  The distribution of hot Jupiters, for which star-planet interactions can be
significant, questions the evolution of exosystems. We aim to follow the
orbital evolution of a planet along the rotational and structural evolution of
the host star by taking into account the coupled effects of tidal and magnetic
torques from ab initio prescriptions. It allows us to better understand the
evolution of star-planet systems and to explain some properties of the
distribution of observed close-in planets. To this end we use a numerical model
of a coplanar circular star-planet system taking into account stellar
structural changes, wind braking and star-planet interactions, called ESPEM
(Benbakoura et al. 2019). We find that depending on the initial configuration
of the system, magnetic effects can dominate tidal effects during the various
phases of the evolution, leading to an important migration of the planet and to
significant changes on the rotational evolution of the star. Both kinds of
interactions thus have to be taken into account to predict the evolution of
compact star-planet systems.


  For classification of the high frequency trading quantities, waiting times,
price increments within and between sessions are referred to as the a-, b-, and
c-increments. Statistics of the a-b-c-increments are computed for the Time &
Sales records posted by the Chicago Mercantile Exchange Group for the futures
traded on Globex. The Weibull, Kumaraswamy, Riemann and Hurwitz Zeta,
parabolic, Zipf-Mandelbrot distributions are tested for the a- and
b-increments. A discrete version of the Fisher-Tippett distribution is
suggested for approximating the extreme b-increments. Kolmogorov and Uspenskii
classification of stochastic, typical, and chaotic random sequences is reviewed
with regard to the futures price limits. Non-parametric L1 and log-likelihood
tests are applied to check dependencies between the a- and b-increments. The
maximum profit strategies and optimal trading elements are suggested as
measures of frequency and magnitude of the market offers and disequilibrium.
Empirical cumulative distribution functions of optimal profits are reported. A
few classical papers are reviewed with more details in order to trace the
origin and foundation of modern finance.


  We theoretically study the electronic transport properties of Dirac fermions
through one and double triangular barriers in graphene. Using the transfer
matrix method, we determine the transmission, conductance and Fano factor. They
are obtained to be various parameters dependent such as well width, barrier
height and barrier width. Therefore, different discussions are given and
comparison with the previous significant works is done. In particular, it is
shown that at Dirac point the Dirac fermions always own a minimum conductance
associated with a maximum Fano factor and change their behaviors in an
oscillatory way (irregularly periodical tunneling peaks) when the potential of
applied voltage is increased.


  Multiparticle production processes in He-Li, He-C, C-C, C-Ne, C-Cu, C-Pb,,
F-Mg, Mg-Mg and O-Pb collsions at energy of 3.7 GeV/nucleon obtained by use of
SKM-200 and GIBS spectrometers of JINR. Collective flow phenomena (directed and
elliptic flows) at this energy have been observed.


  Comparison of human and chimpanzee genomes has received much attention,
because of paramount role for understanding evolutionary step distinguishing us
from our closest living relative. In order to contribute to insight into Y
chromosome evolutionary history, we study and compare tandems, higher order
repeats (HORs), and regularly dispersed repeats in human and chimpanzee Y
chromosome contigs, using robust Global Repeat Map algorithm. We find a new
type of long-range acceleration, human-accelerated HOR regions. In peripheral
domains of 35mer human alphoid HORs, we find riddled features with ten
additional repeat monomers. In chimpanzee, we identify 30mer alphoid HOR. We
construct alphoid HOR schemes showing significant human-chimpanzee difference,
revealing rapid evolution after human-chimpanzee separation. We identify and
analyze over 20 large repeat units, most of them reported here for the first
time as: chimpanzee and human ~1.6 kb 3mer secondary repeat unit (SRU) and
~23.5 kb tertiary repeat unit (~0.55 kb primary repeat unit, PRU); human 10848,
15775, 20309, 60910, and 72140 bp PRUs; human 3mer SRU (~2.4 kb PRU); 715mer
and 1123mer SRUs (5mer PRU); chimpanzee 5096, 10762, 10853, 60523 bp PRUs; and
chimpanzee 64624 bp SRU (10853 bp PRU). We show that substantial
human-chimpanzee differences are concentrated in large repeat structures, at
the level of as much as ~70% divergence, sizably exceeding previous numerical
estimates for some selected noncoding sequences. Smeared over the whole
sequenced assembly (25 Mb) this gives ~14% human--chimpanzee divergence. This
is significantly higher estimate of divergence between human and chimpanzee
than previous estimates.


  We discuss the limitations of the applicability of the Lifshitz formula to
describe the temperature dependence of the Casimir force between two bulk lossy
metals. These limitations follow from the finite sizes of the interacting
bodies. Namely, Lifshitz's theory is not applicable when the characteristic
wavelengths of the fluctuating fields, responsible for the
temperature-dependent terms in the Casimir force, is longer than the sizes of
the samples. As a result of this, the widely discussed linearly decreasing
temperature dependence of the Casimir force can be observed only for dirty
and/or large metal samples at high enough temperatures. This solves the problem
of the inconsistency between the Nernst theorem and the "linearly decreasing
temperature dependence" of the Casimir free energy, because this linear
dependence is not valid when $T \to 0$


  Segmentation of medical images using seeded region growing technique is
increasingly becoming a popular method because of its ability to involve
high-level knowledge of anatomical structures in seed selection process. Region
based segmentation of medical images are widely used in varied clinical
applications like visualization, bone detection, tumor detection and
unsupervised image retrieval in clinical databases. As medical images are
mostly fuzzy in nature, segmenting regions based intensity is the most
challenging task. In this paper, we discuss about popular seeded region grow
methodology used for segmenting anatomical structures in CT Angiography images.
We have proposed a gradient based homogeneity criteria to control the region
grow process while segmenting CTA images.


  Recent discoveries of dispersed, non-periodic impulsive radio signals with
single-dish radio telescopes have sparked significant interest in exploring the
relatively uncharted space of fast transient radio signals. Here we describe
V-FASTR, an experiment to perform a blind search for fast transient radio
signals using the Very Long Baseline Array (VLBA). The experiment runs entirely
in a commensal mode, alongside normal VLBA observations and operations. It is
made possible by the features and flexibility of the DiFX software correlator
that is used to process VLBA data. Using the VLBA for this type of experiment
offers significant advantages over single-dish experiments, including a larger
field of view, the ability to easily distinguish local radio-frequency
interference from real signals and the possibility to localize detected events
on the sky to milliarcsecond accuracy. We describe our software pipeline, which
accepts short integration (~ms) spectrometer data from each antenna in real
time during correlation and performs an incoherent dedispersion separately for
each antenna, over a range of trial dispersion measures. The dedispersed data
are processed by a sophisticated detector and candidate events are recorded. At
the end of the correlation, small snippets of the raw data at the time of the
events are stored for further analysis. We present the results of our event
detection pipeline from some test observations of the pulsars B0329+54 and
B0531+21 (the Crab pulsar).


  Let $\mathrm{R}$ be a real closed field. We prove that the number of
semi-algebraically connected components of a real hypersurface in
$\mathrm{R}^n$ defined by a multi-affine polynomial of degree $d$ is bounded by
$2^{d-1}$. This bound is sharp and is independent of $n$ (as opposed to the
classical bound of $d(2d -1)^{n-1}$ on the Betti numbers of hypersurfaces
defined by arbitrary polynomials of degree $d$ in $\mathrm{R}^n$ due to
Petrovski{\u\i} and Ole{\u\i}nik, Thom and Milnor). Moreover, we show there
exists $c > 1$, such that given a sequence $(B_n)_{n >0}$ where $B_n$ is a
closed ball in $\mathrm{R}^n$ of positive radious, there exist hypersurfaces
$(V_n)_{n_>0}$ defined by symmetric multi-affine polynomials of degree $4$,
such that $\sum_{i \leq 5} b_i(V_n \cap B_n) > c^n$, where $b_i(\cdot)$ denotes
the $i$-th Betti number with rational coeffcients. Finally, as an application
of the main result of the paper we verify a representational stability
conjecture due to Basu and Riener on the cohomology modules of symmetric real
algebraic sets for a new and much larger class of symmetric real algebraic sets
than known before.


  The "Airships: A New Horizon for Science" study at the Keck Institute for
Space Studies investigated the potential of a variety of airships currently
operable or under development to serve as observatories and science
instrumentation platforms for a range of space, atmospheric, and Earth science.
The participants represent a diverse cross-section of the aerospace sector,
NASA, and academia. Over the last two decades, there has been wide interest in
developing a high altitude, stratospheric lighter-than-air (LTA) airship that
could maneuver and remain in a desired geographic position (i.e.,
"station-keeping") for weeks, months or even years. Our study found
considerable scientific value in both low altitude (< 40 kft) and high altitude
(> 60 kft) airships across a wide spectrum of space, atmospheric, and Earth
science programs. Over the course of the study period, we identified
stratospheric tethered aerostats as a viable alternative to airships where
station-keeping was valued over maneuverability. By opening up the sky and
Earth's stratospheric horizon in affordable ways with long-term flexibility,
airships allow us to push technology and science forward in a project-rich
environment that complements existing space observatories as well as aircraft
and high-altitude balloon missions.


  Intermetallic Pd-doped (Fe,Ni)$_3$P, that crystalizes in a
non-centrosymmetric tetragonal structure with $S_4$ symmetry, has recently been
discovered to host magnetic antiskyrmions, antivortex-like topological spin
textures. In this material, uniaxial magnetic anisotropy and dipolar
interactions play a significant role, giving rise to finely branched magnetic
domain patterns near the surface of bulk crystals, as revealed by a previous
magnetic force microscopy (MFM) measurement. However, small-angle neutron
scattering (SANS) is a more suitable method for characterizing bulk properties
and fractal structures at the mesoscopic length scale. In this study, using
SANS and MFM, we quantitatively investigate the magnetic domain structure in
bulk single crystals of (Fe$_{0.63}$Ni$_{0.30}$Pd$_{0.07}$)$_3$P. The SANS
results demonstrate that the magnetic domain structure exhibits anisotropic
fractal character on the length scale down to the width of the magnetic domain
walls. The fractal features are gradually lost in magnetic fields, and
different field dependences are observed at 300 K and 2 K due to a
temperature-dependent anisotropy. This study quantifies the fractality of the
highly anisotropic magnetic domain structures in an antiskyrmion material, and
highlights the versatility of SANS for the study of fractal structures in
magnetic systems.


  The NOMAD experiment collected valuable neutrino data samples, matching both
the large statistics of massive calorimeters and the reconstruction quality of
bubble chambers. This paper describes the recent measurements of neutrino
cross-sections on carbon target. The approach followed for cross-section
modeling is also explained.


  Spatial Mobile Crowdsourcing (SMCS) can be leveraged by exploiting the
capabilities of the Social Internet-of-Things (SIoT) to execute spatial tasks.
Typically, in SMCS, a task requester aims to recruit a subset of IoT devices
and commission them to travel to the task location. However, because of the
exponential increase of IoT networks and their diversified devices (e.g.,
multiple brands, different communication channels, etc.), recruiting the
appropriate devices/workers is becoming a challenging task. To this end, in
this paper, we develop a recruitment process for SMCS platforms using automated
SIoT service discovery to select trustworthy workers satisfying the requester
requirements. The method we purpose includes mainly two stages: 1) a worker
filtering stage, aiming at reducing the workers' search space to a subset of
potential trustworthy candidates using the Louvain community detection
algorithm (CD) applied to SIoT relation graphs. Next, 2) a selection process
stage that uses an Integer Linear Program (ILP) to determine the final set of
selected devices/workers. The ILP maximizes a worker efficiency metric
incorporating the skills/specs level, recruitment cost, and trustworthiness
level of the recruited IoT devices. Selected experiments analyze the
performance of the proposed CD-ILP algorithm using a real-world dataset and
show its superiority in providing an effective recruitment strategy compared to
an existing stochastic algorithm.


  The detection of transits is an efficient technique to uncover faint
companions around stars. The full characterisation of the companions (M-type
stars, brown dwarfs or exoplanets) requires high-resolution spectroscopy to
measure properly masses and radii. With the advent of massive variability
surveys over wide fields, the large number of possible candidates makes such a
full characterisation impractical for all of them. We explore here a fast
technique to pre-select the most promising candidates using either near-IR
photometry or low resolution spectroscopy. We develop a new method based on the
well-calibrated surface brightness relation along with the correlation between
mass and luminosity for main sequence stars, so that not only giant stars can
be excluded but also accurate effective temperatures and radii can be measured.
The main source of uncertainty arises from the unknown dispersion of extinction
at a given distance. We apply this technique to our observations of a sample of
34 stars extracted from the 62 low-depth transits identified by OGLE during
their survey of some 10e5 stars stars in the Carina fields of the Galactic
disc. We infer that at least 78% of the companions of the stars which are well
characterised in this sample are not exoplanets. Stars OGLE-TR-105, OGLE-TR-109
and OGLE-TR-111 are the likeliest to host exoplanets and deserve
high-resolution follow-up studies. OGLE-TR-111 was very recently confirmed as
an exoplanet with M_planet = 0.53 +- 0.1 M_Jup (Pont et al. 2004), confirming
the efficiency of our method in pre-selecting reliable planetary transit
candidates.


  We present the results from multi-frequency VLBA observations from 327 MHz to
8.4 GHz of the gigahertz-peaked spectrum radio source PKS 1518+047 (4C 04.51)
aimed at studying the spectral index distribution across the source. Further
multi-frequency archival VLA data were analysed to constrain the spectral shape
of the whole source. The pc-scale resolution provided by the VLBA data allows
us to resolve the source structure in several sub-components. The analysis of
their synchrotron spectra showed that the source components have steep spectral
indices, suggesting that no supply/re-acceleration of fresh particles is
currently taking place in any region of the source. By assuming the
equipartition magnetic field of 4 mG, we found that only electrons with
$\gamma$ < 600, are still contributing to the radio spectrum, while electrons
with higher energies have been almost completed depleted. The source radiative
lifetime we derived is 2700+/-600 years. Considering the best fit to the
overall spectrum, we find that the time in which the nucleus has not been
active represents almost 20% of the whole source lifetime, indicating that the
source was 2150+/-500 years old when the radio emission switched off.


  The quest to comprehend the origins of intelligence raises intriguing
questions about the evolution of learning abilities in natural systems. Why do
living organisms possess an inherent drive to acquire knowledge of the unknown?
Is this motivation solely explicable through natural selection, favoring
systems capable of learning due to their increased chances of survival? Or do
there exist additional, more rapid mechanisms that offer immediate rewards to
systems entering the "learning mode" in the "right ways"? This article explores
the latter possibility and endeavors to unravel the possible nature of these
ways. We propose that learning may have non-biological and non-evolutionary
origin. It turns out that key properties of learning can be observed,
explained, and accurately reproduced within simple physical models that
describe energy accumulation mechanisms in open resonant-type systems with
dissipation.


  This is the third in a series of papers on standard monomial theory and
invariant theory of arc spaces. For any algebraically closed field $K$, we
prove the arc space analogue of the first and second fundamental theorems of
invariant theory for the special linear group. This is more subtle than the
results for the general linear and symplectic groups obtained in the first two
papers because the arc space of the corresponding affine quotients can be
nonreduced.


  Category theory provides a compact method of encoding mathematical structures
in a uniform way, thereby enabling the use of general theorems on, for example,
equivalence and universal constructions. In this article we develop the method
of additional structures on the objects of a monoidal Kleisli category. It is
proposed to consider any uniform class of information transformers (ITs) as a
family of morphisms of a category that satisfy certain set of axioms. This
makes it possible to study in a uniform way different types of ITs, e.g.,
statistical, multivalued, and fuzzy ITs. Proposed axioms define a category of
ITs as a monoidal category that contains a subcategory (of deterministic ITs)
with finite products. Besides, it is shown that many categories of ITs can be
constructed as Kleisli categories with additional structures.


  We compare a fully quantum mechanical numerical calculation of the
conductivity of graphene to the semiclassical Boltzmann theory. Considering a
disorder potential that is smooth on the scale of the lattice spacing, we find
quantitative agreement between the two approaches away from the Dirac point. At
the Dirac point the two theories are incompatible at weak disorder, although
they may be compatible for strong disorder. Our numerical calculations provide
a quantitative description of the full crossover between the quantum and
semiclassical graphene transport regimes.


  This paper addresses the challenge of point-supervised temporal action
detection, in which only one frame per action instance is annotated in the
training set. Self-training aims to provide supplementary supervision for the
training process by generating pseudo-labels (action proposals) from a base
model. However, most current methods generate action proposals by applying
manually designed thresholds to action classification probabilities and
treating adjacent snippets as independent entities. As a result, these methods
struggle to generate complete action proposals, exhibit sensitivity to
fluctuations in action classification scores, and generate redundant and
overlapping action proposals. This paper proposes a novel framework termed
ADM-Loc, which stands for Actionness Distribution Modeling for point-supervised
action Localization. ADM-Loc generates action proposals by fitting a composite
distribution, comprising both Gaussian and uniform distributions, to the action
classification signals. This fitting process is tailored to each action class
present in the video and is applied separately for each action instance,
ensuring the distinctiveness of their distributions. ADM-Loc significantly
enhances the alignment between the generated action proposals and ground-truth
action instances and offers high-quality pseudo-labels for self-training.
Moreover, to model action boundary snippets, it enforces consistency in action
classification scores during training by employing Gaussian kernels, supervised
with the proposed loss functions. ADM-Loc outperforms the state-of-the-art
point-supervised methods on THUMOS14 and ActivityNet-v1.2 datasets.


  We consider real
  polynomials in one variable without vanishing coefficients and with
  all roots real and of distinct moduli.
  We show that the signs of the coefficients define the order of
  the moduli of the roots on the real positive half-line exactly when no four
  consecutive signs of coefficients equal $(+,+,-,-)$, $(-,-,+,+)$,
  $(+,-,-,+)$ or $(-,+,+,-)$.


  A global protocol for the thermostatistical analysis of hot nuclear sources
is discussed. Within our method of minimization of variances we show that the
abnormal kinetic energy fluctuation signal recently reported in different
experimental data (M.D'Agostino et al.-Phys. Lett. B 473 (2000) 219, N. Le
Neindre et al.- contr. to the XXXVIII Bormio Winter Meeting on Nucl. Phys.
(2001) 404) is a genuine signal of a first order phase transition in a finite
system.


  For a finite set of natural numbers $D$ consider a complex polynomial of the
form $f(z) = \sum_{d \in D} c_d z^d$. Let $\rho_+(f)$ and $\rho_-(f)$ be the
fractions of the unit circle that $f$ sends to the right($\operatorname{Re}
f(z) > 0$) and left($\operatorname{Re} f(z) < 0$) half-planes, respectively.
Note that $\operatorname{Re} f(z)$ is a real trigonometric polynomial, whose
allowed set of frequencies is $D$. Turns out that $\min(\rho_+(f), \rho_-(f))$
is always bounded below by a numerical characteristic $\alpha(D)$ of our set
$D$ that arises from a seemingly unrelated combinatorial problem. Furthermore,
this result could be generalized to power series, almost periodic functions,
functions of several variables and multivalued algebraic functions.


  In this paper, we study counterfactual fairness in text classification, which
asks the question: How would the prediction change if the sensitive attribute
referenced in the example were different? Toxicity classifiers demonstrate a
counterfactual fairness issue by predicting that "Some people are gay" is toxic
while "Some people are straight" is nontoxic. We offer a metric, counterfactual
token fairness (CTF), for measuring this particular form of fairness in text
classifiers, and describe its relationship with group fairness. Further, we
offer three approaches, blindness, counterfactual augmentation, and
counterfactual logit pairing (CLP), for optimizing counterfactual token
fairness during training, bridging the robustness and fairness literature.
Empirically, we find that blindness and CLP address counterfactual token
fairness. The methods do not harm classifier performance, and have varying
tradeoffs with group fairness. These approaches, both for measurement and
optimization, provide a new path forward for addressing fairness concerns in
text classification.


  The photoelectric factor (PEF) is an important well logging tool to
distinguish between different types of reservoir rocks because PEF measurement
is sensitive to elements with high atomic number. Furthermore, the ratio of
rock minerals could be determined by combining PEF log with other well logs.
However, PEF log could be missing in some cases such as in old well logs and
wells drilled with barite-based mud. Therefore, developing models for
estimating missing PEF log is essential in those circumstances. In this work,
we developed various machine learning models to predict PEF values using the
following well logs as inputs: bulk density (RHOB), neutron porosity (NPHI),
gamma ray (GR), compressional and shear velocity.
  The predictions of PEF values using adaptive-network-fuzzy inference system
(ANFIS) and artificial neural network (ANN) models have errors of about 16% and
14% average absolute percentage error (AAPE) in the testing dataset,
respectively. Thus, a different approach was proposed that is based on the
concept of automated machine learning. It works by automatically searching for
the optimal model type and optimizes its hyperparameters for the dataset under
investigation. This approach selected a Gaussian process regression (GPR) model
for accurate estimation of PEF values. The developed GPR model decreases the
AAPE of the predicted PEF values in the testing dataset to about 10% AAPE. This
error could be further decreased to about 2% by modeling the potential noise in
the measurements using the GPR model.


  We start this paper with a historical survey of the Casimir effect, showing
that its origin is related to experiments on colloidal chemistry. We present
two methods of computing Casimir forces, namely: the global method introduced
by Casimir, based on the idea of zero-point energy of the quantum
electromagnetic field, and a local one, which requires the computation of the
energy-momentum stress tensor of the corresponding field. As explicit examples,
we calculate the (standard) Casimir forces between two parallel and perfectly
conducting plates and discuss the more involved problem of a scalar field
submitted to Robin boundary conditions at two parallel plates. A few comments
are made about recent experiments that undoubtedly confirm the existence of
this effect. Finally, we briefly discuss a few topics which are either
elaborations of the Casimir effect or topics that are related in some way to
this effect as, for example, the influence of a magnetic field on the Casimir
effect of charged fields, magnetic properties of a confined vacuum and
radiation reaction forces on non-relativistic moving boundaries.


  Security questions are one of the techniques used to recover passwords. The
main limitation of security questions is that users find strong answers
difficult to remember. This leads users to trade-off security for the
convenience of an improved memorability. Previous research found that increased
fun and enjoyment can lead to an enhanced memorability, which provides a better
learning experience. Hence, we empirically investigate whether a serious game
has the potential of improving the memorability of strong answers to security
questions. For our serious game, we adapted the popular "4 Pics 1 word" mobile
game because of its use of pictures and cues, which psychology research found
to be important to help with memorability. Our findings indicate that the
proposed serious game could potentially improve the memorability of answers to
security questions. This potential improvement in memorability, could
eventually help reduce the trade-off between usability and security in
fall-back authentication.


  Ultrathin epitaxial films of EuNiO3 were grown on a series of substrates
traversing highly compressive (- 2.4%) to highly tensile (2.5%) lattice
mismatch. X-ray diffraction measurements showed the expected c-lattice
parameter shift for compressive strain, but no detectable shift for tensilely
strained substrates, while reciprocal space mapping confirmed the tensile
strained film maintained epitaxial coherence. Transport measurements showed a
successively (from tensile to compressive) lower resistance and a complete
suppression of the metalinsulator transition at highly compressive lattice
mismatch. Corroborating these findings, X-ray absorption spectroscopy
measurements revealed a strong multiplet splitting in the tensile samples that
progressively weakens with increasing compressive strain that, combined with
cluster calculations, showed enhanced covalence between Ni-d and O-p orbitals
leads to the metallic state.


  Using the supersymmetry approach, we study spectral statistical properties of
a two-dimensional quantum particle subject to a non-uniform magnetic field. We
focus mainly on the problem of regularisation of the field theory. Our analysis
begins with an investigation of the spectral properties of the purely classical
evolution operator. We show that, although the kinetic equation is formally
time-reversible, density relaxation is controlled by {\em irreversible}
classical dynamics. In the case of a weak magnetic field, the effective kinetic
operator corresponds to diffusion in the angle space, the diffusion constant
being determined by the spectral resolution of the inhomogeneous magnetic
field. Applying these results to the quantum problem, we demonstrate that the
low-lying modes of the field theory are related to the eigenmodes of the
irreversible classical dynamics, and the higher modes are separated from the
zero mode by a gap associated with the lowest density relaxation rate. As a
consequence, we find that the long-time properties of the system are
characterised by universal Wigner-Dyson statistics. For a weak magnetic field,
we obtain a description in terms of the quasi one-dimensional non-linear
$\sigma$-model.


  Face Recognition is most used for biometric user authentication that
identifies a user based on his or her facial features. The system is in high
demand, as it is used by many businesses and employed in many devices such as
smartphones and surveillance cameras. However, one frequent problem that is
still observed in this user-verification method is its accuracy rate. Numerous
approaches and algorithms have been experimented to improve the stated flaw of
the system. This research develops one such algorithm that utilizes a
combination of two different approaches. Using the concepts from Linear Algebra
and computational geometry, the research examines the integration of Principal
Component Analysis with Delaunay Triangulation; the method triangulates a set
of face landmark points and obtains eigenfaces of the provided images. It
compares the algorithm with traditional PCA and discusses the inclusion of
different face landmark points to deliver an effective recognition rate.


  The purpose of this paper is twofold; (1) to develop several identities for
the Generalized $k$-Pell sequence (including those of Binet, Catalan, Cassini,
and d'Ocagne), and (2) to study applications of tridiagonal generating matrices
for the $k$-Pell and Generalized $k$-Pell sequences.


  We consider the online makespan minimization problem on identical machines.
Chen and Vestjens (ORL 1997) show that the largest processing time first (LPT)
algorithm is 1.5-competitive. For the special case of two machines, Noga and
Seiden (TCS 2001) introduce the SLEEPY algorithm that achieves a competitive
ratio of $(5 - \sqrt{5})/2 \approx 1.382$, matching the lower bound by Chen and
Vestjens (ORL 1997). Furthermore, Noga and Seiden note that in many
applications one can kill a job and restart it later, and they leave an open
problem whether algorithms with restart can obtain better competitive ratios.
  We resolve this long-standing open problem on the positive end. Our algorithm
has a natural rule for killing a processing job: a newly-arrived job replaces
the smallest processing job if 1) the new job is larger than other pending
jobs, 2) the new job is much larger than the processing one, and 3) the
processed portion is small relative to the size of the new job. With
appropriate choice of parameters, we show that our algorithm improves the 1.5
competitive ratio for the general case, and the 1.382 competitive ratio for the
two-machine case.


  Recent advances in photonic integration have propelled microwave photonic
technologies to new heights. The ability to interface hybrid material platforms
to enhance light-matter interactions has led to the developments of ultra-small
and high-bandwidth electro-optic modulators, frequency synthesizers with the
lowest noise, and chip signal processors with orders-of-magnitude enhanced
spectral resolution. On the other hand, the maturity of high-volume
semiconductor processing has finally enabled the complete integration of light
sources, modulators, and detectors in a single microwave photonic processor
chip and has ushered the creation of a complex signal processor with
multi-functionality and reconfigurability similar to their electronic
counterparts. Here we review these recent advances and discuss the impact of
these new frontiers for short and long term applications in communications and
information processing. We also take a look at the future perspectives in the
intersection of integrated microwave photonics with other fields including
quantum and neuromorphic photonics.


  In this paper, we consider a heterogeneous 5G cellular architecture that
separates the outdoor and indoor scenarios and in particular study the
trade-off between the spectrum efficiency (SE), energy efficiency (EE), economy
efficiency (ECE). Mathematical expressions for the system capacity, EE, SE, and
ECE respectively are derived using a proposed realistic power consumption
model. The comparison of system performance in terms of SE, EE, and ECE,
results in the observation that the proposed network architecture, which
separates the outdoor and indoor scenarios, offers a promising solution for
future communication systems that have strict requirements on the data rate and
efficiency.


  We present the explicit solution to the geodesic equations in a warped de
Sitter space-time proposed by Randall-Sundrum. We find that a test particle
moves in the bulk and is not restricted on a 3-brane (to be taken as our
universe). On the 3-brane, the test particle moves with uniform velocity,
giving the appearance that it is not subject to a force. But computing the
particle's energy using the energy-momentum tensor yields a time-dependent
energy that suggests a time-dependent mass. Thus, the extra force, which is the
effect of the warped extra dimension on the particle's motion on the 3-brane,
does not change the velocity but the mass of the particle. The particle's
motion in the bulk also results in a time-dependent modification of the
Heisenberg uncertainty principle as viewed on the 3-brane. These two results
show that the classical physics along the extra dimension results in the
time-dependence of particle masses and the uncertainty principle. If the
particle masses are time-independent and the Heisenberg's uncertainty principle
is to remain unchanged, then there must be a non-gravitational force that will
restrict all particles on the 3-brane. Finally, we just note that although
classically, these time-dependent corrections on the 3-brane can be removed,
quantum mechanical corrections along the extra dimension will restore back the
problem.


  We collected and analyzed Instagram direct messages (DMs) from 173 youth aged
13-21 (including 86 LGBTQ+ youth). We examined youth's risk-flagged social
media trace data with their self-reported mental health outcomes to examine how
the differing online experiences of LGBTQ+ youth compare with their
heterosexual counterparts. We found that LGBTQ+ youth experienced significantly
more high-risk online interactions compared to heterosexual youth. LGBTQ+ youth
reported overall poorer mental health, with online harassment specifically
amplifying Self-Harm and Injury. LGBTQ+ youth's mental well-being linked
positively to sexual messages, unlike heterosexual youth. Qualitatively, we
found that most of the risk-flagged messages of LGBTQ+ youth were sexually
motivated; however, a silver lining was that they sought support for their
sexual identity from peers on the platform. The study highlights the importance
of tailored online safety and inclusive design for LGBTQ+ youth, with
implications for CHI community advancements in fostering a supportive online
environments.


  The observed correlation of the angular momenta $L^{ik}$ and magnetic moments
$\mu_{lm}$ of celestial bodies (the Sun, planets and stars) was discussed by
many authors but without any explanation. In this paper a possible explanation
of this phenomenon is suggested. It is shown that the function $\Phi_{lm}
=(\eta/r_g)L^{ik}R_{iklm}$ satisfy Maxwell equations and can be considered as a
function which determine the electro-magnetic properties of rotating heavy
bodies. The $R_{iklm}$ is the Riemann tensor, which determines the
gravitational field of the body, $r_g$ is the gravitational radius of the body,
and $\eta$ is the constant which has to be determined by observations. The
field $\Phi_{lm}$ describe the observed $\mu \leftrightarrow L$ correlation. In
particular the function $\Phi_{l0}$ describe the electric field created by
rotating heavy bodies. It is possible that the observed electric field of the
Earth is created by the Earth rotation


  We show that a Boolean degree $d$ function on the slice $\binom{[n]}{k} = \{
(x_1,\ldots,x_n) \in \{0,1\} : \sum_{i=1}^n x_i = k \}$ is a junta, assuming
that $k,n-k$ are large enough. This generalizes a classical result of Nisan and
Szegedy on the hypercube. Moreover, we show that the maximum number of
coordinates that a Boolean degree $d$ function can depend on is the same on the
slice and the hypercube.


  I present a formal connection between algebraic effects and game semantics,
two important lines of work in programming languages semantics with
applications in compositional software verification.
  Specifically, the algebraic signature enumerating the possible side-effects
of a computation can be read as a game, and strategies for this game constitute
the free algebra for the signature in a category of complete partial orders
(cpos). Hence, strategies provide a convenient model of computations with
uninterpreted side-effects. In particular, the operational flavor of game
semantics carries over to the algebraic context, in the form of the coincidence
between the initial algebras and the terminal coalgebras of cpo endofunctors.
  Conversely, the algebraic point of view sheds new light on the strategy
constructions underlying game semantics. Strategy models can be reformulated as
ideal completions of partial strategy trees (free dcpos on the term algebra).
Extending the framework to multi-sorted signatures would make this construction
available for a large class of games.


  The ability to change a surface's profile allows biological systems to
effectively manipulate and blend into their surroundings. Current surface
morphing techniques rely either on having a small number of fixed states or on
directly driving the entire system. We discovered a subset of scale-independent
auxetic metamaterials have a state trajectory with a star-graph structure. At
the central node, small nudges can move the material between trajectories,
allowing us to locally shift Poisson's ratio, causing the material to take on
different shapes under loading. While the number of possible shapes grows
exponentially with the size of the material, the probability of finding one at
random is vanishingly small. By actively guiding the material through the node
points, we produce a reprogrammable surface that does not require inputs to
maintain shape and can display arbitrary 2D information and take on complex 3D
shapes. Our work opens new opportunities in micro devices, tactile displays,
manufacturing, and robotic systems.


  We study the transport of heat along a chain of particles interacting through
a harmonic potential and subject to heat reservoirs at its ends. Each particle
has two degrees of freedom and is subject to a stochastic noise that produces
infinitesimal changes in the velocity while keeping the kinetic energy
unchanged. This is modelled by means of a Langevin equation with multiplicative
noise. We show that the introduction of this energy conserving stochastic noise
leads to Fourier's law. By means of an approximate solution that becomes exact
in the thermodynamic limit, we also show that the heat conductivity $\kappa$
behaves as $\kappa = a L/(b+\lambda L)$ for large values of the intensity
$\lambda$ of the energy conserving noise and large chain sizes $L$. Hence, we
conclude that in the thermodynamic limit the heat conductivity is finite and
given by $\kappa=a/\lambda$.


  This article surveys the development of the SYZ conjecture since it was
proposed by Strominger, Yau and Zaslow in their famous 1996 paper, and
discusses how it has been leading us to a thorough understanding of the
geometry underlying mirror symmetry.


  Our view of the microbial world and its impact on human health is changing
radically with the ability to sequence uncultured or unculturable microbes
sampled directly from their habitats, ability made possible by fast and cheap
next generation sequencing technologies. Such recent developments represents a
paradigmatic shift in the analysis of habitat biodiversity, be it the human,
soil or ocean microbiome. We review here some research examples and results
that indicate the importance of the microbiome in our lives and then discus
some of the challenges faced by metagenomic experiments and the subsequent
analysis of the generated data. We then analyze the economic and social impact
on genomic-medicine and research in both developing and developed countries. We
support the idea that there are significant benefits in building capacities for
developing high-level scientific research in metagenomics in developing
countries. Indeed, the notion that developing countries should wait for
developed countries to make advances in science and technology that they later
import at great cost has recently been challenged.


  In the process of rewriting large physics codes at Los Alamos National
Laboratory to perform well on new architectures such as many-core, GPU, and
Intel MIC, we have found a number of areas in which sustainable software
practices can provide significant advantages. We describe several specific
advantages of sustainable practices for future architectures, and report on two
small experimental projects at LANL intended to raise awareness of new software
practices and programming approaches for new architectures.


  The Westerbork Radio Synthesis Telescope, WSRT, has been used to make a deep
radio survey of an ~ 1.7 sq degree field coinciding with the AKARI North
Ecliptic Pole Deep Field. The observations, data reduction and source count
analysis are presented, along with a description of the overall scientific
objectives. The survey consisted of 10 pointings, mosaiced with enough overlap
to maintain a similar sensitivity across the central region that reached as low
as 21 microJy per beam at 1.4 GHz. A catalogue containing 462 sources detected
with a resolution of 17"x15" is presented. The differential source counts
calculated from the WSRT data have been compared with those from the shallow
VLA-NEP survey of Kollgaard et al 1994, and show a pronounced excess for
sources fainter than ~ 1 mJy, consistent with the presence of a population of
star forming galaxies at sub-mJy flux levels. The AKARI North Ecliptic Pole
Deep field is the focus of a major observing campaign conducted across the
entire spectral region. The combination of these data sets, along with the deep
nature of the radio observations will allow unique studies of a large range of
topics including the redshift evolution of the luminosity function of radio
sources, the clustering environment of radio galaxies, the nature of obscured
radio-loud active galactic nuclei, and the radio/far-infrared correlation for
distant galaxies. This catalogue provides the basic data set for a future
series of paper dealing with source identifications, morphologies, and the
associated properties of the identified radio sources.


  The LHCb has reported the observation of a resonancelike structure, the
Pc(4450), in the J/psi p invariant masses. In our work, we discuss the
feasibility of detecting this structure in J/psi photoproduction, e.g. in the
measurements that have been approved for the experiments in Hall A/C and in
Hall B with CLAS12 at JLab. Also the GlueX Collaboration has already reported
preliminary results. We take into account the experimental resolution effects,
and perform a global fit to world J/psi photoproduction data in order to study
the possibility of observing the Pc(4450) signal in future JLab data. We
present a first estimate of the upper limit for the branching ratio of the
Pc(4450) into the J/psi p channel, and we study the angular distributions of
the differential cross sections. This will shed light on the nature and
couplings of the Pc(4450) structure in the future photoproduction experiments.


  We present a theoretical study of inhomogeneous dynamic (resistive) states in
a single plaquette consisting of three Josephson junctions. Resonant
interactions of such a breather state with electromagnetic oscillations
manifest themselves by resonant current steps and voltage jumps in the
current-voltage characteristics. An externally applied magnetic field leads to
a variation of the relative shift between the Josephson current oscillations of
two resistive junctions. By making use of the rotation wave approximation
analysis and direct numerical simulations we show that this effect allows to
effectively control the breather instabilities, e. g. to increase (decrease)
the height of the resonant steps and to suppress the voltage jumps in the
current-voltage characteristics.


  The key issue in Dynamic Ensemble Selection (DES) is defining a suitable
criterion for calculating the classifiers' competence. There are several
criteria available to measure the level of competence of base classifiers, such
as local accuracy estimates and ranking. However, using only one criterion may
lead to a poor estimation of the classifier's competence. In order to deal with
this issue, we have proposed a novel dynamic ensemble selection framework using
meta-learning, called META-DES. An important aspect of the META-DES framework
is that multiple criteria can be embedded in the system encoded as different
sets of meta-features. However, some DES criteria are not suitable for every
classification problem. For instance, local accuracy estimates may produce poor
results when there is a high degree of overlap between the classes. Moreover, a
higher classification accuracy can be obtained if the performance of the
meta-classifier is optimized for the corresponding data. In this paper, we
propose a novel version of the META-DES framework based on the formal
definition of the Oracle, called META-DES.Oracle. The Oracle is an abstract
method that represents an ideal classifier selection scheme. A meta-feature
selection scheme using an overfitting cautious Binary Particle Swarm
Optimization (BPSO) is proposed for improving the performance of the
meta-classifier. The difference between the outputs obtained by the
meta-classifier and those presented by the Oracle is minimized. Thus, the
meta-classifier is expected to obtain results that are similar to the Oracle.
Experiments carried out using 30 classification problems demonstrate that the
optimization procedure based on the Oracle definition leads to a significant
improvement in classification accuracy when compared to previous versions of
the META-DES framework and other state-of-the-art DES techniques.


  We present the analysis of a survey of atomic and molecular gas in
interacting and merging galaxies (Horellou & Booth 1997). The sample is
optically selected and contains all interacting galaxies (~ 60 systems) in a
well-defined region of the Southern sky (Bergvall 1981). In order to take into
account the upper limits due to non-detections, we have carried out a survival
analysis. The results are compared with the ones obtained when ignoring the
non-detections. We have found evidence for a lower atomic gas content per unit
area in interacting galaxies compared to isolated ones. Except for a few
systems with high far-infrared luminosity and correspondingly high CO fluxes,
the interacting galaxies are not unusually CO-bright. The observed
HI-deficiency is therefore not due to a conversion from HI into H2. Atomic gas
from the outer part of the galaxies may have been swept by tidal interaction,
or the optical extent of the galaxies may have increased due to the tidal
interaction. The interacting galaxies seem to be more efficient at transforming
their molecular gas into stars, as indicated by their higher LFIR/M(H2) ratio.
We found no correlation between molecular gas fraction and degree of
morphological distortion.


  In analogy with crystalline solids around us, Wilczek recently proposed the
idea of "time crystals" as phases that spontaneously break the continuous time
translation into a discrete subgroup. The proposal stimulated further studies
and vigorous debates whether it can be realized in a physical system. However,
a precise definition of the time crystal is needed to resolve the issue. Here
we first present a definition of time crystals based on the time-dependent
correlation functions of the order parameter. We then prove a no-go theorem
that rules out the possibility of time crystals defined as such, in the ground
state or in the canonical ensemble of a general Hamiltonian, which consists of
not-too-long-range interactions.


  One of the most important issues in relativistic astrophysics is to explain
the origin mechanisms of (ultra)high energy charged particle components of
cosmic rays. Black holes (BHs) being huge reservoirs of (gravitational) energy
can be candidates for such particle sources. The main idea of this work is to
study the effects of scalar-tensor-vector gravity (STVG) on particle
acceleration by examining charged particle dynamics and their acceleration
through the magnetic Penrose process (MPP) near magnetized Kerr-MOG BHs. First,
we study the horizon structure of the BH. Also, we study the effective
potential to gain insight into the stability of circular orbits. Our results
show that the magnetic field can extend the region of stable circular orbits,
whereas the STVG parameter reduces the {instability} of the circular orbit. The
motion of charged particles around the magnetized BH reveals various feasible
regimes of the ionized Keplerian disk behavior. Thus, from the examination of
particle trajectories we observe that at fixed values of other parameters, the
Schwarzschild BH captures the test particle; in the case of Kerr BH, the test
particle escapes to infinity or is captured by the BH, while in Kerr-MOG BH,
the test particle is trapped in some region around BH and starts orbiting it.
On investigating the MPP, we found that with increasing magnetic field, the
behavior of orbits becomes more chaotic. As a result, the particle escapes to
infinity more quickly.


  We show that the method of distributed noise-shaping beta-quantization offers
superior performance for the problem of spectral super-resolution with
quantization whenever there is redundancy in the number of measurements. More
precisely, we define the oversampling ratio $\lambda$ as the largest integer
such that $\lfloor M/\lambda\rfloor - 1\geq 4/\Delta$, where $M$ denotes the
number of Fourier measurements and $\Delta$ is the minimum separation distance
associated with the atomic measure to be resolved. We prove that for any number
$K\geq 2$ of quantization levels available for the real and imaginary parts of
the measurements, our quantization method combined with either TV-min/BLASSO or
ESPRIT guarantees reconstruction accuracy of order $O(M^{1/4}\lambda^{5/4} K^{-
\lambda/2})$ and $O(M^{3/2} \lambda^{1/2} K^{- \lambda})$ respectively, where
the implicit constants are independent of $M$, $K$ and $\lambda$. In contrast,
naive rounding or memoryless scalar quantization for the same alphabet offers a
guarantee of order $O(M^{-1}K^{-1})$ only, regardless of the reconstruction
algorithm.


  We build Gaussian wave packets for the linear Schr\"odinger equation and its
finite difference space semi-discretization and illustrate the lack of uniform
dispersive properties of the numerical solutions as established in Ignat,
Zuazua, Numerical dispersive schemes for the nonlinear Schr\"odinger equation,
SIAM. J. Numer. Anal., 47(2) (2009), 1366-1390. It is by now well known that
bigrid algorithms provide filtering mechanisms allowing to recover the
uniformity of the dispersive properties as the mesh size goes to zero. We
analyze and illustrate numerically how these high frequency wave packets split
and propagate under these bigrid filtering mechanisms, depending on how the
fine grid/coarse grid filtering is implemented.


  In the present work we used a grid of photoionization models combined with
stellar population synthesis models to derive reliable Ionization Correction
Factors (ICFs) for the sulphur in star-forming regions. These models cover a
large range of nebular parameters and yielding ionic abundances in consonance
with those derived through optical and infrared observational data of
star-forming regions. From our theoretical ICFs, we suggested an {\alpha} value
of 3.27 in the classical Stasinska formulae. We compared the total sulphur
abundance in the gas phase of a large sample of objects by using our
Theoretical ICF and other approaches. In average, the differences between the
determinations via the use of the different ICFs considered are similar to the
uncertainties in the S/H estimations. Nevertheless, we noted that for some
objects it could reach up to about 0.3 dex for the low metallicity regime.
Despite of the large scatter of the points, we found a trend of S/O ratio to
decrease with the metallicity, independently of the ICF used to compute the
sulphur total abundance.


  We present some a - priori bounds from above and from below for solutions to
a class of conformally invariant Schroedinger equations. As a by - product we
deduce some new uniqueness results.


  We investigated the possibility of the homogeneous and isotropic cosmological
solution in Weyl geometry, which differs from the Riemannian geometry by adding
the so called Weyl vector. The Weyl gravity is obtained by constructing the
gravitational Lagrangian both to be quadratic in curvatures and conformal
invariant. It is found that such solution may exist provided there exists the
direct interaction between the Weyl vector and the matter fields. Assuming the
matter Lagrangian is that of the perfect fluid, we found how such an
interaction can be implemented. Due to the existence of quadratic curvature
terms and the direct interaction the perfect fluid particles may be created
straight from the vacuum, and we found the expression for the rate of their
production which appeared to be conformal invariant. In the case of creating
the universe ``from nothing'' in the vacuum state, we investigated the problem,
whether this vacuum may persist or not. It is shown that the vacuum may persist
with respect to producing the non-dust matter (with positive pressure), but
cannot resist to producing the dust particles. These particles, being
non-interactive, may be considered as the candidates for dark matter.


  The backpropagation of error algorithm (BP) is impossible to implement in a
real brain. The recent success of deep networks in machine learning and AI,
however, has inspired proposals for understanding how the brain might learn
across multiple layers, and hence how it might approximate BP. As of yet, none
of these proposals have been rigorously evaluated on tasks where BP-guided deep
learning has proved critical, or in architectures more structured than simple
fully-connected networks. Here we present results on scaling up biologically
motivated models of deep learning on datasets which need deep networks with
appropriate architectures to achieve good performance. We present results on
the MNIST, CIFAR-10, and ImageNet datasets and explore variants of
target-propagation (TP) and feedback alignment (FA) algorithms, and explore
performance in both fully- and locally-connected architectures. We also
introduce weight-transport-free variants of difference target propagation (DTP)
modified to remove backpropagation from the penultimate layer. Many of these
algorithms perform well for MNIST, but for CIFAR and ImageNet we find that TP
and FA variants perform significantly worse than BP, especially for networks
composed of locally connected units, opening questions about whether new
architectures and algorithms are required to scale these approaches. Our
results and implementation details help establish baselines for biologically
motivated deep learning schemes going forward.


  We propose a novel class of Nesterov's stochastic accelerated
forward-reflected-based methods with variance reduction to solve root-finding
problems under $\frac{1}{L}$-co-coerciveness. Our algorithm is single-loop and
leverages a new family of unbiased variance-reduced estimators specifically
designed for root-finding problems. It achieves both $\mathcal{O}(L^2/k^2)$ and
$o(1/k^2)$-last-iterate convergence rates in terms of expected operator squared
norm, where $k$ denotes the iteration counter. We instantiate our framework for
two prominent estimators: SVRG and SAGA. By an appropriate choice of
parameters, both variants attain an oracle complexity of $\mathcal{O}( n +
Ln^{2/3}\epsilon^{-1})$ to reach an $\epsilon$-solution, where $n$ represents
the number of summands in the finite-sum operator. Furthermore, under
$\mu$-strong quasi-monotonicity, our method achieves a linear convergence rate
and an oracle complexity of $\mathcal{O}(n+ \kappa
n^{2/3}\log(\epsilon^{-1}))$, where $\kappa := \frac{L}{\mu}$. We extend our
approach to solve a class of finite-sum monotone inclusions, demonstrating that
our schemes retain the same theoretical guarantees as in the equation setting.
Finally, numerical experiments validate our algorithms and demonstrate their
promising performance compared to state-of-the-art methods.


  We witnessed a massive growth in the supervised learning paradigm in the past
decade. Supervised learning requires a large amount of labeled data to reach
state-of-the-art performance. However, labeling the samples requires a lot of
human annotation. To avoid the cost of labeling data, self-supervised methods
were proposed to make use of largely available unlabeled data. This study
conducts a comprehensive and insightful survey and analysis of recent
developments in the self-supervised paradigm for feature representation. In
this paper, we investigate the factors affecting the usefulness of
self-supervision under different settings. We present some of the key insights
concerning two different approaches in self-supervision, generative and
contrastive methods. We also investigate the limitations of supervised
adversarial training and how self-supervision can help overcome those
limitations. We then move on to discuss the limitations and challenges in
effectively using self-supervision for visual tasks. Finally, we highlight some
open problems and point out future research directions.


  Research on text-to-image generation (TTI) still predominantly focuses on the
English language due to the lack of annotated image-caption data in other
languages; in the long run, this might widen inequitable access to TTI
technology. In this work, we thus investigate multilingual TTI (termed mTTI)
and the current potential of neural machine translation (NMT) to bootstrap mTTI
systems. We provide two key contributions. 1) Relying on a multilingual
multi-modal encoder, we provide a systematic empirical study of standard
methods used in cross-lingual NLP when applied to mTTI: Translate Train,
Translate Test, and Zero-Shot Transfer. 2) We propose Ensemble Adapter (EnsAd),
a novel parameter-efficient approach that learns to weigh and consolidate the
multilingual text knowledge within the mTTI framework, mitigating the language
gap and thus improving mTTI performance. Our evaluations on standard mTTI
datasets COCO-CN, Multi30K Task2, and LAION-5B demonstrate the potential of
translation-enhanced mTTI systems and also validate the benefits of the
proposed EnsAd which derives consistent gains across all datasets. Further
investigations on model variants, ablation studies, and qualitative analyses
provide additional insights on the inner workings of the proposed mTTI
approaches.


  In privacy-preserving machine learning, it is common that the owner of the
learned model does not have any physical access to the data. Instead, only a
secured remote access to a data lake is granted to the model owner without any
ability to retrieve data from the data lake. Yet, the model owner may want to
export the trained model periodically from the remote repository and a question
arises whether this may cause is a risk of data leakage. In this paper, we
introduce the concept of data stealing attack during the export of neural
networks. It consists in hiding some information in the exported network that
allows the reconstruction outside the data lake of images initially stored in
that data lake. More precisely, we show that it is possible to train a network
that can perform lossy image compression and at the same time solve some
utility tasks such as image segmentation. The attack then proceeds by exporting
the compression decoder network together with some image codes that leads to
the image reconstruction outside the data lake. We explore the feasibility of
such attacks on databases of CT and MR images, showing that it is possible to
obtain perceptually meaningful reconstructions of the target dataset, and that
the stolen dataset can be used in turns to solve a broad range of tasks.
Comprehensive experiments and analyses show that data stealing attacks should
be considered as a threat for sensitive imaging data sources.


  Nucleon density distributions and nucleus-nucleus interaction potentials for
the reactions $^{16}$O+$^{40}$Ca, $^{16}$O+$^{56}$Fe and $^{16}$O+$^{90}$Zr
have been calculated in the framework of the modified Thomas-Fermi method and
considering all terms up to the second order in $\hbar$ in the quasi-classical
expansion of the kinetic energy. Skyrme forces dependent on the nucleon density
are used as the nucleon-nucleon interaction. A parametrization of the
nucleus-nucleus interaction potential, which well describes the potential value
calculated within the modified Thomas-Fermi approach with density-dependent
Skyrme forces, is found. On the basis of the obtained potentials, the
cross-sections of elastic scattering are calculated in a good agreement with
experimental data.


  The structure of a complete lattice formed by closed linear subspaces of a
Hilbert space (i.e., a Hilbert lattice) entails some unreasonable consequences
from the physical point of view. Specifically, this structure seems to
contradict to the localized variant of the Kochen-Specker theorem according to
which the bivaluation of a proposition represented by a closed linear subspace
that does not belong to a Boolean algebra shared by the state, in which a
quantum-mechanical system is prepared, must be value indefinite. For this
reason, the Hilbert lattice structure seems to be too strong and needs to be
weakened. The question is, how should it be weakened so that to support the
quantum uncertainty principle and the Kochen-Specker theorem? Which logic will
a weakened structure identify? The present paper tries to answer these
questions.


  We propose a robust parameter estimation method for dynamical systems based
on Statistical Learning techniques which aims to estimate a set of parameters
that well fit the dynamics in order to obtain robust evidences about the
qualitative behaviour of its trajectory. The method is quite general and
flexible, since it does not rely on any specific property of the dynamical
system, and represents a reinterpretation of Approximate Bayesian Computation
methods through the lens of Statistical Learning. The method is specially
useful for estimating parameters in epidemiological compartmental models in
order to obtain qualitative properties of a disease evolution. We apply it to
simulated and real data about COVID-19 spread in the US in order to evaluate
qualitatively its evolution over time, showing how one may assess the
effectiveness of measures implemented to slow the spread and some qualitative
features of the disease current and future evolution.


  All kind of networks, e.g., Internet of Things, social networks, wireless
sensor networks, transportation networks, 4g/5G, etc., are around us to benefit
and help our daily life. The multistate flow network (MFN) is always used to
model network structures and applications. The level d reliability, Rd, of the
MFN is the success probability of sending at least d units of integer flow from
the source node to the sink node. The reliability Rd is a popular index for
designing, managing, controlling, and evaluating MFNs. The traditional indirect
algorithms must have all d-MPs (special connected vectors) or d-MCs (special
disconnected vectors) first, then use Inclusion-Exclusion Technique (IET) or
Sum-of-disjoint Product (SDP) in terms of found d-MPs or d-MCs to calculate Rd.
The above four procedures are all NP-Hard and #P-Hard and cannot calculate Rd
for all d at the same time A novel algorithm based on the binary-addition-tree
algorithm (BAT) is proposed to calculate the Rd directly for all d at the same
time without using any of the above four procedures. The time complexity and
demonstration of the proposed algorithm are analyzed, and examples are
provided. An experiment is also conducted to compare the proposed algorithm and
existing algorithms based on d-MPs, d-MCs, IET, and/or SDP to validate the
proposed algorithm.


  We tackle the problem of cooperative visual exploration where multiple agents
need to jointly explore unseen regions as fast as possible based on visual
signals. Classical planning-based methods often suffer from expensive
computation overhead at each step and a limited expressiveness of complex
cooperation strategy. By contrast, reinforcement learning (RL) has recently
become a popular paradigm for tackling this challenge due to its modeling
capability of arbitrarily complex strategies and minimal inference overhead. In
this paper, we extend the state-of-the-art single-agent visual navigation
method, Active Neural SLAM (ANS), to the multi-agent setting by introducing a
novel RL-based planning module, Multi-agent Spatial Planner (MSP).MSP leverages
a transformer-based architecture, Spatial-TeamFormer, which effectively
captures spatial relations and intra-agent interactions via hierarchical
spatial self-attentions. In addition, we also implement a few multi-agent
enhancements to process local information from each agent for an aligned
spatial representation and more precise planning. Finally, we perform policy
distillation to extract a meta policy to significantly improve the
generalization capability of final policy. We call this overall solution,
Multi-Agent Active Neural SLAM (MAANS). MAANS substantially outperforms
classical planning-based baselines for the first time in a photo-realistic 3D
simulator, Habitat. Code and videos can be found at
https://sites.google.com/view/maans.


  For maintaining gauge invariance in a magnetic field, the heat current
operator should include the magnetic term. Taking this term into account, we
revised calculations of the Nernst-Ettingshausen effect above the
superconducting transition. We found that the fluctuations of the modulus of
the order parameter do not change the particle-hole asymmetry (PHA) of the
thermomagnetic effects. As in the normal state, the thermomagnetic effects in
the fluctuation region are proportional to the square of PHA and, therefore,
small. Large Nernst effect observed in the high-$T_c$ cuprates requires
vortex-like excitations due to the phase fluctuations, which are beyond the
Gaussian-fluctuation theory.


  If a chain is initially at rest in a beaker at a height h1 above the ground,
and the end of the chain is pulled over the rim of the beaker and down towards
the ground and then released, the chain will spontaneously "flow" out of the
beaker under gravity. Furthermore, the beads do not simply drag over the edge
of the beaker but form a fountain reaching a height h2 above it. We show that
the formation of a fountain requires that the beads come into motion not only
by being pulled upwards by the part of the chain immediately above the pile,
but also by being pushed upwards by an anomalous reaction force from the pile
of stationary chain. We propose possible origins for this force, argue that its
magnitude will be proportional to the square of the chain velocity, and predict
and verify experimentally that h2 is proportional to h1.


  Interpreting the recently discovered narrow exotic baryons as pentaquark
states, we discuss, along an old argument of ours, the isospin mixing occurring
within the two doublets of $Q = -1$ and Q=0 states lying inside the $S=-2$
($\Xi$-cascade) sector. We argue that, at least within the Jaffe-Wilczek
assignment, presently available data already indicate that mixing should occur
at an observable level in both charge sectors, with mixing angles that can be
predicted in terms of ratios of observable mass splittings.


  We explicitly compute the Compton amplitude for the scattering of a photon
and a (massless) ``electron/positron'' at tree level and one loop, in a
four-dimensional fermionic heterotic string model. We comment on the
relationship between the amplitudes we compute in string theory and the
corresponding ones in field theory.


  Based on $(448.1 \pm 2.9 )\times 10^6$ $\psi(3686)$ events collected with the
BESIII detector operating at the BEPCII collider, the decay
$\psi(3686)\rightarrow \phi K_{S}^{0} K_{S}^{0}$ is observed for the first
time. Taking the interference between $\psi(3686)$ decay and continuum
production into account, the branching fraction of this decay is measured to be
$\mathcal{B}(\psi(3686)\rightarrow\phi K_S^0 K_S^0 )$ = $(3.53 $ $\pm$ $0.20$
$\pm$ $0.21$)$\times 10^{-5}$, where the first uncertainty is statistical and
the second is systematic. Combining with the world average value for ${\mathcal
B}(J/\psi\to \phi K^0_SK^0_S)$, the ratio $\mathcal{B}(\psi(3686)\rightarrow
\phi K_{S}^{0} K_{S}^{0})/\mathcal{B}(J/\psi\rightarrow \phi K_{S}^{0}
K_{S}^{0}) $ is determined to be $(6.0\pm 1.6)$%, which is suppressed relative
to the 12% rule.


  We present a systematic approach to finding Higgs vacuum expectation values,
which break a symmetry G to differently embedded isomorphic copies of a
subgroup $H \subset G$ . We give an explicit formula for recovering each point
in the vacuum manifold of a Higgs field which breaks G -> H. In particular we
systematically identify the vacuum manifold G/H with linear combinations of the
vacuum expectation values breaking G -> H_1 -> ... -> H_l. We focus on the most
applicable case for current work on grand unified theories in extra dimensional
models and low-energy effective theories for quantum chromodynamics. Here the
subgroup, H, stabilizes the highest weight of the fundamental representation
leading to a simple expression for each element of the vacuum manifold;
especially for an adjoint Higgs field. These results are illustrated explicitly
for adjoint Higgs fields and clearly linked to the mathematical formalism of
Weyl groups. We use the final section to explicitly demonstrate how our work
contributes to two contemporary high-energy physics research areas.


  We perform a study the quark-gluon vertex function with a quenched Wilson
gauge action and a variety of fermion actions. These include the domain wall
fermion action (with exponentially accurate chiral symmetry) and the Wilson
clover action both with the non-perturbatively improved clover coefficient as
well as with a number of different values for this coefficient. We find that
the domain wall vertex function behaves very well in the large momentum
transfer region. The off-shell vertex function for the on-shell improved clover
class of actions does not behave as well as the domain wall case and,
surprisingly, shows only a weak dependence on the clover coefficient $c_{SW}$
for all components of its Dirac decomposition and across all momenta. Including
off-shell improvement rotations for the clover fields can make this action
yield results consistent with those from the domain wall approach, as well as
helping to determine the off-shell improved coefficient $c_q^\prime$.


  Super Star Clusters (Mecl > 10^5 Msol) are the largest stellar nurseries in
our local Universe, containing hundreds of thousands to millions of young stars
within a few light years. Many of these systems are found in external galaxies,
especially in pairs of interacting galaxies, and in some dwarf galaxies, but
relatively few in disk galaxies like our own Milky Way. We show that a possible
explanation for this difference is the presence of shear in normal spiral
galaxies which impedes the formation of the very large and dense super star
clusters but prefers the formation of loose OB associations possibly with a
less massive cluster at the center. In contrast, in interacting galaxies and in
dwarf galaxies, regions can collapse without having a large-scale sense of
rotation. This lack of rotational support allows the giant clouds of gas and
stars to concentrate into a single, dense and gravitationally bound system.


  This is the second part of the work on differential models of the Anderson
duals to the stable tangential $G$-bordism theories $I\Omega^G$, motivated by
classifications of invertible QFT's. Using the model constructed in the first
part \cite{YamashitaYonekura2021}, in this paper we show that pushforwards in
generalized differential cohomology theories induces transformations between
differential cohomology theories which refine the Anderson duals to
multiplicative genera. This gives us a unified understanding of an important
class of elements in the Anderson duals with physical origins.


  This paper proposes a general formulation for temporal parallelisation of
dynamic programming for optimal control problems. We derive the elements and
associative operators to be able to use parallel scans to solve these problems
with logarithmic time complexity rather than linear time complexity. We apply
this methodology to problems with finite state and control spaces, linear
quadratic tracking control problems, and to a class of nonlinear control
problems. The computational benefits of the parallel methods are demonstrated
via numerical simulations run on a graphics processing unit.


  We study the dynamics of a Brownian circle swimmer with a time-dependent
self-propulsion velocity in an external temporally varying harmonic potential.
For several situations, the noise-free swimming paths, the noise-averaged mean
trajectories, and the mean square displacements are calculated analytically or
by computer simulation. Based on our results, we discuss optimal swimming
strategies in order to explore a maximum spatial range around the trap center.
In particular, we find a resonance situation for the maximum escape distance as
a function of the various frequencies in the system. Moreover, the influence of
the Brownian noise is analyzed by comparing noise-free trajectories at zero
temperature with the corresponding noise-averaged trajectories at finite
temperature. The latter reveal various complex self-similar spiral or
rosette-like patterns. Our predictions can be tested in experiments on
artificial and biological microswimmers under dynamical external confinement.


  An ordering between the quantum states emerging from a single mode
gauge-covariant bosonic Gaussian channel is proven. Specifically, we show that
within the set of input density matrices with the same given spectrum, the
element passive with respect to the Fock basis (i.e. diagonal with decreasing
eigenvalues) produces an output which majorizes all the other outputs emerging
from the same set. When applied to pure input states, our finding includes as a
special case the result of A. Mari, et al., Nat. Comm. 5, 3826 (2014) which
implies that the output associated to the vacuum majorizes the others.


  In this work, we present a generic approach to transform CSS codes by
building upon their equivalence to phase-free ZX diagrams. Using the ZX
calculus, we demonstrate diagrammatic transformations between encoding maps
associated with different codes. As a motivating example, we give explicit
transformations between the Steane code and the quantum Reed-Muller code, since
by switching between these two codes, one can obtain a fault-tolerant universal
gate set. To this end, we propose a bidirectional rewrite rule to find a (not
necessarily transversal) physical implementation for any logical ZX diagram in
any CSS code.
  Then we focus on two code transformation techniques: code morphing, a
procedure that transforms a code while retaining its fault-tolerant gates, and
gauge fixing, where complimentary codes can be obtained from a common subsystem
code (e.g., the Steane and the quantum Reed-Muller codes from the [[15,1,3,3]]
code). We provide explicit graphical derivations for these techniques and show
how ZX and graphical encoder maps relate several equivalent perspectives on
these code-transforming operations.


  In this paper we outline an algorithmic approach to compute Puiseux series
expansions for algebraic surfaces. The series expansions originate at the
intersection of the surface with as many coordinate planes as the dimension of
the surface. Our approach starts with a polyhedral method to compute cones of
normal vectors to the Newton polytopes of the given polynomial system that
defines the surface. If as many vectors in the cone as the dimension of the
surface define an initial form system that has isolated solutions, then those
vectors are potential tropisms for the initial term of the Puiseux series
expansion. Our preliminary methods produce exact representations for solution
sets of the cyclic $n$-roots problem, for $n = m^2$, corresponding to a result
of Backelin.


  The peeling decoding for spatially coupled low-density parity-check (SC-LDPC)
codes is analyzed for a binary erasure channel. An analytical calculation of
the mean evolution of degree-one check nodes of protograph-based SC-LDPC codes
is given and an estimate for the covariance evolution of degree-one check nodes
is proposed in the stable decoding phase where the decoding wave propagates
along the chain of coupled codes. Both results are verified numerically.
Protograph-based SC-LDPC codes turn out to have a more robust behavior than
unstructured random SC-LDPC codes. Using the analytically calculated
parameters, the finite- length scaling laws for these constructions are given
and verified by numerical simulations.


  A famous theorem of Szemer\'edi asserts that any set of integers of positive
upper density will contain arbitrarily long arithmetic progressions. In its
full generality, we know of four types of arguments that can prove this
theorem: the original combinatorial (and graph-theoretical) approach of
Szemer\'edi, the ergodic theory approach of Furstenberg, the Fourier-analytic
approach of Gowers, and the hypergraph approach of Nagle-R\"odl-Schacht-Skokan
and Gowers. In this lecture series we introduce the first, second and fourth
approaches, though we will not delve into the full details of any of them. One
of the themes of these lectures is the strong similarity of ideas between these
approaches, despite the fact that they initially seem rather different.


  We employ the pinching theorem, ensuring that some operators A admit any
sequence of contractions as an operator diagonal of A, to deduce/improve two
recent theorems of Kennedy-Skoufranis and Loreaux-Weiss for conditional
expectations onto a masa in the algebra of operators on a Hilbert space. We
also get a few results for sums in a unitary orbit.


  Molecular cooling is essential for studying the formation of sub-structure of
dissipative dark-matter halos that may host compact objects such as black
holes. Here, we analyze the reaction rates relevant for the formation,
dissociation, and transition of hydrogenic molecules while allowing for
different values of the physical parameters: the coupling constant, the proton
mass, and the electron mass. For all cases, we re-scale the reaction rates for
the standard molecular hydrogen, so our results are valid as long as the dark
matter is weakly coupled and one of the fermions is much heavier than the
other. These results will allow a robust numerical treatment of cosmic
structure, in particular for mini-halos for which molecular cooling is
important, in a dissipative dark matter scenario.


  Optimal power flow (OPF) is a critical optimization problem for power systems
to operate at points where cost or operational objectives are optimized. Due to
the non-convexity of the set of feasible OPF operating points, it is
non-trivial to transition the power system from its current operating point to
the optimal one without violating constraints. On top of that, practical
considerations dictate that the transition should be achieved using a small
number of small-magnitude control actions. To solve this problem, this paper
proposes an algorithm for computing a transition path by framing it as a
shortest path problem. This problem is formulated in terms of a discretized
piece-wise linear path, where the number of pieces is fixed a priori in order
to limit the number of control actions. This formulation yields a nonlinear
optimization problem (NLP) with a block tridiagonal structure, which we
leverage by utilizing a specialized interior point method. An initial feasible
path for our method is generated by solving a sequence of relaxations which are
then tightened in a homotopy-like procedure. Numerical experiments illustrate
the effectiveness of the algorithm.


  This paper aims at looking for Frobenius subcategories, via the separated
monomorphism category ${\rm smon}(Q, I, \x)$, and on the other hand, to
establish an {\rm RSS} equivalence from ${\rm smon}(Q, I, \x)$ to its dual
${\rm sepi}(Q, I, \x)$. For a bound quiver $(Q, I)$ and an algebra $A$, where
$Q$ is acyclic and $I$ is generated by monomial relations, let
$\Lambda=A\otimes_k kQ/I$. For any additive subcategory $\x$ of $A$-mod, we
construct ${\rm smon}(Q, I, \x)$ combinatorially. This construction describe
Gorenstein-projective $\m$-modules as $\mathcal {GP}(\m) = {\rm smon}(Q, I,
\mathcal {GP}(A))$. It admits a homological interpretation, and enjoys a
reciprocity ${\rm smon}(Q, I, \ ^\bot T)= \ ^\bot (T\otimes kQ/I)$ for a
cotilting $A$-module $T$. As an application, ${\rm smon}(Q, I, \x)$ has
Auslander-Reiten sequences if $\x$ is resolving and contravariantly finite with
$\widehat{\x}=A$-mod. In particular, ${\rm smon}(Q, I, A)$ has Auslander-Reiten
sequences. It also admits a filtration interpretation as ${\rm smon}(Q, I,
\mathscr{X})={\rm Fil}(\mathscr{X}\otimes \mathcal P(kQ/I))$, provided that
$\x$ is extension-closed. As an application, ${\rm smon}(Q, I, \x)$ is an
extension-closed Frobenius subcategory if and only if so is $\x$. This gives
"new" Frobenius subcategories of $\m$-mod in the sense that they are not
$\mathcal{GP}(\m)$. Ringel-Schmidmeier-Simson equivalence ${\rm smon}(Q, I,
\x)\cong{\rm sepi}(Q, I, \x)$ is introduced and the existence is proved for
arbitrary extension-closed subcategories $\x$. In particular, the Nakayama
functor $\mathcal N_\m$ gives an {\rm RSS} equivalence ${\rm smon}(Q, I,
A)\cong{\rm sepi}(Q, I, A)$ if and only if $A$ is Frobenius. For a chain $Q$
with arbitrary $I$, an explicit formula of an {\rm RSS} equivalence is found
for arbitrary additive subcategories $\x$.


  The major perspective of this paper is to provide more evidence into the
empirical determinants of capital structure adjustment in different
macroeconomics states by focusing and discussing the relative importance of
firm-specific and macroeconomic characteristics from an alternative scope in
U.S. This study extends the empirical research on the topic of capital
structure by focusing on a quantile regression method to investigate the
behavior of firm-specific characteristics and macroeconomic variables across
all quantiles of distribution of leverage (total debt, long-terms debt and
short-terms debt). Thus, based on a partial adjustment model, we find that
long-term and short-term debt ratios varying regarding their partial adjustment
speeds; the short-term debt raises up while the long-term debt ratio slows down
for same periods.


  Quantum key distribution (QKD) takes advantage of fundamental properties of
quantum physics to allow two distant parties to share a secret key; however,
QKD is hampered by a distance limitation of a few hundred kilometers on earth.
The most immediate solution for global coverage is to use a satellite, which
can receive separate QKD transmissions from two or more ground stations and act
as a trusted node to link these ground stations. In this article, we report a
system capable of performing QKD in the high loss regime expected in an uplink
to a satellite using weak coherent pulses and decoy states. Such a scenario
profits from the simplicity of its receiver payload, but has so far considered
to be infeasible due to very high transmission losses (40 - 50 dB). The high
loss is overcome by implementing an innovative photon source and advanced
timing analysis. Our system handles up to 57 dB photon loss in the infinite key
limit, confirming the viability of the satellite uplink scenario. We emphasize
that while this system was designed with a satellite uplink in mind, it could
just as easily overcome high losses on any free space QKD link.


  We investigate the single production of vector-like quarks at the High
Luminosity LHC (HL-LHC). With the assumed (enhanced) couplings to third
generation quarks of the standard model, vector-like quarks $B/X$ are produced
in association with a bottom ($b$) or top ($t$) quark, which correspond to
$Bbq$ and $Btq/Xtq$ production modes, including an additional soft forward jet
from the spectator quark ($q$). This study focuses on high-mass vector-like
quarks $B/X$ decaying into a top quark and a $W$ boson, resulting in the final
state jets emerging from hadronically decaying top quark ($t\to Wb$) and $W$
boson ($W\to q\bar{q}'$). The events with $W$ boson and $t$ quark have been
analysed using tagging techniques for large-radius jets. The scan ranges of the
mass ($1000<m_{B/X}<3000$ GeV) for the relative width
$\Gamma_{B/X}/m_{B/X}=0.1$ and $\Gamma_{B/X}/m_{B/X}=0.01$ of vector-like $B/X$
quarks have been investigated. From the results of the analysis, the masses of
vector like quarks $B$($X$) up to $2491$ ($2364$) GeV and $2018$ ($1873$) GeV
can be excluded corresponding to these relative width cases at $95\%$ CL
depending on the type and branching scenarios at integrated luminosity
projection of $3$ ab$^{-1}$ at the HL-LHC.


  It is known in vacuum that the three-flavor neutrino survival probability can
be approximated by the effective two-flavor form to first orders in $\epsilon
\equiv \Delta m^2_{21} / \Delta m^2_{31}$, with introduction of the effective
$\Delta m^2_{\alpha \alpha}$ ($\alpha = e, \mu, \tau$), in regions of neutrino
energy $E$ and baseline $L$ such that $\Delta m^2_{31} L / 2E \sim \pi$. Here,
we investigate the question of whether the similar effective two-flavor
approximation can be formulated for the survival probability in matter. Using a
perturbative framework with the expansion parameters $\epsilon$ and $s_{13}
\propto \sqrt{\epsilon}$, we give an affirmative answer to this question and
the resultant two-flavor form of the probability is valid to order $\epsilon$.
However, we observe a contrived feature of the effective $\Delta m^2_{\alpha
\alpha} (a)$ in matter. It ceases to be a combination of the fundamental
parameters and has energy dependence, which may be legitimate because it comes
from the matter potential. But, it turned out that $\Delta m^2_{\mu \mu} (a)$
becomes $L$-dependent, though $\Delta m^2_{ee} (a)$ is not, which casts doubt
on adequacy of the concept of effective $\Delta m^2$ in matter. We also find
that the appearance probability in vacuum admits, to order $\epsilon$, the
similar effective two-flavor form with a slightly different effective $\Delta
m^2_{\beta \alpha}$ from the disappearance channel. A general result is derived
to describe suppression of the matter effect in the oscillation probability.


  We investigate the coherent control of the photo\-electron angular
distribution in bichromatic atomic ionization. Neon is selected as target since
it is one of the most popular systems in current gas-phase experiments with
free-electron lasers (FELSs). In particular, we tackle practical questions,
such as the role of the fine-structure splitting, the pulse length, and the
intensity. Time-dependent and stationary perturbation theory are employed, and
we also solve the time-dependent Schr\"odinger equation in a single-active
electron model. We consider neon ionized by a FEL pulse whose fundamental
frequency is in resonance with either $2p-3s$ or $2p-4s$ excitation. The
contribution of the non\-resonant two-photon process and its potential
constructive or destructive role for quantum coherent control is investigated.


  A polar-coded transmission (PCT) scheme with joint channel estimation and
decoding is proposed for channels with unknown channel state information (CSI).
The CSI is estimated via successive cancellation (SC) decoding and the
constraints imposed by the frozen bits. SC list decoding with an outer code
improves performance, including resolving a phase ambiguity when using
quadrature phase-shift keying (QPSK) and Gray labeling. Simulations with 5G
polar codes and QPSK show gains of up to $2$~dB at a frame error rate (FER) of
$10^{-4}$ over pilot-assisted transmission for various non-coherent models.
Moreover, PCT performs within a few tenths of a dB to a coherent receiver with
perfect CSI. For Rayleigh block-fading channels, PCT outperforms an FER upper
bound based on random coding and within one dB of a lower bound.


  In this paper we study the topology of the cobordism category of open and
closed strings. This is a 2-category in which the objects are compact
one-manifolds whose boundary components are labeled by an indexing set (the set
of "D-branes"), the 1-morphisms are cobordisms of manifolds with boundary, and
the 2-morphisms are diffeomorphisms of the surface cobordisms. Our methods and
techniques are direct generalizations of those used by U. Tillmann in her study
of the category of closed strings. We input the striking theorem of Madsen and
Weiss regarding the topology of the stable mapping class group to identify the
homotopy type of the geometric realization of the category of open and closed
strings as an infinite loop space.


  In bosonic quantum metrology, the estimate of a loss parameter is typically
performed by means of pure states, such as coherent, squeezed or entangled
states, while mixed thermal probes are discarded for their inferior
performance. Here we show that thermal sources with suitable correlations can
be engineered in such a way to approach, or even surpass, the error scaling of
coherent states in the presence of general Gaussian decoherence. Our findings
pave the way for practical quantum metrology with thermal sources in optical
instruments (e.g., photometers) or at different wavelengths (e.g., far
infrared, microwave or X-ray) where the generation of quantum features, such as
coherence, squeezing or entanglement, may be extremely challenging.


  To better understand a preferred magnetic field configuration and its
evolution during Coronal Mass Ejection events, we investigated the spatial and
temporal evolution of photospheric magnetic fields in the active region NOAA
9236 that produced eight flare-associated CMEs during the time period of 2000
November 23-26. The time variations of the total magnetic helicity injection
rate and the total unsigned magnetic flux are determined and examined not only
in the entire active region but also in some local regions such as the main
sunspots and the CME-associated flaring regions using SOHO/MDI magnetogram
data. As a result, we found that: (1) in the sunspots, a large amount of
postive (right-handed) magnetic helicity was injected during most of the
examined time period, (2) in the flare region, there was a continuous injection
of negative (left-handed) magnetic helicity during the entire period,
accompanied by a large increase of the unsigned magnetic flux, and (3) the
flaring regions were mainly composed of emerging bipoles of magnetic fragments
in which magnetic field lines have substantially favorable conditions for
making reconnection with large-scale, overlying, and oppositely directed
magnetic field lines connecting the main sunspots. These observational findings
can also be well explained by some MHD numerical simulations for CME initiation
(e.g., reconnection-favored emerging flux models). We therefore conclude that
reconnection-favored magnetic fields in the flaring emerging flux regions play
a crucial role in producing the multiple flare-associated CMEs in NOAA 9236.


  Respiratory disease, the third leading cause of deaths globally, is
considered a high-priority ailment requiring significant research on
identification and treatment. Stethoscope-recorded lung sounds and artificial
intelligence-powered devices have been used to identify lung disorders and aid
specialists in making accurate diagnoses. In this study, audio-spectrogram
vision transformer (AS-ViT), a new approach for identifying abnormal
respiration sounds, was developed. The sounds of the lungs are converted into
visual representations called spectrograms using a technique called short-time
Fourier transform (STFT). These images are then analyzed using a model called
vision transformer to identify different types of respiratory sounds. The
classification was carried out using the ICBHI 2017 database, which includes
various types of lung sounds with different frequencies, noise levels, and
backgrounds. The proposed AS-ViT method was evaluated using three metrics and
achieved 79.1% and 59.8% for 60:40 split ratio and 86.4% and 69.3% for 80:20
split ratio in terms of unweighted average recall and overall scores
respectively for respiratory sound detection, surpassing previous
state-of-the-art results.


  We introduce a new regression framework, Gaussian process regression networks
(GPRN), which combines the structural properties of Bayesian neural networks
with the non-parametric flexibility of Gaussian processes. This model
accommodates input dependent signal and noise correlations between multiple
response variables, input dependent length-scales and amplitudes, and
heavy-tailed predictive distributions. We derive both efficient Markov chain
Monte Carlo and variational Bayes inference procedures for this model. We apply
GPRN as a multiple output regression and multivariate volatility model,
demonstrating substantially improved performance over eight popular multiple
output (multi-task) Gaussian process models and three multivariate volatility
models on benchmark datasets, including a 1000 dimensional gene expression
dataset.


  A consistent framework has been put forward to quantize the isentropic,
compressible and inviscid fluid model in the Hamiltonian framework, using the
Clebsch parameterization. The naive quantization is hampered by the
non-canonical (in particular field dependent) Poisson Bracket algebra. To
overcome this problem, the Batalin-Tyutin \cite{12} quantization formalism is
adopted in which the original system is converted to a local gauge theory and
is embedded in a {\it canonical} extended phase space. In a different reduced
phase space scheme \cite{vy} also the original model is converted to a gauge
theory and subsequently the two distinct gauge invariant formulations of the
fluid model are related explicitly. This strengthens the equivalence between
the relativistic membrane (where a gauge invariance is manifest) and the fluid
(where the gauge symmetry is hidden). Relativistic generalizations of the
extended model is also touched upon.


  We consider higher-spin gravity in (Euclidean) AdS_4, dual to a free vector
model on the 3d boundary. In the bulk theory, we study the linearized version
of the Didenko-Vasiliev black hole solution: a particle that couples to the
gauge fields of all spins through a BPS-like pattern of charges. We study the
interaction between two such particles at leading order. The sum over spins
cancels the UV divergences that occur when the two particles are brought close
together, for (almost) any value of the relative velocity. This is a
higher-spin enhancement of supergravity's famous feature, the cancellation of
the electric and gravitational forces between two BPS particles at rest. In the
holographic context, we point out that these "Didenko-Vasiliev particles" are
just the bulk duals of bilocal operators in the boundary theory. For this
identification, we use the Penrose transform between bulk fields and twistor
functions, together with its holographic dual that relates twistor functions to
boundary sources. In the resulting picture, the interaction between two
Didenko-Vasiliev particles is just a geodesic Witten diagram that calculates
the correlator of two boundary bilocals. We speculate on implications for a
possible reformulation of the bulk theory, and for its non-locality issues.