  In this paper, the fundamental limits on the rates at which information and
energy can be simultaneously transmitted over an additive white Gaussian noise
channel are studied under the following assumptions: $(a)$ the channel is
memoryless; $(b)$ the number of channel input symbols (constellation size) and
block length are finite; and $(c)$ the decoding error probability (DEP) and the
energy outage probability (EOP) are bounded away from zero. In particular, it
is shown that the limits on the maximum information and energy transmission
rates; and the minimum DEP and EOP, are essentially set by the type induced by
the code used to perform the transmission. That is, the empirical frequency
with which each channel input symbol appears in the codewords. Using this
observation, guidelines for optimal constellation design for simultaneous
energy and information transmission are presented.


  Intelligent biological systems are characterized by their embodiment in a
complex environment and the intimate interplay between their nervous systems
and the nonlinear mechanical properties of their bodies. This coordination, in
which the dynamics of the motor system co-evolved to reduce the computational
burden on the brain, is referred to as ``mechanical intelligence'' or
``morphological computation''. In this work, we seek to develop machine
learning analogs of this process, in which we jointly learn the morphology of
complex nonlinear elastic solids along with a deep neural network to control
it. By using a specialized differentiable simulator of elastic mechanics
coupled to conventional deep learning architectures -- which we refer to as
neuromechanical autoencoders -- we are able to learn to perform morphological
computation via gradient descent. Key to our approach is the use of mechanical
metamaterials -- cellular solids, in particular -- as the morphological
substrate. Just as deep neural networks provide flexible and
massively-parametric function approximators for perceptual and control tasks,
cellular solid metamaterials are promising as a rich and learnable space for
approximating a variety of actuation tasks. In this work we take advantage of
these complementary computational concepts to co-design materials and neural
network controls to achieve nonintuitive mechanical behavior. We demonstrate in
simulation how it is possible to achieve translation, rotation, and shape
matching, as well as a ``digital MNIST'' task. We additionally manufacture and
evaluate one of the designs to verify its real-world behavior.


  We obtain a class of exact solutions representing null particles moving in
three-dimensional (anti-) de Sitter spaces by boosting the corresponding static
point source solutions given by Deser and Jackiw. In de Sitter space the
resulting solution describes two null particles moving on the (circular)
cosmological horizon, while in anti-de Sitter space it describes a single null
particle propagating from one side of the universe to the other. We also boost
the BTZ black hole solution to the ultrarelativistic limit and obtain the
solution for a spinning null particle moving in anti-de Sitter space. We find
that the ultrarelativistic geometry of the black hole is exactly the same as
that resulting from boosting the Deser-Jackiw solution when the angular
momentum of the hole vanishes. A general class of solutions is also obtained
which represents several null particles propagating in the Deser-Jackiw
background. The differences between the three-dimensional and four-dimensional
cases are also discussed.


  Exact solutions of the Dirac equation, a system of four partial differential
equations, are rare. The vast majority of them are for highly symmetric
stationary systems. Moreover, only a handful of solutions for time dependent
dynamics exists. Given the growing number of applications of high energy
electron beams interacting with a variety of quantum systems in laser fields,
novel methods for finding exact solutions to the Dirac equation are called for.
We present a method for building up solutions to the Dirac equation employing a
recently introduced approach for the description of spinorial fields and their
driving electromagnetic fields in terms of geometric algebras. We illustrate
the method by developing several stationary as well as non-stationary solutions
of the Dirac equation with well defined orbital angular momentum along the
electron's propagation direction. The first set of solutions describe free
electron beams in terms of Bessel functions as well as stationary solutions for
both a homogeneous and an inhomogeneous magnetic field. The second set of
solutions are new and involve a plane electromagnetic wave combined with a
generally inhomogeneous longitudinal magnetic field. Moreover, the developed
technique allows us to derive general physical properties of the dynamics in
such field configurations, as well as provides physical predictions on the
self-consistent electromagnetic fields induced by the dynamics.


  In this paper, we prove a global bifurcation result for the existence of
non-radial branches of solutions to the paramterized family of
$\Gamma$-symmetric problems $-\Delta u=f(\alpha,z,u)$, $u|_{\partial D}=0$ on
the unit disc $D:=\{z\in \mathbb{C} : |z|<1\}$ with $u(z)\in \mathbb{R}^k$,
where $\mathbb{R}^k$ is an orthogonal $\Gamma$-representation, $f: \mathbb{R}
\times \overline{D} \times \mathbb{R}^k\to \mathbb{R}^k$ is a sub-linear
$\Gamma$-equivariant continuous function, differentiable with respect to $u$ at
zero and satisfying the conditions $f(\alpha, e^{i\theta}z,u)=f(\alpha, z,u)$
for all $\theta\in \mathbb{R}$ and $f(z,-u)=-f(z,u)$.


  YMn$_6$Sn$_6$ consists of two types of Mn-based kagome planes stacked along
$c$-axis having a complex magnetic interactions. We report a spin
reconstruction in YMn$_6$Sn$_6$ from ferromagnet (FM) into a combination of two
incommensurate spin spirals (SSs) originating from two different type of Mn
kagome planes driven by frustrated magnetic exchanges along the $c$-axis with
inclusion of Hubbard U. The pitch angle and wave vector of the incommensurate
SSs are $\sim$89.3$^{\circ}$ and $\sim$ (0 0 0.248) respectively which are in
excellent agreement with experiment. We employed an effective model Hamiltonian
constructed out of exchange interactions to capture experimentally observed
non-equivalent nature of the two incommensurate SSs which also explain FM-SS
crossover due to antiferromagntic spin exchange with correlation. We further
report the existence of topological magnon with spin-orbit coupling in
incommensurate SS phase of YMn$_6$Sn$_6$ by calculating the topological
invariants and Berry curvature profile. The location of Dirac magnon in energy
landscape at 73 meV matches with another experimental report. We demonstrate
the accuracy of our results by highlighting experimental features in
YMn$_6$Sn$_6$.


  Event structures have emerged as a foundational model for concurrent
computation, explaining computational processes by outlining the events and the
relationships that dictate their execution. They play a pivotal role in the
study of key aspects of concurrent computation models, such as causality and
independence, and have found applications across a broad range of languages and
models, spanning realms like persistence, probabilities, and quantum computing.
Recently, event structures have been extended to address reversibility, where
computational processes can undo previous computations. In this context,
reversible event structures provide abstract representations of processes
capable of both forward and backward steps in a computation. Since their
introduction, event structures have played a crucial role in bridging
operational models, traditionally exemplified by Petri nets and process
calculi, with denotational ones, i.e., algebraic domains. In this context, we
revisit the standard connection between Petri nets and event structures under
the lenses of reversibility. Specifically, we introduce a subset of contextual
Petri nets, dubbed reversible causal nets, that precisely correspond to
reversible prime event structures. The distinctive feature of reversible causal
nets lies in deriving causality from inhibitor arcs, departing from the
conventional dependence on the overlap between the post and preset of
transitions. In this way, we are able to operationally explain the full model
of reversible prime event structures.


  A significantly faster algorithm is presented for the original kNN mode
seeking procedure. It has the advantages over the well-known mean shift
algorithm that it is feasible in high-dimensional vector spaces and results in
uniquely, well defined modes. Moreover, without any additional computational
effort it may yield a multi-scale hierarchy of clusterings. The time complexity
is just O(n^1.5). resulting computing times range from seconds for 10^4 objects
to minutes for 10^5 objects and to less than an hour for 10^6 objects. The
space complexity is just O(n). The procedure is well suited for finding large
sets of small clusters and is thereby a candidate to analyze thousands of
clusters in millions of objects.
  The kNN mode seeking procedure can be used for active learning by assigning
the clusters to the class of the modal objects of the clusters. Its feasibility
is shown by some examples with up to 1.5 million handwritten digits. The
obtained classification results based on the clusterings are compared with
those obtained by the nearest neighbor rule and the support vector classifier
based on the same labeled objects for training. It can be concluded that using
the clustering structure for classification can be significantly better than
using the trained classifiers. A drawback of using the clustering for
classification, however, is that no classifier is obtained that may be used for
out-of-sample objects.


  Measures of the direction and strength of the interdependence between two
time series are evaluated and modified in order to reduce the bias in the
estimation of the measures, so that they give zero values when there is no
causal effect. For this, point shuffling is employed as used in the frame of
surrogate data. This correction is not specific to a particular measure and it
is implemented here on measures based on state space reconstruction and
information measures. The performance of the causality measures and their
modifications is evaluated on simulated uncoupled and coupled dynamical systems
and for different settings of embedding dimension, time series length and noise
level. The corrected measures, and particularly the suggested corrected
transfer entropy, turn out to stabilize at the zero level in the absence of
causal effect and detect correctly the direction of information flow when it is
present. The measures are also evaluated on electroencephalograms (EEG) for the
detection of the information flow in the brain of an epileptic patient. The
performance of the measures on EEG is interpreted, in view of the results from
the simulation study.


  A dynamic state estimation method of integrated natural gas and electric
power systems (IGESs) in proposed. Firstly, the coupling model of gas pipeline
networks and power systems by gas turbine units (GTUs) is established.
Secondly, the Kalman filter based linear DSE model for the IGES is built. The
gas density and mass flow rate, as well as the real and imaginary parts of bus
voltages are taken as states, which are predicted by the linearized fluid
dynamic equations of gases and exponential smoothing techniques. Boundary
conditions of pipeline networks are used as supplementary constraints in the
system model. At last, the proposed method is applied to an IGES including a
30-node pipeline network and IEEE 39-bus system coupled by two GTUs. Two
indexes are used to evaluate the DSE performance under three measurement error
conditions, and the results show that the DSE can obtain the accurate dynamic
states in different conditions.


  We investigate the effect of strain on the etching rate of two SiGe wet
etchants, namely NH4OH:H2O2 and H2O2. For both etchants, we found that there is
no appreciable strain selectivity, i.e. the etching rates do not depend on the
actual strain state in the SiGe films. Instead, for the NH4OH:H2O2 solution,
the rates are primarily determined by the Ge content. Finally, we show that
both etchants are isotropic with no preferential etching of particular facets.


  Many real-world applications can be formulated as multi-agent cooperation
problems, such as network packet routing and coordination of autonomous
vehicles. The emergence of deep reinforcement learning (DRL) provides a
promising approach for multi-agent cooperation through the interaction of the
agents and environments. However, traditional DRL solutions suffer from the
high dimensions of multiple agents with continuous action space during policy
search. Besides, the dynamicity of agents' policies makes the training
non-stationary. To tackle the issues, we propose a hierarchical reinforcement
learning approach with high-level decision-making and low-level individual
control for efficient policy search. In particular, the cooperation of multiple
agents can be learned in high-level discrete action space efficiently. At the
same time, the low-level individual control can be reduced to single-agent
reinforcement learning. In addition to hierarchical reinforcement learning, we
propose an opponent modeling network to model other agents' policies during the
learning process. In contrast to end-to-end DRL approaches, our approach
reduces the learning complexity by decomposing the overall task into sub-tasks
in a hierarchical way. To evaluate the efficiency of our approach, we conduct a
real-world case study in the cooperative lane change scenario. Both simulation
and real-world experiments show the superiority of our approach in the
collision rate and convergence speed.


  This paper concerns the density of the Hartman--Watson law. Yor (1980)
obtained an integral formula that gives a closed-form expression of the
Hartman--Watson density. In this paper, based on Yor's formula, we provide
alternative integral representations for the density. As an immediate
application, we recover in part a Dufresne's result (2001) that exhibits
remarkably simple representations for the laws of exponential additive
functionals of Brownian motion.


  We study the properties of t-t'-V model of hard-core bosons on the triangular
lattice that can be realized in optical lattices. By mapping to the spin-1/2
XXZ model in a field, we determine the phase diagram of the t-V model where the
supersolid characterized by the ordering pattern (x,x,-2x') ("ferrimagnetic" or
SS A) is a ground state for chemical potential \mu >3V. By turning on either
temperature or t' at half-filling \mu =3V, we find a first order transition
from SS A to the elusive supersolid characterized by the (x,-x,0) ordering
pattern ("antiferromagnetic" or SS C). In addition, we find a large region
where a superfluid phase becomes a solid upon raising temperature at fixed
chemical potential. This is an analog of the Pomeranchuk effect driven by the
large entropic effects associated with geometric frustration on the triangular
lattice.


  We study the dynamics of a driven Dicke model, where the collective spin is
rotated with a constant velocity around a fixed axis. The time evolution of the
mean photon number and of the atomic inversion is calculated using, on the one
hand, a numerical technique for the quantum dynamics of a small number of
two-level atoms, on the other hand, time-dependent mean-field theory for the
limit of a large number of atoms. We observe a reduction of the mean photon
number as compared to its equilibrium value. This dynamically generated
darkness is particularly pronounced slightly above the transition to a
superradiant phase. We attribute the effect to a slowing down of the motion in
the classical limit of a large ensemble and to an interplay of dynamic and
geometric phases in the quantum case.


  We derive the equation of self-similar solutions to mean curvature flow based
on the generalized Lawson-Osserman cone and prove the existence of
self-expanders by modifying the theory of equilibria in the autonomous system.
In particular, those self-expanders are unique if a local assumption is given.


  A compressible generalization of the Kraichnan model (Phys. Rev. Lett. 72,
1016 (1994)) of passive scalar advection is considered. The dynamical role of
compressibility on the intermittency of the scalar statistics is investigated
for the direct cascade regime. Simple physical arguments suggest that an
enhanced intermittency should appear for increasing compressibility, due to the
slowing down of Lagrangian trajectory separations. This is confirmed by a
numerical study of the dependence of intermittency exponents on the degree of
compressibility, by a Lagrangian method for calculating simultaneous N-point
tracer correlations.


  Much of the theory of large cardinals beyond a measurable cardinal concerns
the structure of elementary embeddings of the universe of sets into inner
models. This paper seeks to answer the question of whether the inner model
uniquely determines the elementary embedding.


  We show that $\bigoplus_{n \ge 0} {\mathrm H}^t({\bf GL}_n({\bf F}_q), {\bf
F}_\ell)$ canonically admits the structure of a module over the $q$-divided
power algebra (assuming $q$ is invertible in ${\bf F}_{\ell}$), and that, as
such, it is free and (for $q \neq 2$) generated in degrees $\le t$. As a
corollary, we show that the cohomology of a finitely generated ${\bf
VI}$-module in non-describing characteristic is eventually periodic in $n$. We
apply this to obtain a new result on the cohomology of unipotent Specht
modules.


  The standard energy conditions of classical general relativity are applied to
FLRW cosmologies containing sudden future singularities. Here we show, in a
model independent way, that although such cosmologies can satisfy the null,
weak and strong energy conditions, they always fail to satisfy the dominant
energy condition. They require a divergent spacelike energy flux in all but the
comoving frame.


  A thermo-mechanical continuum theory is proposed for dynamically loaded
glassy polymers. The theory is based on an ansatz for the Helmholtz free energy
where both the deviatoric and the volumetric contributions to the free energy
are rate-dependent. The requirement that the free energy is fully rate
dependent arises from the need to model the full range of conditions between
those found in quasi-static applications to those common in high-rate shock
loading scenarios. Using a purely equilibrium equation of state is found to be
insufficient. The resulting model, called the Glassy Amorphous Polymer (GAP)
model, suitably captures the thermo-mechanical behavior of both equilibrium
properties, but also high-rate phenomena like the shock Hugoniot.
Polymethylmethacrylate (PMMA) is used as a representative polymer because it is
one of the few polymers where sufficient experiments have been done to
determine many of the parameters required by the GAP model. An important part
of the GAP model is the Hierarchical Flow Stress (HFS) model, which is shown to
accurately represent the stress-strain behavior of PMMA over a broad range of
strain rates and temperatures. The HFS model replicates the details of stress
plateau, softening, and hardening behavior observed in glassy amorphous
polymers. The theory is not restricted to isothermal conditions. Analysis is
devoted to several issues associated with a non-equilibrium equation of state
(EOS). Because data is insufficient for the full determination of the model's
non-equilibrium EOS, several plausible conditions called the quasi-equilibrium
hypothesis are put forth to complete the model. Comparisons of experimental and
theoretical results over a wide-range of loading rates and conditions are
reported.


  Earth's interior, I posit, is like one of the rare, oxygen-starved "enstatite
chondrite" meteorites (and unlike a more-oxidized "ordinary chondrite" as has
been believed for seventy years). Laboratory-analyzed enstatite-chondrite
samples are comparable to having-in-hand impossibleto- gather deep-Earth
samples. Enstatite-chondrite formation in oxygen-starved conditions caused
oxygen-loving elements to occur, in part, as non-oxides in their iron-alloy.
Observations, consistent with solar abundance and behavior of chemical
elements, lead me to a new interpretation of: (1) Earth's early formation as a
Jupiter-like gas-giant, (2) its decompressionpowered surface geology, (3)
Earth's internal composition, and (4) a natural, planetocentric nuclear-fission
reactor as source of both the geomagnetic field and energy channeled to surface
"hot-spots". I present a unified vision of Earth formation and concomitant
dynamics that explains in a logical and causally related way: (1) fluid
Earth-core formation without wholeplanet melting, and (2) the myriad
measurements and observations, previously attributed to "plate tectonics", but
without necessitating mantle convection.


  On the basis of an electronic model with separable attractive interaction,
the precursors at high temperature and strong coupling of the d-wave
superconducting state are investigated in the one-particle spectral function
$A({\bf k},\omega)$ and the total density of states $\rho(\omega)$, with the
use of the self-consistent $t$-matrix approximation. In the low-density region,
it is found that a gap-like structure at the Fermi level appears in $A({\bf
k},\omega)$ and $\rho(\omega)$ above the superconducting transition
temperature. It is shown that the pseudogap energy scale is determined by the
binding energy of the Cooper-pair.


  The next generation of telescopes will acquire terabytes of image data on a
nightly basis. Collectively, these large images will contain billions of
interesting objects, which astronomers call sources. The astronomers' task is
to construct a catalog detailing the coordinates and other properties of the
sources. The source catalog is the primary data product for most telescopes and
is an important input for testing new astrophysical theories, but to construct
the catalog one must first detect the sources. Existing algorithms for catalog
creation are effective at detecting sources, but do not have rigorous
statistical error control. At the same time, there are several multiple testing
procedures that provide rigorous error control, but they are not designed to
detect sources that are aggregated over several pixels. In this paper, we
propose a technique that does both, by providing rigorous statistical error
control on the aggregate objects themselves rather than the pixels. We
demonstrate the effectiveness of this approach on data from the Chandra X-ray
Observatory Satellite. Our technique effectively controls the rate of false
sources, yet still detects almost all of the sources detected by procedures
that do not have such rigorous error control and have the advantage of
additional data in the form of follow up observations, which will not be
available for upcoming large telescopes. In fact, we even detect a new source
that was missed by previous studies. The statistical methods developed in this
paper can be extended to problems beyond Astronomy, as we will illustrate with
an example from Neuroimaging.


  In this review article we discuss recent constructions of global F-theory GUT
models and explain how to make use of toric geometry to do calculations within
this framework. After introducing the basic properties of global F-theory GUTs
we give a self-contained review of toric geometry and introduce all the tools
that are necessary to construct and analyze global F-theory models. We will
explain how to systematically obtain a large class of compact Calabi-Yau
fourfolds which can support F-theory GUTs by using the software package PALP.


  The Planck constant, with its mathematical symbol $h$, is a fundamental
constant in quantum mechanics that is associated with the quantization of light
and matter. It is also of fundamental importance to metrology, such as the
definition of ohm and volt, and the latest definition of kilogram. One of the
first measurements to determine the Planck constant is based on the
photoelectric effect, however, the values thus obtained so far have exhibited a
large uncertainty. The accepted value of the Planck constant,
6.62607015$\times$10$^{-34}$ J$\cdot$s, is obtained from one of the most
precise methods, the Kibble balance, which involves quantum Hall effect,
Josephson effect and the use of the International Prototype of the Kilogram
(IPK) or its copies. Here we present a precise determination of the Planck
constant by modern photoemission spectroscopy technique. Through the direct use
of the Einstein's photoelectric equation, the Planck constant is determined by
measuring accurately the energy position of the gold Fermi level using light
sources with various photon wavelengths. The precision of the measured Planck
constant, 6.62610(13)$\times$10$^{-34}$ J$\cdot$s, is four to five orders of
magnitude improved from the previous photoelectric effect measurements. It has
rendered photoemission method to become one of the most accurate methods in
determining the Planck constant. We propose that this direct method of
photoemission spectroscopy has advantages and a potential to further increase
its measurement precision of the Planck constant to be comparable to the most
accurate methods that are available at present.


  Recognition of multifrequency microwave (MW) electric fields is challenging
because of the complex interference of multifrequency fields in practical
applications. Rydberg atom-based measurements for multifrequency MW electric
fields is promising in MW radar and MW communications. However, Rydberg atoms
are sensitive not only to the MW signal but also to noise from atomic
collisions and the environment, meaning that solution of the governing Lindblad
master equation of light-atom interactions is complicated by the inclusion of
noise and high-order terms. Here, we solve these problems by combining Rydberg
atoms with deep learning model, demonstrating that this model uses the
sensitivity of the Rydberg atoms while also reducing the impact of noise
without solving the master equation. As a proof-of-principle demonstration, the
deep learning enhanced Rydberg receiver allows direct decoding of the
frequency-division multiplexed (FDM) signal. This type of sensing technology is
expected to benefit Rydberg-based MW fields sensing and communication.


  We study the response of a scalar thermal field to a $\delta$-probe in the
context of non-local ghost-free theories. In these theories a non-local form
factor is inserted into the kinetic part of the action which does not introduce
new poles. For the case of a static $\delta$-potential we obtain an explicit
expression for the thermal Hadamard function and use it for the calculation of
the thermal fluctuations. We then demonstrate how the presence of non-locality
modifies the amplitude of these fluctuations. Finally, we also discuss the
fluctuation-dissipation theorem in the context of ghost-free quantum field
theories at finite temperature.


  We calculate the chromatic polynomials $P$ for $n$-vertex strip graphs of the
form $J(\prod_{\ell=1}^m H)I$, where $J$ and $I$ are various subgraphs on the
left and right ends of the strip, whose bulk is comprised of $m$-fold
repetitions of a subgraph $H$. The strips have free boundary conditions in the
longitudinal direction and free or periodic boundary conditions in the
transverse direction. This extends our earlier calculations for strip graphs of
the form $(\prod_{\ell=1}^m H)I$. We use a generating function method. From
these results we compute the asymptotic limiting function $W=\lim_{n \to
\infty}P^{1/n}$; for $q \in {\mathbb Z}_+$ this has physical significance as
the ground state degeneracy per site (exponent of the ground state entropy) of
the $q$-state Potts antiferromagnet on the given strip. In the complex $q$
plane, $W$ is an analytic function except on a certain continuous locus ${\cal
B}$. In contrast to the $(\prod_{\ell=1}^m H)I$ strip graphs, where ${\cal B}$
(i) is independent of $I$, and (ii) consists of arcs and possible line segments
that do not enclose any regions in the $q$ plane, we find that for some
$J(\prod_{\ell=1}^m H)I$ strip graphs, ${\cal B}$ (i) does depend on $I$ and
$J$, and (ii) can enclose regions in the $q$ plane. Our study elucidates the
effects of different end subgraphs $I$ and $J$ and of boundary conditions on
the infinite-length limit of the strip graphs.


  Pattern formation exhibited by a two-dimensional reaction-diffusion system in
the fast inhibitor limit is considered from the point of view of interface
motion. A dissipative nonlocal equation of motion for the boundary between high
and low concentrations of the slow species is derived heuristically. Under
these dynamics, a compact domain of high concentration may develop into a
space-filling labyrinthine structure in which nearby fronts repel. Similar
patterns have been observed recently by Lee, McCormick, Ouyang, and Swinney in
a reacting chemical system.


  The task of identifying emotions from a given music track has been an active
pursuit in the Music Information Retrieval (MIR) community for years. Music
emotion recognition has typically relied on acoustic features, social tags, and
other metadata to identify and classify music emotions. The role of lyrics in
music emotion recognition remains under-appreciated in spite of several studies
reporting superior performance of music emotion classifiers based on features
extracted from lyrics. In this study, we use the transformer-based approach
model using XLNet as the base architecture which, till date, has not been used
to identify emotional connotations of music based on lyrics. Our proposed
approach outperforms existing methods for multiple datasets. We used a robust
methodology to enhance web-crawlers' accuracy for extracting lyrics. This study
has important implications in improving applications involved in playlist
generation of music based on emotions in addition to improving music
recommendation systems.


  The popularity of social media makes politicians use it for political
advertisement. Therefore, social media is full of electoral agitation
(electioneering), especially during the election campaigns. The election
administration cannot track the spread and quantity of messages that count as
agitation under the election code. It addresses a crucial problem, while also
uncovering a niche that has not been effectively targeted so far. Hence, we
present the first publicly open data set for detecting electoral agitation in
the Polish language. It contains 6,112 human-annotated tweets tagged with four
legally conditioned categories. We achieved a 0.66 inter-annotator agreement
(Cohen's kappa score). An additional annotator resolved the mismatches between
the first two improving the consistency and complexity of the annotation
process. The newly created data set was used to fine-tune a Polish Language
Model called HerBERT (achieving a 68% F1 score). We also present a number of
potential use cases for such data sets and models, enriching the paper with an
analysis of the Polish 2020 Presidential Election on Twitter.


  We study the phenomenon of super-roughening found on surfaces growing on
disordered substrates. We consider a one-dimensional version of the problem for
which the pure, ordered model exhibits a roughening phase transition. Extensive
numerical simulations combined with analytical approximations indicate that
super-roughening is a regime of asymptotically flat surfaces with non-trivial,
rough short-scale features arising from the competition between surface tension
and disorder. Based on this evidence and on previous simulations of the
two-dimensional Random sine-Gordon model [Sanchez et al., Phys. Rev. E 62, 3219
(2000)], we argue that this scenario is general and explains equally well the
hitherto poorly understood two-dimensional case.


  Abstraction is key to human and artificial intelligence as it allows one to
see common structure in otherwise distinct objects or situations and as such it
is a key element for generality in AI. Anti-unification (or generalization) is
\textit{the} part of theoretical computer science and AI studying abstraction.
It has been successfully applied to various AI-related problems, most
importantly inductive logic programming. Up to this date, anti-unification is
studied only from a syntactic perspective in the literature. The purpose of
this paper is to initiate an algebraic (i.e. semantic) theory of
anti-unification within general algebras. This is motivated by recent
applications to similarity and analogical proportions.


  We present a 3-D hydro + cascade model in which viscosity and a realistic
freezeout process for the hadronic phase are taken into account. We compare our
results to experimental data and discuss the finite state interaction effects
on physical observables.


  We study experimentally how gaseous HCl and NH_3 diffuse from opposite sides
of and react in silica aerogel rods with porosity of 92 % and average pore size
of about 50 nm. The reaction leads to solid NH_4Cl, which is deposited in thin
sheet-like structures. We present a numerical study of the phenomenon. Due to
the difference in boundary conditions between this system and those usually
studied, we find the sheet-like structures in the aerogel to differ
significantly from older studies. The influence of random nucleation centers
and inhomogeneities in the aerogel is studied numerically.


  In this paper we presents results of research about elderly users of Stack
Overflow (Question and Answer portal for programmers). They have different
roles, different main activities and different habits. They are an important
part of the community, as they tend to have higher reputation and they like to
share their knowledge. This is a great example of possible way of keeping
elderly people active and helpful for society.


  In a very recent breakthrough, Behnezhad and Ghafari [arXiv'24] developed a
novel fully dynamic randomized algorithm for maintaining a
$(1-\epsilon)$-approximation of maximum matching with amortized update time
potentially much better than the trivial $O(n)$ update time. The runtime of the
BG algorithm is parameterized via the following graph theoretical concept:
  * For any $n$, define $ORS(n)$ -- standing for Ordered RS Graph -- to be the
largest number of edge-disjoint matchings $M_1,\ldots,M_t$ of size $\Theta(n)$
in an $n$-vertex graph such that for every $i \in [t]$, $M_i$ is an induced
matching in the subgraph $M_{i} \cup M_{i+1} \cup \ldots \cup M_t$.
  Then, for any fixed $\epsilon > 0$, the BG algorithm runs in \[
  O\left( \sqrt{n^{1+O(\epsilon)} \cdot ORS(n)} \right) \] amortized update
time with high probability, even against an adaptive adversary. $ORS(n)$ is a
close variant of a more well-known quantity regarding RS graphs (which require
every matching to be induced regardless of the ordering). It is currently only
known that $n^{o(1)} \leqslant ORS(n) \leqslant n^{1-o(1)}$, and closing this
gap appears to be a notoriously challenging problem.
  In this work, we further strengthen the result of Behnezhad and Ghafari and
push it to limit to obtain a randomized algorithm with amortized update time of
\[
  n^{o(1)} \cdot ORS(n) \] with high probability, even against an adaptive
adversary. In the limit, i.e., if current lower bounds for $ORS(n) = n^{o(1)}$
are almost optimal, our algorithm achieves an $n^{o(1)}$ update time for
$(1-\epsilon)$-approximation of maximum matching, almost fully resolving this
fundamental question. In its current stage also, this fully reduces the
algorithmic problem of designing dynamic matching algorithms to a purely
combinatorial problem of upper bounding $ORS(n)$ with no algorithmic
considerations.


  We investigate by Molecular Dynamics simulation a system of $N$ particles
moving on the surface of a two-dimensional sphere and interacting by a
Lennard-Jones potential. We detail the way to account for the changes brought
by a nonzero curvature, both at a methodological and at a physical level. When
compared to a two-dimensional Lennard-Jones liquid on the Euclidean plane,
where a phase transition to an ordered hexagonal phase takes place, we find
that the presence of excess defects imposed by the topology of the sphere
frustrates the hexagonal order. We observe at high density a rapid increase of
the relaxation time when the temperature is decreased, whereas in the same
range of temperature the pair correlation function of the system evolves only
moderately.


  The Dark Matter Time Projection Chamber collaboration recently reported a
dark matter limit obtained with a 10 liter time projection chamber filled with
CF4 gas. The 10 liter detector was capable of 2D tracking (perpendicular to the
drift direction) and 2D fiducialization, and only used information from two CCD
cameras when identifying tracks and rejecting backgrounds. Since that time, the
collaboration has explored the potential benefits of photomultiplier tube and
electronic charge readout to achieve 3D tracking, and particle identification
for background rejection. The latest results of this effort is described here.


  The third moment variation of a financial asset return process is defined by
the quadratic covariation between the return and square return processes. The
skew and fat tail risk of an underlying asset can be hedged using a third
moment variation swap under which a predetermined fixed leg and the floating
leg of the realized third moment variation are exchanged. The probability
density function of the hedged portfolio with the third moment variation swap
was examined using a partial differential equation approach. An alternating
direction implicit method was used for numerical analysis of the partial
differential equation. Under the stochastic volatility and jump diffusion
stochastic volatility models, the distributions of the hedged portfolio return
are symmetric and have more Gaussian-like thin-tails.


  Currently available topological censorship theorems are meant for
gravitationally isolated black hole spacetimes with cosmological constant
$\Lambda=0$ or $\Lambda<0$. Here, we prove a topological censorship theorem
that is compatible with $\Lambda>0$ and which can be applied to whole universes
containing possibly multiple collections of black holes. The main assumption in
the theorem is that distinct black hole collections eventually become isolated
from one another at late times, and the conclusion is that the regions near the
various black hole collections have trivial fundamental group, in spite of
there possibly being nontrivial topology in the universe.


  The physical principles that determine the effect of the electron shell of an
atom on the alpha decay rate of the nucleus are presented. The effect is shown
to be negative. Numerical calculations of the effect in helium-like ions are
performed. It accounts for more than 80% of the effect in neutral atoms. The
prospects for experimental detection of the effect in the storage rings of the
GSI Darmstadt, ISF Lanzhou are discussed.


  When frying potato snacks, it is typically observed that the dough, which is
submerged in hot oil, after some critical time increases its buoyancy and
floats to the surface. The lift-off time is a useful metric in ensuring that
the snacks are properly cooked. Here we propose a multiphase mathematical model
for the frying of potato snacks, where water inside the dough is evaporated
from both the top and bottom surfaces of the snack at two receding evaporation
fronts. The vapour created at the top of the snack bubbles away to the surface,
whereas the vapour released from the bottom surface forms a buoyant blanket
layer. By asymptotic analysis, we show that the model simplifies to solving a
one-dimensional Stefan problem in the snack coupled to a thin-film equation in
the vapour blanket through a non-linear boundary condition. Using our
mathematical model, we predict the change in the snack density as a function of
time, and investigate how lift-off time depends on the different parameters of
the problem.


  The discrete-dipole approximation (DDA) is a flexible technique for computing
scattering and absorption by targets of arbitrary geometry. In this paper we
perform systematic study of various non-stationary iterative (conjugate
gradient) methods in search for the most efficient one in order to solve the
system of equations arising in DDA. We document implementation of these methods
in our public domain code DDSCAT.5a


  This monograph is the English version of the book "Quantum systems with
hidden symmetry. Interbasis expansions" published in 2006 by the publishing
house FIZMATLIT (Moscow) in Russian. When compiling this version of the book,
typos and inaccuracies noted since the release of the Russian edition have been
corrected.


  We study the m-component vector spin glass in the limit m to infinity on a
Bethe lattice. The cavity method allows for a solution of the model in a
self-consistent field approximation and for a perturbative solution of the full
problem near the phase transition. The low temperature phase of the model is
analyzed numerically and a generalized Bose-Einstein condensation is found, as
in the fully connected model. Scaling relations between four distinct
zero-temperature exponents are found.


  Labelling of human behavior analysis data is a complex and time consuming
task. In this paper, a fully automatic technique for labelling an image based
gaze behavior dataset for driver gaze zone estimation is proposed. Domain
knowledge is added to the data recording paradigm and later labels are
generated in an automatic manner using Speech To Text conversion (STT). In
order to remove the noise in the STT process due to different illumination and
ethnicity of subjects in our data, the speech frequency and energy are
analysed. The resultant Driver Gaze in the Wild (DGW) dataset contains 586
recordings, captured during different times of the day including evenings. The
large scale dataset contains 338 subjects with an age range of 18-63 years. As
the data is recorded in different lighting conditions, an illumination robust
layer is proposed in the Convolutional Neural Network (CNN). The extensive
experiments show the variance in the dataset resembling real-world conditions
and the effectiveness of the proposed CNN pipeline. The proposed network is
also fine-tuned for the eye gaze prediction task, which shows the
discriminativeness of the representation learnt by our network on the proposed
DGW dataset. Project Page:
https://sites.google.com/view/drivergazeprediction/home


  Optimizing lower-body exoskeleton walking gaits for user comfort requires
understanding users' preferences over a high-dimensional gait parameter space.
However, existing preference-based learning methods have only explored
low-dimensional domains due to computational limitations. To learn user
preferences in high dimensions, this work presents LineCoSpar, a
human-in-the-loop preference-based framework that enables optimization over
many parameters by iteratively exploring one-dimensional subspaces.
Additionally, this work identifies gait attributes that characterize broader
preferences across users. In simulations and human trials, we empirically
verify that LineCoSpar is a sample-efficient approach for high-dimensional
preference optimization. Our analysis of the experimental data reveals a
correspondence between human preferences and objective measures of dynamicity,
while also highlighting differences in the utility functions underlying
individual users' gait preferences. This result has implications for
exoskeleton gait synthesis, an active field with applications to clinical use
and patient rehabilitation.


  We report the first-time use of the Aqueye+ and Iqueye instruments to record
lunar occultation events. High-time resolution recordings in different filters
have been acquired for several occultations taken from January 2016 through
January 2018 with Aqueye+ at the Copernicus telescope and Iqueye at the Galileo
telescope in Asiago, Italy. Light curves with different time bins were
calculated in post-processing and analyzed using a least-square model-dependent
method. A total of nine occultation light curves were recorded, including one
star for which we could measure for the first time the size of the chromosphere
($\mu$ Psc) and one binary star for which discrepant previous determinations
existed in the literature (SAO 92922). A disappearance of Alf Tau shows an
angular diameter in good agreement with literature values. The other stars were
found to be unresolved, at the milliarcsecond level. We discuss the unique
properties of Aqueye+ and Iqueye for this kind of observations, namely the
simultaneous measurement in up to four different filters thanks to pupil
splitting, and the unprecedented time resolution well exceeding the microsecond
level. This latter makes Aqueye+ and Iqueye suitable to observe not just
occultations by the Moon, but also much faster events such as e.g. occultations
by artificial screens in low orbits. We provide an outlook of future possible
observations in this context.


  In this paper we consider developable surfaces which are isometric to planar
domains and which are piecewise differentiable, exhibiting folds along curves.
The paper revolves around the longstanding problem of existence of the
so-called folded annulus with multiple creases, which we partially settle by
building upon a deeper understanding of how a curved fold propagates to
additional prescribed foldlines. After recalling some crucial properties of
developables, we describe the local behaviour of curved folding employing
normal curvature and relative torsion as parameters and then compute the very
general relation between such geometric descriptors at consecutive folds,
obtaining novel formulae enjoying a nice degree of symmetry. We make use of
these formulae to prove that any proper fold can be propagated to an arbitrary
finite number of rescaled copies of the first foldline and to give reasons why
problems involving infinitely many foldlines are harder to solve.


  We consider invertible discrete-time dynamical systems having a hyperbolic
product structure in some region of the phase space with infinitely many
branches and variable recurrence time. We show that the decay of correlations
of the SRB measure associated to that hyperbolic structure is related to the
tail of the recurrence times. We also give sufficient conditions for the
validity of the Central Limit Theorem. This generalizes previous results by
Benedicks and Young.


  The measurement of identified charged-hadron production at mid-rapidity ($|y|
< 0.5$) performed with the ALICE experiment at the LHC is presented for pp
collisions at $\sqrt{s}$ = 900 GeV and 7 TeV and for Pb--Pb collisions at
$\sqrt{s_{NN}}$ = 2.76 TeV. Transverse momentum spectra of $\pi^{\pm}$,
K$^{\pm}$, p, $\rm \bar{p}$ and multi-strange baryons are measured over a wide
momentum range using the $dE/dx$, the time-of-flight and topological
particle-identification techniques. In this report, the particle-identification
detectors and techniques, as well as the achieved performance, are shortly
reviewed. Proton-proton results on particle production yields, spectral shapes
and particle ratios are presented as a function of the collision energy and
compared to previous experiments and commonly-used Monte Carlo models. Particle
spectra, yields and ratios in Pb--Pb are measured as a function of the
collision centrality and the results are compared with published RHIC data in
Au--Au collisions at $\sqrt{s_{NN}}$ = 200 GeV and predictions for the LHC.


  We find new twisted Yangian symmetries of the AdS/CFT reflection matrices for
the Y=0 maximal giant graviton and D5-brane. These new symmetries originate
from the known secret symmetries of the Yangian symmetry of the AdS/CFT
S-matrix.


  Latent Dirichlet Allocation (LDA) mining thematic structure of documents
plays an important role in nature language processing and machine learning
areas. However, the probability distribution from LDA only describes the
statistical relationship of occurrences in the corpus and usually in practice,
probability is not the best choice for feature representations. Recently,
embedding methods have been proposed to represent words and documents by
learning essential concepts and representations, such as Word2Vec and Doc2Vec.
The embedded representations have shown more effectiveness than LDA-style
representations in many tasks. In this paper, we propose the Topic2Vec approach
which can learn topic representations in the same semantic vector space with
words, as an alternative to probability. The experimental results show that
Topic2Vec achieves interesting and meaningful results.


  In nanofabrication, just as in any other craft, the scale of spatial details
is limited by the dimensions of the tool at hand. For example, the smallest
details for direct laser writing with far-field light are set by the
diffraction limit, which is approximately half of the used wavelength. In this
work, we overcome this universal assertion by optically forging graphene
ripples that show features with dimensions unlimited by diffraction. Thin sheet
elasticity simulations suggest that the scaled-down ripples originate from the
interplay between substrate adhesion, in-plane strain, and circular symmetry.
The optical forging technique thus offers an accurate way to modify and shape
two-dimensional materials and facilitates the creation of controllable
nanostructures for plasmonics, resonators, and nano-optics.


  We present a generalized formalism to describe the optical energy flow and
spatially resolved absorption in arbitrarily anisotropic layered structures.
The algorithm is capable of treating any number of layers of arbitrarily
anisotropic, birefringent, and absorbing media and is implemented in an open
access computer program. We derive explicit expressions for the transmitted and
absorbed power at any point in the multilayer structure, using the electric
field distribution from a 4 $\times$ 4 transfer matrix formalism. As a test
ground, we study three nanophotonic device structures featuring unique
layer-resolved absorption characteristics, making use of (i) in-plane
hyperbolic phonon polaritons, (ii) layer-selective, cavity-enhanced exciton
absorption in transition metal dichalcogenide monolayers, and (iii)
intersubband-cavity polaritons in quantum wells. Covering such a broad spectral
range from the far-infrared to the visible, the case studies demonstrate the
generality and wide applicability of our approach.


  This work focuses on sequential locally recoverable codes (SLRCs), a special
family of locally repairable codes, capable of correcting multiple code symbol
erasures, which are commonly used for distributed storage systems. First, we
construct an extended $q$-ary family of non-binary SLRCs using code products
with a novel maximum number of recoverable erasures $t$ and a minimal repair
alternativity $A$. Second, we study how MDS and BCH codes can be used to
construct $q$-ary SLRCs. Finally, we compare our codes to other LRCs.


  To investigate the star formation process, we present a multi-wavelength
study of a massive star-forming site RAFGL 5085, which has been associated with
the molecular outflow, HII region, and near-infrared cluster. The continuum
images at 12, 250, 350, and 500 $\mu$m show a central region (having M$_{\rm
clump}$ $\sim$225 M$_{\odot}$) surrounded by five parsec-scale filaments,
revealing a hub-filament system (HFS). In the {\it Herschel} column density
($N({{\rm{H}}}_{2})$) map, filaments are identified with higher aspect ratios
(length/diameter) and lower $N({{\rm{H}}}_{2})$ values ($\sim$0.1--2.4
$\times$10$^{21}$ cm$^{-2}$), while the central hub is found with a lower
aspect ratio and higher $N({{\rm{H}}}_{2})$ values ($\sim$3.5--7.0
$\times$10$^{21}$ cm$^{-2}$). The central hub displays a temperature range of
[19, 22.5]~K in the {\it Herschel} temperature map, and is observed with
signatures of star formation (including radio continuum emission). The JCMT
$^{13}$CO(J= 3--2) line data confirm the presence of the HFS and its hub is
traced with supersonic and non-thermal motions having higher Mach number and
lower thermal to non-thermal pressure ratio. In the $^{13}$CO position-velocity
diagrams, velocity gradients along the filaments toward the HFS appear to be
observed, suggesting the gas flow in the RAFGL 5085 HFS and the applicability
of the clump-fed scenario.


  Using first principles calculations, the energetic stability of
two-dimensional (2D) binary compounds $XY$ is investigated, where $X$ and $Y$
indicate the metallic element from Li to Pb in the periodic table. Here, 1081
compounds in the buckled honeycomb (BHC), buckled square, B2, L1$_0$, and B$_h$
structures are studied. For the compounds that have negative formation energy
in the BHC structure or the compounds that can have the B$_h$ structure, the
phonon dispersions of the 2D structures are also calculated. We demonstrate
that (i) a negative formation energy is neither a sufficient nor necessary
condition for yielding the dynamical stability of 2D compounds; and (ii) if a
compound in the B$_h$ structure has been synthesized experimentally, that in
the BHC structure is dynamically stable.


  Scale-invariant spatial or temporal patterns and L\'evy flight motion have
been observed in a large variety of biological systems. It has been argued that
animals in general might perform L\'evy flight motion with power law
distribution of times between two changes of the direction of motion. Here we
study the temporal behaviour of nesting gilts. The time spent by a gilt in a
given form of activity has power law probability distribution without finite
average. Further analysis reveals intermittent eruption of certain periodic
behavioural sequences which are responsible for the scaling behaviour and
indicates the existence of a critical state. We show that this behaviour is in
close analogy with temporal sequences of velocity found in turbulent flows,
where random and regular sequences alternate and form an intermittent sequence.


  We study higher rank Jacobi partial and false theta functions
(generalizations of the classical partial and false theta functions) associated
to positive definite rational lattices. In particular, we focus our attention
on certain Kostant's partial theta functions coming from ADE root lattices,
which are then linked to representation theory of W-algebras. We derive modular
transformation properties of regularized Kostant's partial and certain higher
rank false theta functions. Modulo conjectures in representation theory, as an
application, we compute regularized quantum dimensions of atypical and typical
modules of "narrow" logarithmic W-algebras associated to rescaled root
lattices. Results in this paper substantially generalize our previous work [19]
pertaining to (1,p)-singlet W-algebras (the sl_2 case).


  Robotic telesurgery has a potential to provide extreme and urgent health care
services and bring unprecedented opportunities to deliver highly specialized
skills globally. It has a significant societal impact and is regarded as one of
the appealing use cases of Tactile Internet and 5G applications. However, the
performance of robotic telesurgery largely depends on the network performance
in terms of latency, jitter and packet loss, especially when telesurgical
system is equipped with haptic feedback. This imposes significant challenges to
design a reliable and secure but cost-effective communication solution. This
article aims to give a better understanding of the characteristics of robotic
telesurgical system, and the limiting factors, the possible telesurgery
services and the communication quality of service (QoS) requirements of the
multi-modal sensory data. Based on this, a viable network architecture enabled
by the converged edge and core cloud is presented and the relevant research
challenges, open issues and enabling technologies in the 5G communication
system are discussed.


  We consider the moduli space of isotropic maps from a closed surface $\Sigma$
to a symplectic affine space and construct a K\"ahler moment map geometry, on a
space of differential forms on $\Sigma$, such that the isotropic maps
correspond to certain zeroes of the moment map. The moment map geometry induces
a modified moment map flow, whose fixed point set correspond to isotropic maps.
This construction can be adapted to the polyhedral setting. In particular, we
prove that the polyhedral modified moment map flow induces a strong deformation
retraction from the space of polyhedral maps onto the space of polyhedral
isotropic maps.


  Recent work on formal verification of differential privacy shows a trend
toward usability and expressiveness -- generating a correctness proof of
sophisticated algorithm while minimizing the annotation burden on programmers.
Sometimes, combining those two requires substantial changes to program logics:
one recent paper is able to verify Report Noisy Max automatically, but it
involves a complex verification system using customized program logics and
verifiers.
  In this paper, we propose a new proof technique, called shadow execution, and
embed it into a language called ShadowDP. ShadowDP uses shadow execution to
generate proofs of differential privacy with very few programmer annotations
and without relying on customized logics and verifiers. In addition to
verifying Report Noisy Max, we show that it can verify a new variant of Sparse
Vector that reports the gap between some noisy query answers and the noisy
threshold. Moreover, ShadowDP reduces the complexity of verification: for all
of the algorithms we have evaluated, type checking and verification in total
takes at most 3 seconds, while prior work takes minutes on the same algorithms.


  Node representation learning has demonstrated its efficacy for various
applications on graphs, which leads to increasing attention towards the area.
However, fairness is a largely under-explored territory within the field, which
may lead to biased results towards underrepresented groups in ensuing tasks. To
this end, this work theoretically explains the sources of bias in node
representations obtained via Graph Neural Networks (GNNs). Our analysis reveals
that both nodal features and graph structure lead to bias in the obtained
representations. Building upon the analysis, fairness-aware data augmentation
frameworks on nodal features and graph structure are developed to reduce the
intrinsic bias. Our analysis and proposed schemes can be readily employed to
enhance the fairness of various GNN-based learning mechanisms. Extensive
experiments on node classification and link prediction are carried out over
real networks in the context of graph contrastive learning. Comparison with
multiple benchmarks demonstrates that the proposed augmentation strategies can
improve fairness in terms of statistical parity and equal opportunity, while
providing comparable utility to state-of-the-art contrastive methods.


  Wireless systems beyond 5G evolve towards embracing both sensing and
communication, resulting in increased convergence of the digital and the
physical world. The existence of fused digital-physical realms raises critical
questions regarding temporal ordering, causality, and the synchronization of
events. This paper addresses the temporal challenges arising from the fact that
the wireless infrastructure becomes an entity with multisensory perception.
With the growing reliance on real-time interactions and applications such as
digital twins, extended reality, and the metaverse, the need for accurate
timestamping and temporal forensics becomes crucial. The paper introduces a
model that incorporates Temporal Windows of Integration (TWI) to emulate human
multisensory perception and discusses the implications for setting timing
constraints in real-time applications and enabling temporal forensics. The
analysis explores trade-offs, probabilities, and bounds for simultaneity and
causality violation in the context of wireless systems evolving towards
perceptive networks. This work underscores the significance of timestamping in
the evolving wireless landscape, provide insights into system-level
implications, and points out new research avenues for systems that combine
sensing and communications.


  The robustness testing has been performed for standard CNN models and Vision
Transformers, however there is a lack of comprehensive study between the
robustness of traditional Vision Transformers without an extra attentional
channel design and the latest fully attentional network(FAN) models. So in this
paper, we use the ImageNet dataset to compare the robustness of fully
attentional network(FAN) models with traditional Vision Transformers to
understand the role of an attentional channel processing design using white box
attacks and also study the transferability between the same using black box
attacks.


  The performace of an ATLAS-A silicon micro-strip detector prototype with
FELIX 128 analogue read out chip has been studied. The noise level and the
signal to noise ratio have been measured as a funtion of both detector bias and
temperature. No evidence of micro-discharge was observed for detector bias
voltages up to 300 V.


  Recent research demonstrated that mutation-based fault localization
techniques are relatively accurate and practical. However, these methods have
never been compared and have only been assessed with simple hand-seeded faults.
Therefore, their actual practicality is questionable when it comes to real-wold
faults. To deal with this limitation we asses and compare the two main
mutation-based fault localization methods, named Metallaxis and MUSE, on a set
of real-world programs and faults. Our results based on three typical
evaluation metrics indicate that mutation-based fault localization methods are
relatively accurate and provide relevant information to developers. Overall,
our result indicate that Metallaxis and MUSE require 18% and 37% of the program
statements to find the sought faults. Additionally, both methods locate 50% and
80% of the studied faults when developers inspect 10 and 25 statements.


  The synthesis of reactive systems from linear temporal logic (LTL)
specifications is an important aspect in the design of reliable software and
hardware. We present our adaption of the classic automata-theoretic approach to
LTL synthesis, implemented in the tool Strix which has won the two last
synthesis competitions (Syntcomp2018/2019). The presented approach is (1)
structured, meaning that the states used in the construction have a semantic
structure that is exploited in several ways, it performs a (2) forward
exploration such that it often constructs only a small subset of the reachable
states, and it is (3) incremental in the sense that it reuses results from
previous inconclusive solution attempts. Further, we present and study
different guiding heuristics that determine where to expand the on-demand
constructed arena. Moreover, we show several techniques for extracting an
implementation (Mealy machine or circuit) from the witness of the
tree-automaton emptiness check. Lastly, the chosen constructions use a symbolic
representation of the transition functions to reduce runtime and memory
consumption. We evaluate the proposed techniques on the Syntcomp2019 benchmark
set and show in more detail how the proposed techniques compare to the
techniques implemented in other leading LTL synthesis tools.


  Deep learning's great success motivates many practitioners and students to
learn about this exciting technology. However, it is often challenging for
beginners to take their first step due to the complexity of understanding and
applying deep learning. We present CNN Explainer, an interactive visualization
tool designed for non-experts to learn and examine convolutional neural
networks (CNNs), a foundational deep learning model architecture. Our tool
addresses key challenges that novices face while learning about CNNs, which we
identify from interviews with instructors and a survey with past students. CNN
Explainer tightly integrates a model overview that summarizes a CNN's
structure, and on-demand, dynamic visual explanation views that help users
understand the underlying components of CNNs. Through smooth transitions across
levels of abstraction, our tool enables users to inspect the interplay between
low-level mathematical operations and high-level model structures. A
qualitative user study shows that CNN Explainer helps users more easily
understand the inner workings of CNNs, and is engaging and enjoyable to use. We
also derive design lessons from our study. Developed using modern web
technologies, CNN Explainer runs locally in users' web browsers without the
need for installation or specialized hardware, broadening the public's
education access to modern deep learning techniques.


  We study two-component (or pseudospin-1/2) bosons with pair hopping
interactions in synthetic dimension, for which a feasible experimental scheme
on a square optical lattice is also presented. Previous studies have shown that
two-component bosons with on-site interspecies interaction can only generate
nontrivial interspecies paired superfluid (super-counter-fluidity or
pair-superfluid) state. In contrast, apart from interspecies paired superfluid,
we reveal two new phases by considering this additional pair hopping
interaction. These novel phases are intraspecies paired superfluid (molecular
superfluid) and an exotic non-integer Mott insulator which shows a non-integer
atom number at each site for each species, but an integer for total atom
number.


  We consider the multiple scattering of a scalar wave in a disordered medium
with a weak nonlinearity of Kerr type. The perturbation theory, developed to
calculate the temporal autocorrelation function of scattered wave, fails at
short correlation times. A self-consistent calculation shows that for
nonlinearities exceeding a certain threshold value, the multiple-scattering
speckle pattern becomes unstable and exhibits spontaneous fluctuations even in
the absence of scatterer motion. The instability is due to a distributed
feedback in the system "coherent wave + nonlinear disordered medium". The
feedback is provided by the multiple scattering. The development of instability
is independent of the sign of nonlinearity.


  In this paper we consider high dimension models based on dependent
observations defined through autoregressive processes. For such models we
develop an adaptive efficient estimation method via the robust sequential model
selection procedures. To this end, firstly, using the Van Trees inequality, we
obtain a sharp lower bound for robust risks in an explicit form given by the
famous Pinsker constant. It should be noted, that for such models this constant
is calculated for the first time. Then, using the weighted least square method
and sharp non asymptotic oracle inequalities we provide the efficiency property
in the minimax sense for the proposed estimation procedure, i.e. we establish,
that the upper bound for its risk coincides with the obtained lower bound. It
should be emphasized that this property is obtained without using sparse
conditions and in the adaptive setting when the parameter dimension and model
regularity are unknown.


  With the help of El Bachraoui's lemma, the creative microscoping method, and
a new form of the Chinese remainder theorem for coprime polynomials, we prove a
$q$-supercongruence for double series and a $q$-supercongruence for triple
series modulo the sixth power of a cyclotomic polynomial. As conclusions, two
corresponding supercongruences for double and triple series, which are
associated with the (D.2) supercongruence of Van Hamme, are given.


  Thermal noise arising from mechanical dissipation in dielectric reflective
coatings is expected to critically limit the sensitivity of precision
measurement systems such as high-resolution optical spectroscopy, optical
frequency standards and future generations of interferometric gravitational
wave detectors. We present measurements of the effect of post-deposition heat
treatment on the temperature dependence of the mechanical dissipation in
ion-beam sputtered tantalum pentoxide between 11\,K and 300\,K. We find the
temperature dependence of the dissipation is strongly dependent on the
temperature at which the heat treatment was carried out, and we have identified
three dissipation peaks occurring at different heat treatment temperatures. At
temperatures below 200\,K, the magnitude of the loss was found to increase with
higher heat treatment temperatures, indicating that heat treatment is a
significant factor in determining the level of coating thermal noise.


  We recently discovered that NGC 3201 has characteristics that set it outside
the current twofold classification scheme for Galactic globular clusters (GCs).
Most GCs are mono-metallic and show light-element abundance variations (e.g.,
Na-O and C-N anti-correlations); but a minority of clusters also present
variations in Fe correlating with s-process element and C+N+O abundances, and
they possess multiple C-N sequences. These anomalous GCs also have a broad
sub-giant branch (SGB) and follow the same mass-size relation as dwarf galaxies
possibly evolving into GCs. We now revealed that NGC 3201 belongs to neither
group. It has multiple C-N sequences, but no broad SGB, no strong evidence of a
Fe-spread, and it does not follow the mass-size relation.


  An experimental model of transmission of ocean waves by an ice floe is
presented. Thin plastic plates with different material properties and
thicknesses are used to model the floe. Regular incident waves with different
periods and steepnesses are used, ranging from gently-sloping to storm-like
conditions. A wave gauge is used to measure the water surface elevation in the
lee of the floe. The depth of wave overwash on the floe is measured by a gauge
in the centre of the floe's upper surface. Results show transmitted waves are
regular for gently-sloping incident waves but irregular for storm-like incident
waves. The proportion of the incident wave transmitted is shown to decrease as
incident wave steepness increases, and to be at its minimum for an incident
wavelength equal to the floe length. Further, a trend is noted for transmission
to decrease as the mean wave height in the overwash region increases.


  This paper presents the effects of radio frequency interference (RFI)
mitigation on a radio telescope's sensitivity and beam pattern. It specifically
explores the impact of subspace-projection mitigation on the phased array feed
(PAF) beams of the Australian SKA Pathfinder (ASKAP) telescope. The goal is to
demonstrate ASKAP's ability to make science observations during active RFI
mitigation. The target interfering signal is a self-generated clock signal from
the digital receivers of ASKAP's PAFs. This signal is stationary, so we apply
the mitigation projection to the beamformer weights at the beginning of the
observation and hold them fixed. We suppressed the unwanted narrowband signal
by 31dB, to the noise floor of an 880s integration on one antenna, with a
typical degradation in sensitivity of just 1.5%. Sensitivity degradation over
the whole 36 antenna array of 3.1% was then measured via interferometric
assessment of system equivalent flux density (SEFD). These measurements are in
line with theoretical calculation of noise increase using the correlation of
the beam weights and RFI spatial signature. Further, degradation to the main
beam's gain is 0.4% on average at the half-power point, with no significant
change to the gain in the first sidelobe and no variation during extended
observations; also consistent with our modelling. In summary, we present the
first demonstration of mitigation via spatial nulling with PAFs on a large
aperture synthesis array telescope and assess impact on sensitivity and beam
shape via SEFD and holography measurements. The mitigation introduces smaller
changes to sensitivity than intrinsic sensitivity differences between beams,
does not preclude high dynamic range imaging and, in continuum 1MHz mode,
recovers an otherwise corrupted holography beam map and usable astronomical
source correlations in the RFI-affected channel.


  We suggest that superconductivity (SC) in the organic charge transfer solids
(CTS) is reached from a Bond-Charge Density Wave (BCDW). We discuss an
effective model for the BCDW to SC transition, an attractive U extended Hubbard
Hamiltonian with repulsive nearest neighbor interaction V. We discuss
experimental consequences of the theory for different classes of CTS
superconductors as well as related inorganic materials.


  The interplay between non-Hermitian effects and topological insulators has
become a frontier of research in non-Hermitian physics. However, the existence
of a non-Hermitian skin effect for topological-protected edge states remains
controversial. In this paper, we discover an alternative form of the
non-Hermitian skin effect called the non-Hermitian chiral skin effect (NHCSE).
NHCSE is a non-Hermitian skin effect under periodic boundary condition rather
than open boundary condition. Specifically, the chiral modes of the NHCSE
localize around \textquotedblleft topological defects\textquotedblright
characterized by global dissipation rather than being confined to the system
boundaries. We show its detailed physical properties by taking the
non-Hermitian Haldane model as an example. As a result, the intrinsic mechanism
of the hybrid skin-topological effect in Chern insulators is fully understood
via NHCSE. Therefore, this progress will be helpful for solving the
controversial topic of hybrid skin-topological effect and thus benefit the
research on both non-Hermitian physics and topological quantum states.


  Recently, hidden Markov models (HMMs) have achieved promising results for
offline handwritten Chinese text recognition. However, due to the large
vocabulary of Chinese characters with each modeled by a uniform and fixed
number of hidden states, a high demand of memory and computation is required.
In this study, to address this issue, we present parsimonious HMMs via the
state tying which can fully utilize the similarities among different Chinese
characters. Two-step algorithm with the data-driven question-set is adopted to
generate the tied-state pool using the likelihood measure. The proposed
parsimonious HMMs with both Gaussian mixture models (GMMs) and deep neural
networks (DNNs) as the emission distributions not only lead to a compact model
but also improve the recognition accuracy via the data sharing for the tied
states and the confusion decreasing among state classes. Tested on ICDAR-2013
competition database, in the best configured case, the new parsimonious DNN-HMM
can yield a relative character error rate (CER) reduction of 6.2%, 25%
reduction of model size and 60% reduction of decoding time over the
conventional DNN-HMM. In the compact setting case of average 1-state HMM, our
parsimonious DNN-HMM significantly outperforms the conventional DNN-HMM with a
relative CER reduction of 35.5%.


  With the introduction of the variational autoencoder (VAE), probabilistic
latent variable models have received renewed attention as powerful generative
models. However, their performance in terms of test likelihood and quality of
generated samples has been surpassed by autoregressive models without
stochastic units. Furthermore, flow-based models have recently been shown to be
an attractive alternative that scales well to high-dimensional data. In this
paper we close the performance gap by constructing VAE models that can
effectively utilize a deep hierarchy of stochastic variables and model complex
covariance structures. We introduce the Bidirectional-Inference Variational
Autoencoder (BIVA), characterized by a skip-connected generative model and an
inference network formed by a bidirectional stochastic inference path. We show
that BIVA reaches state-of-the-art test likelihoods, generates sharp and
coherent natural images, and uses the hierarchy of latent variables to capture
different aspects of the data distribution. We observe that BIVA, in contrast
to recent results, can be used for anomaly detection. We attribute this to the
hierarchy of latent variables which is able to extract high-level semantic
features. Finally, we extend BIVA to semi-supervised classification tasks and
show that it performs comparably to state-of-the-art results by generative
adversarial networks.


  We derive an analytical connection between kinetic relaxation rate and bulk
viscosity of a relativistic fluid in d spatial dimensions, all the way from the
ultra-relativistic down to the near non-relativistic regime. Our derivation is
based on both Chapman-Enskog asymptotic expansion and Grad's method of moments.
We validate our theoretical results against a benchmark flow, providing further
evidence of the correctness of the Chapman-Enskog approach; we define the range
of validity of this approach and provide evidence of mounting departures at
increasing Knudsen number. Finally, we present numerical simulations of
transport processes in quark gluon plasmas, with special focus on the effects
of bulk viscosity which might prove amenable to future experimental
verification.


  A continuous-time quantum walk on a graph $X$ is represented by the complex
matrix $\exp (-\mathrm{i} t A)$, where $A$ is the adjacency matrix of $X$ and
$t$ is a non-negative time. If the graph models a network of interacting
qubits, transfer of state among such qubits throughout time can be formalized
as the action of the continuous-time quantum walk operator in the
characteristic vectors of the vertices.
  Here we are concerned with the problem of determining which graphs admit a
perfect transfer of state. More specifically, we will study graphs whose
adjacency matrix is a sum of tensor products of $01$-matrices, focusing on the
case where a graph is the tensor product of two other graphs. As a result, we
will construct many new examples of perfect state transfer.


  Boson Sampling is a computational paradigm representing one of the most
viable and pursued approaches to demonstrate the regime of quantum advantage.
Recent results have demonstrated significant technological leaps in
single-photon generation and detection, leading to progressively larger
experimental instances of Boson Sampling experiments in different photonic
systems. However, a crucial requirement for a fully-fledged platform solving
this problem is the capability of implementing large-scale interferometers,
that must simultaneously exhibit low losses, high degree of reconfigurability
and the realization of arbitrary transformations. In this work, we move a step
forward in this direction by demonstrating the adoption of a compact and
reconfigurable 3D-integrated platform for photonic Boson Sampling. We perform
3- and 4-photon experiments by using such platform, showing the possibility of
programming the circuit to implement a large number of unitary transformations.
These results show that such compact and highly-reconfigurable layout can be
scaled up to experiments with larger number of photons and modes, and can
provide a viable direction for hybrid computing with photonic processors.


  Rigorous bounds on the rate of energy exchanges between vibrational and
translational degrees of freedom are established in simple classical models of
diatomic molecules. The results are in agreement with an elementary
approximation introduced by Landau and Teller. The method is perturbative
theory ``beyond all orders'', with diagrammatic techniques (tree expansions) to
organize and manipulate terms, and look for compensations, like in recent
studies on KAM theorem homoclinic splitting.


  Power generation and synchronisation in Josephson junction arrays have
attracted attention for a long time. This stems from fundamental interest in
nonlinear coupled systems as well as from potential in practical applications.
In this paper we study the case of an array of junctions coupled to a
distributed transmission line either driven by an external microwave or in a
self-oscillating mode. We simplify the theoretical treatment in terms of
harmonic analysis and power balance. We apply the model to explain the large
operation margins of SNS- and SINIS-junction arrays. We show the validity of
the approach by comparing with experiments and simulations with
self-oscillating es-SIS junction arrays.


  Quantum correlations encoded in photonic Laguerre-Gaussian modes were shown
to be related to the Gouy phase shifts (D. Kawase et al., Phys. Rev. Lett. 101,
050501 (2008)) allowing for a non-destructive manipulation of photonic quantum
states. In this work we exploit the relation between phase space correlations
of biphotons produced by spontaneously parametric down conversion (SPDC) as
encoded in the logarithmic negativity (LN) and the Gouy phase as they are
diffracted through an asymmetrical double slit setup. Using an analytical
approach based on a double-gaussian approximation for type-I SPDC biphotons, we
show that measurements of Gouy phase differences provide information on their
phase space entanglement variation, governed by the physical parameters of the
experiment and expressed by the LN via covariance matrix elements.


  We show that the ground states of the three-dimensional XXZ Heisenberg
ferromagnet with a 111 interface have excitations localized in a subvolume of
linear size R with energies bounded by O(1/R^2). As part of the proof we show
the equivalence of ensembles for the 111 interface states in the following
sense: In the thermodynamic limit the states with fixed magnetization yield the
same expectation values for gauge invariant local observables as a suitable
grand canonical state with fluctuating magnetization. Here, gauge invariant
means commuting with the total third component of the spin, which is a
conserved quantity of the Hamiltonian. As a corollary of equivalence of
ensembles we also prove the convergence of the thermodynamic limit of sequences
of canonical states (i.e., with fixed magnetization).


  We prove that if two nonzero homomorphisms from the Cuntz algebra O_infinity
to a purely infinite simple C*-algebra have the same class in KK-theory, and if
either both are unital or both are nonunital, then they are approximately
unitarily equivalent. It follows that O_infinity is classifiable in the sense
of Rordam. In particular, Rordam's classification theorem for direct limits of
matrix algebras over even Cuntz algebras extends to direct limits involving
both matrix algebras over even Cuntz algebras and corners of O_infinity for
which the K_0 group can be an arbitrary countable abelian group with no even
torsion.


  The aim of this book is to show that the use of f-analytic families of finite
type cycles (cycles having finitely many irreducible components, but not
compact in general) in a given complex space may be useful in complex geometry,
despite the fact that the corresponding functor is not, in general,
representable, in contrast to the compact case. This study leads to the notion
of strongly quasi-proper map which is characterized by the existence of a
geometric f-flattening which is a generalization of the Geometric Flattening
Theorem for proper holomorphic maps. As applications we prove an existence
theorem for meromorphic quotients of reduced complex spaces and a
generalization of the classic Stein factorization.


  The ATLAS Forward Proton (AFP) detector is intended to measure protons
scattered at small angles from the ATLAS interaction point. To this end, a
combination of 3D Silicon pixel tracking modules and Quartz-Cherenkov
time-of-flight (ToF) detectors is installed 210m away from the interaction
point at both sides of ATLAS. Beam tests with an AFP prototype detector
combining tracking and timing sub-detectors and a common readout have been
performed at the CERN-SPS test-beam facility in November 2014 and September
2015 to complete the system integration and to study the detector performance.
The successful tracking-timing integration was demonstrated. Good tracker hit
efficiencies above 99.9% at a sensor tilt of 14{\deg}, as foreseen for AFP,
were observed. Spatial resolutions in the short pixel direction with 50 {\mu}m
pitch of 5.5 +/- 0.5 {\mu}m per pixel plane and of 2.8 +/- 0.5 {\mu}m for the
full four-plane tracker at 14{\deg} were found, largely surpassing the AFP
requirement of 10 {\mu}m. The timing detector showed also good hit efficiencies
above 99%, and a full-system time resolution of 35 +/- 6 ps was found for the
ToF prototype detector with two Quartz bars in-line (half the final AFP size)
without dedicated optimisation, fulfilling the requirements for initial
low-luminosity AFP runs.


  Dense optical flow estimation plays a key role in many robotic vision tasks.
In the past few years, with the advent of deep learning, we have witnessed
great progress in optical flow estimation. However, current networks often
consist of a large number of parameters and require heavy computation costs,
largely hindering its application on low power-consumption devices such as
mobile phones. In this paper, we tackle this challenge and design a lightweight
model for fast and accurate optical flow prediction. Our proposed FastFlowNet
follows the widely-used coarse-to-fine paradigm with following innovations.
First, a new head enhanced pooling pyramid (HEPP) feature extractor is employed
to intensify high-resolution pyramid features while reducing parameters.
Second, we introduce a new center dense dilated correlation (CDDC) layer for
constructing compact cost volume that can keep large search radius with reduced
computation burden. Third, an efficient shuffle block decoder (SBD) is
implanted into each pyramid level to accelerate flow estimation with marginal
drops in accuracy. Experiments on both synthetic Sintel data and real-world
KITTI datasets demonstrate the effectiveness of the proposed approach, which
needs only 1/10 computation of comparable networks to achieve on par accuracy.
In particular, FastFlowNet only contains 1.37M parameters; and can execute at
90 FPS (with a single GTX 1080Ti) or 5.7 FPS (embedded Jetson TX2 GPU) on a
pair of Sintel images of resolution 1024x436.


  Considering increasing requirements to the coordinates measurement precision
by the end of XX century International Astronomical Union commenced
implementation of the new astrometric system ICRF (International Celestial
Reference Frame). This quasi-inertial reference frame system centered in the
barycenter of the Solar System and has axes defined by the positions of distant
extragalactic sources - frames. Unlike equatorial system ICRF has no
shortcomings of the coordinates identification due to the Earth axis
precession, stellar proper motions and other factors. Extragalactic frames of
the ICRF system are mostly quasars, radio galaxies, blazars and Seyfert
galaxies i.e. different types of the active galaxy nuclei (AGN). Active galaxy
nuclei are characterized by processes with significant. Such processes quite
often are followed by X-ray emission generation. The purpose of this work is to
consider X-ray emission of ICRF sources and features of their possible proper
motions. Among 295 selected reference frames of the system we identified 54
X-ray sources which were observed by space observatory XMM Newton and noticed
rapid variability of the blazars 2E 2673 (W Com) and 2E 1802 which enables to
conclude that they have some very active processes in the sources centers. With
regards to the future more detailed analysis we beleive that evidences of the
objects proper motion could be found in their spectra. Based on the constructed
luminosity and spectral graphs we could conclude that apart from above
mentioned AGNs rest 52 objects do not show veriability and special attention
should be paid to blazars within ICRF system development and use. Major part of
the X-ray sources between the reference frames are stable.


  The Szego kernel of a strictly pseudoconvex domain admits a singularity on
the boundary diagonal, which consists of a pole and logarithmic type
singularity. In this paper, we prove that the integral over the boundary of the
coefficient of the logarithmic singularity gives a biholomorphic invariant of a
domain, or a CR invariant of the boundary. We also show that the same invariant
appears as the coefficient of the logarithmic term of the volume expansion of
the domain with respect to the Bergman volume element.


  Over the last few years there have been dramatic advances in our
understanding of mathematical and computational models of complex systems in
the presence of uncertainty. This has led to a growth in the area of
uncertainty quantification as well as the need to develop efficient, scalable,
stable and convergent computational methods for solving differential equations
with random inputs. Stochastic Galerkin methods based on polynomial chaos
expansions have shown superiority to other non-sampling and many sampling
techniques. However, for complicated governing equations numerical
implementations of stochastic Galerkin methods can become non-trivial. On the
other hand, Monte Carlo and other traditional sampling methods, are
straightforward to implement. However, they do not offer as fast convergence
rates as stochastic Galerkin. Other numerical approaches are the stochastic
collocation (SC) methods, which inherit both, the ease of implementation of
Monte Carlo and the robustness of stochastic Galerkin to a great deal. However,
stochastic collocation and its powerful extensions, e.g. sparse grid stochastic
collocation, can simply fail to handle more levels of complication. The
seemingly innocent Burgers equation driven by Brownian motion is such an
example. In this work we propose a novel enhancement to stochastic collocation
methods using locally improved deterministic model reduction techniques that
can handle this pathological example and hopefully other more complicated
equations like Stochastic Navier-Stokes. Local improvements to reduced-order
models are achieved using sensitivity analysis of the proper orthogonal
decomposition. Our numerical results show that the proposed technique is not
only reliable and robust but also very efficient.


  Compact Symmetric Objects (CSOs) have been observed with Chandra and
XMM-Newton to gain insights into the initial stages of a radio source evolution
and probe the black hole activity at the time of relativistic outflow
formation. However, there have been no CSO observations to date at the hard
X-ray energies (> 10 keV), impeding our ability to robustly constrain the
properties of the intrinsic X-ray emission and of the medium surrounding the
young expanding jets. We present the first hard X-ray observation of a CSO
performed with NuSTAR. Our target, OQ+208, is detected up to 30 keV, and thus
we establish CSOs as a new class of NuSTAR sources. We analyze the NuSTAR data
jointly with our new Chandra and archival XMM-Newton data and find that a
young, ~250 years old, radio jet spanning the length of ~10 pc coexists with
cold obscuring matter, consistent with a dusty torus, with an equivalent
hydrogen column density $N_H = 10^{23}$-$10^{24}$ cm$^{-2}$. The primary X-ray
emission is characterized by a photon index $\Gamma \sim 1.45$ and intrinsic
0.5-30 keV luminosity $L \sim 10^{43}$ erg s$^{-1}$. The results of our
spectral modeling and broad-line optical classification of the source suggest a
porous structure of the obscuring torus. Alternatively, the source may belong
to the class of optically un-obscured/X-ray obscured AGN. The observed X-ray
emission is too weak compared to that predicted by the expanding radio lobes
model, leaving an accretion disk corona or jets as the possible origins of the
X-ray emission from this young radio galaxy.


  We present the results obtained from a comprehensive timing and spectral
study of two high-mass X-ray binary sources using NuSTAR observations. These
two sources, IGR J16320-4751 and IGR J16479-4514, were discovered by INTEGRAL
and have been characterized for the first time in the hard X-ray band (beyond
10~keV) in this work. In these sources, we observe the occurrence of intense
X-ray flares, with average luminosities exceeding 10$^{36}$~erg~s$^{-1}$. Our
analysis reveals that these flares can be described consistently in the
quasi-spherical accretion regime. The orbital phase of the first flare in
NuSTAR observation of IGR J16479-4514 matches with the orbital phases of
previous flares ($\phi=0.35$) in this source detected by other telescopes. We
conclude that this flare occurs as a result of the periastron passage of the
neutron star, rather than due to the presence of a corotating interaction
region (CIR). Furthermore, from the energy-resolved pulse profile analysis of
IGR J16320-4751, we find that the pulse fraction is lower in hard X-rays
compared to soft X-rays. We present the hard X-ray spectral parameters of these
two sources using several standard spectral model components. We do not detect
a cyclotron absorption feature in either target. We provide estimates of the
surface magnetic field strength of NS in IGR J16320-4751 using two indirect
methods. Lastly, we observe spectral hardening during flaring segments compared
to the off-flaring segments which indicates that comptonization is more
effective during the flaring segments.


  We present a simple and fast geometric method for modeling data by a union of
affine subspaces. The method begins by forming a collection of local best-fit
affine subspaces, i.e., subspaces approximating the data in local
neighborhoods. The correct sizes of the local neighborhoods are determined
automatically by the Jones' $\beta_2$ numbers (we prove under certain geometric
conditions that our method finds the optimal local neighborhoods). The
collection of subspaces is further processed by a greedy selection procedure or
a spectral method to generate the final model. We discuss applications to
tracking-based motion segmentation and clustering of faces under different
illuminating conditions. We give extensive experimental evidence demonstrating
the state of the art accuracy and speed of the suggested algorithms on these
problems and also on synthetic hybrid linear data as well as the MNIST
handwritten digits data; and we demonstrate how to use our algorithms for fast
determination of the number of affine subspaces.


  We study reaction-diffusion systems where diffusion is by jumps whose sizes
are distributed exponentially. We first study the Fisher-like problem of
propagation of a front into an unstable state, as typified by the A+B $\to$ 2A
reaction. We find that the effect of fluctuations is especially pronounced at
small hopping rates. Fluctuations are treated heuristically via a density
cutoff in the reaction rate. We then consider the case of propagating up a
reaction rate gradient. The effect of fluctuations here is pronounced, with the
front velocity increasing without limit with increasing bulk particle density.
The rate of increase is faster than in the case of a reaction-gradient with
nearest-neighbor hopping. We derive analytic expressions for the front velocity
dependence on bulk particle density. Compute simulations are performed to
confirm the analytical results.


  Incoming sound is in cochlea and auditory nerve encoded into spike trains. At
the third neuron of the auditory pathway, spike trains of the left and right
sides are processed in brainstem nuclei to yield sound localization
information. Two different localization encoding mechanisms are employed in two
centers for low and high sound frequencies in the brainstem. The centers are
superior olivary nuclei, medial and lateral. This paper contains analytical
estimates of parameters needed in description of auditory coding in sound
localization neural circuit. Our model spike trains are based on
electro-physiological recordings. We arrive to best estimates for neuronal
signaling with the use of just noticeable difference of the ideal observer. We
describe spike timing jitter and its role in the spike train processing. All
parameters are accompanied with detailed estimates of their values and
variability. Intervals bounding all the parameter from lower and higher values
are discussed.


  We present an isogeometric method for Kirchhoff-Love shell analysis of shell
structures with geometries composed of multiple patches and which possibly
possess extraordinary vertices, i.e. vertices with a valency different to four.
The proposed isogeometric shell discretisation is based on the one hand on the
approximation of the mid-surface by a particular class of multi-patch surfaces,
called analysis-suitable~$G^1$ [1], and on the other hand on the use of the
globally $C^1$-smooth isogeometric multi-patch spline space [2]. We use our
developed technique within an isogeometric Kirchhoff-Love shell formulation [3]
to study linear and non-linear shell problems on multi-patch structures.
Thereby, the numerical results show the great potential of our method for
efficient shell analysis of geometrically complex multi-patch structures which
cannot be modeled without the use of extraordinary vertices.


  Cosmology in general, and relation between redshift and cosmic epoch in
particular, is usually obscure to first years university students, secondary
students, as well as journalists, politicians and the general public scientists
may have interactions with. I identify the need for a simple artifact
scientists may give to the public to clarify a few relations between redshift
and other physical quantities, more meaningful for a non-scientist audience.
This simple bookmark aims at completing previous "pen-and-pencil cosmological
calculator" nomograms. I created a small, handy, duplicable bookmark with two
printed sides, showing the corresponding cosmological values of redshift, age,
time, and angular scale (for 1 kpc), using the Planck 2018 cosmology. On the
recto, the redshift range of [0.1, 1000] approaches the recombination with a
logarithmic scale. On the verso, the redshift range is chosen to be [0, 30]
using a linear scale, covering the range of current (and future) detections of
galaxies. A few examples are given, illustrating e.g. Planck, JWST or Euclid
capabilities and complementarities, time interval non-linearity, properties of
galaxies and clusters. This handy bookmark may be printed cheaply and offered
to every student in physics (undergrad and grad student) in our universities or
to secondary schools students we visit. The Cosmology Ruler Bookmark included
is ready to print (single- or double-sided). The python script is available on
github, allowing changes adapted to everyone's needs for teaching and outreach
purposes, including with other cosmologies or applied to other scientific
fields.