  Proactive failure detection of instances is vitally essential to microservice
systems because an instance failure can propagate to the whole system and
degrade the system's performance. Over the years, many single-modal (i.e.,
metrics, logs, or traces) data-based nomaly detection methods have been
proposed. However, they tend to miss a large number of failures and generate
numerous false alarms because they ignore the correlation of multimodal data.
In this work, we propose AnoFusion, an unsupervised failure detection approach,
to proactively detect instance failures through multimodal data for
microservice systems. It applies a Graph Transformer Network (GTN) to learn the
correlation of the heterogeneous multimodal data and integrates a Graph
Attention Network (GAT) with Gated Recurrent Unit (GRU) to address the
challenges introduced by dynamically changing multimodal data. We evaluate the
performance of AnoFusion through two datasets, demonstrating that it achieves
the F1-score of 0.857 and 0.922, respectively, outperforming the
state-of-the-art failure detection approaches.


  Measuring the fermion Yukawa coupling constants is important for
understanding the origin of the fermion masses and its relationship to the
spontaneously electroweak symmetry breaking. On the other hand, some new
physics models will change the Lorentz structure of the Yukawa interactions
between the standard model (SM) fermions and the SM-like Higgs boson even in
their decoupling limit. Thus the precisely measurement of the fermion Yukawa
interactions is a powerful tool of new physics searching in the decoupling
limit. In this work, we show the possibility of investigating the Lorentz
structure of the bottom-quark Yukawa interaction with the 125GeV SM-like Higgs
boson at future $e^+e^-$ colliders.


  We highlight modular equations discovered by Somos and Ramanujan, and use
them to prove new relations between lattice sums and hypergeometric functions.
We also discuss progress towards solving Boyd's Mahler measure conjectures, and
we conjecture a new formula for $L(E,2)$ of conductor 17 elliptic curves.


  The goal of privacy metrics is to measure the degree of privacy enjoyed by
users in a system and the amount of protection offered by privacy-enhancing
technologies. In this way, privacy metrics contribute to improving user privacy
in the digital world. The diversity and complexity of privacy metrics in the
literature makes an informed choice of metrics challenging. As a result,
instead of using existing metrics, new metrics are proposed frequently, and
privacy studies are often incomparable. In this survey we alleviate these
problems by structuring the landscape of privacy metrics. To this end, we
explain and discuss a selection of over eighty privacy metrics and introduce
categorizations based on the aspect of privacy they measure, their required
inputs, and the type of data that needs protection. In addition, we present a
method on how to choose privacy metrics based on nine questions that help
identify the right privacy metrics for a given scenario, and highlight topics
where additional work on privacy metrics is needed. Our survey spans multiple
privacy domains and can be understood as a general framework for privacy
measurement.


  Using the epiperimetric inequalities approach, we study the obstacle problem
$\min\{(-\Delta)^su,u-\varphi\}=0,$ for the fractional Laplacian $(-\Delta)^s$
with obstacle $\varphi\in C^{k,\gamma}(\mathbb{R}^n)$, $k\ge2$ and
$\gamma\in(0,1)$.
  We prove an epiperimetric inequality for the Weiss' energy $W_{1+s}$ and a
logarithmic epiperimetric inequality for the Weiss' energy $W_{2m}$. Moreover,
we also prove two epiperimetric inequalities for negative energies $W_{1+s}$
and $W_{2m}$.
  By these epiperimetric inequalities, we deduce a frequency gap and a
characterization of the blow-ups for the frequencies $\lambda=1+s$ and
$\lambda=2m$. Finally, we give an alternative proof of the regularity of the
points on the free boundary with frequency $1+s$ and we describe the structure
of the points on the free boundary with frequency $2m$, with $m\in\mathbb{N}$
and $2m\le k.$


  In this work, we investigate new constraints on $f(T)$ gravity using the
recent Baryon Acoustic Oscillation (BAO) data released by the Dark Energy
Spectroscopic Instrument (DESI) and the Type Ia supernovae (SNIa) catalog from
the full 5-years of the Dark Energy Survey Supernova Program (DES-SN5YR). The
$f(T)$ cosmological models considered are characterised by power law late-time
accelerated expansion. Our results show that the combination DESI BAO +$r_d$
CMB Planck suggests a Bayesian preference for late-time $f(T)$ cosmological
models over $\Lambda$CDM, obtaining a value of $H_0=
68.3^{+3.0}_{-3.5}$[km/s/Mpc] in agreement with SH0ES collaboration, however,
due to a bigger uncertainty.


  Ground-based observations of the secondary transit in the 2MASS K band are
presented for the hot Jupiter WASP-121b. These are the first occultation
observations of an extrasolar planet carried out with an instrument attached to
a 1m-class telescope (SMARTS' 1.3 m). We find a highly significant transit
depth of (0.228 +/- 0.023)%. Together with the Hubble Space Telescope near
infrared emission spectrum, current data support more involved atmosphere
models with species producing emission/absorption features, rather than simple
smooth black body emission. Analysis of the time difference between the primary
and secondary transits and the durations of these events yield an eccentricity
of e=0.0207 +/- 0.0153, which is consistent with the earlier estimates of
low/zero eccentricity, but with a smaller error. Together with the existing
K-band data on other systems, WASP-121b lends further support to the lack of
efficient heat transport between the day and night sides for nearly all Hot
Jupiters.


  The effect of microwave irradiation on the phase dynamics of intrinsic
Josephson junctions in high temperature superconductors is investigated. We
demonstrate the influence of microwave's amplitude variation on the
current-voltage characteristics and on the time dependence (temporal
oscillations) of the electric charge in the superconducting layers. A
remarkable changing of the longitudinal plasma wavelength at parametric
resonance is shown. We demonstrate an effect of the microwave radiation on the
width of the parametric resonance region.


  More often than not, bad decisions are bad regardless of where and when they
are made. Information sharing might thus be utilized to mitigate them. Here we
show that sharing the information about strategy choice between players
residing on two different networks reinforces the evolution of cooperation. In
evolutionary games the strategy reflects the action of each individual that
warrants the highest utility in a competitive setting. We therefore assume that
identical strategies on the two networks reinforce themselves by lessening
their propensity to change. Besides network reciprocity working in favour of
cooperation on each individual network, we observe the spontaneous emerge of
correlated behaviour between the two networks, which further deters defection.
If information is shared not just between individuals but also between groups,
the positive effect is even stronger, and this despite the fact that
information sharing is implemented without any assumptions with regards to
content.


  We study the strong coupling between the molecular excited state and the
plasmonic modes of silver hole arrays with a resonant frequency very close to
the asymptotic line of the plasmonic dispersion relation, at the nonlinear
regime. We demonstrate that the strong coupling regime can be achieved between
the two sub-systems at low molecular densities with negligible damping of the
electromagnetic field. Our results are supported by rigorous numerical
simulations showing that the strong coupling is observed when the molecular
transition lies within the nonlinear regime of the dispersion relation rather
than the linear regime.


  In this talk I summarize several recent results concerning the
four-dimensional effective supergravity obtained using a Calabi-Yau
compactification of the $E_8\times E_8$ heterotic string from M-theory. A
simple macroscopic study is provided expanding the theory in powers of two
dimensionless variables. Higher order terms in the K\"ahler potential are
identified and matched with the heterotic string corrections. In the context of
this M-theory expansion, I discuss several phenomenological issues:
universality of soft scalar masses, relations between the different scales of
the theory (eleven-dimensional Planck mass, compactification scale and orbifold
scale) in order to obtain unification at $3\times 10^{16}$ GeV or lower values,
soft supersymmetry-breaking terms, and finally charge and colour breaking
minima. The above analyses are also carried out in the presence of
(non-perturbative) five-branes.


  Given a family of lattice polytopes, a common endeavor in Ehrhart theory is
the classification of those polytopes in the family that are Gorenstein, or
more generally level. In this article, we consider these questions for
$\boldsymbol{s}$-lecture hall polytopes, which are a family of simplices
arising from $\boldsymbol{s}$-lecture hall partitions. In particular, we
provide concrete classifications for both of these properties purely in terms
of $\boldsymbol{s}$-inversion sequences. Moreover, for a large subfamily of
$\boldsymbol{s}$-lecture hall polytopes, we provide a more geometric
classification of the Gorenstein property in terms of its tangent cones. We
then show how one can use the classification of level $\boldsymbol{s}$-lecture
hall polytopes to construct infinite families of level $\boldsymbol{s}$-lecture
hall polytopes, and to describe level $\boldsymbol{s}$-lecture hall polytopes
in small dimensions.


  Paired comparison models are used for analyzing data that involves pairwise
comparisons among a set of objects. When the outcomes of the pairwise
comparisons have no ties, the paired comparison models can be generalized as a
class of binary response models. Receiver operating characteristic (ROC) curves
and their corresponding areas under the curves are commonly used as performance
metrics to evaluate the discriminating ability of binary response models.
Despite their individual wide range of usage and their close connection to
binary response models, ROC analysis to our knowledge has never been extended
to paired comparison models since the problem of using different objects as the
reference in paired comparison models prevents traditional ROC approach from
generating unambiguous and interpretable curves. We focus on addressing this
problem by proposing two novel methods to construct ROC curves for paired
comparison data which provide interpretable statistics and maintain desired
asymptotic properties. The methods are then applied and analyzed on
head-to-head professional sports competition data.


  We prove the global existence and uniqueness of classical solutions with
small initial data and with wake-like decaying null infinity for the
spherically symmetric Einstein-scalar-field equations with potential, where the
scalar potential V satisfies (1.13) and (1.14).


  Acting as a highly nonlinear response to the strong laser field, high
harmonic generation (HHG) naturally contains the fingerprints of atomic and
electronic properties of materials. Electronic properties of a solid such as
band structure and topology can thus be probed, while the phonon dynamics
during HHG are often neglected. Here we show that by exploiting the effects of
phonon deformation on HHG, the intrinsic phonon information can be deciphered
and direct probing of band- and mode-resolved electron-phonon couplings (EPC)
of photoexcited materials is possible. Considering HHG spectroscopy can be
vacuum free and unrestricted to electron occupation, this work suggests HHG is
promising for all-optical characterization of EPC in solids, especially for
gapped quantum states or materials under high pressure.


  We determine the hyperon vector couplings $f_1(0)$ for $\Sigma^{-}\rightarrow
nl^-\bar{\nu_l}$ and $\Xi^0\rightarrow\Sigma^{+}l^-\bar{\nu_l}$ semileptonic
decays in the continuum limit with (2+1)-flavors of dynamical domain-wall
fermions, using the Iwasaki gauge action at two different lattice spacings of
$a$=0.114(2) and 0.086(2) fm. A theoretical estimation of flavor SU(3)-breaking
effect on the vector coupling is required to extract $V_{us}$ from the
experimental rate of hyperon beta decays. We obtain the vector couplings
$f_1(0)$ for $\Sigma\rightarrow N$ and $\Xi\rightarrow \Sigma$ beta-decays with
an accuracy of less than one percent. We then find that lattice results of
$f_1(0)$ combined with the best estimate of $|V_{us}|$ with imposing
Cabibbo-Kobayashi-Maskawa (CKM) unitarity are slightly deviated from the
experimental result of $|V_{us}f_1(0)|$ for the $\Sigma\rightarrow N$
beta-decay. This discrepancy can be attributed to an assumption made in the
experimental analysis on $|V_{us}f_1(0)|$, where the induced second-class form
factor $g_2$ is set to be zero regardless of broken SU(3) symmetry. We report
on this matter and then estimate the possible value of $g_2(0)$, which is
evaluated from the experimental decay rate with our lattice result of $f_1(0)$
under the first-row CKM-unitarity condition.


  Let $(N, J)$ be a simply connected $2n$-dimensional nilpotent Lie group
endowed with an invariant complex structure. We define a left invariant
Riemannian metric on $N$ compatible with $J$ to be minimal, if it minimizes the
norm of the invariant part of the Ricci tensor among all compatible metrics
with the same scalar curvature. In [L1], J. Lauret proved that minimal metrics
(if any) are unique up to isometry and scaling. This uniqueness allows us to
distinguish two complex structures with Riemannian data, giving rise to a great
deal of invariants.
  We show how to use a Riemannian invariant: the eigenvalues of the Ricci
operator, polynomial invariants and discrete invariants to give an alternative
proof of the pairwise non-isomorphism between the structures which have
appeared in the classification of abelian complex structures on 6-dimensional
nilpotent Lie algebras given in [ABD]. We also present some continuous families
in dimension 8.


  In this paper, we study low-complexity algorithms for beam and channel
tracking for millimeter-wave (mmWave) communications. In particular, the least
mean squares (LMS) and bidirectional LMS (BiLMS) algorithms are derived for a
mobile mmWave transmission scenario, where channel measurement is a nonlinear
function of the unknown angle-of-arrival (AoA) and angle-of-departure (AoD).
Numerical results confirm that LMS is superior to widely used Extended Kalman
Filter (EKF) algorithm in tracking the mmWave beam, when the initialization of
AoA/AoD and channel gains is imperfect (i.e., performed using noisy channel
estimates). Moreover, BiLMS exhibits a very good mean square error (MSE)
performance as compared to both LMS and EKF, which makes it a promising channel
tracking algorithm for a mobile mmWave transmission scenario. We also show that
LMS and BiLMS algorithms are more robust against the impairments due to the
non-optimal antenna array size as compared to EKF, and show relatively faster
convergence characteristic along with increasing signal-to-noise ratio (SNR).


  Various aspects of the construction, operation and calibration of the
recently completed deep-sea ANTARES neutrino telescope are described. Some
first results obtained with a partial five line configuration are presented,
including depth dependence of the atmospheric muon rate, the search for
point-like cosmic neutrino sources and the search for dark matter annihilation
in the Sun.


  The use of polarized beams enhance the possibility of the precision
measurements at the International Linear Collider (ILC). In order to preserve
the degree of polarization during beam transport spin rotators are included in
the current TDR ILC Lattice. In this report some advantages of using a combined
spin rotator/spin flipper are discussed. A few possible lattice designs of spin
flipper developed at DESY in 2012 are presented.


  Many dynamic ensemble selection (DES) methods are known in the literature. A
previously-developed by the authors, method consists in building a randomized
classifier which is treated as a model of the base classifier. The model is
equivalent to the base classifier in a certain probabilistic sense. Next, the
probability of correct classification of randomized classifier is taken as the
competence of the evaluated classifier.
  In this paper, a novel randomized model of base classifier is developed. In
the proposed method, the random operation of the model results from a random
selection of the learning set from the family of learning sets of a fixed size.
The paper presents the mathematical foundations of this approach and shows how,
for a practical application when learning and validation sets are given, one
can determine the measure of competence and build a MC system with the DES
scheme.
  The DES scheme with the proposed model of competence was experimentally
evaluated on the collection of 67 benchmark datasets and compared in terms of
eight quality criteria with two ensemble classifiers which use the
previously-proposed concepts of randomized model. The proposed approach
achieved the lowest ranks for almost all investigated quality criteria.


  In this paper, we address the rigid body pose stabilization problem using
dual quaternion formalism. We propose a hybrid control strategy to design a
switching control law with hysteresis in such a way that the global asymptotic
stability of the closed-loop system is guaranteed and such that the global
attractivity of the stabilization pose does not exhibit chattering, a problem
that is present in all discontinuous-based feedback controllers. Using
numerical simulations, we illustrate the problems that arise from existing
results in the literature -- as unwinding and chattering -- and verify the
effectiveness of the proposed controller to solve the robust global pose
stability problem.


  The Julia programming language was designed to fill the needs of scientific
computing by combining the benefits of productivity and performance languages.
Julia allows users to write untyped scripts easily without needing to worry
about many implementation details, as do other productivity languages. If one
just wants to get the work done-regardless of how efficient or general the
program might be, such a paradigm is ideal. Simultaneously, Julia also allows
library developers to write efficient generic code that can run as fast as
implementations in performance languages such as C or Fortran. This combination
of user-facing ease and library developer-facing performance has proven quite
attractive, and the language has increasing adoption.
  With adoption comes combinatorial challenges to correctness. Multiple
dispatch -- Julia's key mechanism for abstraction -- allows many libraries to
compose "out of the box." However, it creates bugs where one library's
requirements do not match what another provides. Typing could address this at
the cost of Julia's flexibility for scripting.
  I developed a "best of both worlds" solution: gradual typing for Julia. My
system forms the core of a gradual type system for Julia, laying the foundation
for improving the correctness of Julia programs while not getting in the way of
script writers. My framework allows methods to be individually typed or
untyped, allowing users to write untyped code that interacts with typed library
code and vice versa. Typed methods then get a soundness guarantee that is
robust in the presence of both dynamically typed code and dynamically generated
definitions. I additionally describe protocols, a mechanism for typing
abstraction over concrete implementation that accommodates one common pattern
in Julia libraries, and describe its implementation into my typed Julia
framework.


  In this paper we estimate the parameters of the qubit Pauli channel using the
channel matrix formalism. The main novelty of this work is that we do not
assume the directions of the Pauli channel to be known, but they are determined
through the tomography process, too. The results show that for optimally
estimating the contraction parameters and the channel matrix we should have
input qubits and measurements in the channel directions. However, for optimally
estimating the channel directions, we should use different tomography
conditions.


  This article has been removed by arXiv administrators due to falsified
authorship.


  Information spreading in complex networks is often modeled as diffusing
information with certain probability from nodes that possess it to their
neighbors that do not. Information cascades are triggered when the activation
of a set of initial nodes (seeds) results in diffusion to large number of
nodes. Here, several novel approaches for seed initiation that replace the
commonly used activation of all seeds at once with a sequence of initiation
stages are introduced. Sequential strategies at later stages avoid seeding
highly ranked nodes that are already activated by diffusion active between
stages. The gain arises when a saved seed is allocated to a node difficult to
reach via diffusion. Sequential seeding and a single stage approach are
compared using various seed ranking methods and diffusion parameters on real
complex networks. The experimental results indicate that, regardless of the
seed ranking method used, sequential seeding strategies deliver better coverage
than single stage seeding in about 90% of cases. Longer seeding sequences tend
to activate more nodes but they also extend the duration of diffusion. Various
variants of sequential seeding resolve the trade-off between the coverage and
speed of diffusion differently.


  We present numerical 2D magnetostatic models for sunspot penumbrae consisting
of radially aligned field-free gaps in a potential magnetic field, as proposed
by Spruit and Scharmer (2006). The shape of the gaps and the field
configurations around them are computed consistently from the condition of
magnetostatic pressure balance between the gap and the magnetic field. The
results show that field-free gaps in the {\it inner} penumbra are cusp-shaped
and bounded by a magnetic field inclined by about $70^\circ$ from the vertical.
Here, the magnetic component has a Wilson depression on the order 200--300 km
relative to the top of the field-free gap; the gaps should thus appear as
noticeably elevated features. This structure explains the large variations in
field strength in the inner penumbra inferred from magnetograms and
two-component inversions, and the varying appearance of the inner penumbra with
viewing angle. In the {\it outer} penumbra, on the other hand, the gaps are
flat-topped with a horizontal magnetic field above the middle of the gap. The
magnetic field has large inclination variations horizontally, but only small
fluctuations in field strength, in agreement with observations.


  The overdamped dynamics of a charged particle driven by an uniform electric
field through a random sequence of scatterers in one dimension is investigated.
Analytic expressions of the mean velocity and of the velocity power spectrum
are presented. These show that above a threshold value of the field normal
diffusion is superimposed to ballistic motion. The diffusion constant can be
given explicitly. At the threshold field the transition between conduction and
localization is accompanied by an anomalous diffusion. Our results exemplify
that, even in the absence of time-dependent stochastic forces, a purely
mechanical model equipped with a quenched disorder can exhibit normal as well
as anomalous diffusion, the latter emerging as a critical property.


  Much of human knowledge is encoded in text, available in scientific
publications, books, and the web. Given the rapid growth of these resources, we
need automated methods to extract such knowledge into machine-processable
structures, such as knowledge graphs. An important task in this process is
entity normalization, which consists of mapping noisy entity mentions in text
to canonical entities in well-known reference sets. However, entity
normalization is a challenging problem; there often are many textual forms for
a canonical entity that may not be captured in the reference set, and entities
mentioned in text may include many syntactic variations, or errors. The problem
is particularly acute in scientific domains, such as biology. To address this
problem, we have developed a general, scalable solution based on a deep Siamese
neural network model to embed the semantic information about the entities, as
well as their syntactic variations. We use these embeddings for fast mapping of
new entities to large reference sets, and empirically show the effectiveness of
our framework in challenging bio-entity normalization datasets.


  The proton-dissociative diffractive photoproduction of J/psi mesons has been
studied in ep collisions with the ZEUS detector at HERA using an integrated
luminosity of 112 pb^-1. The cross section is presented as a function of the
photon-proton centre-of-mass energy and of the squared four-momentum transfer
at the proton vertex. The results are compared to perturbative QCD
calculations.


  With the unprecedented developments in deep learning, automatic segmentation
of main abdominal organs seems to be a solved problem as state-of-the-art
(SOTA) methods have achieved comparable results with inter-rater variability on
many benchmark datasets. However, most of the existing abdominal datasets only
contain single-center, single-phase, single-vendor, or single-disease cases,
and it is unclear whether the excellent performance can generalize on diverse
datasets. This paper presents a large and diverse abdominal CT organ
segmentation dataset, termed AbdomenCT-1K, with more than 1000 (1K) CT scans
from 12 medical centers, including multi-phase, multi-vendor, and multi-disease
cases. Furthermore, we conduct a large-scale study for liver, kidney, spleen,
and pancreas segmentation and reveal the unsolved segmentation problems of the
SOTA methods, such as the limited generalization ability on distinct medical
centers, phases, and unseen diseases. To advance the unsolved problems, we
further build four organ segmentation benchmarks for fully supervised,
semi-supervised, weakly supervised, and continual learning, which are currently
challenging and active research topics. Accordingly, we develop a simple and
effective method for each benchmark, which can be used as out-of-the-box
methods and strong baselines. We believe the AbdomenCT-1K dataset will promote
future in-depth research towards clinical applicable abdominal organ
segmentation methods. The datasets, codes, and trained models are publicly
available at https://github.com/JunMa11/AbdomenCT-1K.


  Data-structure dynamization is a general approach for making static data
structures dynamic. It is used extensively in geometric settings and in the
guise of so-called merge (or compaction) policies in big-data databases such as
Google Bigtable and LevelDB (our focus). Previous theoretical work is based on
worst-case analyses for uniform inputs -- insertions of one item at a time and
constant read rate. In practice, merge policies must not only handle batch
insertions and varying read/write ratios, they can take advantage of such
non-uniformity to reduce cost on a per-input basis.
  To model this, we initiate the study of data-structure dynamization through
the lens of competitive analysis, via two new online set-cover problems. For
each, the input is a sequence of disjoint sets of weighted items. The sets are
revealed one at a time. The algorithm must respond to each with a set cover
that covers all items revealed so far. It obtains the cover incrementally from
the previous cover by adding one or more sets and optionally removing existing
sets. For each new set the algorithm incurs build cost equal to the weight of
the items in the set. In the first problem the objective is to minimize total
build cost plus total query cost, where the algorithm incurs a query cost at
each time $t$ equal to the current cover size. In the second problem, the
objective is to minimize the build cost while keeping the query cost from
exceeding $k$ (a given parameter) at any time. We give deterministic online
algorithms for both variants, with competitive ratios of $\Theta(\log^* n)$ and
$k$, respectively. The latter ratio is optimal for the second variant.


  High-Voltage Monolithic Active Pixel Sensors (HV-MAPS) based on the 180 nm
HV-CMOS process have been proposed to realize thin, fast and highly integrated
pixel sensors. The MuPix7 prototype, fabricated in the commercial AMS H18
process, features a fully integrated on-chip readout, i.e. hit-digitization,
zero suppression and data serialization. It is the first fully monolithic
HV-CMOS pixel sensor that has been tested for the use in high irradiation
environments like HL-LHC. We present results from laboratory and test beam
measurements of MuPix7 prototypes irradiated with neutrons (up to
$5.0\cdot10^{15}{\,\rm{n}_{\rm{eq}}/cm^2}$) and protons (up to $7.8\cdot
10^{15} \,\rm{protons}/cm^2$) and compare the performance with non-irradiated
sensors. Efficiencies well above 90 % at noise rates below 200 Hz per pixel are
measured. A time resolution better than 22 ns is measured for all tested
settings and sensors, even at the highest irradiation fluences. The data
transmission at 1.25 Gbit/s and the on-chip PLL remain fully functional.


  Planet atmospheric escape induced by high-energy stellar irradiation is a key
phenomenon shaping the structure and evolution of planetary atmospheres.
Therefore, the present-day properties of a planetary atmosphere are intimately
connected with the amount of stellar flux received by a planet during its
lifetime, thus with the evolutionary path of its host star. Using a recently
developed analytic approximation based on hydrodynamic simulations for
atmospheric escape rates, we track within a Bayesian framework the evolution of
a planet as a function of stellar flux evolution history, constrained by the
measured planetary radius, with the other system parameters as priors. We find
that the ideal objects for this type of study are close-in sub-Neptune-like
planets, as they are highly affected by atmospheric escape, and yet retain a
significant fraction of their primordial hydrogen-dominated atmospheres.
Furthermore, we apply this analysis to the HD3167 and K2-32 planetary systems.
For HD3167, we find that the most probable irradiation level at 150 Myr was
between 40 and 130 times solar, corresponding to a rotation period of
1.78^{+2.69}_{-1.23} days. For K2-32, we find a surprisingly low irradiation
level ranging between half and four times solar at 150 Myr. Finally, we show
that for multi-planet systems, our framework enables one to constrain poorly
known properties of individual planets.


  We report an experiment that demonstrates full function of a quantum router
using entangled photons, where the paths of a single-photon pulse are
controlled in a coherent fashion by polarization of another single photon.
Through a projective measurement, we prepare the polarization of the control
photon in arbitrary superposition states, leading to coherent routing of the
target photon in quantum superposition of different paths. We demonstrate
quantum nature of this router through optical measurements based on quantum
state tomography and show an average fidelity of $(93.24\pm 0.23)%$ for the
quantum routing operation.


  At the Paul Scherrer Institut (PSI), we are currently working on the
development of a high-precision apparatus with the aim of searching for the
muon electric dipole moment (EDM) with unprecedented sensitivity. The
underpinning principle of this experiment is the frozen-spin technique, a
method that suppresses the spin precession due to the anomalous magnetic
moment, thereby enhancing the signal-to-noise ratio for EDM signals. This
increased sensitivity facilitates measurements that would be difficult to
achieve with conventional $g - 2$ muon storage rings. Given the availability of
the $p = 125$ MeV/$c$ muon beam at PSI, the anticipated statistical sensitivity
for the EDM after a year of data collection is $6\times 10^{-23}e\cdot$cm. To
achieve this goal, it is imperative to meticulously analyse and mitigate any
potential spurious effects that could mimic EDM signals. In this study, we
present a quantitative methodology to evaluate the systematic effects that
might arise in the context of employing the frozen-spin technique within a
compact storage ring. Our approach entails the analytical derivation of
equations governing the motion of the muon spin in the electromagnetic (EM)
fields intrinsic to the experimental setup, validated through subsequent
numerical simulations. We also illustrate a method to calculate the cumulative
geometric (Berry's) phase. This work complements ongoing experimental efforts
to detect a muon EDM at PSI and contributes to a broader understanding of
spin-precession systematic effects.


  Bohmian mechanics, a hydrodynamic formulation of the quantum theory,
constitutes a useful tool to understand the role of the phase as the mechanism
responsible for the dynamical evolution displayed by quantum systems. This role
is analyzed and discussed here in the context of quantum interference,
considering to this end two well-known scenarios, namely Young's two-slit
experiment and Wheeler's delayed choice experiment. A numerical implementation
of the first scenario is used to show how interference in a coherent
superposition of two counter-propagating wave packets can be seen and explained
in terms of an effective model consisting of a single wave packet scattered off
an attractive hard wall. The outcomes from this model are then applied to the
analysis of Wheeler's delayed choice experiment, also recreated by means of a
reliable realistic simulation. Both examples illustrate quite well how the
Bohmian formulation helps to explain in a natural way (and therefore to
demystify) aspects of the quantum theory typically regarded as paradoxical. In
other words, they show that a proper understanding of quantum phase dynamics
immediately removes any trace of unnecessary artificial wave-particle
arguments.


  In this paper, we propose a single-channel speech dereverberation system
(DeReGAT) based on convolutional, bidirectional long short-term memory and deep
feed-forward neural network (CBLDNN) with generative adversarial training
(GAT). In order to obtain better speech quality instead of only minimizing a
mean square error (MSE), GAT is employed to make the dereverberated speech
indistinguishable form the clean samples. Besides, our system can deal with
wide range reverberation and be well adapted to variant environments. The
experimental results show that the proposed model outperforms weighted
prediction error (WPE) and deep neural network-based systems. In addition,
DeReGAT is extended to an online speech dereverberation scenario, which reports
comparable performance with the offline case.


  Long short-term memory (LSTM) has been widely used for sequential data
modeling. Researchers have increased LSTM depth by stacking LSTM cells to
improve performance. This incurs model redundancy, increases run-time delay,
and makes the LSTMs more prone to overfitting. To address these problems, we
propose a hidden-layer LSTM (H-LSTM) that adds hidden layers to LSTM's original
one level non-linear control gates. H-LSTM increases accuracy while employing
fewer external stacked layers, thus reducing the number of parameters and
run-time latency significantly. We employ grow-and-prune (GP) training to
iteratively adjust the hidden layers through gradient-based growth and
magnitude-based pruning of connections. This learns both the weights and the
compact architecture of H-LSTM control gates. We have GP-trained H-LSTMs for
image captioning and speech recognition applications. For the NeuralTalk
architecture on the MSCOCO dataset, our three models reduce the number of
parameters by 38.7x [floating-point operations (FLOPs) by 45.5x], run-time
latency by 4.5x, and improve the CIDEr score by 2.6. For the DeepSpeech2
architecture on the AN4 dataset, our two models reduce the number of parameters
by 19.4x (FLOPs by 23.5x), run-time latency by 15.7%, and the word error rate
from 12.9% to 8.7%. Thus, GP-trained H-LSTMs can be seen to be compact, fast,
and accurate.


  With the great success of the T-product based real tensor methods in the
color image and gray video processing, the establishment of T-product based
quaternion tensor methods in the color video processing has encountered a
challenge, which is the block diagonalization of block circulant quaternion
matrices. In this paper, we show that the discrete Fourier matrix
$\mathbf{F_p}$ cannot diagonalize $p\times p$ circulant quaternion matrices,
nor can the unitary quaternion matrices $\mathbf{F_p}\mathbf{j}$ and
$\mathbf{F_p}(1+\mathbf{j})/\sqrt{2}$ with $\mathbf{j}$ being an imaginary unit
of quaternion algebra. Further, we establish sufficient and necessary
conditions for a unitary quaternion matrix being a diagonalization matrix of
circulant quaternion matrices, which shows that achieving the diagonalization
of circulant quaternion matrices in the quaternion domain is too hard. We turn
to the octonion domain for achieving the diagonalization of circulant
quaternion matrices. We prove that the unitary octonion matrix
$\mathbf{F_p}\mathbf{p}$ with $\mathbf{p}=\mathbf{l},\mathbf{il}$ or
$(\mathbf{l}+\mathbf{il})/\sqrt{2}$ can diagonalize a circulant quaternion
matrix of size $p\times p$, at the cost of $O(p\log p)$ via the fast Fourier
transform (FFT); and unitary matrices $\mathbf{F_p}\mathbf{p}\otimes
\mathbf{I_m}$ and $\mathbf{F_p}\mathbf{p}\otimes \mathbf{I_n}$ can block
diagonalize a block circulant quaternion matrix of size $mp\times np$, at the
cost of $O(mnp\log p)$ via the FFT. As a result, we propose a fast algorithm to
calculate the T-product between $m\times n\times p$ and $n\times s\times p$
third-order quaternion tensors via FFTs, at the cost of $O(mnsp)$, which is
almost $1/p$ of the computational magnitude of computing T-product by its
definition. Numerical calculations verify the correctness of the complexity
analysis.


  Fountain codes like LT or Raptor codes, also known as rateless erasure codes,
allow to encode a message as some number of packets, such that any large enough
subset of these packets is sufficient to fully reconstruct the message. It
requires undamaged packets, while the packets which were not lost are usually
damaged in real scenarios. Hence, an additional error correction layer is often
required: adding some level of redundancy to each packet to be able to repair
eventual damages. This approach requires a priori knowledge of the final damage
level of every packet - insufficient redundancy leads to packet loss,
overprotection means suboptimal channel rate. However, the sender may have
inaccurate or even no a priori information about the final damage levels, for
example in applications like broadcasting, degradation of a storage medium or
damage of picture watermarking.
  Joint Reconstruction Codes (JRC) setting is introduced and discussed in this
paper for the purpose of removing the need of a priori knowledge of damage
level and sub-optimality caused by overprotection and discarding underprotected
packets. It is obtained by combining both processes: reconstruction from
multiple packets and forward error correction. The decoder combines the
resultant informational content of all received packets accordingly to their
actual noise level, which can be estimated a posteriori individually for each
packet. Assuming binary symmetric channel (BSC) of $\epsilon$ bit-flip
probability, every potentially damaged bit carries
$R_0(\epsilon)=1-h_1(\epsilon)$ bits of information, where $h_1$ is the Shannon
entropy. The minimal requirement to fully reconstruct the message is that the
sum of rate $R_0(\epsilon)$ over all bits is at least the size of the message.
We will discuss sequential decoding for the reconstruction purpose, which
statistical behavior can be estimated using Renyi entropy.


  Developing quantum technologies requires the control and understanding of the
non-equilibrium dynamics of quantum information in many-body systems. Local
information propagates in the system by creating complex correlations known as
information scrambling, as this process prevents extracting the information
from local measurements. In this work, we develop a model adapted from
solid-state NMR methods, to quantify the information scrambling. The scrambling
is measured via time-reversal Loschmidt echoes (LE) and Multiple Quantum
Coherences experiments that intrinsically contain imperfections. Considering
these imperfections, we derive expressions for out-of-time-order correlators
(OTOCs) to quantify the observable information scrambling based on measuring
the number of active spins where the information was spread. Based on the OTOC
expressions, decoherence effects arise naturally by the effects of the
nonreverted terms in the LE experiment. Decoherence induces localization of the
measurable degree of information scrambling. These effects define a
localization cluster size for the observable number of active spins that
determines a dynamical equilibrium. We contrast the model's predictions with
quantum simulations performed with solid-state NMR experiments, that measure
the information scrambling with time-reversal echoes with controlled
imperfections. An excellent quantitative agreement is found with the dynamics
of quantum information scrambling and its localization effects determined from
the experimental data. The presented model and derived OTOCs set tools for
quantifying the quantum information dynamics of large quantum systems (more
than $10^{4}$ spins) consistent with experimental implementations that
intrinsically contain imperfections.


  Unbiased learning to rank (ULTR) aims to mitigate various biases existing in
user clicks, such as position bias, trust bias, presentation bias, and learn an
effective ranker. In this paper, we introduce our winning approach for the
"Unbiased Learning to Rank" task in WSDM Cup 2023. We find that the provided
data is severely biased so neural models trained directly with the top 10
results with click information are unsatisfactory. So we extract multiple
heuristic-based features for multi-fields of the results, adjust the click
labels, add true negatives, and re-weight the samples during model training.
Since the propensities learned by existing ULTR methods are not decreasing
w.r.t. positions, we also calibrate the propensities according to the click
ratios and ensemble the models trained in two different ways. Our method won
the 3rd prize with a DCG@10 score of 9.80, which is 1.1% worse than the 2nd and
25.3% higher than the 4th.


  Given an entire $C^2$ function $u$ on $\mathbb{R}^n$, we consider the graph
of $D u$ as a Lagrangian submanifold of $\mathbb{R}^{2n}$, and deform it by the
mean curvature flow in $\mathbb{R}^{2n}$. This leads to the special Lagrangian
evolution equation, a fully nonlinear Hessian type PDE. We prove long-time
existence and convergence results under a 2-positivity assumption of $(I+(D^2
u)^2)^{-1}D^2 u$. Such results were previously known only under the stronger
assumption of positivity of $D^2 u$.


  We investigate early dark energy models in the context of the lensing anomaly
by considering two different Cosmic Microwave Background (CMB) datasets: a
complete Planck, and a second one primarily based on SPTPol and Planck
temperature ($l<1000$). We contrast the effects of allowing the
phenomenological lensing amplitude ($\Al$) to be different from unity. We find
that the fraction of early dark energy, while not immediately affected by the
lensing anomaly, can induce mild deviations, through correlations with the
parameters $H_0$ and $S_8$. {We extend the analysis also by marginalizing the
Newtonian lensing potential, finding a $\gtrsim 1\sigma$ deviation, when
allowing for an amplitude rescaling and scale-dependence. Modeling the
rescaling of the theory lensing potential and the acoustic smoothing of the CMB
spectra, we find that only to a moderate level the anomaly can be addressed by
modifying the lensing signal itself and that an additional $\Al \sim 1.1$ at
$\sim 2\sigma$ significance should be addressed by pre-recombination physics.
Finally, we also comment on the lensing anomaly in a non-flat ($\Omega_{\rm k}
\neq 0$) scenario, finding that the late-time flatness of the universe is
robust and not correlated with the additional smoothing in the CMB spectra.


  Purely photometric models can be used to determine the binary parameters of
eclipsing cataclysmic variables with a high degree of precision. However, the
photometric method relies on a number of assumptions, and to date there have
been very few independent checks of this method in the literature. We present
time-resolved spectroscopy of the P=90.9 min eclipsing cataclysmic variable OY
Carinae obtained with X-shooter on the VLT, in which we detect the donor star
from K I lines in the J-band. We measure the radial velocity amplitude of the
donor star K2 = 470.0 +/- 2.7 km/s, consistent with predictions based upon the
photometric method (470 +/- 7 km/s). Additionally, the spectra obtained in the
UVB arm of X-shooter show a series of Fe I and Fe II lines with a phase and
velocity consistent with an origin in the accretion disc. This is the first
unambiguous detection at optical wavelengths of the `iron curtain' of disc
material which has been previously reported to veil the white dwarf in this
system. The velocities of these lines do not track the white dwarf, reflecting
a distortion of the outer disc that we see also in Doppler images. This is
evidence for considerable radial motion in the outer disk, at up to 90 km/s
towards and away from the white dwarf.


  We describe a new form of small-scale magnetic flux emergence in the quiet
Sun. This process seems to take vertical magnetic fields from the solar
interior to the photosphere, where they appear above granular convection cells.
High-cadence time series of spectropolarimetric measurements obtained by Hinode
in a quiet region near disk center are analyzed. We extract line parameters
from the observed Stokes profiles and study their evolution with time. The
circular polarization maps derived from the observed \ion{Fe}{i} 630 nm lines
show clear magnetic signals emerging at the center of granular cells. We do not
find any evidence for linear polarization signals associated with these events.
The magnetic flux patches grow with time, occupying a significant fraction of
the granular area. The signals then fade until they disappear completely. The
typical lifetime of these events is of the order of 20 minutes. No significant
changes in the chromosphere seem to occur in response to the emergence, as
revealed by co-spatial \ion{Ca}{ii} H filtergrams. The Stokes I and V profiles
measured in the emerging flux concentrations show strong asymmetries and
Doppler shifts. The origin of these events is unclear at present, but we
suggest that they may represent the emergence of vertical fields lines from the
bottom of the photosphere, possibly dragged by the convective upflows of
granules. Preliminary inversions of the Stokes spectra indicate that this
scenario is compatible with the observations. The emergence of vertical field
lines is not free from conceptual problems, though.


  Several implications of well-known fluctuation theorems, on the statistical
properties of the entropy production, are studied using various approaches. We
begin by deriving a tight lower bound on the variance of the entropy production
for a given mean of this random variable. It is shown that the Evans-Searles
fluctuation theorem alone imposes a significant lower bound on the variance
only when the mean entropy production is very small. It is then nonetheless
demonstrated that upon incorporating additional information concerning the
entropy production, this lower bound can be significantly improved, so as to
capture extensivity properties. Another important aspect of the fluctuation
properties of the entropy production is the relationship between the mean and
the variance, on the one hand, and the probability of the event where the
entropy production is negative, on the other hand. Accordingly, we derive upper
and lower bounds on this probability in terms of the mean and the variance.
These bounds are tighter than previous bounds that can be found in the
literature. Moreover, they are tight in the sense that there exist probability
distributions, satisfying the Evans-Searles fluctuation theorem, that achieve
them with equality. Finally, we present a general method for generating a wide
class of inequalities that must be satisfied by the entropy production. We use
this method to derive several new inequalities which go beyond the standard
derivation of the second law.


  We present a novel method to search for structures of coherently aligned
patterns in ultra-high energy cosmic-ray arrival directions simultaneously
across the entire sky. This method can be used to obtain information on the
Galactic magnetic field, in particular the integrated component perpendicular
to the line of sight, from cosmic-ray data only. Using a likelihood-ratio
approach, neighboring cosmic rays are related by rotatable, elliptically shaped
density distributions and the significance of their alignment with respect to
circular distributions is evaluated. In this way, a vector field tangential to
the celestial sphere is fitted which approximates the local deflections in
cosmic magnetic fields if significant deflection structures are detected. The
sensitivity of the method is evaluated on the basis of astrophysical
simulations of the ultra-high energy cosmic-ray sky, where a discriminative
power between isotropic and signal-induced scenarios is found.


  Given a simple vertex algebra A and a reductive group G of automorphisms of
A, the invariant subalgebra A^G is strongly finitely generated in most examples
where its structure is known. This phenomenon is subtle, and is generally not
true of the classical limit of A^G, which often requires infinitely many
generators and infinitely many relations to describe. Using tools from
classical invariant theory, together with recent results on the structure of
the W_{1+\infty} algebra, we establish the strong finite generation of a large
family of invariant subalgebras of \beta\gamma-systems, bc-systems, and
bc\beta\gamma-systems.


  This paper examines the completion of an w-ordered sequence of recursive
definitions which on the one hand defines an increasing sequence of nested set
and on the other redefines successively a numeric variable as the cardinal of
the successively defined nested sets. The consequence is a contradiction
involving the consistency of w-order and then that of the Axiom of Infinity.


  We quantize the electromagnetic field in the presence of a static magnetic
monopole, within the loop-representation formalism. We find that the
loop-dependent wave functional becomes multivalued, in the sense that it
acquires a dependence on the surfaces bounded by the loop. This generalizes
what occurs in quantum mechanics in multiply connected spaces. When Dirac's
quantization condition holds, this surface-dependence disappears, together with
the effect of the monopole on the electromagnetic field.


  We have observed a narrow state near 2.32 GeV/c^2 in the inclusive Ds+ pi0
invariant mass distributionfrom e+e- annihilation data at energies near 10.6
GeV. The observed width is consistent with the experimental resolution. The
small intrinsic width and the quantum numbers of the final state indicate that
the decay violates isospin conservation. The state has natural spin-parity and
the low mass suggests a JP=0+ assignment. The data sample corresponds to an
integrated luminosity of 91 fb-1 recorded by the BABAR detector at the PEP2
asymmetric-energy e+e- storage ring.


  This paper summarizes our experience in teaching courses on formal methods
(FM) to Computer Science (CS) and Software Engineering (SE) students at various
universities around the world, including University of Madeira (UMa) in
Portugal, Pontificia Universidad Javeriana (PUJ) and University of Los Andes
(Uniandes) in Colombia, Carnegie Mellon University (CMU) in the USA, and at
Innopolis University (INNO) in the Russian Federation. We report challenges
faced during the past 10 to 15 years to teach FM to millennials undergradu- ate
and graduate students and describe how we have coped with those challenges. We
formulate a characterization of millennials, based on our experience, and show
how this characterization has shaped our decisions in terms of course structure
and content. We show how these decisions are reflected on the current structure
of the MSS (Models of Software Systems) course that currently runs as part of
the MSIT-SE (Master of Science in Information Technology - Software
Engineering) programme offered at INNO. We have conducted two surveys among
students, the first one at CMU and the second one at INNO that we have used to
document and justify our decisions. The first survey is about the choice of
Event-B as mathematical formalism and the second one is about the organization
of teams of students within the classroom to work on software projects based on
Event-B.


  The concept of Smarandache Bryant Schneider Group of a Smarandache loop is
introduced. Relationship(s) between the Bryant Schneider Group and the
Smarandache Bryant Schneider Group of an S-loop are discovered and the later is
found to be useful in finding Smarandache isotopy-isomorphy condition(s) in
S-loops just like the formal is useful in finding isotopy-isomorphy
condition(s) in loops. Some properties of the Bryant Schneider Group of a loop
are shown to be true for the Smarandache Bryant Schneider Group of a
Smarandache loop. Some interesting and useful cardinality formulas are also
established for a type of finite Smarandache loop.


  Pedestrian trajectory prediction is a key technology in autopilot, which
remains to be very challenging due to complex interactions between pedestrians.
However, previous works based on dense undirected interaction suffer from
modeling superfluous interactions and neglect of trajectory motion tendency,
and thus inevitably result in a considerable deviance from the reality. To cope
with these issues, we present a Sparse Graph Convolution Network~(SGCN) for
pedestrian trajectory prediction. Specifically, the SGCN explicitly models the
sparse directed interaction with a sparse directed spatial graph to capture
adaptive interaction pedestrians. Meanwhile, we use a sparse directed temporal
graph to model the motion tendency, thus to facilitate the prediction based on
the observed direction. Finally, parameters of a bi-Gaussian distribution for
trajectory prediction are estimated by fusing the above two sparse graphs. We
evaluate our proposed method on the ETH and UCY datasets, and the experimental
results show our method outperforms comparative state-of-the-art methods by 9%
in Average Displacement Error(ADE) and 13% in Final Displacement Error(FDE).
Notably, visualizations indicate that our method can capture adaptive
interactions between pedestrians and their effective motion tendencies.


  The geometric arrangement of interacting (magnetic) dipoles is a question of
fundamental importance in physics, chemistry and engineering. Motivated by
recent progress concerning the self-assembly of magnetic structures, the
equilibrium orientation of 8 interacting dipoles in a cubic cluster is
investigated in detail. Instead of discrete equilibria we find a new type of
ground state consisting of infinitely many orientations. This continuum of
energetically degenerate states represents a yet unknown form of magnetic
frustration. The corresponding dipole rotations in the flat potential valley of
this Goldstone mode enable the construction of frictionless magnetic couplings.
Using novel computer-assisted algebraic geometry methods, we moreover
completely enumerate all equilibrium configurations. The seemingly simple cubic
system allows for exactly 9536 unstable discrete equilibria falling into 183
distinct energy families.


  The method of the quasiclassical Green's function is used to determine the
equilibrium properties of one-dimensional (1D) interacting Fermi systems, in
particular, the bulk and the local (near a hard wall) density of states. While
this is a novel approach to 1D systems, our findings do agree with standard
results for Luttinger liquids obtained with the bosonization method. Analogies
to the so-called $P(E)$ theory of tunneling through ultrasmall junctions are
pointed out and are exploited. Further applications of the Green's function
method for 1D systems are discussed.


  So far there exist just a few results about the uniqueness of maximal
immediate valued differential field extensions and about the relationship
between differential-algebraic maximality and differential-henselianity; see
arXiv:1509.02588, Chapter 7. We remove here the assumption of monotonicity in
these results but replace it with the assumption that the value group is the
union of its convex subgroups of finite (archimedean) rank. We also show the
existence and uniqueness of differential-henselizations of asymptotic fields
with such a value group.


  In this paper, we seek lower bounds of the dyadic Hilbert transform (Haar
shift) of the form $\left\Vert S f\right\Vert_{L^2(K)}\geq C(I,K)\left\Vert
f\right\Vert_{L^2(I)}$ where $I$ and $K$ are two dyadic intervals and $f$
supported in $I$. If $I\subset K$ such bound exist while in the other cases
$K\subsetneq I$ and $K\cap I=\emptyset$ such bounds are only available under
additional constraints on the derivative of $f$. In the later case, we
establish a bound of the form $\left\Vert S f\right\Vert_{L^2(K)}\geq
C(I,K)|\left\langle f\right\rangle_I|$ where $\left\langle f\right\rangle_I$ is
the mean of $f$ over $I$. This sheds new light on the similar problem for the
usual Hilbert transform that we exploit.


  Hard X-ray observations are crucial to study the non-thermal jet emission
from high-redshift, powerful blazars. We observed two bright z>2 flat spectrum
radio quasars (FSRQs) in hard X-rays to explore the details of their
relativistic jets and their possible variability. S5 0014+81 (at z=3.366) and
B0222+185 (at z=2.690) have been observed twice by the Nuclear Spectroscopic
Telescope Array (NuSTAR) simultaneously with Swift/XRT, showing different
variability behaviours. We found that NuSTAR is instrumental to explore the
variability of powerful high-redshift blazars, even when no gamma-ray emission
is detected. The two sources have proven to have respectively the most luminous
accretion disk and the most powerful jet among known blazars. Thanks to these
properties, they are located at the extreme end of the jet-accretion disk
relation previously found for gamma-ray detected blazars, to which they are
consistent.


  The topology of production networks determines the propagation mechanisms of
local shocks and thus the co-movement of industries. As a result, we need a
more precisely defined production network to model economic growth accurately.
In this study, we analyse Leontief's input-output model from a network theory
perspective, aiming to construct a production network in such a way that it
allows the most accurate modelling of the propagation mechanisms of changes
that generate industry growth. We do this by revisiting a prevalent threshold
in the literature that determines industry-industry interdependence. Our
hypothesis is that changing the threshold changes the topological structure of
the network and the core industries to a large extent. This is significant,
because if the production network topology is not precisely defined, the
resulting internal propagation mechanisms will be distorted, and thus industry
growth modelling will not be accurate. We prove our hypothesis by examining the
network topology, and centrality metrics under different thresholds on a
network derived from the US input-output accounts data for 2007 and 2012.


  In electronics systems, the Weyl points can be classified into three types
based on the geometry of the Fermi surface, and each type exhibits various
unique and intriguing phenomena. While the type-I and type-II Weyl points have
been achieved in both spinful and spinless systems, the realization of type-III
Weyl points remains challenging, and has not been reported in artificial
periodic systems. Here, we for the first time report the experimental
observation of the type-III Weyl points in a sonic crystal. Remarkably, a
single pair of type-III Weyl points are observed as the only band crossings in
a frequency range, experimentally disproving a common belief in the field,
namely, the minimal number of Weyl points in nonmagnetic systems is four. The
consistency between experimental results and theoretical predictions confirms
the existence of type-III Weyl points, noncontractible Fermi arc surface
states, and chiral edge states. Our work not only fill the gap of the type-III
Weyl point in sonic crystal but also stimulate related researches in other
systems, such as photonic, mechanical and cold atom systems.


  We report a comprehensive angle-resolved photoemission spectroscopy study of
the tridimensional electronic bands in the recently discovered Fe selenide
superconductor (Tl,Rb)$_y$Fe$_{2-x}$Se$_2$ ($T_c=32$ K). We determined the
orbital characters and the $k_z$ dependence of the low energy electronic
structure by tuning the polarization and the energy of the incident photons. We
observed a small 3D electron Fermi surface pocket near the Brillouin zone
center and a 2D like electron Fermi surface pocket near the zone boundary. The
photon energy dependence, the polarization analysis and the local-density
approximation calculations suggest a significant contribution from the Se
4$p_z$ and Fe 3$d_{xy}$ orbitals to the small electron pocket. We argue that
the emergence of Se 4$p_z$ states might be the cause of the different magnetic
properties between Fe chalcogenides and Fe pnictides.


  We present recent results of the TELAMON program, which is using the
Effelsberg 100-m telescope to monitor the radio spectra of active galactic
nuclei (AGN) under scrutiny in astroparticle physics, namely TeV blazars and
neutrino-associated AGN. Our sample includes all known Northern TeV-emitting
blazars as well as blazars positionally coincident with IceCube neutrino
alerts. Polarization can give additional insight into the source properties, as
the polarized emission is often found to vary on different timescales and
amplitudes than the total intensity emission. Here, we present an overview of
the polarization properties of the TeV-emitting TELAMON sources at four
frequencies in the 20 mm and 7 mm bands. While at 7 mm roughly $82\,\%$ of all
observed sources are found to be significantly polarized, for 20 mm the
percentage is $\sim58\,\%$. We find that most of the sources exhibit mean
fractional polarizations of $<5\%$, matching the expectations of rather low
polarization levels in these sources from previous studies at lower radio
frequencies. Nevertheless, we demonstrate examples of how the polarized
emission can provide additional information over the total intensity.


  We calculate the hybrid entanglement entropy between coin and walker degrees
of freedom in a non-unitary quantum walk. The model possesses a joint parity
and time-reversal symmetry or PT-symmetry and supports topological phases when
this symmetry is unbroken by its eigenstates. An asymptotic analysis at long
times reveals that the quantum walk can indefinitely sustain hybrid
entanglement in the unbroken symmetry phase even when gain and loss mechanisms
are present. However, when the gain-loss strength is too large, the PT-symmetry
of the model is spontaneously broken and entanglement vanishes. The
entanglement entropy is therefore an effective and robust parameter for
constructing PT-symmetry and topological phase diagrams in this non-unitary
dynamical system.


  The neutrino mass hierarchy, i.e., whether the $\nu_3$ neutrino mass
eigenstate is heavier or lighter than the $\nu_1$ and $\nu_2$ mass eigenstates,
is one of the remaining undetermined fundamental features of the neutrino
Standard Model. Its determination would represent an important step in the
formulation of the generalized model, and would have a profound impact on the
quest of the nature of neutrinos (Dirac or Majorana) and the search for a
theory of flavor. In this review, we summarize the status of experimental and
theoretical work in this field and explore the future opportunities that emerge
in light of the recently discovered non-zero and relatively large third
neutrino mixing angle $\theta_{13}$.


  We observe the process $\psi(3686) \to p \bar{p} \eta^{\prime}$ for the first
time, with a statistical significance higher than 10$\sigma$, and measure the
branching fraction of $J/\psi \to p \bar{p} \eta^{\prime}$ with an improved
accuracy compared to earlier studies. The measurements are based on $4.48
\times 10^8$ $\psi(3686)$ and $1.31 \times 10^{9}$ $J/\psi$ events collected by
the BESIII detector operating at the BEPCII. The branching fractions are
determined to be $B(\psi(3686) \to p \bar{p} \eta^{\prime}) =
(1.10\pm0.10\pm0.08)\times10^{-5}$ and $B(J/\psi \to p \bar{p}
\eta^{\prime})=(1.26\pm0.02\pm 0.07)\times10^{-4}$, where the first
uncertainties are statistical and the second ones systematic. Additionally, the
$\eta-\eta^{\prime}$ mixing angle is determined to be $-24^{\circ} \pm
11^{\circ}$ based on $\psi(3686) \to p \bar{p} \eta^{\prime}$, and $-24^{\circ}
\pm 9^{\circ}$ based on $J/\psi \to p \bar{p} \eta^{\prime}$, respectively.


  The effective mass approximation (EMA) could be an efficient method for the
computational study of semiconductor nanostructures with sizes too large to be
handled by first-principles calculations, but the scheme to accurately and
reliably introduce EMA parameters for given nanostructures remains to be
devised. Herein, we report on an EMA approach based on first-principles-derived
data, which enables accurate predictions of the optoelectronic properties of
quantum nanostructures. For the CdS/ZnS core/shell quantum rods, for which we
recently reported its experimental synthesis, we first carry out density
functional theory (DFT) calculations for an infinite nanowire to obtain the
nanoscopic dielectric constant, effective mass, and Kohn-Sham potential. The
DFT-derived data are then transferred to the finite nanorod cases to set up the
EMA equations, from which we estimate the photoluminescence (PL)
characteristics. Compared with the corresponding method based on bulk EMA
parameters and abrupt potential, we confirm that our EMA approach more
accurately describes the PL properties of nanorods. We find that, in agreement
with the experimentally observed trends, the optical gap of nanorods is roughly
determined by the nanorod diameter and the PL intensity is reduced with
increasing the nanorod length. The developed methodology is additionally
applied to CdSe nanoplatelets, where reliable experimental data became recently
available. Here, we again obtain excellent agreements between calculated and
measured optical gap values, confirming the generality of our approach. It is
finally shown that the abrupt confinement potential approximation most
adversely affects the accuracy of EMA simulations.


  We investigate quantum dots in clean single-wall carbon nanotubes with
ferromagnetic PdNi-leads in the Kondo regime. In most odd Coulomb valleys the
Kondo resonance exhibits a pronounced splitting, which depends on the tunnel
coupling to the leads and an external magnetic field $B$, and only weakly on
gate voltage. Using numerical renormalization group calculations, we
demonstrate that all salient features of the data can be understood using a
simple model for the magnetic properties of the leads. The magnetoconductance
at zero bias and low temperature depends in a universal way on $g \mu_B (B-B_c)
/ k_B T_K$, where $T_K$ is the Kondo temperature and $B_c$ the external field
compensating the splitting.


  The thermoelectric power of the two-dimensional electron system (2DES) at the
LaAlO3/SrTiO3 interface is explored below room temperature, in comparison with
that of Nb-doped SrTiO3 single crystals. For the interface we find a region
below T =50 K where thermopower is dominated by phonon-drag, whose amplitude is
hugely amplified with respect to the corresponding bulk value, reaching values
~mV/K and above. The phonon-drag enhancement at the interface is traced back to
the tight carrier confinement of the 2DES, and represents a sharp signature of
strong electron-acoustic phonon coupling at the interface.


  Diffferentially rotating stars can support significantly more mass in
equilibrium than nonrotating or uniformly rotating stars, according to general
relativity. The remnant of a binary neutron star merger may give rise to such a
``hypermassive'' object. While such a star may be dynamically stable against
gravitational collapse and bar formation, the radial stabilization due to
differential rotation is likely to be temporary. Magnetic braking and viscosity
combine to drive the star to uniform rotation, even if the seed magnetic field
and the viscosity are small. This process inevitably leads to delayed collapse,
which will be accompanied by a delayed gravitational wave burst and, possibly,
a gamma-ray burst. We provide a simple, Newtonian, MHD calculation of the
braking of differential rotation by magnetic fields and viscosity. The star is
idealized as a differentially rotating, infinite cylinder consisting of a
homogeneous, incompressible conducting gas. We solve analytically the simplest
case in which the gas has no viscosity and the star resides in an exterior
vacuum. We treat numerically cases in which the gas has internal viscosity and
the star is embedded in an exterior, low-density, conducting medium. Our
evolution calculations are presented to stimulate more realistic MHD
simulations in full 3+1 general relativity. They serve to identify some of the
key physical and numerical parameters, scaling behavior and competing
timescales that characterize this important process.


  We show that all Sugihara monoids can be represented as algebras of binary
relations, with the monoid operation given by relational composition. Moreover,
the binary relations are weakening relations. The first step is to obtain an
explicit relational representation of all finite odd Sugihara chains. Our
construction mimics that of Maddux (2010), where a relational representation of
the finite even Sugihara chains is given. We define the class of representable
Sugihara monoids as those which can be represented as reducts of distributive
involutive FL-algebras of binary relations. We then show that the class of
representable distributive involutive FL-algebras is closed under
ultraproducts. This fact is used to demonstrate that the two infinite Sugihara
monoids that generate the quasivariety are also representable. From this it
follows that all Sugihara monoids are representable.


  5G will enable and greatly accelerate digital transformation of vertical
sectors. In the longer term this will evolve from per-vertical connectivity
services in 5G to the emergence of the 6G-enabled Internet of Verticals
(6G-IoV). In this paper we describe and examine enabling technologies for this
further transformation of verticals and examine some examples of 6G-IoV, next
generation cloud manufacturing and manufacturing as a service, next generation
smart energy grids and the Internet of Robotics (IoR).


  We provide precise constraints on the size of any black holes forming in the
early Universe for a variety of formation scenarios. In particular, we prove
that the size of the apparent horizon of a primordial black hole formed by
causal processes in a flat Friedmann universe is considerably smaller than the
cosmological apparent horizon size for an equation of state $p=k\rho$
($1/3<k<1$). This also applies for a stiff equation of state ($k=1$) or for a
massless scalar field. The apparent horizon of a primordial black hole formed
through hydrodynamical processes is also considerably smaller than the
cosmological apparent horizon for $0<k\le 1$. We derive an expression for the
maximum size which an overdense region can have without being a separate closed
universe rather than part of our own. Newtonian argument shows that a black
hole smaller than the cosmological horizon can never accrete much.


  The Fisher information metric or the Fisher-Rao metric corresponds to a
natural Riemannian metric defined on a parameterized family of probability
density functions. As in the case of Riemannian geometry, we can define a
distance in terms of the Fisher information metric, called the Fisher-Rao
distance. The Fisher information metric has a wide range of applications in
estimation and information theories. Indeed, it provides the most informative
Cramer-Rao bound for an unbiased estimator. The Goldberg conjecture is a
well-known unsolved problem which states that any compact Einstein almost
K\"ahler manifold is necessarily a K\"ahler-Einstein. Note that, there is also
a known odd-dimensional analog of the Goldberg conjecture in the literature.
The main objective of this paper is to establish a new characterization of
coK\"ahler manifolds and K\"ahler manifolds; our characterization is
statistical in nature. Finally, we corroborate that every, K\"ahler and
co-K\"ahler manifolds, can be viewed as being a parametric family of
probability density functions, whereas K\"ahler and coK\"ahler metrics can be
regarded as Fisher information metrics. In particular, we prove that, when the
K\"ahler metric is real analytic, it is always locally the Fisher information
of an exponential family. We also tackle the link between K\"ahler potential
and Kullback-Leibler divergence.


  In the random hypergraph H=H(n,p;3) each possible triple appears
independently with probability p. A loose Hamilton cycle can be described as a
sequence of edges {x_i,y_i,x_{i+1}\} for i=1,2,...,n/2. We prove that there
exists an absolute constant K>0 such that if p>K\log n/n^2 then lim_{n->oo 4
|n}}Pr(H(n,p;3) contains a loose Hamilton cycle)=1.


  We examine the behaviour of the pseudo-marginal random walk Metropolis
algorithm, where evaluations of the target density for the accept/reject
probability are estimated rather than computed precisely. Under relatively
general conditions on the target distribution, we obtain limiting formulae for
the acceptance rate and for the expected squared jump distance, as the
dimension of the target approaches infinity, under the assumption that the
noise in the estimate of the log-target is additive and is independent of the
position. For targets with independent and identically distributed components,
we also obtain a limiting diffusion for the first component. We then consider
the overall efficiency of the algorithm, in terms of both speed of mixing and
computational time. Assuming the additive noise is Gaussian and is inversely
proportional to the number of unbiased estimates that are used, we prove that
the algorithm is optimally efficient when the variance of the noise is
approximately 3.283 and the acceptance rate is approximately 7.001%. We also
find that the optimal scaling is insensitive to the noise and that the optimal
variance of the noise is insensitive to the scaling. The theory is illustrated
with a simulation study using the particle marginal random walk Metropolis.


  This work provides a general overview for the treatment of symmetries in
classical field theories and (pre)multisymplectic geometry. The geometric
characteristics of the relation between how symmetries are interpreted in
theoretical physics and in the geometric formulation of these theories are
clarified. Finally, a general discussion is given on the structure of
symmetries in the presence of constraints appearing in singular field theories.
Symmetries of some typical theories in theoretical physics are analyzed through
the construction of the relevant multimomentum maps which are the conserved
quantities (by Noether's theorem) on the (pre)multisymplectic phase spaces.


  Efficient scheduling of distributed deep learning (DL) jobs in large GPU
clusters is crucial for resource efficiency and job performance. While server
sharing among jobs improves resource utilization, interference among co-located
DL jobs occurs due to resource contention. Interference-aware job placement has
been studied, with white-box approaches based on explicit interference modeling
and black-box schedulers with reinforcement learning. In today's clusters
containing thousands of GPU servers, running a single scheduler to manage all
arrival jobs in a timely and effective manner is challenging, due to the large
workload scale. We adopt multiple schedulers in a large-scale cluster/data
center, and propose a multi-agent reinforcement learning (MARL) scheduling
framework to cooperatively learn fine-grained job placement policies, towards
the objective of minimizing job completion time (JCT). To achieve
topology-aware placements, our proposed framework uses hierarchical graph
neural networks to encode the data center topology and server architecture. In
view of a common lack of precise reward samples corresponding to different
placements, a job interference model is further devised to predict interference
levels in face of various co-locations, for training of the MARL schedulers.
Testbed and trace-driven evaluations show that our scheduler framework
outperforms representative scheduling schemes by more than 20% in terms of
average JCT, and is adaptive to various machine learning cluster topologies.


  In this note, we prove that for every $0<\sigma<1$, there exists a smooth
complete hypersurface $\Sigma$ in $\mathbb{H}^{n+1}$ with prescribed asymptotic
boundary $\partial \Sigma=\Gamma$ at infinity, whose principal curvatures
$\kappa=(\kappa_1,\ldots,\kappa_n)$ lie in a general cone $K$ and satisfy
$f(\kappa)=\sigma$ at each point of $\Sigma$. Previously, the problem has been
studied by Guan-Spruck in [J. Eur. Math. Soc. (JEMS) 12 (2010), no. 3,
797-817], and they proved the existence result for $\sigma \in (\sigma_0,1)$,
where $\sigma_0>0$. A major ingredient of our proof is a refined curvature
estimate of theirs that is applicable when the curvature function $f(\kappa)$
has controllable partial derivatives, but it is adequate for our purpose;
specifically, we solve the problem for $f=H_{k}/H_{k-1}$ in the $k$-th Garding
cone where $H_k$ is the normalized $k$-th elementary symmetric polynomial and
$1 \leq k \leq n$.


  Neural network architectures for image demosaicing have been become more and
more complex. This results in long training periods of such deep networks and
the size of the networks is huge. These two factors prevent practical
implementation and usage of the networks in real-time platforms, which
generally only have limited resources. This study investigates the
effectiveness of neural network architectures in hyperspectral image
demosaicing. We introduce a range of network models and modifications, and
compare them with classical interpolation methods and existing reference
network approaches. The aim is to identify robust and efficient performing
network architectures. Our evaluation is conducted on two datasets,
"SimpleData" and "SimRealData," representing different degrees of realism in
multispectral filter array (MSFA) data. The results indicate that our networks
outperform or match reference models in both datasets demonstrating exceptional
performance. Notably, our approach focuses on achieving correct spectral
reconstruction rather than just visual appeal, and this emphasis is supported
by quantitative and qualitative assessments. Furthermore, our findings suggest
that efficient demosaicing solutions, which require fewer parameters, are
essential for practical applications. This research contributes valuable
insights into hyperspectral imaging and its potential applications in various
fields, including medical imaging.


  We show that simple laser configurations can give rise to "optical flux
lattices", in which optically dressed atoms experience a periodic effective
magnetic flux with high mean density. These potentials lead to narrow energy
bands with non-zero Chern number. Optical flux lattices will greatly facilitate
the achievement of the quantum Hall regime for ultracold atomic gases.


  Locality is a fundamental principle used extensively in program and system
optimization. It can be measured in many ways. This paper formalizes the
metrics of locality into a measurement theory. The new theory includes the
precise definition of locality metrics based on access frequency, reuse time,
reuse distance, working set, footprint, and the cache miss ratio. It gives the
formal relation between these definitions and the proofs of equivalence or
non-equivalence. It provides the theoretical justification for four successful
locality models in operating systems, programming languages, and computer
architectures which were developed empirically.


  We construct a class of simple and calculable theories for the supersymmetry
breaking soft terms. They are based on quantum modified moduli spaces. These
theories do not break supersymmetry in their ground state; instead we postulate
that we live in a supersymmetry breaking plateau of false vacua. We demonstrate
that tunneling from the plateau to the supersymmetric ground state is highly
supressed. At one loop, the plateau develops a local minimum which can be
anywhere between $10^8$ GeV and the grand unification scale. The value of this
minimum is the mass of the messengers of supersymmetry breaking. Primordial
element abundances indicate that the messengers' mass is smaller than $10^{12}$
GeV.


  Feedforward control can greatly improve the response time and control
accuracy of any mechatronic system. However, in order to compensate for the
effects of modeling errors or disturbances, it is imperative that this type of
control works in conjunction with some form of feedback. In this paper, we
present a new adaptive feedforward control scheme for electromechanical systems
in which real-time measurements or estimates of the position and its
derivatives are not technically or economically feasible. This is the case, for
example, of commercial electromechanical switching devices such as solenoid
actuators. Our proposal consists of two blocks: on the one hand, a feedforward
controller based on differential flatness theory; on the other, an iterative
adaptation law that exploits the repetitive operation of these devices to
modify the controller parameters cycle by cycle. As shown, this law can be fed
with any available measurement of the system, with the only requirement that it
can be processed and converted into an indicator of the performance of any
given operation. Simulated and experimental results show that our proposal is
effective in dealing with a long-standing control problem in electromechanics:
the soft-landing control of electromechanical switching devices.


  Fair division is a significant, long-standing problem and is closely related
to social and economic justice. The conventional division methods such as
cut-and-choose are hardly applicable to realworld problems because of their
complexity and unrealistic assumptions about human behaviors. Here we propose a
fair division method from a completely different perspective, using the
Boltzmann distribution. The Boltzmann distribution adopted from the physical
sciences gives the most probable and unbiased distribution derived from a
goods-centric, rather than a player-centric, division process. The mathematical
model of the Boltzmann fair division was developed for both homogeneous and
heterogeneous division problems, and the players' key factors (contributions,
needs, and preferences) could be successfully integrated. We show that the
Boltzmann fair division is a well-balanced division method maximizing the
players' total utility, and it could be easily finetuned and applicable to
complex real-world problems such as income/wealth redistribution or
international negotiations on fighting climate change.


  By mixing glass beads with a curable polymer we create a well-defined
cohesive granular medium, held together by solidified, and hence elastic,
capillary bridges. This material has a geometry similar to a wet packing of
beads, but with an additional control over the elasticity of the bonds holding
the particles together. We show that its mechanical response can be varied over
several orders of magnitude by adjusting the size and stiffness of the bridges,
and the size of the particles. We also investigate its mechanism of failure
under unconfined uniaxial compression in combination with in situ x-ray
microtomography. We show that a broad linear-elastic regime ends at a limiting
strain of about 8%, whatever the stiffness of the agglomerate, which
corresponds to the beginning of shear failure. The possibility to finely tune
the stiffness, size and shape of this simple material makes it an ideal model
system for investigations on, for example, fracturing of porous rocks,
seismology, or root growth in cohesive porous media.


  Observations of debris disks offer a window into the physical and dynamical
properties of planetesimals in extrasolar systems through the size distribution
of dust grains. In particular, the millimeter spectral index of thermal dust
emission encodes information on the grain size distribution. We have made new
VLA observations of a sample of seven nearby debris disks at 9 mm, with 3"
resolution and $\sim5$ $\mu$Jy/beam rms. We combine these with archival ATCA
observations of eight additional debris disks observed at 7 mm, together with
up-to-date observations of all disks at (sub)millimeter wavelengths from the
literature to place tight constraints on the millimeter spectral indices and
thus grain size distributions. The analysis gives a weighted mean for the slope
of the power law grain size distribution, $n(a)\propto a^{-q}$, of $\langle q
\rangle = 3.36\pm0.02$, with a possible trend of decreasing $q$ for later
spectral type stars. We compare our results to a range of theoretical models of
collisional cascades, from the standard self-similar, steady-state size
distribution ($q=3.5$) to solutions that incorporate more realistic physics
such as alternative velocity distributions and material strengths, the
possibility of a cutoff at small dust sizes from radiation pressure, as well as
results from detailed dynamical calculations of specific disks. Such effects
can lead to size distributions consistent with the data, and plausibly the
observed scatter in spectral indices. For the AU Mic system, the VLA
observations show clear evidence of a highly variable stellar emission
component; this stellar activity obviates the need to invoke the presence of an
asteroid belt to explain the previously reported compact millimeter source in
this system.


  In this article, we propose a Lyapunov stability approach to analyze the
convergence of the density operator of a quantum system. In contrast to many
previously studied convergence analysis methods for invariant density operators
which use weak convergence, in this article we analyze the convergence of
density operators by considering the set of density operators as a subset of
Banach space. We show that the set of invariant density operators is both
closed and convex, which implies the impossibility of having multiple isolated
invariant density operators. We then show how to analyze the stability of this
set via a candidate Lyapunov operator.


  We study the question of whether two frames of a given physical theory are
equivalent or not in the presence of quantum corrections. By using field theory
arguments we claim that equivalence is broken in the presence of anomalous
symmetries in one of the frames. This is particularized to the case of the
relation between the Einstein and Jordan frames in scalar-tensor theories used
to describe early Universe dynamics. Although in this case a regularization
that cancels the anomaly exists, the renormalized theory always develop a
non-vanishing contribution to the S-matrix that is present only in the Jordan
frame, promoting the different frames to different physical theories that must
be UV completed in a different way.


  All industries are trying to leverage Artificial Intelligence (AI) based on
their existing big data which is available in so called tabular form, where
each record is composed of a number of heterogeneous continuous and categorical
columns also known as features. Deep Learning (DL) has constituted a major
breakthrough for AI in fields related to human skills like natural language
processing, but its applicability to tabular data has been more challenging.
More classical Machine Learning (ML) models like tree-based ensemble ones
usually perform better. This paper presents a novel DL model using Graph Neural
Network (GNN) more specifically Interaction Network (IN), for contextual
embedding and modelling interactions among tabular features. Its results
outperform those of a recently published survey with DL benchmark based on five
public datasets, also achieving competitive results when compared to
boosted-tree solutions.


  The usual inflationary scenario predicts a Gaussian random primordial density
fluctuation, different Fourier modes of which do not correlate with each other.
In this paper we propose a correlation between these different modes. A simple
case is that these different Fourier modes correlate with each other following
a Gaussian function. For such a primordial density fluctuation we calculate the
CMB angular power spectrum and find that its amplitude decreases but the
decrease is different for different $l$. This feature can be used to constrain
the the correlation strength from the real data.


  Among all the sub-sections in a typical radiology report, the Clinical
Indications, Findings, and Impression often reflect important details about the
health status of a patient. The information included in Impression is also
often covered in Findings. While Findings and Impression can be deduced by
inspecting the image, Clinical Indications often require additional context.
The cognitive task of interpreting medical images remains the most critical and
often time-consuming step in the radiology workflow. Instead of generating an
end-to-end radiology report, in this paper, we focus on generating the Findings
from automated interpretation of medical images, specifically chest X-rays
(CXRs). Thus, this work focuses on reducing the workload of radiologists who
spend most of their time either writing or narrating the Findings. Unlike past
research, which addresses radiology report generation as a single-step image
captioning task, we have further taken into consideration the complexity of
interpreting CXR images and propose a two-step approach: (a) detecting the
regions with abnormalities in the image, and (b) generating relevant text for
regions with abnormalities by employing a generative large language model
(LLM). This two-step approach introduces a layer of interpretability and aligns
the framework with the systematic reasoning that radiologists use when
reviewing a CXR.


  Let $f$ and $g$ be two noncommutative polynomials in disjoint sets of
variables. An algebra $A$ is verbally prime if whenever $f\cdot g$ is an
identity for $A$ then either $f$ or $g$ is also an identity. As an analogue of
this property Regev proved that the verbally prime algebra $M_k(F)$ of $k\times
k$ matrices over an infinite field $F$ has the following primeness property for
central polynomials: whenever the product $f\cdot g$ is a central polynomial
for $M_k(F)$ then both $f$ and $g$ are central polynomials. In this paper we
prove that over a field of characteristic zero Regev' s result holds for the
verbally prime algebras $M_k(E)$ and $M_{k,k}(E)$, where $E$ is the infinite
dimensional Grassmann algebra.


  There are two main quantities involved in the deviation of a stochastic
process from a Poisson process: the squared coefficient of variation of the
time intervals between adjacent events and the Fano factor of the number of
reaction events. As well known, these two quantities are equal for renewal
processes, while their relationship remains unexplored for non-renewal
processes. In this paper, we establish an explicit relation between the two
statistics that is applicable to non-renewal processes. The new relation, which
reduces to the previously mentioned result for renewal processes, is confirmed
to be accurate in several cases of non-renewal processes.


  Modified matter power spectra with approximately Gaussian bump on sub-Mpc
scales can be a result of a complex inflation. We consider five spectra with
different Gaussian amplitudes $A$ and locations $k_0$ and run N-body
simulations in a cube $(5 Mpc/h)^3$ at $z>8$ to reveal the halo mass functions
and their evolution with redshift. We have found that the Sheth-Tormen formula
provides a good approximation to a such kind of halo mass functions. In the
considered models the dark matter halo formation starts much more earlier than
in $\Lambda$CDM, which in turn can result in an earlier star formation and a
nuclear activity in galaxies and can be detected and tested by, e.g., JWST. At
$z=0$ the halo mass functions are hardly distinguishable from the standard
$\Lambda$CDM, therefore the models with the bumpy spectra can be identified in
observations by their excess in number of bright sources at high redshift only.


  We provide a geometric interpretation of the local contribution of a line to
the count of lines on a quintic threefold over a field k of characteristic not
equal to 2, that is, we define the type of a line on a quintic threefold and
show that it coincides with the local index at the corresponding zero of the
section of Sym^5 S^* -> Gr(2, 5) defined by the threefold. Furthermore, we
define the dynamic Euler number which allows us to compute the A^1-Euler number
as the sum of local contributions of zeros of a section with non-isolated zeros
which deform with a general deformation. As an example we provide a quadratic
count of 2875 distinguished lines on the Fermat quintic threefold which
computes the dynamic Euler number of Sym^5 S^* -> Gr(2, 5). Combining those two
results we get that the sum of the types of lines on a general quintic
threefold is 1445<1> + 1430<-1> in GW(k) when k is a field of characteristic
not equal to 2 or 5.


  It has been well recognized that modeling object-to-object relations would be
helpful for object detection. Nevertheless, the problem is not trivial
especially when exploring the interactions between objects to boost video
object detectors. The difficulty originates from the aspect that reliable
object relations in a video should depend on not only the objects in the
present frame but also all the supportive objects extracted over a long range
span of the video. In this paper, we introduce a new design to capture the
interactions across the objects in spatio-temporal context. Specifically, we
present Relation Distillation Networks (RDN) --- a new architecture that
novelly aggregates and propagates object relation to augment object features
for detection. Technically, object proposals are first generated via Region
Proposal Networks (RPN). RDN then, on one hand, models object relation via
multi-stage reasoning, and on the other, progressively distills relation
through refining supportive object proposals with high objectness scores in a
cascaded manner. The learnt relation verifies the efficacy on both improving
object detection in each frame and box linking across frames. Extensive
experiments are conducted on ImageNet VID dataset, and superior results are
reported when comparing to state-of-the-art methods. More remarkably, our RDN
achieves 81.8% and 83.2% mAP with ResNet-101 and ResNeXt-101, respectively.
When further equipped with linking and rescoring, we obtain to-date the best
reported mAP of 83.8% and 84.7%.


This paper has been withdrawn.


  This paper presents recent results concerning the existence and qualitative
properties of travelling wave solutions to the Gross-Pitaevskii equation posed
on the whole space R^N. Unlike the defocusing nonlinear Schr\"odinger equations
with null condition at infinity, the presence of non-zero conditions at
infinity yields a rather rich and delicate dynamics. We focus on the case N = 2
and N = 3, and also briefly review some classical results on the
one-dimensional case. The works we survey provide rigorous justifications to
the impressive series of results which Jones, Putterman and Roberts established
by formal and numerical arguments.


  The physics of glasses can be studied from many viewpoints, from material
scientists interested in the development of new materials to statistical
physicists inventing new theoretical tools to deal with disordered systems. In
these lectures I described a variety of physical phenomena observed in actual
glassy materials, from disordered magnetic systems to soft gels. Despite the
very large gap between experimental and numerical time windows, I showed that
computer simulations represent an efficient theoretical tool which can shed
light on the microscopic origins of glassy dynamics.


  We use optical transient-grating spectroscopy to measure spin diffusion of
optically oriented electrons in bulk, semi-insulating GaAs(100). Trapping and
recombination do not quickly deplete the photoexcited population. The spin
diffusion coefficient of 88 +/- 12 cm2/s is roughly constant at temperatures
from 15 K to 150 K, and the spin diffusion length is at least 450 nm. We show
that it is possible to use spin diffusion to estimate the electron diffusion
coefficient. Due to electron-electron interactions, the electron diffusion is
1.4 times larger than the spin diffusion.


  Multiple Borel-Cantelli Lemma is a criterion that characterizes the
occurrence of multiple rare events on the same time scale. We generalize the
multiple Borel-Cantelli Lemma in dynamics established by Dolgopyat, Fayad and
Liu [J. Mod. Dyn. 18 (2022) 209--289], broadening its applications to encompass
several non-smooth systems with absolute continuous measures. Utilizing this
generalization, we derive multiple Logarithm Law for hitting time and
recurrence of dispersing billiard maps and piecewise expanding maps under some
regular conditions, including tent map, Lorentz-like map and Gauss map.