conversion can also rescue
some massive, spin-supported millisecond pulsars from collapsing into black
holes. Besides, we extend the concept of critical mass $M_{\rm cr}$ for the
neutron star sequence (Berezhiani et al. 2003; Bombaci et al. 2004) to the case
of fast-spinning neutron stars, and point out that neutron star EoS models
cannot be ruled out by the stellar mass measurement alone. Finally, we
emphasize the additional complexity for constraining EoS models, for example,
by stellar radius measurements using X-ray observations, if two families of
compact stars coexist.


  We compute the high-dimensional limit of the free energy associated with a
multi-layer generalized linear model. Under certain technical assumptions, we
identify the limit in terms of a variational formula. The approach is to first
show that the limit is a solution to a Hamilton-Jacobi equation whose initial
condition is related to the limiting free energy of a model with one fewer
layer. Then, we conclude by an iteration.


  Finite nonassociative division algebras (i.e., finite semifields) with 243
elements are completely classified.


  We investigate the evolution of the random interfaces in a two dimensional
Potts model at zero temperature under Glauber dynamics for some particular
initial conditions. We prove that under space-time diffusive scaling the shape
of the interfaces converges in probability to the solution of a non-linear
parabolic equation. This Law of Large Numbers is obtained from the Hydrodynamic
limit of a coupling between an exclusion process and an inhomogeneous one
dimensional zero range process with asymmetry at the origin.


  We consider the problem of obtaining the scattering length for a fermion
colliding with a dimer, formed from a fermion identical to the incident one and
another different fermion. This is done in the universal regime where the range
of interactions is short enough so that the scattering length $a$ for non
identical fermions is the only relevant quantity. This is the generalization to
fermions with different masses of the problem solved long ago by Skorniakov and
Ter-Martirosian for particles with equal masses. We solve this problem
analytically in the two limiting cases where the mass of the solitary fermion
is very large or very small compared to the mass of the two other identical
fermions. This is done both for the value of the scattering length and for the
function entering the Skorniakov-Ter-Martirosian integral equation, for which
simple explicit expressions are obtained.


  Some years ago, Fendley found an explicit solution to Thermodynamic Bethe
Ansatz (TBA) equation for a N=2 supersymmetric theory in 2D with a specific
F-term. Motivated by this, we seek for explicit solutions for other
super-potential cases utilizing the idea from the ODE/IM correspondence. We
find that TBA equations, corresponding to a wider class of super-potentials,
admit solutions in terms of elementary functions such as modified Bessel
functions and confluent hyper-geometric series.


  In this paper, we establish some new Ostrowski type inequalities for
s-logarithmically convex functions by using Riemann-Liouville fractional
integrals. Some applications of our results to P.D.F.'s are given.


  Asteroseismology has been impressively boosted during the last decade mainly
thanks to space missions such as Kepler/K2 and CoRoT. This has a large impact,
in particular, in exoplanetary sciences since the accurate characterization of
the exoplanets is convoluted in most cases with the characterization of their
hosting star. Until the expected launch of the ESA mission PLATO 2.0, there is
almost a decade where only two important missions will provide short-cadence
high-precision photometric time-series: NASA--TESS and ESA--CHEOPS missions,
both having high capabilities for exoplanetary sciences. In this work, we want
to explore the asteroseismic potential of CHEOPS time-series. Following the
works done for estimating the asteroseismic potential of Kepler and TESS, we
have analyzed the probability of detecting solar-like pulsations using CHEOPS
light-curves. Since CHEOPS will collect runs with observational times from
hours up to a few days, we have analyzed the accuracy and precision we can
obtain for the estimation of nu_max, the only asteroseismic observable we can
recover using CHEOPS observations. Finally, we have analyzed the impact of
knowing nu_max in the characterization of exoplanet host stars. Using CHEOPS
light-curves with the expected observational times we can determine nu_max for
massive G and F-type stars from late Main Sequence on, and for F, G, and K-type
stars from post-Main Sequence on with an uncertainty lower than a 5%. For
magnitudes V<12 and observational times from eight hours up to two days, the HR
zone of potential detectability changes. The determination of nu_max leads to
an internal age uncertainty reduction in the characterization of exoplanet host
stars from 52% to 38%; mass uncertainty reduction from 2.1% to 1.8%; radius
uncertainty reduction from 1.8% to 1.6%; density uncertainty reduction from
5.6% to 4.7%, in our best scenarios.


  Two-body charmless nonleptonic decays of B_u and B_d mesons are studied
within the framework of generalized factorization in which the effective Wilson
coefficients $c^{eff}_i$ are renormalization-scale and -scheme independent
while factorization is applied to the tree-level hadronic matrix elements.
Contrary to previous studies, our $c_i^{eff}$ do not suffer from gauge and
infrared problems. Nonfactorizable effects are parametrized in terms of N_c(LL)
and N_c(LR), the effective numbers of colors arising from (V-A)(V-A) and
(V-A)(V+A) four-quark operators, respectively. Tree and penguin transitions are
classified into six different classes. The data of $B^-\to\rho^0\pi^-$ and
$B^-\to\phi K^-$ clearly indicate that $N_c(LR)\neq N_c(LL)$: The first
measurement of the b -> u mode $B^-\to\rho^0\pi^-$ and the experimental
information on the tree-dominated mode $B^-\to\omega\pi^-$ all imply that
Nc(LL) is less than 3, whereas the CLEO measurement of $B^-\to\phi K^-$ shows
Nc(LR)>3. For given input parameters, the prediction of ${\cal B}(B\to\eta' K)$
is largely improved by setting Nc(LL)~2 and Nc(LR)>Nc(LL); in particular, the
charm content of the eta' contributes in the right direction. The decay rate of
$B\to\phi K^*$ is very sensitive to the form-factor ratio A_2/A_1; the absence
of $B\to\phi K$ events does not necessarily invalidate the factorization
approach. If the branching ratio of $B^-\to\omega K^-$ is experimentally found
to be significantly larger than that of $B^-\to\rho^0 K^-$, we argue that
inelastic final-state rescattering may account for the disparity between
$\omega K^-$ and $\rho^0 K^-$.


  If $G$ is a reductive Lie group of Harish-Chandra class, $H$ is a symmetric
subgroup, and $\pi$ is a discrete series representation of $G$, the authors
give a condition on the pair $(G,H)$ which guarantees that the direct integral
decomposition of $\pi|_H$ contains each irreducible representation of $H$ with
finite multiplicity. In addition, if $G$ is a reductive Lie group of
Harish-Chandra class, and $H\subset G$ is a closed, reductive subgroup of
Harish-Chandra class, the authors show that the multiplicity function in the
direct integral decomposition of $\pi|_H$ is constant along `continuous
parameters'. In obtaining these results, the authors develop a new technique
for studying multiplicities in the restriction $\pi|_H$ via convolution with
Harish-Chandra characters. This technique has the advantage of being useful for
studying the continuous spectrum as well as the discrete spectrum.


  A triangulated category $\mathcal{C}$ with a canonical Bott's isomorphism
$[2]\xrightarrow{\sim}id$ is called a cyclic category in this paper. We give a
new notion of stability conditions on a $k$-linear Krull-Schmidt cyclic
category. Given such a stability condition $\sigma$, we can assign a Maslov
index to each basic loop in such a category. If all Maslov indexes vanish, we
get $\mathcal{C}',\sigma'$ as the $\mathbb{Z}$-lifts of $\mathcal{C},\sigma$
respectively such that $\mathcal{C}'$ is a $\mathbb{Z}$-graded triangulated
category and $\sigma'$ is a Bridgeland stability condition on $\mathcal{C}'$.
Moreover, we showed that there is an isomorphism
$$Stab^{0,e}(\mathcal{C})\xrightarrow{\simeq} BStab(\mathcal{C}')$$ where
$Stab^{0,e}(\mathcal{C})$ denotes the equivalence classes of stability
conditions which are deformation equivalent to $\sigma$, and
$BStab(\mathcal{C}')$ denotes the space of Bridgeland stability conditions on
$\mathcal{C}'$.
  We provide examples of stability conditions on a simple cyclic category. We
also discuss some interesting phenomena in these examples, such as the
chirality symmetry breaking phenomenon and nontrivial monodromy. The chirality
symmetry breaking phenomenon involves stability conditions which can not be
lifted to Bridgeland stability conditions.


  The problem of discrete universal filtering, in which the components of a
discrete signal emitted by an unknown source and corrupted by a known DMC are
to be causally estimated, is considered. A family of filters are derived, and
are shown to be universally asymptotically optimal in the sense of achieving
the optimum filtering performance when the clean signal is stationary, ergodic,
and satisfies an additional mild positivity condition. Our schemes are
comprised of approximating the noisy signal using a hidden Markov process (HMP)
via maximum-likelihood (ML) estimation, followed by the use of the forward
recursions for HMP state estimation. It is shown that as the data length
increases, and as the number of states in the HMP approximation increases, our
family of filters attain the performance of the optimal distribution-dependent
filter.


  Several algorithms have been proposed to compute partitions of networks into
communities that score high on a graph clustering index called modularity.
While publications on these algorithms typically contain experimental
evaluations to emphasize the plausibility of results, none of these algorithms
has been shown to actually compute optimal partitions. We here settle the
unknown complexity status of modularity maximization by showing that the
corresponding decision version is NP-complete in the strong sense. As a
consequence, any efficient, i.e. polynomial-time, algorithm is only heuristic
and yields suboptimal partitions on many instances.


  Fundamental big-picture challenges face the enterprise of burgeoning space
test, which may also have an impact on the syllabus and training of a possible
future Space Test Pilot School. Test fundamentals and test conduct under
stresses of time and fuel will be where the rubber meets the road. This paper
specifically discusses four of those challenges, and their impact on US Space
Force operators. (1) Testing limits of space capabilities. Space vehicles have
traditionally imposed very strict operating limits. A culture shift from the
top-down will be required before space testers are allowed to test spacecraft
limits as freely as air-breathing test pilots do today. (2) Permitted
procedures. There are a limited number of contingency procedures at a space
operator's disposal, further constrained within themselves. (3) Safety nets. A
discussion of space-specific methods that mitigate risks in operations, and the
need for more agile fault-detection. (4) Operator proficiency. The
qualifications and recency of a tester at the controls must be considered in
the context of a single misstep potentially resulting in the entire asset being
lost. We suggest that hours in high-risk test per spacecraft may become the
defining factor for high-risk space test execution.


  Taking into account results obtained from light-curve analysis and
out-of-eclipse analyses, we discuss the nature of GSC 02038-00293 and also its
magnetic activity behaviour. We obtained light curves of the system during
observing seasons 2007, 2008 and 2011. We obtained its secondary minimum
clearly in I-band observations in 2008 for the first time. Analysing this light
curve, we found the physical parameters of the components. The light-curve
analysis indicates that the possible mass ratio of the system is 0.35. We
obtained the remaining V-band light curves, extracting the eclipses. We
modelled these remaining curves using the spotmodel program and found possible
spot configurations of the magnetically active component for each observing
season. The models demonstrated that there are two active longitudes for the
active component. The models reveal that both active longitudes migrate in the
direction of decreasing longitude. We also examined the light curves in
out-of-eclipse phases with respect to minimum and maximum brightness,
amplitude, etc. The amplitude of the curves during out-of-eclipse phases varies
in a sinusoidal way with a period of ~8.9yr the mean brightness of the system
is dramatically decreasing. The phases of the deeper minimum during
out-of-eclipse periods exhibit a migration toward decreasing phase.


  We study turbulent flows in planar channels with unstable thermal
stratification, using direct numerical simulations in a wide range of Reynolds
and Rayleigh numbers and reaching flow conditions which are representative of
asymptotic developed turbulence. The combined effect of forced and free
convection produces a peculiar pattern of quasi--streamwise rollers occupying
the full channel thickness with aspect--ratio considerably higher than unity;
it has been observed that they have an important redistributing effect on
temperature and momentum. The mean values and the variances of the flow
variables do not appear to follow Prandtl's scaling in the flow regime near
free convection, except for the temperature and vertical velocity fluctuations,
which are more affected by turbulent plumes. Nevertheless, we find that the
Monin--Obukhov theory still yields a useful representation of the main flow
features. In particular, the widely used Businger--Dyer relationships provide a
convenient way of accounting for the bulk effects of shear and buoyancy,
although individual profiles may vary widely from the alleged trends.
Significant deviations are found in DNS with respect to the commonly used
parametrization of the mean velocity in the light-wind regime, which may have
important practical impact in models of atmospheric dynamics. Finally, for
modelling purposes, we devise a set of empirical predictive formulas for the
heat flux and friction coefficients which can be used with about $10\%$ maximum
error in a wide range of flow parameters.


  We introduce a technique that allows one to connect any two arbitrary (pure
or mixed) superposition states of an N-state quantum system. The proposed
solution to this inverse quantum mechanical problem is analytical, exact, and
very compact. The technique uses standard and generalized quantum Householder
reflections (QHRs), which require external pulses of precise areas and
frequencies. We show that any two pure states can be linked by just a single
generalized QHR. The transfer between any two mixed states with the same
dynamic invariants (e.g., the same density matrix eigenvalues) requires in
general N QHRs. Moreover, we propose recipes for synthesis of arbitrary
preselected mixed states using a combination of QHRs and incoherent processes
(pure dephasing or spontaneous emission).


  We give a general criterion for conformal embeddings of vertex operator
algebras associated to affine Lie algebras at arbitrary levels. Using that
criterion, we construct new conformal embeddings at admissible rational and
negative integer levels. In particular, we construct all remaining conformal
embeddings associated to automorphisms of Dynkin diagrams of simple Lie
algebras. The semisimplicity of the corresponding decompositions is obtained by
using the concept of fusion rules for vertex operator algebras.


  Numerous algorithms have been proposed to $\textit{align}$ language models to
remove undesirable behaviors. However, the challenges associated with a very
large state space and creating a proper reward function often result in various
jailbreaks. Our paper aims to examine this effect of reward in the controlled
setting of positive sentiment language generation. Instead of online training
of a reward model based on human feedback, we employ a statically learned
sentiment classifier. We also consider a setting where our model's weights and
activations are exposed to an end-user after training. We examine a pretrained
GPT-2 through the lens of mechanistic interpretability before and after
proximal policy optimization (PPO) has been applied to promote positive
sentiment responses. Using these insights, we (1) attempt to "hack" the PPO-ed
model to generate negative sentiment responses and (2) add a term to the reward
function to try and alter `negative' weights.


  An inverse obstacle scattering problem for the wave governed by the Maxwell
system in the time domain, in particular, over a finite time interval is
considered. It is assumed that the electric field $\mbox{\boldmath $E$}$ and
magnetic field $\mbox{\boldmath $H$}$ which are solutions of the Maxwell system
are generated only by a current density at the initial time located not far a
way from an unknown obstacle. The obstacle is embedded in a medium like air
which has constant electric permittivity $\epsilon$ and magnetic permeability
$\mu$. It is assumed that the fields on the surface of the obstacle satisfy the
impedance-or the Leontovich boundary condition $\mbox{\boldmath
$\nu$}\times\mbox{\boldmath $H$} -\lambda\,\mbox{\boldmath
$\nu$}\times(\mbox{\boldmath $E$}\times\mbox{\boldmath $\nu$})=\mbox{\boldmath
$0$}$ with $\lambda$ an unknown positive function and $\mbox{\boldmath $\nu$}$
the unit outward normal. The observation data are given by the electric field
observed at the same place as the support of the current density over a finite
time interval. It is shown that an indicator function computed from the
electric fields corresponding two current densities enables us to know: the
distance of the center of the common spherical support of the current densities
to the obstacle; whether the value of the impedance $\lambda$ is greater or
less than the special value $\sqrt{\epsilon/\mu}$.


  Conditional kernel mean embeddings form an attractive nonparametric framework
for representing conditional means of functions, describing the observation
processes for many complex models. However, the recovery of the original
underlying function of interest whose conditional mean was observed is a
challenging inference task. We formalize deconditional kernel mean embeddings
as a solution to this inverse problem, and show that it can be naturally viewed
as a nonparametric Bayes' rule. Critically, we introduce the notion of task
transformed Gaussian processes and establish deconditional kernel means as
their posterior predictive mean. This connection provides Bayesian
interpretations and uncertainty estimates for deconditional kernel mean
embeddings, explains their regularization hyperparameters, and reveals a
marginal likelihood for kernel hyperparameter learning. These revelations
further enable practical applications such as likelihood-free inference and
learning sparse representations for big data.


  We determine the cone of nef divisors on the Voronoi compactification A_g^*
of the moduli space A_g of principally polarized abelian varieties of dimension
g for genus g=2,3. As a corollary we obtain that the spaces A_g^*(n) with
level-n structure are a minimal, resp. canonical, model for g=2, n>=4, resp.
n>=5 and g=3, n>=3, resp. n>=4. We give two proofs: The easy and quick one
reduces the problem to \bar M_g where we can use a result of Faber. This
approach cannot be generalized to higher genus g. The main point of the paper
is, therefore, to give a second proof using theta functions and a result of
Weissauer. This technique can be at least partially generalized to higher
genus. We formulate a conjecture for the nef cone of A_g^* for all g.


  We study real time classical matrix mechanics of a simplified $2\times 2$
matrix model inspired by the black hole evaporation problem. This is a step
towards making a quantitative model of real time evaporation of a black hole,
which is realized as a bound state of D0-branes in string theory. The model we
study is the reduction of Yang Mills in $2+1$ dimension to $0+1$ dimensions,
which has been corrected with an additional potential that can be interpreted
as a zero point energy for fermions. Our goal is to understand the lifetime of
such a classical bound state object in the classical regime. To do so, we pay
particular attention to when D-particles separate to check that the "off
diagonal modes" of the matrices become adiabatic and use that information to
improve on existing models of evaporation. It turns out that the naive
expectation value of the lifetime with the fermionic correction is infinite.
This is a logarithmic divergence that arises from very large excursions in the
separation between the branes near the threshold for classical evaporation. The
adiabatic behavior lets us get some analytic control of the dynamics in this
regime to get this estimate. This divergence is cutoff in the quantum theory
due to quantization of the adiabatic parameter, resulting in a long lifetime of
the bound state, with a parametric dependence of order $\log(1/\hbar)$.


  The ability to live without being controlled by any action, judgment and any
outside factors including any opinions and regulations is defined by the term
Independent. But in reality physical movement for travelling or simply walking
through a crowded street pose great challenge for a visually impaired person.
Also they must learn every detail about the home environment such as placement
of tables; chairs etc. to prevent injury. Because of this disability they have
to sacrifice their independence in daily living by depending on the sighted
people in every busy place like bus, footpaths, railway stations etc. This
paper aims to design an artificial navigating system with adjustable
sensitivity with the help of ultrasonic proximity sensor to assist these blind
persons to walk fearlessly and independently in both indoor and outdoor
environment. This system can detect any type of upcoming obstacles and potholes
using the reflection properties of ultrasound. Attachment of the system to
different body areas makes its utilization more versatile and reliable.


  We investigate a special kind of contraction of symmetric spaces
(respectively, of Lie triple systems), called homotopy. In this first part of a
series of two papers we construct such contractions for classical symmetric
spaces in an elementary way by using associative algebras with several
involutions. This construction shows a remarkable duality between the
underlying "space" and the "deformation parameter".


  This study proposes introducing convex optimization to find initial
perturbations of atmospheric models for realizing specified changes in
subsequent forecasts. In the proposed method, we formulate and solve an inverse
problem to find effective perturbations in atmospheric variables so that
controlled variables satisfy specified changes at a specified time. The
proposed method first constructs a sensitivity matrix of controlled variables,
such as accumulated precipitation, to the initial atmospheric variables, such
as temperature and humidity, through sensitivity analysis using numerical
weather prediction (NWP) models. The sensitivity matrix is used to solve the
inverse problem as convex optimization, in which a global optimal solution can
be found computationally efficiently. The proposed method was validated through
a benchmark warm bubble experiment using an NWP model. The experiments showed
that identified perturbation successfully realized specified spatial
distributions of accumulated precipitation. These results demonstrated the
possibility of controlling the real atmosphere by solving inverse problems and
adding small perturbations to atmospheric states.


  A one-dimensional non-iterative direct method was employed for normalized
crystal truncation rod. The non-iterative approach, utilizing Kramers-Kronig
relation, avoids the ambiguities due to the improper initial model or the
incomplete convergence in the conventional iterative methods. The validity and
limitation of the present method are demonstrated through both numerical
simulations and experiments with Pt (111) in 0.1 M CsF aqueous solution. The
present method is compared to conventional iterative phase-retrieval methods.


  We present a systematic algorithm testing for the existence of collective
self-organization in the behavior of agents in social systems, with a concrete
empirical implementation on the Dow Jones Industrial Average index (DJIA) over
the 20th century and on Hong Kong Hang Seng composite index (HSI) since 1969.
The algorithm combines ideas from critical phenomena, the impact of agents'
expectation, multi-scale analysis and the mathematical method of pattern
recognition of sparse data. Trained on the three major crashes in DJIA of the
century, our algorithm exhibits a remarkable ability for generalization and
detects in advance 8 other significant drops or changes of regimes. An
application to HSI gives promising results as well. The results are robust with
respect to the variations of the recognition algorithm. We quantify the
prediction procedure with error diagrams.


  The current ordinal analysis provides the proof-theoretic ordinal of a
theory, which calibrates the robustness of the $\Pi^1_1$-consequences of the
theory. We can ask whether there is an ordinal characteristic capturing more
complex consequences, and it turns out that we can define the
$\Sigma^1_2$-proof-theoretic ordinal capturing the robustness of the
$\Sigma^1_2$-consequences of a theory. In this paper, we study the behavior of
$\Sigma^1_2$-proof-theoretic ordinal, and it turns out that
$\Sigma^1_2$-proof-theoretic ordinal also follows an analogue of Walsh's
characterization of proof-theoretic ordinal.


  We consider scenario of the dark matter consisting of two fractions, stable
part being dominant and a smaller unstable fraction, which has decayed after
the recombination epoch. It has been suggested in Ref. [arxiv:1505.03644] that
the above scenario may alleviate tension between high-redshift (CMB anisotropy)
and low-redshift (cepheid variables and SNe Ia, cluster counts) cosmological
measurements. We derive constraints on the heavy relics branching to
$q\bar{q}$, $e^+e^-$, $\mu^+\mu^-$, $\tau^+\tau^-$, $\nu_e\bar{\nu_e}$,
$\nu_\mu\bar{\nu_\mu}$, $W^+W^-$ and $\gamma\gamma$ in the above scenario by
comparison of the secondary $\gamma$ and $\nu$ fluxes produced by the process
with recent diffuse $\gamma$ and $\nu$ flux measurements.


  Systematic compositionality is the ability to recombine meaningful units with
regular and predictable outcomes, and it's seen as key to humans' capacity for
generalization in language. Recent work has studied systematic compositionality
in modern seq2seq models using generalization to novel navigation instructions
in a grounded environment as a probing tool, requiring models to quickly
bootstrap the meaning of new words. We extend this framework here to settings
where the model needs only to recombine well-trained functional words (such as
"around" and "right") in novel contexts. Our findings confirm and strengthen
the earlier ones: seq2seq models can be impressively good at generalizing to
novel combinations of previously-seen input, but only when they receive
extensive training on the specific pattern to be generalized (e.g.,
generalizing from many examples of "X around right" to "jump around right"),
while failing when generalization requires novel application of compositional
rules (e.g., inferring the meaning of "around right" from those of "right" and
"around").


  We consider a weakly interacting uniform atomic Bose gas with a
time-dependent nonlinear coupling constant. By developing a suitable Bogoliubov
treatment we investigate the time evolution of several observables, including
the momentum distribution, the degree of coherence in the system, and their
dependence on dimensionality and temperature. We rigorously prove that the
low-momentum Bogoliubov modes remain frozen during the whole evolution, while
the high-momentum ones adiabatically follow the change in time of the
interaction strength. At intermediate momenta we point out the occurrence of
oscillations, which are analogous to Sakharov oscillations. We identify two
wide classes of time-dependent behaviors of the coupling for which an exact
solution of the problem can be found, allowing for an analytic computation of
all the relevant observables. A special emphasis is put on the study of the
coherence property of the system in one spatial dimension. We show that the
system exhibits a smooth "light-cone effect," with typically no
prethermalization.


  We present a number of identities involving standard and associated Laguerre
polynomials. They include double-, and triple-lacunary, ordinary and
exponential generating functions of certain classes of Laguerre polynomials.


  Bifurcation phenomena are common in multi-dimensional multi-parameter
dynamical systems. Normal form theory suggests that the bifurcations themselves
are driven by relatively few parameters; however, these are often nonlinear
combinations of the bare parameters in which the equations are expressed.
Discovering reparameterizations to transform such complex original equations
into normal-form is often very difficult, and the reparameterization may not
even exist in a closed-form. Recent advancements have tied both information
geometry and bifurcations to the Renormalization Group. Here, we show that
sloppy model analysis (a method of information geometry) can be used directly
on bifurcations of increasing time scales to rapidly characterize the system's
topological inhomogeneities, whether the system is in normal form or not. We
anticipate that this novel analytical method, which we call time-widening
information geometry (TWIG), will be useful in applied network analysis.


  We study the standing waves for a fourth-order Schr\"odinger equation with
mixed dispersion that minimize the associated energy when the $L^2-$norm (the
\textit{mass}) } is kept fixed. We need some non-homogeneous
Gagliardo-Nirenberg-type inequalities and we develop a method to prove such
estimates that should be useful elsewhere. We prove optimal results on the
existence of minimizers in the {\it mass-subcritical } and {\it mass-critical }
cases. In the { \it mass supercritical} case we show that global minimizers do
not exist, and we investigate the existence of local minimizers. If the mass
does not exceed some threshold $ \mu_0 \in (0,+\infty)$, our results on "best"
local minimizers are also optimal.


  A KdV flow is constructed on a space whose structure is described in terms of
the spectrum of the underlying Schr\"odinger operators. The space includes the
conventional decaying functions and ergodic ones. Especially any smooth almost
periodic function can be initial data for the KdV equation.


  The Narain lattice construction of string compactifications is generalized to
include spontaneously broken supersymmetry. Consistency conditions from modular
invariance and Lorentz symmetry are solved in full generality. This framework
incorporates models where supersymmetry breaking is inversely proportional to
the radii of compact dimensions. The enhanced lattice description, however,
might allow for models with a different geometrical or even non-geometrical
interpretation.


  In a recent article, Galam and Mauger proposed an invariant for site and bond
percolation thresholds, based on known values for twenty lattices (Eur. Phys.
J. B 1 (1998) 255-258). Here we give a larger list of values for more than
forty lattices in two to six dimensions. In this list are new results for fcc,
bcc, and diamond lattices in 4, 5, and 6 dimensions.
  The list contains examples of lattices with equal site percolation
thresholds, but different bond percolation thresholds. These and other examples
show that there are deviations from the proposed invariant of up to 12% in two
dimensions, increasing to 69% in higher dimensions.


  We search for signatures of transition region explosive events (EEs) in
hydrogen Ly-beta profiles. Two rasters made by the SUMER (Solar Ultraviolet
Measurements of Emitted Radiation) instrument on board SOHO in a quiet-Sun
region and an equatorial coronal hole are selected for our study. Transition
region explosive events are identified from profiles of C II 1037 Angstrom and
O VI 1032 Angstrom, respectively. We compare Ly-beta profiles during EEs with
those averaged in the entire quiet-Sun and coronal-hole regions. The
relationship between the peak emission of Ly-beta profiles and the wing
emission of C II and O VI during EEs is investigated. We find that the central
part of Ly-beta profiles becomes more reversed and the distance of the two
peaks becomes larger during EEs, both in the coronal hole and in the quiet Sun.
The average Ly-beta profile of the EEs detected by C II has an obvious stronger
blue peak. During EEs, there is a clear correlation between the increased peak
emission of Ly-beta profiles and the enhanced wing emission of the C II and O
VI lines. The correlation is more pronounced for the Ly-beta peaks and C II
wings, and less significant for the Ly-beta blue peak and O VI blue wing. We
also find that the Ly-beta profiles are more reversed in the coronal hole than
in the quiet Sun. We suggest that the jets produced by EEs emit Doppler-shifted
Ly-beta photons, causing enhanced emission at positions of the peaks of Ly-beta
profiles. The more-reversed Ly-beta profiles confirm the presence of a larger
opacity in the coronal hole than in the quiet Sun. The finding that EEs modify
the Ly-beta line profile in QS and CHs implies that one should be careful in
the modelling and interpretation of relevant observational data.


  High-dimensional penalized rank regression is a powerful tool for modeling
high-dimensional data due to its robustness and estimation efficiency. However,
the non-smoothness of the rank loss brings great challenges to the computation.
To solve this critical issue, high-dimensional convoluted rank regression is
recently proposed, and penalized convoluted rank regression estimators are
introduced. However, these developed estimators cannot be directly used to make
inference. In this paper, we investigate the inference problem of
high-dimensional convoluted rank regression. We first establish estimation
error bounds of penalized convoluted rank regression estimators under weaker
conditions on the predictors. Based on the penalized convoluted rank regression
estimators, we further introduce a debiased estimator. We then provide Bahadur
representation for our proposed estimator. We further develop simultaneous
inference procedures. A novel bootstrap procedure is proposed and its
theoretical validity is also established. Finally, simulation and real data
analysis are conducted to illustrate the merits of our proposed methods.


  Long-slit echelle spectra reveal bright extended emission from the K I
lambda7699 resonance line in the reflection nebula surrounding the extreme red
supergiant VY Canis Majoris. The central star has long been known for its
unusually-bright K I emission lines, but this is the first report of intrinsic
emission from K I in the nebula. The extended emission is not just a reflected
spectrum of the star, but is due to resonant scattering by K atoms in the outer
nebula itself, and is therefore a valuable probe of the kinematics and geometry
of VY CMa's circumstellar environment. Dramatic velocity structure is seen in
the long-slit spectra, and most lines of sight intersect multiple distinct
velocity components. A faint ``halo'' at large distances from the star does
appear to show a reflected spectrum, however, and suggests a systemic velocity
of +40 km/s with respect to the Sun. The most striking feature is blueshifted
emission from the filled interior of a large shell seen in images; the
kinematic structure is reminiscent of a Hubble flow, and provides strong
evidence for asymmetric and episodic mass loss due to localized eruptions on
the star's surface.


  We solve the generalized relativistic harmonic oscillator in 1+1 dimensions,
i.e., including a linear pseudoscalar potential and quadratic scalar and vector
potentials which have equal or opposite signs. We consider positive and
negative quadratic potentials and discuss in detail their bound-state solutions
for fermions and antifermions. The main features of these bound states are the
same as the ones of the generalized three-dimensional relativistic harmonic
oscillator bound states. The solutions found for zero pseudoscalar potential
are related to the spin and pseudospin symmetry of the Dirac equation in 3+1
dimensions. We show how the charge conjugation and $\gamma^5$ chiral
transformations relate the several spectra obtained and find that for massless
particles the spin and pseudospin symmetry related problems have the same
spectrum, but different spinor solutions. Finally, we establish a relation of
the solutions found with single-particle states of nuclei described by
relativistic mean-field theories with scalar, vector and isoscalar tensor
interactions and discuss the conditions in which one may have both nucleon and
antinucleon bound states.


  We present an approach to generalization of practical Identity-Based
Encryption scheme of Boneh and Franklin. In particular we show how the protocol
could be used on finite modular lattices and as a special case on vector spaces
over finite field. The original proof of security for this protocol does not
hold in this general algebraic structure, thus this is still a work in
progress.


  A $1$-parameter family of invertible states gives a topological transport
phenomenon, similar to the Thouless pumping. As a natural generalization of
this, we can consider a family of invertible states parametrized by some
topological space $X$. This is called a higher pump. It is conjectured that
$(1+1)$-dimensional bosonic invertible state parametrized by $X$ is classified
by $\mathrm{H}^{3}(X;\mathbb{Z})$. In this paper, we construct two higher
pumping models parametrized by $X=\mathbb{R}P^{2}\times S^1$ and
$X=\mathrm{L}(3,1)\times S^1$ that corresponds to the torsion part of
$\mathrm{H}^{3}(X;\mathbb{Z})$. As a consequence of the nontriviality as a
family, we find that a quantum mechanical system with a nontrivial discrete
Berry phase is pumped to the boundary of the $(1+1)$-dimensional system. We
also study higher pump phenomena by using matrix product states (MPS), and
construct a higher pump invariant which takes value in a torsion part of
$\mathrm{H}^{3}(X;\mathbb{Z})$. This is a higher analog of the ordinary
discrete Berry phase that takes value in the torsion part of
$\mathrm{H}^{2}(X;\mathbb{Z})$. In order to define the higher pump invariant,
we utilize the smooth Deligne cohomology and its integration theory. We confirm
that the higher pump invariant of the model has a nontrivial value.


  The many-multiplet method applied to high redshift quasar absorption spectra
has indicated a possible time variation of the fine structure constant.
Alternatively, a constant value of alpha is consistent with the observational
analysis if a non-solar isotopic ratio of Mg24,25,26 occurs at high redshift.
In particular, a higher abundance of the heavier isotopes Mg25,26 are required
to explain the observed multiplet splitting. We show that the synthesis of
Mg25,26 at the base of the convective envelope in low-metallicity asymptotic
giant branch stars, combined with a simple model of galactic chemical
evolution, can produce the required isotopic ratios and is supported by recent
observations of high abundances of the neutron-rich Mg isotopes in metal-poor
globular-cluster stars. We conclude that the present data based on high
redshift quasar absorption spectra may be providing interesting information on
the nucleosynthetic history of such systems, rather than a time variation of
fundamental constants.


  Fluorescence molecular tomography (FMT) is a promising modality for
non-invasive imaging of internal fluorescence agents in biological tissues
especially in small animal models, with applications in diagnosis, therapy, and
drug design. In this paper, we present a new fluorescent reconstruction
algorithm that combines time-resolved fluorescence imaging data with
photon-counting micro-CT (PCMCT) images to estimate the quantum yield and
lifetime of fluorescent markers in a mouse model. By incorporating PCMCT
images, a permissible region of interest of fluorescence yield and lifetime can
be roughly estimated as prior knowledge, reducing the number of unknown
variables in the inverse problem and improving image reconstruction stability.
Our numerical simulation results demonstrate the accuracy and stability of this
method in the presence of data noise, with an average relative error of 18% in
fluorescent yield and lifetime reconstruction.


  Using the formalism developed in a previous paper we analyze the cosmological
implications of our conclusions concerning the scaling behaviour of a network
of cosmic strings, in particular the idea that once gravitational back-reaction
becomes important the transient scaling regime so far explored by numerical
simulations will be replaced by a new `full scaling' regime, with slightly
different parameters. This has consequences for the normalization of the string
tension on all scales. We show how the new scaling solutions affect the
gravitational wave bound from nucleosynthesis and the milli-second pulsar, and
also describe the consequences from large scale structure up to COBE scales.


  We report about the state of the art on complex and real generic
identifiability of tensors, we describe some of our recent results obtained in
[6] and we present perspectives on the subject.


  Rational pure bubble models feature multiple (and often a continuum of)
equilibria, which makes model predictions and policy analyses non-robust. We
show that when the interest rate in the fundamental equilibrium is below the
economic growth rate ($R<G$), a bubbly equilibrium with $R=G$ exists. By
injecting dividends to the bubble asset that grow slower than the aggregate
economy, we can eliminate the fundamental steady state and resolve equilibrium
indeterminacy. We show the general applicability of dividend injection through
examples in overlapping generations and infinite-horizon models with or without
production or financial frictions.


  This talk will review the status of art of nuclear and Coulomb breakup
theories and their relation to optical models of elastic scattering of exotic
projectiles. The effect of the final state interactions between the breakup
particle and the core and target nuclei will be clarified and some typical
numerical calculations for the relevant observables will be presented and
compared to experimental data. Finally new results will be shown to demonstrate
the feasibility of a novel type of experiment involving heavy projectiles far
from stability on heavy targets.


  Event cameras, offering high temporal resolutions and high dynamic ranges,
have brought a new perspective to address common challenges (e.g., motion blur
and low light) in monocular depth estimation. However, how to effectively
exploit the sparse spatial information and rich temporal cues from asynchronous
events remains a challenging endeavor. To this end, we propose a novel
event-based monocular depth estimator with recurrent transformers, namely
EReFormer, which is the first pure transformer with a recursive mechanism to
process continuous event streams. Technically, for spatial modeling, a novel
transformer-based encoder-decoder with a spatial transformer fusion module is
presented, having better global context information modeling capabilities than
CNN-based methods. For temporal modeling, we design a gate recurrent vision
transformer unit that introduces a recursive mechanism into transformers,
improving temporal modeling capabilities while alleviating the expensive GPU
memory cost. The experimental results show that our EReFormer outperforms
state-of-the-art methods by a margin on both synthetic and real-world datasets.
We hope that our work will attract further research to develop stunning
transformers in the event-based vision community. Our open-source code can be
found in the supplemental material.


  We offer an umbrella type result which extends weak convergence of the
classical empirical process on the line to that of more general processes
indexed by functions of bounded variation. This extension is not contingent on
the type of dependence of the underlying sequence of random variables. As a
consequence we establish weak convergence for stationary empirical processes
indexed by general classes of functions under alpha mixing conditions.


  In this paper, we present and analyze fully discrete finite difference
schemes designed for solving the initial value problem associated with the
fractional Korteweg-de Vries (KdV) equation involving the fractional Laplacian.
We design the scheme by introducing the discrete fractional Laplacian operator
which is consistent with the continuous operator, and posses certain properties
which are instrumental for the convergence analysis. Assuming the initial data
(u_0 \in H^{1+\alpha}(\mathbb{R})), where (\alpha \in [1,2)), our study
establishes the convergence of the approximate solutions obtained by the fully
discrete finite difference schemes to a classical solution of the fractional
KdV equation. Theoretical results are validated through several numerical
illustrations for various values of fractional exponent $\alpha$. Furthermore,
we demonstrate that the Crank-Nicolson finite difference scheme preserves the
inherent conserved quantities along with the improved convergence rates.


  For Axiom A flows on basic sets satisfying certain additional conditions we
prove strong spectral estimates for Ruelle transfer operators similar to these
of Dolgopyat (1998) for geodesic flows on compact surfaces (for general
potentials)and transitive Anosov flows on compact manifolds with C^1 jointly
non-integrable horocycle foliations (for the Sinai-Bowen-Ruelle potential).
Here we deal with general potentials. As is now well known, such results have
deep implications in some related areas, e.g. in studying analytic properties
of Ruelle zeta functions and partial differential operators, closed orbit
counting functions, decay of correlations for H\"older continuous potentials.


  Every set of natural numbers determines a generating function convergent for
$q \in (-1,1)$ whose behavior as $q \rightarrow 1^-$ determines a germ. These
germs admit a natural partial ordering that can be used to compare sets of
natural numbers in a manner that generalizes both cardinality of finite sets
and density of infinite sets. For any finite set $D$ of positive integers, call
a set $S$ "$D$-avoiding" if no two elements of $S$ differ by an element of $D$.
We study the problem of determining, for fixed $D$, all $D$-avoiding sets that
are maximal in the germ order. In many cases, we can show that there is exactly
one such set. We apply this to the study of one-dimensional packing problems.


  The combination of strong disorder and interactions in closed quantum systems
can lead to many-body localization (MBL). However this quantum phase is not
stable when the system is coupled to a thermal environment. We investigate how
MBL is destroyed in systems that are weakly coupled to a dephasive Markovian
environment by focusing on their entanglement dynamics. We numerically study
the third R\'{e}nyi negativity $R_3$, a recently proposed entanglement proxy
based on the negativity that captures the unbounded logarithmic growth in the
closed case and that can be computed efficiently with tensor networks. We also
show that the decay of $R_3$ follows a stretched exponential law, similarly to
the imbalance, with however a smaller stretching exponent.


  A very popular theory circulating among non-scientific communities claims
that the massive deployment of Base Stations (BSs) over the territory, a.k.a.
cellular network densification, always triggers an uncontrolled and exponential
increase of human exposure to Radio Frequency "Pollution" (RFP). To face such
concern in a way that can be understood by the layman, in this work we develop
a very simple model to compute the RFP, based on a set of worst-case and
conservative assumptions. We then provide closed-form expressions to evaluate
the RFP variation in a pair of candidate 5G deployments, subject to different
densification levels. Results, obtained over a wide set of representative 5G
scenarios, dispel the myth: cellular network densification triggers an RFP
decrease (up to three orders of magnitude) when the radiated power from the BS
is adjusted to ensure a minimum sensitivity at the cell edge. Eventually, we
analyze the conditions under which the RFP may increase when the network is
densified (e.g., when the radiated power does not scale with the cell size),
proving that the amount of RFP is always controlled. Finally, the results
obtained by simulation confirm the outcomes of the RFP model.


  Carbon Radio Recombination Lines trace the interface between molecular and
atomic gas. We present GMRT observations of Carbon Radio Recombination Lines
(CRRL), C$\alpha$244-C$\alpha$250 towards Cassiopeia A. We use a novel
technique of stacking the emission lines in the visibility domain to obtain,
for the first time, sub-pc resolution optical depth maps of these CRRLs. The
emission shows a wide range of spatial and velocity structures, some of which
are unresolved within our synthesis beam of 0.29 pc and velocity channel of
0.55 km/s. These variations in the emission optical depth and line width are
indicative of inhomogeneity and fragmentation in the intervening Perseus Arm
gas. We compare the distribution of the CRRL emission with that of diffuse and
dense molecular gas using existing CO and H$_2$CO studies. We find that the CO
emission in the -47 km/s Perseus Arm component is primarily concentrated along
an elongated structure detected in our CRRL maps, to the south of which lies
the high-density molecular clumps traced by H$_2$CO. This spatial distribution
of CRRL and molecular tracers is similar to what one would observe for a Photo
Dissociation Region (PDR). In the other Perseus Arm component centered at -37
km/s, there is evidence for high column density (N$_{H_2}$ ~
$10^{22}$cm$^{-2}$) molecular clumps embedded in diffuse CO as well as CRRL
emission towards the center of Cassiopeia A. We propose that the CRRL emissions
coincident with molecular tracers originates from the line of sight integrated
component of the C$^{+}$ envelope of the molecular gas.


  We propose ChatGPT-EDSS, an empathetic dialogue speech synthesis (EDSS)
method using ChatGPT for extracting dialogue context. ChatGPT is a chatbot that
can deeply understand the content and purpose of an input prompt and
appropriately respond to the user's request. We focus on ChatGPT's reading
comprehension and introduce it to EDSS, a task of synthesizing speech that can
empathize with the interlocutor's emotion. Our method first gives chat history
to ChatGPT and asks it to generate three words representing the intention,
emotion, and speaking style for each line in the chat. Then, it trains an EDSS
model using the embeddings of ChatGPT-derived context words as the conditioning
features. The experimental results demonstrate that our method performs
comparably to ones using emotion labels or neural network-derived context
embeddings learned from chat histories. The collected ChatGPT-derived context
information is available at
https://sarulab-speech.github.io/demo_ChatGPT_EDSS/.


  It is believed that choked gamma-ray bursts (CGRBs) are the potential
candidates for the production of high energy neutrinos in GeV-TeV energy range.
These CGRBs out number the successful GRBs by many orders. So it is important
to observe neutrinos from these cosmological objects with the presently
operating neutrino telescope IceCube. We study the three flavor neutrino
oscillation of these high energy neutrinos in the presupernova star environment
which is responsible for the CGRB. For the presupernova star we consider three
different models and calculate the neutrino oscillation probabilities, as well
as neutrino flux on the surface of these star. The matter effect modifies the
neutrino flux of different flavors on the surface of the star. We have also
calculated the flux of these high energy neutrinos on the surface of the Earth.
We found that for neutrino energies below \le 10 TeV the flux ratio does not
amount to 1:1:1, whereas for higher energy neutrinos it does.


  We consider the heat flow of Yang-Mills-Higgs functional where the base
manifold is a Riemannian surface and the fiber is a compact symplectic
manifold. We show that the corresponding Cauchy problem admits a global weak
solution for any $H^1$-initial data. Moreover, the solution is smooth except
finitely many singularities. We prove an energy identity at finite time
singularities and give a description of the asymptotic behavior at time
infinity.


  Two dimensional classical string theory is solved in any curved spacetime.
The complete spacetime required to describe the classical string motions turns
out to be larger than the global space required by complete particle geodesics.
The solutions are fully classified by their behavior in the asymptotically flat
region of spacetime. When the curvature is smooth, the string solutions are
deformed folded string solutions as compared to flat spacetime folded strings
that were known for 19 years. However, surprizing new stringy behavior becomes
evident at curvature singularities such as black holes. The global properties
of the classical string theory require that the ``bare singularity region'' of
the black hole be included along with the usual black hole spacetime. The
mathematical structure needed to describe the solutions include a recursion
relation that is analogous to the transfer matrix of lattice theories. This
encodes lattice-like properties on the worldsheet on the one hand and the
geometry of spacetime on the other hand. A case is made for the presence of
folded strings in the quantum theory of non-critical strings for $d\geq 2$.


  Flux penetration into type-II superconducing films is simulated for
transverse applied magnetic field and flux creep dynamics. The films contain
macroscopic, non-conducting holes and we suggest a new method to introduce the
holes in the simulation formalism. The method implies reconstruction of the
magnetic field change inside the hole. We find that in the region between the
hole and the edge the current density is compressed so that the flux density is
slightly reduced, but the traffic of flux is significantly increased. The
results are in good agreement with magneto-optical studies of flux
distributions in YBCO films.


  The structure of hadrons relevant for deep-inelastic scattering are
completely characterised by the Compton amplitude. A direct calculation of the
Compton amplitude in a lattice QCD setup provides a way to accessing the
structure functions, circumventing the operator mixing and renormalisation
issues of the standard operator product expansion approach. In this
contribution, we focus on the QCDSF/UKQCD Collaboration's advances in
calculating the forward Compton amplitude via an implementation of the
second-order Feynman-Hellmann theorem. We highlight our progress in
investigating the moments of nucleon structure functions.


  In a model independent manner, we explore the local implications of a single
neutrino oscillation measurement which cannot be reconciled within a
three-neutrino theory. We examine this inconsistency for a single region of
baseline to neutrino energy $L/E$. Assuming that sterile neutrinos account for
the anomaly, we find that the {\it local} demands of this datum can require the
addition to the theory of one to three sterile neutrinos. We examine the
constraints which can be used to determine when more than one neutrino would be
required. The results apply only to a given region of $L/E$. The question of
the adequacy of the sterile neutrinos to satisfy a global analysis is not
addressed here. Finally, using the results of a 3+2 analysis, we indicate
values for unknown mixing matrix elements which would require two sterile
neutrinos due to local demands only.


  Diagnostic, prognostic and therapeutic decision-making of cancer in pathology
clinics can now be carried out based on analysis of multi-gigapixel tissue
images, also known as whole-slide images (WSIs). Recently, deep convolutional
neural networks (CNNs) have been proposed to derive unsupervised WSI
representations; these are attractive as they rely less on expert annotation
which is cumbersome. However, a major trade-off is that higher predictive power
generally comes at the cost of interpretability, posing a challenge to their
clinical use where transparency in decision-making is generally expected. To
address this challenge, we present a handcrafted framework based on deep CNN
for constructing holistic WSI-level representations. Building on recent
findings about the internal working of the Transformer in the domain of natural
language processing, we break down its processes and handcraft them into a more
transparent framework that we term as the Handcrafted Histological Transformer
or H2T. Based on our experiments involving various datasets consisting of a
total of 5,306 WSIs, the results demonstrate that H2T based holistic WSI-level
representations offer competitive performance compared to recent
state-of-the-art methods and can be readily utilized for various downstream
analysis tasks. Finally, our results demonstrate that the H2T framework can be
up to 14 times faster than the Transformer models.


  The Internet of Things (IoT) extends the Internet connectivity into billions
of IoT devices around the world, where the IoT devices collect and share
information to reflect status of the physical world. The Autonomous Control
System (ACS), on the other hand, performs control functions on the physical
systems without external intervention over an extended period of time. The
integration of IoT and ACS results in a new concept - autonomous IoT (AIoT).
The sensors collect information on the system status, based on which the
intelligent agents in the IoT devices as well as the Edge/Fog/Cloud servers
make control decisions for the actuators to react. In order to achieve
autonomy, a promising method is for the intelligent agents to leverage the
techniques in the field of artificial intelligence, especially reinforcement
learning (RL) and deep reinforcement learning (DRL) for decision making. In
this paper, we first provide a tutorial of DRL, and then propose a general
model for the applications of RL/DRL in AIoT. Next, a comprehensive survey of
the state-of-art research on DRL for AIoT is presented, where the existing
works are classified and summarized under the umbrella of the proposed general
DRL model. Finally, the challenges and open issues for future research are
identified.


  Bulk magnetic measurements and inelastic neutron scattering were used to
investigate the spin-singlet ground state and magnetic gap excitations in
BaCuSi2O6, a quasi-2-dimensional antiferromagnet with a bilayer structure. The
results are well described by a model based on weakly interacting
antiferromagnetic dimers. A strongly temperature-dependent dispersion in the
gap modes was found. We suggest that the observed excitations are analogous to
magneto-excitons in light rare-earth compounds, but are an intrinsic property
of a simple Heisenberg Hamiltonian for the S=1/2 magnetic bilayer.


  We provide numerical evidence of global diffusion occurring in slightly
perturbed integrable Hamiltonian systems and symplectic maps. We show that even
if a system is sufficiently close to be integrable, global diffusion occurs on
a set with peculiar topology, the so--called Arnold web, and is qualitatively
different from Chirikov diffusion, occurring in more perturbed systems.


  Some recent advances in the theoretical description of the Nucleon
electromagnetic form factors, both in the space- and time-like regions, will be
briefly illustrated. In particular, both the present stage of the lattice
calculations and updated phenomenological approaches, like the ones based on
dispersion relations and on microscopical models, will be reported.


  We propose a new method to compute glueball masses in finite temperature
Lattice Gauge Theories which at low temperature is fully compatible with the
known zero temperature results and as the temperature increases leads to a
glueball spectrum which vanishes at the deconfinement transition. We show that
this definition is consistent with the Isgur-Paton model and with the expected
contribution of the glueball spectrum to various thermodynamic quantities at
finite temperature. We test our proposal with a set of high precision numerical
simulations in the 3d gauge Ising model and find a good agreement with our
predictions.


  One of the distinguishing characteristics of modern deep learning systems is
that they typically employ neural network architectures that utilize enormous
numbers of parameters, often in the millions and sometimes even in the
billions. While this paradigm has inspired significant research on the
properties of large networks, relatively little work has been devoted to the
fact that these networks are often used to model large complex datasets, which
may themselves contain millions or even billions of constraints. In this work,
we focus on this high-dimensional regime in which both the dataset size and the
number of features tend to infinity. We analyze the performance of random
feature regression with features $F=f(WX+B)$ for a random weight matrix $W$ and
random bias vector $B$, obtaining exact formulae for the asymptotic training
and test errors for data generated by a linear teacher model. The role of the
bias can be understood as parameterizing a distribution over activation
functions, and our analysis directly generalizes to such distributions, even
those not expressible with a traditional additive bias. Intriguingly, we find
that a mixture of nonlinearities can improve both the training and test errors
over the best single nonlinearity, suggesting that mixtures of nonlinearities
might be useful for approximate kernel methods or neural network architecture
design.


  We present a slightly modified version of the well known "geometric Lorenz
attractor". It consists in a C1 open set O of vector fields in R3 having an
attracting region U containing: (1) a unique singular saddle point sigma; (2) a
unique attractor Lambda containing the singular point; (3) the maximal
invariant in U contains at most 2 chain recurrence classes, which are Lambda
and (at most) one hyperbolic horseshoe. The horseshoe and the singular
attractor have a collision along the union of 2 co-dimension 1 sub-manifolds
which divide O in 3 regions. By crossing this collision locus, the attractor
and the horseshoe may merge in a two-sided Lorenz attractor, or they may
exchange their nature: the Lorenz attractor expel the singular point sigma and
becomes a horseshoe and the horseshoe absorbs sigma becoming a Lorenz
attractor.
  By crossing this collision locus, the attractor and the horseshoe may merge
in a two-sided Lorenz attractor, or they may exchange their nature: the Lorenz
attractor expel the singular point sigma and becomes a horseshoe and the
horseshoe absorbs sigma becoming a Lorenz attractor.


  Time-resolved optical measurements in (110)-oriented GaAs/AlGaAs quantum
wells show a ten-fold increase of the spin-relaxation rate as a function of
applied electric field from 20 to 80 kV cm-1 at 170 K and indicate a similar
variation at 300 K, in agreement with calculations based on the Rashba effect.
Spin relaxation is almost field-independent below 20 kV cm-1 reflecting quantum
well interface asymmetry. The results indicate the achievability of
voltage-gateable spin-memory time longer than 3 ns simultaneously with high
electron mobility.


  Donsker-type functional limit theorems are proved for empirical processes
arising from discretely sampled increments of a univariate L\'evy process. In
the asymptotic regime the sampling frequencies increase to infinity and the
limiting object is a Gaussian process that can be obtained from the composition
of a Brownian motion with a covariance operator determined by the L\'evy
measure. The results are applied to derive the asymptotic distribution of
natural estimators for the distribution function of the L\'evy jump measure. As
an application we deduce Kolmogorov-Smirnov type tests and confidence bands.


  This paper contributes to an emerging literature that models votes and text
in tandem to better understand polarization of expressed preferences. It
introduces a new approach to estimate preference polarization in
multidimensional settings, such as international relations, based on
developments in the natural language processing and network science literatures
-- namely word embeddings, which retain valuable syntactical qualities of human
language, and community detection in multilayer networks, which locates densely
connected actors across multiple, complex networks. We find that the employment
of these tools in tandem helps to better estimate states' foreign policy
preferences expressed in UN votes and speeches beyond that permitted by votes
alone. The utility of these located affinity blocs is demonstrated through an
application to conflict onset in International Relations, though these tools
will be of interest to all scholars faced with the measurement of preferences
and polarization in multidimensional settings.


  We consider the nonlinear Schr\"odinger equation with periodic dispersion
management. We first establish global-in-time Strichartz estimates for the
underlying linear equation with suitable dispersion maps. As an application, we
establish a small-data scattering result for the $3d$ cubic equation. Finally,
we use a virial argument to demonstrate the existence of blowup solutions for
the $3d$ cubic equation with piecewise constant dispersion map.


  Recently, commonsense learning has been a hot topic in image-text matching.
Although it can describe more graphic correlations, commonsense learning still
has some shortcomings: 1) The existing methods are based on triplet semantic
similarity measurement loss, which cannot effectively match the intractable
negative in image-text sample pairs. 2) The weak generalization ability of the
model leads to the poor effect of image and text matching on large-scale
datasets. According to these shortcomings. This paper proposes a novel
image-text matching model, called Active Mining Sample Pair Semantics
image-text matching model (AMSPS). Compared with the single semantic learning
mode of the commonsense learning model with triplet loss function, AMSPS is an
active learning idea. Firstly, the proposed Adaptive Hierarchical Reinforcement
Loss (AHRL) has diversified learning modes. Its active learning mode enables
the model to more focus on the intractable negative samples to enhance the
discriminating ability. In addition, AMSPS can also adaptively mine more hidden
relevant semantic representations from uncommented items, which greatly
improves the performance and generalization ability of the model. Experimental
results on Flickr30K and MSCOCO universal datasets show that our proposed
method is superior to advanced comparison methods.


  A model of color particle confinement is considered. The model is based on
the Snyder-Yang algebra, which takes into account a non-commutativity of
generalized momenta and coordinates of a color particle and contains two new
constants. An extended kinematical invariance in a quantum phase space of a
color particle gives rise to an invariant equation with an oscillator rising
potential. The presence of the oscillator rising potential can simulate a
confinement of a color particle. Mass and lenght parameters involved in the
Snyder-Yang commutation relations along with parameters of current and
constituent quarks are estimated.


  As the development of a dengue vaccine is ongoing, we simulate an
hypothetical vaccine as an extra protection to the population. In a first
phase, the vaccination process is studied as a new compartment in the model,
and different ways of distributing the vaccines investigated: pediatric and
random mass vaccines, with distinct levels of efficacy and durability. In a
second step, the vaccination is seen as a control variable in the
epidemiological process. In both cases, epidemic and endemic scenarios are
included in order to analyze distinct outbreak realities.


  The coronal magnetic configuration of an active region typically evolves
quietly during few days before becoming suddenly eruptive and launching a
coronal mass ejection (CME). The precise origin of the eruption is still
debated. Among several mechanisms, it has been proposed that a loss of
equilibrium, or an ideal magneto-hydrodynamic (MHD) instability such as the
torus instability, could be responsible for the sudden eruptivity. Distinct
approaches have also been formulated for limit cases having circular or
translation symmetry. We revisit the previous theoretical approaches, setting
them in the same analytical framework. The coronal field results from the
contribution of a non-neutralized current channel added to a background
magnetic field, which in our model is the potential field generated by two
photospheric flux concentrations. The evolution on short Alfvenic time scale is
governed by ideal MHD. We show analytically first that the loss of equilibrium
and the stability analysis are two different views of the same physical
mechanism. Second, we identify that the same physics is involved in the
instability of circular and straight current channels. Indeed, they are just
two particular limiting case of more general current paths. A global
instability of the magnetic configuration is present when the current channel
is located at a coronal height, h, large enough so that the decay index of the
potential field, (d ln |Bp|) / (d ln h) is larger than a critical value. At the
limit of very thin current channels, previous analysis found a critical decay
index of 1.5 and 1 for circular and straight current channels, respectively.
However, with current channels being deformable and as thick as expected in the
corona, we show that this critical index has similar values for circular and
straight current channels, typically in the range [1.1,1.3].


  Ultrafast demagnetization in magnetic nanoparticles using pulsed laser has
attracted considerable attention because of its potential applications in
spintronics, such as data storage. In such applications, it is necessary to
control magnetization using low energy laser pulses, however, this poses the
problem of increasing the amount of energy from the excitation laser pulses to
the spin subsystem. We take advantage of the phenomenon known as localized
surface plasmon resonance (LSPR) to enhance the energy transfer from laser
pulses to the spin subsystem. To induce LSPR, hybrid nanoparticles consisting
of noble metal nanoparticles with LSPR absorption and magnetic metal
nanoparticles are prepared using a novel method. Specifically, AgCo hybrid
nanoparticles are prepared by a self assembly method using pulsed laser
deposition. We performed measurements of the static Faraday and time-resolved
Faraday effects using a pump probe technique on the AgCo hybrid nanoparticles
with various AgCo ratios. The data suggest that the LSPR absorption and
demagnetization amplitude increase with the increasing AgCo ratio. The results
indicate that the amount of energy transferred from the laser pulses to the
spin system of magnetic nanoparticles can increase via LSPR absorption.


  We use the geometry of the stellahedral toric variety to study matroids. We
identify the valuative group of matroids with the cohomology ring of the
stellahedral toric variety, and show that valuative, homological, and numerical
equivalence relations for matroids coincide. We establish a new log-concavity
result for the Tutte polynomial of a matroid, answering a question of Wagner
and Shapiro-Smirnov-Vaintrob on Postnikov-Shapiro algebras, and calculate the
Chern-Schwartz-MacPherson classes of matroid Schubert cells. The central
construction is the "augmented tautological classes of matroids," modeled after
certain vector bundles on the stellahedral toric variety.


  In this paper, we examine how large language models (LLMs) solve multi-step
problems under a language agent framework with three components: a generator, a
discriminator, and a planning method. We investigate the practical utility of
two advanced planning methods, iterative correction and tree search. We present
a comprehensive analysis of how discrimination accuracy affects the overall
performance of agents when using these two methods or a simpler method,
re-ranking. Experiments on two tasks, text-to-SQL parsing and mathematical
reasoning, show that: (1) advanced planning methods demand discriminators with
at least 90% accuracy to achieve significant improvements over re-ranking; (2)
current LLMs' discrimination abilities have not met the needs of advanced
planning methods to achieve such improvements; (3) with LLM-based
discriminators, advanced planning methods may not adequately balance accuracy
and efficiency. For example, compared to the other two methods, tree search is
at least 10--20 times slower but leads to negligible performance gains, which
hinders its real-world applications. Code and data are available at
https://github.com/OSU-NLP-Group/llm-planning-eval.


  Pair Hidden Markov Models (PHMMs) are probabilistic models used for pairwise
sequence alignment, a quintessential problem in bioinformatics. PHMMs include
three types of hidden states: match, insertion and deletion. Most previous
studies have used one or two hidden states for each PHMM state type. However,
few studies have examined the number of states suitable for representing
sequence data or improving alignment accuracy.We developed a novel method to
select superior models (including the number of hidden states) for PHMM. Our
method selects models with the highest posterior probability using Factorized
Information Criteria (FIC), which is widely utilised in model selection for
probabilistic models with hidden variables. Our simulations indicated this
method has excellent model selection capabilities with slightly improved
alignment accuracy. We applied our method to DNA datasets from 5 and 28
species, ultimately selecting more complex models than those used in previous
studies.


  We obtain through a Matrix Product Ansatz (MPA) the exact solution of the
most general $N$-state spin chain with $U(1)^N$ symmetry and nearest neighbour
interaction. In the case N=6 this model contain as a special case the
integrable SO(6) spin chain related to the one loop mixing matrix for anomalous
dimensions in ${\cal N} = 4$ SYM, dual to type $IIB$ string theory in the
generalised Lunin-Maldacena backgrounds. This MPA is construct by a map between
scalar fields and abstract operators that satisfy an appropriate associative
algebra. We analyses the Yang-Baxter equation in the N=3 sector and the
consistence of the algebraic relations among the matrices defining the MPA and
find a new class of exactly integrable model unknown up to now.


  Consider a rotating and possibly pulsating "star" in (2+1) dimensions. If the
star is axially symmetric, then in the vacuum region surrounding the star, (a
region that we assume at most contains a cosmological constant), the Einstein
equations imply that under physically plausible conditions the geometry is in
fact stationary. Furthermore, the geometry external to the star is then
uniquely guaranteed to be the (2+1) dimensional analogue of the Kerr-de Sitter
spacetime, the BTZ geometry. This Birkhoff-like theorem is very special to
(2+1) dimensions, and fails in (3+1) dimensions. Effectively, this is a "no
hair" theorem for (2+1) dimensional axially symmetric stars: the exterior
geometry is completely specified by the mass, angular momentum, and
cosmological constant.


  We explore a nonlinear field model to describe the interplay between the
ability of excitons to be Bose-condensed and their interaction with other modes
of a crystal. We apply our consideration to the long-living para-excitons in
Cu2O. Taking into account the exciton-phonon interaction and introducing a
coherent phonon part of the moving condensate, we derive the dynamic equations
for the exciton-phonon condensate. These equations can support localized
solutions, and we discuss the conditions for the moving inhomogeneous
condensate to appear in the crystal. We calculate the condensate wave function
and energy, and a collective excitation spectrum in the semiclassical
approximation; the inside-excitations were found to follow the asymptotic
behavior of the macroscopic wave function exactly. The stability conditions of
the moving condensate are analyzed by use of Landau arguments, and Landau
critical parameters appear in the theory. Finally, we apply our model to
describe the recently observed interference and strong nonlinear interaction
between two coherent exciton-phonon packets in Cu2O.