  In this paper, we study Bose-Einstein condensation of Rydberg-dressed atoms
considering finite range interactions. We use Hartree-Fock-Bogoliubov
approximation based on Mean-Field approach. Moreover, within this approximation
modified by the finite-range character of the two-body interaction we shall
obtain analytical expressions for thermodynamic quantities of Rydberg-dressed
Bose gas. The imaginary part of the quasiparticle spectrum of a BEC signals the
instability of the roton mode with respect to the formation of supersolid
state. Our theory predicts a second-order quantum phase transition from BEC to
supersolid phase for Rydberg-dressed bosons in three dimensions.


  If $T$ is the operator given by convolution with surface measure on the
sphere, $(E,F)$ is a quasi-extremal pair of sets for $T$ if $\langle T\chi_E,
\chi_F \rangle \gtrsim |E|^{d/(d+1)}|F|^{d/(d+1)}$. In this article, we
explicitly define a family $\mathcal{F}$ of quasi-extremal pairs of sets for
$T$. We prove that $\mathcal{F}$ is fundamental in the sense that every
quasi-extremal pair $(E,F)$ is comparable (in a rather strong sense) to a pair
from $\mathcal{F}$. This extends work carried out by M. Christ for convolution
with surface measure on the paraboloid.


  Idiomatic expression (IE) processing and comprehension have challenged
pre-trained language models (PTLMs) because their meanings are
non-compositional. Unlike prior works that enable IE comprehension through
fine-tuning PTLMs with sentences containing IEs, in this work, we construct
IEKG, a commonsense knowledge graph for figurative interpretations of IEs. This
extends the established ATOMIC2020 graph, converting PTLMs into knowledge
models (KMs) that encode and infer commonsense knowledge related to IE use.
Experiments show that various PTLMs can be converted into KMs with IEKG. We
verify the quality of IEKG and the ability of the trained KMs with automatic
and human evaluation. Through applications in natural language understanding,
we show that a PTLM injected with knowledge from IEKG exhibits improved IE
comprehension ability and can generalize to IEs unseen during training.


  Today, complex networks have attracted increasing attention from various
fields of science and engineering. It has been demonstrated that many complex
networks display various synchronization phenomena. In this paper, we introduce
a time-varying complex dynamical network model. We then further investigate its
synchronization phenomenon and prove several network synchronization theorems.
Especially, we show that synchronization of such a time-varying dynamical
network is completely determined by the inner-coupling matrix, and the
eigenvalues and the corresponding eigenvectors of the coupling configuration
matrix of the network.


  The eigenvalue distribution of the sum of two large Hermitian matrices, when
one of them is conjugated by a Haar distributed unitary matrix, is
asymptotically given by the free convolution of their spectral distributions.
We prove that this convergence also holds locally in the bulk of the spectrum,
down to the optimal scales larger than the eigenvalue spacing. The
corresponding eigenvectors are fully delocalized. Similar results hold for the
sum of two real symmetric matrices, when one is conjugated by a Haar orthogonal
matrix.


  In this paper, we study the maximum number, denoted by $H(m,n)$, of
hyperelliptic limit cycles of the Li\'enard systems
  $$\dot x=y, \qquad \dot y=-f_m(x)y-g_n(x),$$ where, respectively, $f_m(x)$
and $g_n(x)$ are real polynomials of degree $m$ and $n$, $g_n(0)=0$. The main
results of the paper are as follows: In term of $m$ and $n$ of the system, we
obtain the upper bound and lower bound of $H(m,n)$ in all the possible cases.
Furthermore, these upper bound can be reached in some cases.


  While building up a catalog of Earth orbiting objects, if the available
optical observations are sparse, not deliberate follow ups of specific objects,
no orbit determination is possible without previous correlation of observations
obtained at different times. This correlation step is the most computationally
intensive, and becomes more and more difficult as the number of objects to be
discovered increases. In this paper we tested two different algorithms (and the
related prototype software) recently developed to solve the correlation problem
for objects in geostationary orbit (GEO), including the accurate orbit
determination by full least squares solutions with all six orbital elements.
Because of the presence in the GEO region of a significant subpopulation of
high area to mass objects, strongly affected by non-gravitational
perturbations, it was actually necessary to solve also for dynamical parameters
describing these effects, that is to fit between 6 and 8 free parameters for
each orbit. The validation was based upon a set of real data, acquired from the
ESA Space Debris Telescope (ESASDT) at the Teide observatory (Canary Islands).
We proved that it is possible to assemble a set of sparse observations into a
set of objects with orbits, starting from a sparse time distribution of
observations, which would be compatible with a survey capable of covering the
region of interest in the sky just once per night. This could result in a
significant reduction of the requirements for a future telescope network, with
respect to what would have been required with the previously known algorithm
for correlation and orbit determination.


  The results of three-color BVR photometric study of a recently discovered
unusual binary system VSX J052807.9+725606 = USNO-B1.0 1629-0064825 are
presented. This system is very similar to V361 Lyr, which was assumed to be
unique. We confirmed a strong asymmetry of the phase curve and found the
wavelength dependence of the amplitude. This is interpreted by a "direct
impact" model with a "hot spot" in the atmosphere of the accreting component.
Color temperatures are determined. Characteristics of the "hot spot" are
estimated. We also calculated the new ephemeris for VSX J052807.9+725606.


  Ground-state properties of bosons interacting via inverse square potential
(three dimensional Calogero-Sutherland model) are analyzed. A number of
quantities scale with the density and can be naturally expressed in units of
the Fermi energy and Fermi momentum multiplied by a dimensionless constant
(Bertsch parameter). Two analytical approaches are developed: the Bogoliubov
theory for weak and the harmonic approximation (HA) for strong interactions.
Diffusion Monte Carlo method is used to obtain the ground-state properties in a
non-perturbative manner. We report the dependence of the Bertsch parameter on
the interaction strength and construct a Pad\'e approximant which fits the
numerical data and reproduces correctly the asymptotic limits of weak and
strong interactions. We find good agreement with beyond-mean field theory for
the energy and the condensate fraction. The pair distribution function and the
static structure factor are reported for a number of characteristic
interactions. We demonstrate that the system experiences a gas-solid phase
transition as a function of the dimensionless interaction strength. A
peculiarity of the system is that by changing the density it is not possible to
induce the phase transition. We show that the low-lying excitation spectrum
contains plasmons in both phases, in agreement with the Bogoliubov and HA
theories. Finally, we argue that this model can be interpreted as a realization
of the unitary limit of a Bose system with the advantage that the system stays
in the genuine ground state contrarily to the metastable state realized in
experiments with short-range Bose gases.


  The Reissner-Nordstrom black hole in four dimensions can be made unstable
without violating the dominant energy condition by introducing a real massive
scalar with non-renormalizable interactions with the gauge field. New stable
black hole solutions then exist with greater entropy for fixed mass and charge
than the Reissner-Nordstrom solution. In these new solutions, the scalar
condenses to a non-zero value near the horizon. Various generalizations of
these hairy black holes are discussed, and an attempt is made to characterize
when black hole hair can occur.


  Context: The need of replicating empirical studies in Computer Science (CS)
is widely recognized among the research community to consolidate acquired
knowledge generalizing results. It is essential to report the changes of each
replication to understand the evolution of the experimental validity across a
family of studies. Unfortunately, the lack of proposals undermines these
objectives.
  Objective. The main goal of our work is to provide researchers in CS, and in
other areas of research, with a systematic, tool-supported approach for the
reporting of changes in the replications of their empirical studies.
  Method: Applying DSR, we have developed and validated a composite artifact
consisting of (i) a metamodel of the relevant concepts of replications and
their changes; (ii) templates and linguistic patterns for reporting those
concepts; and (iii) a proof-of-concept model-based software tool that supports
the proposed approach. For its validation, we have carried out a multiple case
study including 9 families of empirical studies from CS and Agrobiology. The 9
families encompass 23 replication studies and 92 replication changes, for which
we have analyzed the suitability of our proposal.
  Results: The multiple case study revealed some initial limitations of our
approach related to threats to experimental validity or context variables.
After several improvement iterations, all the 92 replication changes could be
properly specified, including also their qualitatively estimated effects on
experimental validity across the family of experiments and its corresponding
visualization.
  Conclusions: Our proposal for the specification of replication changes seems
to fit the needs not only of replications in CS, but also in other research
areas. Nevertheless, further research is needed to improve it and to
disseminate its use among the research community.


  We have derived an analytical trace formula for the level density of the
H\'enon-Heiles potential using the improved stationary phase method, based on
extensions of Gutzwiller's semiclassical path integral approach. This trace
formula has the correct limit to the standard Gutzwiller trace formula for the
isolated periodic orbits far from all (critical) symmetry-breaking points. It
continuously joins all critical points at which an enhancement of the
semiclassical amplitudes occurs. We found a good agreement between the semi-
classical and the quantum oscillating level densities for the gross shell
structures and for the energy shell corrections, solving the symmetry breaking
problem at small energies.


  We study large arrays of mesoscopic junctions between gapless superconductors
where the tunneling processes of both, particle-hole and Cooper, pairs give
rise to a strongly retarded effective action which, contrary to the standard
case, can not be readily characterized in terms of a local Josephson energy.
This complexity is expected to arise in, e.g., the grain boundary and c-axis
junctions in layered high-T_c superconductors. A new representation for
describing collective phenomena in this system is introduced, and its phase
diagram is discussed, alongside the electrical conductivity.


  The centre of a monoidal category is a braided monoidal category. Monoidal
categories are monoidal objects (or pseudomonoids) in the monoidal bicategory
of categories. This paper provides a universal construction in a braided
monoidal bicategory that produces a braided monoidal object from any monoidal
object. Some properties and sufficient conditions for existence of the
construction are examined.


  Recent data from the ATOMKI group continues to confirm their claim of the
existence of a new $\sim17$ MeV particle. We review and numerically analyze the
data and then put into context constraints from other experiments, notably
neutrino scattering experiments such as the latest reactor anti-neutrino
coherent elastic neutrino nucleus scattering data and unitarity constraints
from solar neutrino observations. We show that minimal scenarios are disfavored
and discuss the model requirements to evade these constraints.


  A model for the wave motion of an internal wave in the presence of current in
the case of intermediate long wave approximation is studied. The lower layer is
considerably deeper, with a higher density than the upper layer. The flat
surface approximation is assumed. The fluids are incompressible and inviscid.
The model equations are obtained from the Hamiltonian formulation of the
dynamics in the presence of a depth-varying current. It is shown that an
appropriate scaling leads to the integrable Intermediate Long Wave Equation
(ILWE). Two limits of the ILWE leading to the integrable Benjamin-Ono and KdV
equations are presented as well.


  The ASACUSA (Atomic Spectroscopy And Collisions Using Slow Antiprotons)
collaboration at the Antiproton Decelerator at CERN aims to measure the ground
state hyperfine structure of antihydrogen. A Rabi-like spectrometer line has
been built for this purpose. A detector for counting antihydrogen is located at
the end of the beam line. This contribution will focus on the tracking
detector, whose challenging task it is to discriminate between background
events and antiproton annihilations originating from antihydrogen atoms which
are produced only in small amounts.


  Healthy ageing is associated with decline in cognitive abilities such as
language. Aerobic fitness has been shown to ameliorate decline in some
cognitive domains, but the potential benefits for language have not been
examined. In a cross-sectional sample, we investigated the relationship between
aerobic fitness and tip-of-the-tongue states. These are among the most frequent
cognitive failures in healthy older adults and occur when a speaker knows a
word but is unable to produce it. We found that healthy older adults indeed
experience more tip-of-the-tongue states than young adults. Importantly, higher
aerobic fitness levels decrease the probability of experiencing
tip-of-the-tongue states in healthy older adults. Fitness-related differences
in word finding abilities are observed over and above effects of age. This is
the first demonstration of a link between aerobic fitness and language
functioning in healthy older adults.


  We characterise regular Goursat categories through a specific stability
property of regular epimorphisms with respect to pullbacks. Under the
assumption of the existence of some pushouts this property can be also
expressed as a restricted Beck-Chevalley condition, with respect to the
fibration of points, for a special class of commutative squares. In the case of
varieties of universal algebras these results give, in particular, a structural
explanation of the existence of the ternary operations characterising
$3$-permutable varieties of universal algebras.


  We present results of cosmological N-body hydrodynamic chemistry simulations
of primordial structure growth and evolution in a scenario with warm dark
matter (WDM) having a mass of 3 keV (thermal relic) and compare with a model
consisting of standard cold dark matter (CDM). We focus on the high-redshift
universe ($z>6$), where the structure formation process should better reflect
the primordial (linear) differences in terms of matter power spectrum. We find
that early epochs can be exceptional probes of the dark-matter nature.
Non-linear WDM power spectra and mass functions are up to 2 dex lower than in
CDM and show spreads of factor of a few persisting in the whole first Gyr.
Runaway molecular cooling in WDM haloes results severely inhibited because of
the damping of power at large $k$ modes and hence cosmic (population III and
II-I) star formation rate (SFR) is usually suppressed with respect to CDM
predictions. Luminous objects formed in a WDM background are very rare at
$z>10$, due to the sparser and retarded evolution of early WDM mini-haloes
during the dark ages and their lack can be fitted with a simple analytical
formula depending only on magnitude and redshift. Future high-$z$ observations
of faint galaxies have the potential to discriminate between CDM and WDM
scenarios by means of cosmic stellar mass density (SMD) and specific SFR, as
well. When compared to the effects of alternative cosmologies (e.g.
non-Gaussian or dark-energy models) or of high-order corrections at large $z$
(e.g. primordial streaming motions or changes in the pristine IMF) the ones
caused by WDM are definitely more dramatic.


  We study a family of stationary increment Gaussian processes, indexed by
time. These processes are determined by certain measures sigma (generalized
spectral measures), and our focus here is on the case when the measure sigma is
a singular measure. We characterize the processes arising from when sigma is in
one of the classes of affine self-similar measures. Our analysis makes use of
Kondratiev-white noise spaces. With the use of a priori estimates and the Wick
calculus, we extend and sharpen earlier computations of Ito stochastic
integration developed for the special case of stationary increment processes
having absolutely continuous measures. We further obtain an associated Ito
formula.


  In undirected graphical models, learning the graph structure and learning the
functions that relate the predictive variables (features) to the responses
given the structure are two topics that have been widely investigated in
machine learning and statistics. Learning graphical models in two stages will
have problems because graph structure may change after considering the
features. The main contribution of this paper is the proposed method that
learns the graph structure and functions on the graph at the same time. General
graphical models with binary outcomes conditioned on predictive variables are
proved to be equivalent to multivariate Bernoulli model. The reparameterization
of the potential functions in graphical model by conditional log odds ratios in
multivariate Bernoulli model offers advantage in the representation of the
conditional independence structure in the model. Additionally, we impose a
structure penalty on groups of conditional log odds ratios to learn the graph
structure. These groups of functions are designed with overlaps to enforce
hierarchical function selection. In this way, we are able to shrink higher
order interactions to obtain a sparse graph structure. Simulation studies show
that the method is able to recover the graph structure. The analysis of county
data from Census Bureau gives interesting relations between unemployment rate,
crime and others discovered by the model.


  The importance of snow cover and ice extent in the Northern Hemisphere was
recognized by various authors leading to a positive feedback of surface
reflectivity on climate. In fact, the retreat of Arctic sea ice is accompanied
by enhanced solar input in the Arctic region, i.e. a decrease of the
terrestrial albedo. We have studied this effect for the past six decades and
estimate the corresponding global warming in the northern hemisphere. A simple
1-dimensional model is used that includes the simultaneous increase of the
greenhouse gases. Our results indicate that the latter directly cause a
temperature rise of only 0.2 K in 1955 to 2015, while a notably larger effect
0.7 +/- 0.2 K is found for the loss of Arctic sea ice in the same time. These
numbers comprise most of the reported mean temperature rise of 1.2 +/- 0.2 K of
the northern hemisphere. The origin of the sea-ice retreat is discussed, e.g.
internal variability or feedback by the CO2 concentration increase. Our data
also suggest a delayed response of the global surface temperature rise to the
loss of sea ice with a time constant of approximately 10 to 20 years.


  Detecting objects seamlessly blended into their surroundings represents a
complex task for both human cognitive capabilities and advanced artificial
intelligence algorithms. Currently, the majority of methodologies for detecting
camouflaged objects mainly focus on utilizing discriminative models with
various unique designs. However, it has been observed that generative models,
such as Stable Diffusion, possess stronger capabilities for understanding
various objects in complex environments; Yet their potential for the cognition
and detection of camouflaged objects has not been extensively explored. In this
study, we present a novel denoising diffusion model, namely FocusDiffuser, to
investigate how generative models can enhance the detection and interpretation
of camouflaged objects. We believe that the secret to spotting camouflaged
objects lies in catching the subtle nuances in details. Consequently, our
FocusDiffuser innovatively integrates specialized enhancements, notably the
Boundary-Driven LookUp (BDLU) module and Cyclic Positioning (CP) module, to
elevate standard diffusion models, significantly boosting the detail-oriented
analytical capabilities. Our experiments demonstrate that FocusDiffuser, from a
generative perspective, effectively addresses the challenge of camouflaged
object detection, surpassing leading models on benchmarks like CAMO, COD10K and
NC4K.


  Several statistics have been proposed for measuring the kSZ effect by
combining the small-scale CMB with galaxy surveys. We review five such
statistics, and show that they are all mathematically equivalent to the optimal
bispectrum estimator of type $\langle ggT \rangle$. Reinterpreting these kSZ
statistics as special cases of bispectrum estimation makes many aspects
transparent, for example optimally weighting the estimator, or incorporating
photometric redshift errors. We analyze the information content of the
bispectrum and show that there are two observables: the small-scale
galaxy-electron power spectrum $P_{ge}(k_S)$, and the large-scale
galaxy-velocity power spectrum $P_{gv}(k)$. The cosmological constraining power
of the kSZ arises from its sensitivity to fluctuations on large length scales,
where its effective noise level can be much better than galaxy surveys.


  Multi-frequency observations are needed to separate the CMB from foregrounds
and accurately extract cosmological information from the data. The Analytical
Blind Separation (ABS) method is dedicated to extracting the CMB power spectrum
from multi-frequency observations in the presence of contamination from
astrophysical foreground emission and instrumental noise. In this study, we
apply the ABS method to simulated sky maps as could be observed with a future
space-borne survey, in order to test the method's capability for determining
the CMB polarization $E$- and $B$-mode power spectra. We present the ABS method
performance on simulations for both a full-sky analysis and for an analysis
concentrating on sky regions less impacted by Galactic foreground emission. We
discuss the origin and minimization of biases in the estimated CMB polarization
angular power spectra. We find that the ABS method performs quite well for the
analysis of full-sky observations at intermediate and small angular scales, in
spite of strong foreground contamination. On the largest scales, extra work is
still required to reduce biases of various origins and the impact of confusion
between CMB $E$ and $B$ polarization for partial-sky analyses.


  Rotating systems in thermal equilibrium are ubiquitous in our world. In the
context of high energy physics, rotations would affect the phase structure of
QCD. However, the standard Monte-Carlo methods in rotating systems are
problematic because the chemical potentials for the angular momenta (angular
velocities) cause sign problems even for bosonic variables. In this article, we
demonstrate that the complex Langevin method (CLM) may overcome this issue. We
apply the CLM to the Yang-Mills (YM) type one-dimensional matrix model (matrix
quantum mechanics) that is a large-$N$ reduction (or dimensional reduction) of
the $(D+1)$-dimensional U$(N)$ pure YM theory (bosonic BFSS model). This model
shows a large-$N$ phase transition at finite temperature, which is analogous to
the confinement/deconfinement transition of the original YM theory, and our CLM
predicts that the transition temperature decreases as the angular momentum
chemical potential increases. In order to verify our results, we compute
several quantities via the minimum sensitivity method and find good
quantitative agreements. Hence, the CLM properly works in this rotating system.
We also argue that our results are qualitatively consistent with a holography
and the recent studies of the imaginary angular velocity in QCD. As a
byproduct, we develop an analytic approximation to treat the so-called ``small
black hole" phase in the matrix model.


  We propose that feedback-delayed manual tracking performance is limited by
fundamental constraints imposed by the physics of negative group delay. To test
this hypothesis, the results of an experiment in which subjects demonstrate
both reactive and predictive dynamics are modeled by a linear system with
delay-induced negative group delay. Although one of the simplest real-time
predictors conceivable, this model explains key components of experimental
observations. Most notably, it explains the observation that prediction time
linearly increases with feedback delay, up to a certain point when tracking
performance deteriorates. It also explains the transition from reactive to
predictive behavior with increasing feedback delay. The model contains only one
free parameter, the feedback gain, which has been fixed by comparison with one
set of experimental observations for the reactive case. Our model provides
quantitative predictions that can be tested in further experiments.


  Generating high quality texts with high diversity is important for many NLG
applications, but current methods mostly focus on building deterministic models
to generate higher quality texts and do not provide many options for promoting
diversity. In this work, we present a novel latent structured variable model to
generate high quality texts by enriching contextual representation learning of
encoder-decoder models. Specifically, we introduce a stochastic function to map
deterministic encoder hidden states into random context variables. The proposed
stochastic function is sampled from a Gaussian process prior to (1) provide
infinite number of joint Gaussian distributions of random context variables
(diversity-promoting) and (2) explicitly model dependency between context
variables (accurate-encoding). To address the learning challenge of Gaussian
processes, we propose an efficient variational inference approach to
approximate the posterior distribution of random context variables. We evaluate
our method in two typical text generation tasks: paraphrase generation and text
style transfer. Experimental results on benchmark datasets demonstrate that our
method improves the generation quality and diversity compared with other
baselines.


  We observe dark and bright intrinsic localized modes (ILMs) or discrete
breathers (DB) experimentally and numerically in a diatomic-like electrical
lattice. The generation of dark ILMs by driving a dissipative lattice with
spatially-homogenous amplitude is, to our knowledge, unprecedented. In
addition, the experimental manifestation of bright breathers within the bandgap
is also novel in this system. In experimental measurements the dark modes
appear just below the bottom of the top branch in frequency. As the frequency
is then lowered further into the band-gap, the dark DBs persist, until the
nonlinear localization pattern reverses and bright DBs appear on top of the
finite background. Deep into the bandgap, only a single bright structure
survives in a lattice of 32 nodes. The vicinity of the bottom band also
features bright and dark self-localized excitations. These results pave the way
for a more systematic study of dark breathers and their bifurcations in
diatomic-like chains.


  We present the experimental realization of the optimal estimation protocol
for a Pauli noisy channel. The method is based on the generation of 2-qubit
Bell states and the introduction of quantum noise in a controlled way on one of
the state subsystems. The efficiency of the optimal estimation, achieved by a
Bell measurement, is shown to outperform quantum process tomography.


  There has been an increased focus on creating conversational open-domain
dialogue systems in the spoken dialogue community. Unlike traditional dialogue
systems, these conversational systems cannot assume any specific information
need or domain restrictions, i.e., the only inherent goal is to converse with
the user on an unknown set of topics. While massive improvements in Natural
Language Understanding (NLU) and the growth of available knowledge resources
can partially support a robust conversation, these conversations generally lack
the rapport between two humans that know each other. We developed a robust
open-domain conversational system, Athena, that real Amazon Echo users access
and evaluate at scale in the context of the Alexa Prize competition. We
experiment with methods intended to increase intimacy between Athena and the
user by heuristically developing a rule-based user model that personalizes both
the current and subsequent conversations and evaluating specific personal
opinion question strategies in A/B studies. Our results show a statistically
significant positive impact on perceived conversation quality and length when
employing these strategies.


  In a quantum-noise limited system, weak-value amplification using
post-selection normally does not produce more sensitive measurements than
standard methods for ideal detectors: the increased weak value is compensated
by the reduced power due to the small post-selection probability. Here we
experimentally demonstrate recycled weak-value measurements using a pulsed
light source and optical switch to enable nearly deterministic weak-value
amplification of a mirror tilt. Using photon counting detectors, we demonstrate
a signal improvement by a factor of $4.4 \pm 0.2$ and a signal-to-noise ratio
improvement of $2.10 \pm 0.06$, compared to a single-pass weak-value
experiment, and also compared to a conventional direct measurement of the tilt.
The signal-to-noise ratio improvement could reach around 6 for the parameters
of this experiment, assuming lower loss elements.


  We discuss the meaning of a Casher-Banks relation for the Dirac operator
eigenvalues in MQCD. It suggests the interpretaion of the eigenvalue as a
coordinate involved in the brane configuration.


  Word embeddings are a core component of modern natural language processing
systems, making the ability to thoroughly evaluate them a vital task. We
describe DiaLex, a benchmark for intrinsic evaluation of dialectal Arabic word
embedding. DiaLex covers five important Arabic dialects: Algerian, Egyptian,
Lebanese, Syrian, and Tunisian. Across these dialects, DiaLex provides a
testbank for six syntactic and semantic relations, namely male to female,
singular to dual, singular to plural, antonym, comparative, and genitive to
past tense. DiaLex thus consists of a collection of word pairs representing
each of the six relations in each of the five dialects. To demonstrate the
utility of DiaLex, we use it to evaluate a set of existing and new Arabic word
embeddings that we developed. Our benchmark, evaluation code, and new word
embedding models will be publicly available.


  With the entire Small Magellanic Cloud (SMC) mapped by the Spitzer Space
Telescope and Herschel Space Observatory, we were able to search 8-250 micron
images in order to identify infrared (IR) emission associated with SMC
supernova remnants (SNRs). A valid detection had to correspond with known
X-ray, Halpha and radio emission from the SNRs. From the 24 known SNRs, we made
5 positive detections with another 5 possible detections. Two detections are
associated with pulsars or pulsar wind nebula, and another three detections are
part of the extended nebulous emission from the SNRs. We modelled dust emission
where fast moving electrons are predicted to collide and heat dust grains which
then radiate in IR. With known distance (62.44+-0.47kpc), measured SNR sizes,
electron densities, temperatures from X-ray emission as well as hydrogen
densities, the modelling of SMC SNRs is straightforward.
  If the higher range of hydrogen and electron densities were to be accepted,
we would expect almost all SMC SNRs to be detected in the IR, at least at 24
micron, but the actual detection rate is only 25%. One possible and common
explanation for this discrepancy is that small grains have been destroyed by
the SNRs shockwave. However, within the uncertainties of hydrogen and electron
densities, we find that infrared dust emission can be explained reasonably
well, without invoking dust destruction. There is no conclusive evidence that
SNRs destroy swept-up ISM dust.


  Lack of global data inventories obstructs scientific modeling of and response
to landslide hazards which are oftentimes deadly and costly. To remedy this
limitation, new approaches suggest solutions based on citizen science that
requires active participation. However, as a non-traditional data source,
social media has been increasingly used in many disaster response and
management studies in recent years. Inspired by this trend, we propose to
capitalize on social media data to mine landslide-related information
automatically with the help of artificial intelligence (AI) techniques.
Specifically, we develop a state-of-the-art computer vision model to detect
landslides in social media image streams in real time. To that end, we create a
large landslide image dataset labeled by experts and conduct extensive model
training experiments. The experimental results indicate that the proposed model
can be deployed in an online fashion to support global landslide susceptibility
maps and emergency response.


  The intrinsic instability of underdoped copper oxides towards inhomogeneous
states is one of the central puzzles of the physics of correlated materials.
The influence of the Mott physics on the doping-temperature phase diagram of
copper oxides represents a major issue that is subject of intense theoretical
and experimental effort. Here, we investigate the ultrafast electron dynamics
in prototypical single-layer Bi-based cuprates at the energy scale of the
O-2p$\rightarrow$Cu-3d charge-transfer (CT) process. We demonstrate a clear
evolution of the CT excitations from incoherent and localized, as in a Mott
insulator, to coherent and delocalized, as in a conventional metal. This
reorganization of the high-energy degrees of freedom occurs at the critical
doping p$_{cr}\simeq$0.16 irrespective of the temperature, and it can be well
described by dynamical mean field theory calculations. We argue that the onset
of the low-temperature charge instabilities is the low-energy manifestation of
the underlying Mottness that characterizes the p<p$_{cr}$ region of the phase
diagram. This discovery sets a new framework for theories of charge order and
low-temperature phases in underdoped copper oxides.


  Recent Suzaku X-ray observations of the ejecta-dominated supernova remnant
W49B have shown that in the global spectrum there is a clear indication for the
presence of overionized plasma whose physical origin is still under debate. In
order to ascertain the physical origin of such a rapidly cooling plasma, we
focus on the study of its spatial localization within the X-ray emitting
ejecta. We confirm the presence of a saw-edged excess (interpreted as a strong
radiative recombination continuum) in the global spectrum above 8 keV, emerging
above the ionization-equilibrium model. We produce a hardness ratio map to
determine where the plasma is overionized and we perform a spectral analysis of
the regions with and without strong overionization. We find that the
overionized plasma is localized in the center of the remnant and in its western
jet, while it is not detected in the bright eastern jet, where the expansion of
the ejecta is hampered by their interaction with a dense interstellar cloud.
The location of overionized plasma suggests that the inner ejecta are rapidly
cooling by expansion, unlike the outer ejecta, for which expansion is hampered
by interstellar clouds seen in H2


  Gauge theory is the foundation of the particle physics Standard Model (SM).
Considering the multiple gauge sectors for one gauge transformation, we study
the generalized Abelian and non-Abelian (Yang-Mills theory) gauge theories. We
first point out that the U(1) gauge theory has a few unique properties, which
provide the motivations for the generalized Yang-Mills theory. Also, we
consider the generalized Abelian gauge theory, and study the Higgs mechanism
with new interesting properties. In addition, we propose the simple and generic
generalizations of Yang-Mills theory. In the simple generalization, we realize
two specific properties in the Abelian gauge theory. For applications in
particle physics, we propose the invisible axion model with TeV-scale
Peceei-Quinn symmetry breaking. We can solve the strong CP problem, and obtain
the effective decay constant around the intermediate scale. Moreover, we study
the SM electroweak symmetry breaking induced from the symmetry breaking in the
other gauge Sector. In particular, we can easily obtain the strong first order
electroweak phase transition in the SM, which is important for electroweak
baryogenesis and gravitational wave.


  The development of microfluidic devices has recently revived the interest in
"old" problems associated with transport at, or across, interfaces. As the
characteristic sizes are decreased, the use of pressure gradients to transport
fluids becomes problematic, and new, interface driven, methods must be
considered. This has lead to new investigations of flow near interfaces, and to
the conception of interfaces engineered at various scales to reduce flow
friction. In this review, we discuss the present theoretical understanding of
flow past solid interfaces at different length scales. We also briefly discuss
the corresponding phenomenon of heat transport, and the influence of surface
slip on interface driven (e.g. electro-osmotic) flows.


  The primary objective of most lead optimization campaigns is to enhance the
binding affinity of ligands. For large molecules such as antibodies,
identifying mutations that enhance antibody affinity is particularly
challenging due to the combinatorial explosion of potential mutations. When the
structure of the antibody-antigen complex is available, relative binding free
energy (RBFE) methods can offer valuable insights into how different mutations
will impact the potency and selectivity of a drug candidate, thereby reducing
the reliance on costly and time-consuming wet-lab experiments. However,
accurately simulating the physics of large molecules is computationally
intensive. We present an active learning framework that iteratively proposes
promising sequences for simulators to evaluate, thereby accelerating the search
for improved binders. We explore different modeling approaches to identify the
most effective surrogate model for this task, and evaluate our framework both
using pre-computed pools of data and in a realistic full-loop setting.


  We present an ab-initio study of the temperature dependent elastic constants
of BAs, a semiconductor that exhibits ultra-high thermal conductivity and is
under investigation for thermal management in electronics. We test the
consistency of our predictions by computing the temperature dependent sound
velocity of the longitudinal acoustic mode along the $[111]$ direction and
comparing with experiment. Furthermore, as a byproduct, we present the room
temperature phonon dispersions, and the temperature dependent thermal
expansion, isobaric heat capacity, and average Gr\"{u}neisen parameter
comparing with the most updated experiments and previous calculations when
available. Finally, we present the theoretical estimate of the temperature
dependent mean square atomic displacements.


  This study investigates engagement patterns related to OpenAI's ChatGPT on
Japanese Twitter, focusing on two distinct user groups - early and late
engagers, inspired by the Innovation Theory. Early engagers are defined as
individuals who initiated conversations about ChatGPT during its early stages,
whereas late engagers are those who began participating at a later date. To
examine the nature of the conversations, we employ a dual methodology,
encompassing both quantitative and qualitative analyses. The quantitative
analysis reveals that early engagers often engage with more forward-looking and
speculative topics, emphasizing the technological advancements and potential
transformative impact of ChatGPT. Conversely, the late engagers intereact more
with contemporary topics, focusing on the optimization of existing AI
capabilities and considering their inherent limitations. Through our
qualitative analysis, we propose a method to measure the proportion of shared
or unique viewpoints within topics across both groups. We found that early
engagers generally concentrate on a more limited range of perspectives, whereas
late engagers exhibit a wider range of viewpoints. Interestingly, a weak
correlation was found between the volume of tweets and the diversity of
discussed topics in both groups. These findings underscore the importance of
identifying semantic bias, rather than relying solely on the volume of tweets,
for understanding differences in communication styles between groups within a
given topic. Moreover, our versatile dual methodology holds potential for
broader applications, such as studying engagement patterns within different
user groups, or in contexts beyond ChatGPT.


  This paper presents an alternate representation framework to commonly used
time-frequency representation for acoustic scene classification (ASC). A raw
audio signal is represented using a pre-trained convolutional neural network
(CNN) using its various intermediate layers. The study assumes that the
representations obtained from the intermediate layers lie in low-dimensions
intrinsically. To obtain low-dimensional embeddings, principal component
analysis is performed, and the study analyzes that only a few principal
components are significant. However, the appropriate number of significant
components are not known. To address this, an automatic dictionary learning
framework is utilized that approximates the underlying subspace. Further, the
low-dimensional embeddings are aggregated in a late-fusion manner in the
ensemble framework to incorporate hierarchical information learned at various
intermediate layers. The experimental evaluation is performed on publicly
available DCASE 2017 and 2018 ASC datasets on a pre-trained 1-D CNN, SoundNet.
Empirically, it is observed that deeper layers show more compression ratio than
others. At 70% compression ratio across different datasets, the performance is
similar to that obtained without performing any dimensionality reduction. The
proposed framework outperforms the time-frequency representation based methods.


  Ultrastable vapor-deposited glasses display uncommon material properties.
Most remarkably, upon heating they are believed to melt via a liquid front that
originates at the free surface and propagates over a mesoscopic crossover
length, before crossing over to bulk melting. We combine swap Monte Carlo with
molecular dynamics simulations to prepare and melt isotropic amorphous films of
unprecedendtly high kinetic stability. We are able to directly observe both
bulk and front melting, and the crossover between them. We measure the front
velocity over a broad range of conditions, and a crossover length scale that
grows to nearly $400$ particle diameters in the regime accessible to
simulations. Our results disentangle the relative roles of kinetic stability
and vapor deposition in the physical properties of stable glasses.


  Reliability-oriented sensitivity analysis aims at combining both reliability
and sensitivity analyses by quantifying the influence of each input variable of
a numerical model on a quantity of interest related to its failure. In
particular, target sensitivity analysis focuses on the occurrence of the
failure, and more precisely aims to determine which inputs are more likely to
lead to the failure of the system. The Shapley effects are quantitative global
sensitivity indices which are able to deal with correlated input variables.
They have been recently adapted to the target sensitivity analysis framework.
In this article, we investigate two importance-sampling-based estimation
schemes of these indices which are more efficient than the existing ones when
the failure probability is small. Moreover, an extension to the case where only
an i.i.d. input/output N-sample distributed according to the importance
sampling auxiliary distribution is proposed. This extension allows to estimate
the Shapley effects only with a data set distributed according to the
importance sampling auxiliary distribution stemming from a reliability analysis
without additional calls to the numerical model. In addition, we study
theoretically the absence of bias of some estimators as well as the benefit of
importance sampling. We also provide numerical guidelines and finally,
realistic test cases show the practical interest of the proposed methods.


  Probabilistic modelling of power systems operation and planning processes
depends on data-driven methods, which require sufficiently large datasets. When
historical data lacks this, it is desired to model the underlying data
generation mechanism as a probability distribution to assess the data quality
and generate more data, if needed. Kernel density estimation (KDE) based models
are popular choices for this task, but they fail to adapt to data regions with
varying densities. In this paper, an adaptive KDE model is employed to
circumvent this, where each kernel in the model has an individual bandwidth.
The leave-one-out maximum log-likelihood (LOO-MLL) criterion is proposed to
prevent the singular solutions that the regular MLL criterion gives rise to,
and it is proven that LOO-MLL prevents these. Relying on this guaranteed
robustness, the model is extended by adjustable weights for the kernels. In
addition, a modified expectation-maximization algorithm is employed to
accelerate the optimization speed reliably. The performance of the proposed
method and models are exhibited on two power systems datasets using different
statistical tests and by comparison with Gaussian mixture models. Results show
that the proposed models have promising performance, in addition to their
singularity prevention guarantees.


  Coarse-graining is a standard method of extracting a simple Markov process
from a more complicated one by identifying states. Here we extend
coarse-graining to open Markov processes. An "open" Markov process is one where
probability can flow in or out of certain states called "inputs" and "outputs".
One can build up an ordinary Markov process from smaller open pieces in two
basic ways: composition, where we identify the outputs of one open Markov
process with the inputs of another, and tensoring, where we set two open Markov
processes side by side. In previous work, Fong, Pollard and the first author
showed that these constructions make open Markov processes into the morphisms
of a symmetric monoidal category. Here we go further by constructing a
symmetric monoidal double category where the 2-morphisms are ways of
coarse-graining open Markov processes. We also extend the already known
"black-boxing" functor from the category of open Markov processes to our double
category. Black-boxing sends any open Markov process to the linear relation
between input and output data that holds in steady states, including
nonequilibrium steady states where there is a nonzero flow of probability
through the process. To extend black-boxing to a functor between double
categories, we need to prove that black-boxing is compatible with
coarse-graining.


  Spherical black-hole (BH) solutions have been found in the bumblebee gravity
where a vector field nonminimally couples to the Ricci tensor. We study dynamic
(in)stability associated with the gravitational and vector perturbations of odd
parity against these bumblebee BHs. Under the plane-wave approximation, we find
that bumblebee BHs do not suffer ghost instability, but gradient instability
and tachyonic instability exist when the bumblebee charge exceeds certain
values. The existence of the instabilities also depends on the nonminimal
coupling constant $\xi$ that, there is a minimal value $\xi \sim 4\pi G$ with
$G$ the gravitational constant for the instabilities to happen. The theoretical
consideration for bumblebee BH stability turns out to place stronger
constraints on the parameter space than those from the recent observations of
supermassive BH shadows by the Event Horizon Telescope Collaboration. It is
also reminiscent of Penrose's cosmic censorship conjecture since the charge of
bumblebee BHs cannot be too large due to the dynamic instabilities.
Specifically, for $\xi(\xi-16\pi G) > 0$, we find that the charge of a
bumblebee BH cannot be larger than its mass.


  The Expectation-Maximization (EM) algorithm has been predominantly used to
approximate the maximum likelihood estimation of the location-scale Gaussian
mixtures. However, when the models are over-specified, namely, the chosen
number of components to fit the data is larger than the unknown true number of
components, EM needs a polynomial number of iterations in terms of the sample
size to reach the final statistical radius; this is computationally expensive
in practice. The slow convergence of EM is due to the missing of the locally
strong convexity with respect to the location parameter on the negative
population log-likelihood function, i.e., the limit of the negative sample
log-likelihood function when the sample size goes to infinity. To efficiently
explore the curvature of the negative log-likelihood functions, by specifically
considering two-component location-scale Gaussian mixtures, we develop the
Exponential Location Update (ELU) algorithm. The idea of the ELU algorithm is
that we first obtain the exact optimal solution for the scale parameter and
then perform an exponential step-size gradient descent for the location
parameter. We demonstrate theoretically and empirically that the ELU iterates
converge to the final statistical radius of the models after a logarithmic
number of iterations. To the best of our knowledge, it resolves the
long-standing open question in the literature about developing an optimization
algorithm that has optimal statistical and computational complexities for
solving parameter estimation even under some specific settings of the
over-specified Gaussian mixture models.


  We define different non-relativistic limit of p-brane with the help of
canonical form of the p-brane action. We discuss properties of these actions
and their symmetries.


  In this paper we propose a special type of aggregation function which
generalizes the notion of Ordered Weighted Averaging Function - OWA. The
resulting functions are called Dynamic Ordered Weighted Averaging Functions ---
DYOWAs. This generalization will be developed in such way that the weight
vectors are variables depending on the input vector. Particularly, this
operators generalize the aggregation functions: Minimum, Maximum, Arithmetic
Mean, Median, etc, which are extensively used in image processing. In this
field of research two problems are considered: The determination of methods to
reduce images and the construction of techniques which provide noise reduction.
The operators described here are able to be used in both cases. In terms of
image reduction we apply the methodology provided by Patermain et al. We use
the noise reduction operators obtained here to treat the images obtained in the
first part of the paper, thus obtaining images with better quality.


  By replacing the spatial derivative with the Dunkl derivative, we generalize
the Fokker-Planck equation in (1+1) dimensions. We obtain the
Dunkl-Fokker-Planck eigenvalues equation and solve it for the harmonic
oscillator plus a centrifugal-type potential. Furthermore, when the drift
function is odd, we reduce our results to those of the recently developed
Wigner-Dunkl supersymmetry.


  The variational principle for a thin dust shell in General Relativity is
constructed. The principle is compatible with the boundary-value problem of the
corresponding Euler-Lagrange equations, and leads to ``natural boundary
conditions'' on the shell. These conditions and the gravitational field
equations which follow from an initial variational principle, are used for
elimination of the gravitational degrees of freedom. The transformation of the
variational formula for spherically-symmetric systems leads to two natural
variants of the effective action. One of these variants describes the shell
from a stationary interior observer's point of view, another from the exterior
one. The conditions of isometry of the exterior and interior faces of the shell
lead to the momentum and Hamiltonian constraints. The canonical equivalence of
the mentioned systems is shown in the extended phase space. Some particular
cases are considered.


  We prove decoupling inequalities for mixed-homogeneous bivariate polynomials,
which partially answers a conjecture of Bourgain, Demeter and Kemp.


  We have performed a systematic analysis of the dynamics of different galaxy
populations in galaxy groups from the 2dFGRS. For this purpose we have combined
all the groups into a single system, where velocities v and radius r are
expressed adimensionally. We have used several methods to compare the
distributions of relative velocities of galaxies with respect to the group
centre for samples selected according to their spectral type (as defined by
Madgwick et al., 2002), bj band luminosity and B-R colour index. We have found
strong segregation effects: spectral type I objects show a statistically
narrower velocity distribution than that of galaxies with a substantial star
formation activity (type II-IV). Similarly, the same behavior is observed for
galaxies with colour index B-R>1 compared to galaxies with B-R<1. Bright
(Mb<-19) and faint (Mb>-19) galaxies show the same segregation. It is not
important once the sample is restricted to a given spectral type. These effects
are particularly important in the central region (Rp<Rvirial/2) and do not have
a strong dependence on the mass of the parent group. These trends show a strong
correlation between the dynamics of galaxies in groups and star formation rate
reflected both by spectral type and by colour index.


  Calabi's Bernstein-type theorem asserts that a zero mean curvature entire
graph in Lorentz-Minkowski space $\boldsymbol L^3$ which admits only space-like
points is a space-like plane. Using the fluid mechanical duality between
minimal surfaces in Euclidean 3-space $\boldsymbol E^3$ and maximal surfaces in
Lorentz-Minkowski space $\boldsymbol L^3$, we give an improvement of this
Bernstein-type theorem. More precisely, we show that a zero mean curvature
entire graph in $\boldsymbol L^3$ which does not admit time-like points
(namely, a graph consists of only space-like and light-like points) is a plane.


  The spectrum of the 1.0-8.0 keV cosmic X-ray background (CXB) at galactic
latitudes > 25 degrees has been measured using the BeppoSAX LECS and MECS
instruments. The spectrum is consistent with a power-law of photon index 1.40
+/- 0.04 and normalization 11.7 +/- 0.5 photon cm^{-2} s^{-1} keV^{-1} sr^{-1}
at 1 keV. Our results are in good agreement with previous ROSAT PSPC
(Georgantopuolos et al. 1996), ASCA GIS (Myaji et al. 1998) and rocket
(McCammon & Sanders 1990) measurements. On the contrary, previous measurements
with the HEAO1 A2 (Marshall et al. 1980) and the ASCA SIS (Gendreau et al.
1995) instruments, are characterized by normalizations which are respectively
35% and 25% smaller than ours.


  We show that diffraction features of $1D$ quasicrystals can be retrieved from
a single topological quantity, the \v{C}ech cohomology group,
$\check{H}^{1}\cong\mathbb{Z}^2$, which encodes all relevant combinatorial
information of tilings. We present a constructive way to calculate
$\check{H}^{1}$ for a large variety of aperiodic tilings. By means of two
winding numbers, we compare the diffraction features contained in
$\check{H}^{1}$ to the gap labeling theorem, another topological tool used to
label spectral gaps in the integrated density of states. In the light of this
topological description, we discuss similarities and differences between
families of aperiodic tilings, and the resilience of topological features
against perturbations.


  Stokes flows with near-touching rigid particles induce near-singular
lubrication forces under relative motion, making their accurate numerical
treatment challenging. With the aim of controlling the accuracy with a
computationally cheap method, we present a new technique that combines the
method of fundamental solutions (MFS) with the method of images. For rigid
spheres, we propose to represent the flow using Stokeslet proxy sources on
interior spheres, augmented by lines of image sources adapted to each
near-contact to resolve lubrication. Source strengths are found by a
least-squares solve at contact-adapted boundary collocation nodes. We include
extensive numerical tests, and validate against reference solutions from a
well-resolved boundary integral formulation. With less than 60 image sources
per particle per contact, we show controlled uniform accuracy to three relative
digits in surface velocities, and up to five digits in particle forces and
torques, for all separations down to a thousandth of the radius. In the special
case of flows around fixed particles, the proxy sphere alone gives controlled
accuracy. A one-body preconditioning strategy allows acceleration with the fast
multipole method, hence close to linear scaling in the number of particles.
This is demonstrated by solving problems of up to 2000 spheres on a workstation
using only 700 proxy sources per particle.


  From personalised medicine to targeted advertising, it is an inherent task to
provide a sequence of decisions with historical covariates and outcome data.
This requires understanding of both the dynamics and heterogeneity of treatment
effects. In this paper, we are concerned with detecting abrupt changes in the
treatment effects in terms of the conditional average treatment effect (CATE)
in a sequential fashion. To be more specific, at each time point, we consider a
nonparametric model to allow for maximal flexibility and robustness. Along the
time, we allow for temporal dependence on historical covariates and noise
functions. We provide a kernel-based change point estimator, which is shown to
be consistent in terms of its detection delay, under an average run length
control. Numerical results are provided to support our theoretical findings.


  We present a rigorous mathematical treatment of the zero-field orbital
magnetic susceptibility of a non-interacting Bloch electron gas, at fixed
temperature and density, for both metals and semiconductors/insulators. In
particular, we obtain the Landau-Peierls formula in the low temperature and
density limit as conjectured by T. Kjeldaas and W. Kohn in 1957.


  Experimental evidences show that in gene transcription, RNA polymerase has
the possibility to be stalled at certain position of the transcription
template. This may be due to the template damage, or protein barriers. Once
stalled, polymerase may backtrack along the template to the previous nucleotide
to wait for the repair of the damaged site, or simply bypass the barrier or
damaged site and consequently synthesize an incorrect messenger RNA, or degrade
and detach from the template. Thus, the {\it effective} transcription rate (the
rate to synthesize correct product mRNA) and the transcription {\it
effectiveness} (the ratio of the {\it effective} transcription rate to the {\it
effective} transcription initiation rate) are both influenced by polymerase
stalling events. This study shows that, Without backtracking, detachment of
stalled polymerase can also help to increase the {\it effective} transcription
rate and transcription {\it effectiveness}. Generally, the increase of bypass
rate of the stalled polymerase will lead to the decrease of the {\it effective}
transcription rate and transcription {\it effectiveness}. But when both
detachment rate and backtracking rate of the stalled polymerase vanish, the
{\it effective} transcription rate may also be increased by the bypass
mechanism.


  The nominal Kepler mission provided very high-precision photometric data.
Using these data, interesting phenomena such as spots, and ``hump and spike''
features were observed in the light curves of some normal A and metallic lined
A stars (Am stars). However, the connection between such phenomena and the
chemical peculiarity of the Am stars is still unclear. In order to make
progress on these issues, its important to collect high-resolution
spectroscopic data to determine their fundamental parameters and individual
chemical abundances. In this paper, we present a spectroscopic study of a
sample of ``hump and spike'' stars in the nominal Kepler field. We used data
collected with the High Efficiency and Resolution Mercator \'{E}chelle
Spectrograph (HERMES). We determined the spectral type of these stars and
obtained the atmospheric stellar parameters such as effective temperatures,
surface gravities, projected rotational, microturbulent and radial velocities.
We also performed a detailed individual chemical abundance analysis for each
target. We confirmed KIC 3459226 and KIC 6266219 as Am stars, KIC 9349245 as a
marginal Am star, while KIC 4567097, KIC 4818496, KIC 5524045, KIC 5650229, KIC
7667560, and KIC 9272082 are non-Am stars. To estimate their evolutionary
phases, all the stars were placed in the Hertzsprung-Russell (HR) diagram.
Based on their spectral classification and chemical abundance pattern, we
reclassified KIC 6266219 (previously treated as chemically normal) as an Am
star (kA3hA7mF1) and KIC 9272082 (previously treated as Am) as non-Am.


  We consider a few ansatzs for the four and seven forms of 11-dimensional
supergravity over AdS_4 x S^7/Z_k while try to keep the geometry unchanged.
From the 4-form equations, we arrive at some massless scalars and pseudoscalars
in the bulk of Euclidean AdS_4 that match with some boundary $\Delta_+$=3
operators. Indeed, the main objects are instantons and domain walls as the
fully and partially localized objects in the external space, respectively. The
latter comes from an (anti)M5-brane wrapping partly around three internal
directions similar to the fuzzy S^3/Z_k solutions. Except for the first
solutions of adding some anti-M2-branes$\mid$(M2-branes) to the original
M2-branes, the objects backreact on the geometry although small$\mid$(break all
supersymmetries and destabilize the vacua). The dual 3-dimensional field theory
solutions are got by the skew-whiffing 8_s $\rightarrow$ 8_v and 8_s
$\rightarrow$ 8_c for the scalars and pseudoscalars respectively, while the
gauge fields are used mainly for the k=1,2 cases where the R-symmetry and
supersymmetry are enhanced as SU(4) x U(1) $\rightarrow$ SO(8) and N=6
$\rightarrow$ N=8 respectively, and also for pseudoscalars. Further, for the
pseudoscalars we propose a special boundary deformation, with a fermion field,
that is equivalent to a multi-trace deformation already studied for the bulk
m^2=-2 conformally coupled pseudoscalar.


  We approach the problem of constructing an explicit holographic dictionary
for the AdS$_2$/CFT$_1$ correspondence in the context of higher derivative
gravitational actions in AdS$_2$ space-times. These actions are obtained by an
$S^2$ reduction of four-dimensional ${\cal N}=2$ Wilsonian effective actions
with Weyl squared interactions restricted to constant scalar backgrounds. BPS
black hole near-horizon space-times fall into this class of backgrounds, and by
identifying the boundary operators dual to the bulk fields, we explicitly show
how the Wald entropy of the BPS black hole is holographically encoded in the
anomalous transformation of the operator dual to a composite bulk field.
Additionally, using a 2d/3d lift, we show that the CFT holographically dual to
AdS$_2$ is naturally embedded in the chiral half of the CFT$_2$ dual to the
AdS$_3$ space-time, and we identify the specific operator in CFT$_1$ that
encodes the chiral central charge of the CFT$_2$.


  Let $X$ be a projective variety and let $E$ be a reduced divisor. We study
the asymptotic growth of the dimension of the space of global sections of
powers of a divisor $D$ on $X\backslash E$. We show that it is always bounded
by a polynomial of degree $\dim(X)$, if finite. Furthermore, when $D$ is big,
we characterize the finiteness of the cohomology groups in question. This
answers a question of Zariski and Koll\'ar.


  Let $ \Omega \subsetneq \mathbf{R}^n\,(n\geq 2)$ be an unbounded convex
domain. We study the minimal surface equation in $\Omega$ with boundary value
given by the sum of a linear function and a bounded uniformly continuous
function in $ \mathbf{R}^n$. If $ \Omega $ is not a half space, we prove that
the solution is unique. If $ \Omega $ is a half space, we prove that graphs of
all solutions form a foliation of $\Omega\times\mathbf{R}$. This can be viewed
as a stability type theorem for Edelen-Wang's Bernstein type theorem in
\cite{EW2021}. We also establish a comparison principle for the minimal surface
equation in $\Omega$.


  We tackle the task of text-to-3D creation with pre-trained latent-based NeRFs
(NeRFs that generate 3D objects given input latent code). Recent works such as
DreamFusion and Magic3D have shown great success in generating 3D content using
NeRFs and text prompts, but the current approach of optimizing a NeRF for every
text prompt is 1) extremely time-consuming and 2) often leads to low-resolution
outputs. To address these challenges, we propose a novel method named
3D-CLFusion which leverages the pre-trained latent-based NeRFs and performs
fast 3D content creation in less than a minute. In particular, we introduce a
latent diffusion prior network for learning the w latent from the input CLIP
text/image embeddings. This pipeline allows us to produce the w latent without
further optimization during inference and the pre-trained NeRF is able to
perform multi-view high-resolution 3D synthesis based on the latent. We note
that the novelty of our model lies in that we introduce contrastive learning
during training the diffusion prior which enables the generation of the valid
view-invariant latent code. We demonstrate through experiments the
effectiveness of our proposed view-invariant diffusion process for fast
text-to-3D creation, e.g., 100 times faster than DreamFusion. We note that our
model is able to serve as the role of a plug-and-play tool for text-to-3D with
pre-trained NeRFs.


  Samtla (Search And Mining Tools with Linguistic Analysis) is a digital
humanities system designed in collaboration with historians and linguists to
assist them with their research work in quantifying the content of any textual
corpora through approximate phrase search and document comparison. The
retrieval engine uses a character-based n-gram language model rather than the
conventional word-based one so as to achieve great flexibility in language
agnostic query processing.
  The index is implemented as a space-optimised character-based suffix tree
with an accompanying database of document content and metadata. A number of
text mining tools are integrated into the system to allow researchers to
discover textual patterns, perform comparative analysis, and find out what is
currently popular in the research community.
  Herein we describe the system architecture, user interface, models and
algorithms, and data storage of the Samtla system. We also present several case
studies of its usage in practice together with an evaluation of the systems'
ranking performance through crowdsourcing.


  We present a self-consistent evaluation of the constituent quark masses in
the three flavor Larkin-Ovchinnikov-Fulde-Ferrell (LOFF) phases of QCD,
employing an improved Nambu-Jona Lasinio model. This result allows to determine
the window for values of the baryonic chemical potential where the LOFF state
is energetically favored.


  This document describes the Gloss Ontology. The ontology and associated class
model are organised into several packages. Section 2 describes each package in
detail, while Section 3 contains a summary of the whole ontology.


  $G_0W_0$ calculations for predicting vertical ionization potentials (IPs) and
electron affinities of molecules and clusters are known to show a significant
dependence on the density functional theory (DFT) starting point. A number of
non-empirical procedures to find an optimal starting point have been proposed,
typically based on tuning the amount of HF exchange in the underlying hybrid
functional specifically for the system at hand. For the case of
$\pi$-conjugated molecular chains, these approaches lead to a significantly
different amount of HF exchange for different oligomer sizes. In this study, we
analyze if and how strongly this size dependence affects the ability of
non-empirical tuning approaches to predict accurate IPs for $\pi$-conjugated
molecular chains of increasing chain length. To this end, we employ three
different non-empirical tuning procedures for the $G_0W_0$ starting point to
calculate the IP of polyene oligomers up to 22 repeat units and compare the
results to highly accurate coupled-cluster calculations. We find that, despite
its size dependence, using an IP-tuned hybrid functional as a starting point
for $G_0W_0$ yields excellent agreement with the reference data for all chain
lengths.


  We present new high angular resolution observations of the 13CO 1-0
rotational line towards the HBe star R Mon, obtained with the IRAM Bure
Interferometer, along with the previous results in the observed transitions
12CO 1-0 and 2-1. We have used a flat disk model to fit the 12CO 1-0 and 2-1,
and 13CO 1-0 emission, in a strip perpendicular to the outflow axis. The model
assumes standard abundances (X(12CO) = 8x10^-5, X(13CO) = 9x10^7), radial
potential temperature and density laws (T (K) = T0 r^-q, rho (cm^-3) = rho0
r^-p), and Local Thermodynamic Equilibrium. The 13CO and 12CO emission is
consistent with a flat disk at an inclination angle of 20 degrees in Keplerian
rotation around the star. The gaseous disk is fitted with a mass of 0.014 Msun,
an outer radius of 1500 AU, a temperature of 4500 K at the inner radius (1 AU),
and values of q=0.62 and p=1.3 for the indexes of the temperature and density
laws. This new 13CO observations allow us to conclude that the disk around R
Mon is flat. Our result confirms previous works suggesting a predominant flat
geometry in disks around early Be stars.


  In this paper, we propose a novel structural correlation filter combined with
a multi-task Gaussian particle filter (KCF-GPF) model for robust visual
tracking. We first present an assemble structure where several KCF trackers as
weak experts provide a preliminary decision for a Gaussian particle filter to
make a final decision. The proposed method is designed to exploit and
complement the strength of a KCF and a Gaussian particle filter. Compared with
the existing tracking methods based on correlation filters or particle filters,
the proposed tracker has several advantages. First, it can detect the tracked
target in a large-scale search scope via weak KCF trackers and evaluate the
reliability of weak trackers\rq decisions for a Gaussian particle filter to
make a strong decision, and hence it can tackle fast motions, appearance
variations, occlusions and re-detections. Second, it can effectively handle
large-scale variations via a Gaussian particle filter. Third, it can be
amenable to fully parallel implementation using importance sampling without
resampling, thereby it is convenient for VLSI implementation and can lower the
computational costs. Extensive experiments on the OTB-2013 dataset containing
50 challenging sequences demonstrate that the proposed algorithm performs
favourably against 16 state-of-the-art trackers.


  This paper presents a cross-layer approach to jointly design adaptive
modulation and coding (AMC) at the physical layer and cooperative truncated
automatic repeat request (ARQ) protocol at the data link layer. We first derive
an exact closed form expression for the spectral efficiency of the proposed
joint AMC-cooperative ARQ scheme. Aiming at maximizing this system performance
measure, we then optimize an AMC scheme which directly satisfies a prescribed
packet loss rate constraint at the data-link layer. The results indicate that
utilizing cooperative ARQ as a retransmission strategy, noticeably enhances the
spectral efficiency compared with the system that employs AMC alone at the
physical layer. Moreover, the proposed adaptive rate cooperative ARQ scheme
outperforms the fixed rate counterpart when the transmission modes at the
source and relay are chosen based on the channel statistics. This in turn
quantifies the possible gain achieved by joint design of AMC and ARQ in
wireless relay networks.


  This is a systematic review of the concept of indistinguishability in both
classical and quantum mechanics, with particular attention to Gibbs' paradox.
Section 1 is on the Gibbs paradox; section 2 is a defense of the concept of
classical indistinguishability, that addresses (and refutes) the view that
classical particles can always be distinguished by their trajectories so are
distinguishable. Section 3 is on the notion of object more generally, and on
whether indistinguishables should be thought of as objects at all


  The present paper is a follow up of our paper \cite{nS}. We investigate here
the maximization of higher order eigenvalues in a conformal class on a smooth
compact boundaryless Riemannian surface. Contrary to the case of the first
nontrivial eigenvalue as shown in \cite{nS}, bubbling phenomena appear.


  In this work we study the effects of a longitudinal periodic potential on a
parabolic quantum wire defined in a two-dimensional electron gas with Rashba
spin-orbit interaction. For an infinite wire superlattice we find, by direct
diagonalization, that the energy gaps are shifted away from the usual Bragg
planes due to the Rashba spin-orbit interaction. Interestingly, our results
show that the location of the band gaps in energy can be controlled via the
strength of the Rashba spin-orbit interaction. We have also calculated the
charge conductance through a periodic potential of a finite length via the
non-equilibrium Green's function method combined with the Landauer formalism.
We find dips in the conductance that correspond well to the energy gaps of the
infinite wire superlattice. From the infinite wire energy dispersion, we derive
an equation relating the location of the conductance dips as a function of the
(gate controllable) Fermi energy to the Rashba spin-orbit coupling strength. We
propose that the strength of the Rashba spin-orbit interaction can be extracted
via a charge conductance measurement.


  We propose a new splitting behavior of tree-level string/particle amplitudes
for scalars, gluons and gravitons. We identify certain subspaces in the space
of Mandelstam variables, where the universal Koba-Nielsen factor splits into
two parts (each with an off-shell leg). Both open- and closed-string amplitudes
with Parke-Taylor factors naturally factorize into two stringy ${\it
currents}$, which implies the splitting of bi-adjoint $\phi^3$ amplitudes and
via a simple deformation to unified stringy amplitudes, the splitting of
amplitudes in the non-linear sigma model and Yang-Mills-scalar theory; the same
splitting holds for scalar amplitudes without color such as the special
Galileon. Remarkably, if we impose similar constraints on Lorentz products
involving polarizations, gluon and graviton amplitudes in bosonic string and
superstring theories also split into two (stringy) currents. A special case of
the splitting implies soft theorems, and more generally it extends recently
proposed smooth splittings and new factorizations near zeros to all these
theories.


  Engineering quantum states of free-propagating light is of paramount
importance for quantum technologies. Coherent states ubiquitous in classical
and quantum communications, squeezed states used in quantum sensing, and even
highly-entangled cluster states studied in the context of quantum computing can
be produced deterministically, but they obey quasi-classical optical field
statistics described by Gaussian, positive Wigner functions. Fully harnessing
the potential of many quantum engineering protocols requires using non-Gaussian
Wigner-negative states, so far produced using intrinsically probabilistic
methods. Here we describe the first fully deterministic preparation of
non-Gaussian Wigner-negative free-propagating states of light, obtained by
mapping the internal state of an intracavity Rydberg superatom onto an optical
qubit encoded as a superposition of 0 and 1 photons. This approach allows us to
reach a 60% photon generation efficiency in a well-controlled spatio-temporal
mode, while maintaining a strong photon antibunching. By changing the qubit
rotation angle, we observe an evolution from quadrature squeezing to Wigner
negativity. Our experiment sets this new technique as a viable method to
deterministically generate non-Gaussian photonic resources, lifting several
major roadblocks in optical quantum engineering.


  Given a lattice basis of n vectors in Z^n, we propose an algorithm using
12n^3+O(n^2) floating point operations for checking whether the basis is
LLL-reduced. If the basis is reduced then the algorithm will hopefully answer
''yes''. If the basis is not reduced, or if the precision used is not
sufficient with respect to n, and to the numerical properties of the basis, the
algorithm will answer ''failed''. Hence a positive answer is a rigorous
certificate. For implementing the certificate itself, we propose a floating
point algorithm for computing (certified) error bounds for the entries of the R
factor of the QR matrix factorization. This algorithm takes into account all
possible approximation and rounding errors. The cost 12n^3+O(n^2) of the
certificate is only six times more than the cost of numerical algorithms for
computing the QR factorization itself, and the certificate may be implemented
using matrix library routines only. We report experiments that show that for a
reduced basis of adequate dimension and quality the certificate succeeds, and
establish the effectiveness of the certificate. This effectiveness is applied
for certifying the output of fastest existing floating point heuristics of LLL
reduction, without slowing down the whole process.


  We present the results on period search and modeling of the cool DAV star KUV
02464+3239. Our observations resolved the multiperiodic pulsational behaviour
of the star. In agreement with its position near the red edge of the DAV
instability strip, it shows large amplitude, long period pulsation modes, and
has a strongly non-sinusoidal light curve. We determined 6 frequencies as
normal modes and revealed remarkable short-term amplitude variations. A
rigorous test was performed for the possible source of amplitude variation:
beating of modes, effect of noise, unresolved frequencies or rotational
triplets. Among the best-fit models resulting from a grid search, we selected 3
that gave l=1 solutions for the largest amplitude modes. These models had
masses of 0.645, 0.650 and 0.680 M_Sun. The 3 `favoured' models have M_H
between 2.5x10^-5 - 6.3x10^-6 M_* and give 14.2 - 14.8 mas seismological
parallax. The 0.645 M_Sun (11400 K) model also matches the spectroscopic log g
and T_eff within 1 sigma. We investigated the possibility of mode trapping and
concluded that while it can explain high amplitude modes, it is not required.


  Let the complexity of a closed manifold M be the minimal number of simplices
in a triangulation of M. Such a quantity is clearly submultiplicative with
respect to finite coverings, and by taking the infimum on all finite coverings
of M normalized by the covering degree we can promote it to a multiplicative
invariant, a characteristic number already considered by Milnor and Thurston,
which call the "stable complexity" of M.
  We study here the relation between the stable complexity of M and Gromov's
simplicial volume ||M||. It is immediate to show that ||M|| is smaller or equal
than the stable complexity of M and it is natural to ask whether the two
quantities coincide on aspherical manifolds with residually finite fundamental
group. We show that this is not always the case: there is a constant C_n<1 such
that ||M|| is smaller than C_n times the stable complexity for any hyperbolic
manifold M of dimension at least 4.
  The question in dimension 3 is still open in general. We prove that the
stable complexity equals ||M|| for any aspherical irreducible 3-manifold M
whose JSJ decomposition consists of Seifert pieces and/or hyperbolic pieces
commensurable with the figure-eight knot complement. The equality holds for all
closed hyperbolic 3-manifolds if a particular three-dimensional version of the
Ehrenpreis conjecture is true.


  MRI analysis takes central position in brain tumor diagnosis and treatment,
thus it's precise evaluation is crucially important. However, it's 3D nature
imposes several challenges, so the analysis is often performed on 2D
projections that reduces the complexity, but increases bias. On the other hand,
time consuming 3D evaluation, like, segmentation, is able to provide precise
estimation of a number of valuable spatial characteristics, giving us
understanding about the course of the disease.\newline Recent studies, focusing
on the segmentation task, report superior performance of Deep Learning methods
compared to classical computer vision algorithms. But still, it remains a
challenging problem. In this paper we present deep cascaded approach for
automatic brain tumor segmentation. Similar to recent methods for object
detection, our implementation is based on neural networks; we propose
modifications to the 3D UNet architecture and augmentation strategy to
efficiently handle multimodal MRI input, besides this we introduce approach to
enhance segmentation quality with context obtained from models of the same
topology operating on downscaled data. We evaluate presented approach on BraTS
2018 dataset and discuss results.


  Thermal conductivity measurements can provide key and experimentally
verifiable insight into the electronic transport of unconventional
superconductors. In this work, electronic thermal transport of two-dimensional
tight-binding metallic systems with coexisting $d$-wave superconducting (SC)
and antiferromagnetic spin density wave (SDW) orders with nesting vector
$\mathbf{Q} = (\pi/2,\pi/2)$ or $(\pi,0)$ are considered. The coexisting SC and
SDW orders are modelled at the mean-field level. Thermal conductivities are
numerically calculated within Boltzmann kinetic theory in the weak impurity
scattering (Born) limit. These SDW nesting vectors are chosen for their unique
property of reconstructing the Fermi surface (FS) parallel to $\mathbf{Q}$ and
preserving the metallic FS perpendicular to $\mathbf{Q}$. This leads to
anisotropic electronic thermal conductivities parallel and perpendicular to
$\mathbf{Q}$, which also depend on the presence or absence of additional
gapless excitations exclusive to the coexistence phase. It was found that the
$\mathbf{Q} = (\pi/2,\pi/2)$ and $(\pi,0)$ SDW systems exhibit equivalent
electron transport relative to $\mathbf{Q}$. These systems also had equivalent
electron transport when coexisting with a $d$-wave SC gap when
$\Delta_{\mathbf{k}}$ had the same symmetry class under translations of
$\mathbf{Q}$.


  Electroencephalography (EEG) has become the most significant input signal for
brain computer interface (BCI) based systems. However, it is very difficult to
obtain satisfactory classification accuracy due to traditional methods can not
fully exploit multimodal information. Herein, we propose a novel approach to
modeling cognitive events from EEG data by reducing it to a video
classification problem, which is designed to preserve the multimodal
information of EEG. In addition, optical flow is introduced to represent the
variant information of EEG. We train a deep neural network (DNN) with
convolutional neural network (CNN) and recurrent neural network (RNN) for the
EEG classification task by using EEG video and optical flow. The experiments
demonstrate that our approach has many advantages, such as more robustness and
more accuracy in EEG classification tasks. According to our approach, we
designed a mixed BCI-based rehabilitation support system to help stroke
patients perform some basic operations.


  We first recall the basic theory of double vector bundles and the canonical
pairing of their duals introduced by the author and by Konieczna and Urbanski.
We then show that the relationship between a double vector bundle and its two
duals can be understood simply in terms of an associated cotangent triple
vector bundle. In particular we show that the dihedral group of the triangle
acts on this triple via forms of the isomorphisms R introduced by the author
and Ping Xu. We then consider the three duals of a general triple vector bundle
and show that the corresponding group is neither the dihedral group of the
square nor the symmetry group on four symbols.


  Applying concepts and tools from classical tangent bundle geometry and using
the apparatus of the calculus along the tangent bundle projection ('pull-back
formalism'), first we enrich the known lists of the characterizations of affine
vector fields on a spray manifold and conformal vector fields on a Finsler
manifold. Second, we deduce consequences on vector fields on the underlying
manifold of a Finsler structure having one or two of the mentioned geometric
properties.


  A serious defect with the Halpern-Pearl (HP) definition of causality is
repaired by combining a theory of causality with a theory of defaults. In
addition, it is shown that (despite a claim to the contrary) a cause according
to the HP condition need not be a single conjunct. A definition of causality
motivated by Wright's NESS test is shown to always hold for a single conjunct.
Moreover, conditions that hold for all the examples considered by HP are given
that guarantee that causality according to (this version) of the NESS test is
equivalent to the HP definition.


  We consider possible high temperature superconductivity (high-T$_c$) in
transition metal compounds with a cubic zinc-blende lattice structure. When the
electron filling configuration in the d-shell is close to d$^7$, all three
t$_{2g}$ orbitals are near half filling with strong nearest neighbor
antiferromagnetic (AFM) superexchange interactions. We argue that upon doping,
this electronic environment can be one of "genes" to host unconventional high
T$_c$ with a time reversal symmetry broken $d_{2z^2-x^2-y^2} \pm i d_{x^2-y^2}$
pairing symmetry. With gappless nodal points along the diagonal directions,
this state is a direct three dimensional analogue to the two dimensional
$B_{1g}$ d-wave state in cuprates. We suggest that such a case may be realized
in electron doped CoN, such as CoN$_{1-x}$O$_x$ and (H, Li)$_{1-x}$CoN.


  We study the existence and stability of periodic traveling-wave solutions for
the quadratic and cubic nonlinear Schr\"odinger equations in one space
dimension.


  The gapped Dirac-like surface states of compensated magnetic topological
insulator MnBi$_{2-x}$Sb$_x$Te$_4$ (MBST) are a promising host for exotic
quantum phenomena such as the quantum anomalous Hall effect and axion
insulating states. However, it has become clear that atomic defects undermine
the stabilization of such quantum phases as they lead to spatial variations in
the surface state gap and doping levels. The large number of possible defect
configurations in MBST make studying the influence of individual defects
virtually impossible. Here, we present a statistical analysis of the nanoscale
effect of defects in MBST with $x=0.64$, by scanning tunneling
microscopy/spectroscopy (STM/S). We identify (Bi,Sb)$_{\rm Mn}$ anti-site
defects to be the main source of the observed doping fluctuations, leading
towards the formation of nanoscale charge puddles and effectively closing the
transport gap. Our findings will guide further optimization of this material
system via defect engineering, to enable exploitation of its promising
properties.


  Measurements of a wide variety of aerial phenomena such as drones, birds,
planes, and other aerial objects can in principle be obtained from open access
radio detection and ranging equipment. Passive strategies involve existing cell
towers as transmitters and cell phones as receivers. Another active possibility
is the creation of a multistatic, possibly phased array, network of
transmission and receiving stations by open-source realizations such as GNU
radio. We also suggest provision of uncorrelated targets or anomalies from
existing military sources.


  Multi-TeV e+e- collisions provide with a large enough sample of Higgs bosons
to enable measurements of its suppressed decays. Results of a detailed study of
the determination of the muon Yukawa coupling at 3 TeV, based on full detector
simulation and event reconstruction, are presented. The muon Yukawa coupling
can be determined with a relative accuracy of 0.04 to 0.08 for Higgs bosons
masses from 120 GeV to 150 GeV, with an integrated luminosity of 5 inverse-ab.
The result is not affected by overlapping two-photon background.


  In the present paper we show how obtain the energy distribution f(E) in our
vicinity starting from WIMP density profiles in a self consistent way by
employing the Eddington approach and adding reasonable angular momentum
dependent terms in the expression of the energy. We then show how we can obtain
the velocity dispersion and the asymmetry parameter {\beta} in terms of the
parameters describing the angular momentum dependence. From this expression for
f(E) we proceed to construct an axially symmetric WIMP velocity distributions,
which for a gravitationally bound system automatically has an velocity upper
bound and is characterized by the the same asymmetries. This approach is tested
and clarified by constructing analytic expressions in a simple model, with
adequate structure. We then show how such velocity distributions can be used in
determining the event rates, including modulation, both in the standard as well
directional WIMP searches. find that some density profiles lead to approximate
Maxwell-Boltzmann distributions, which are automatically defined in a finite
domain, i.e. the escape velocity need not be put by hand. The role of such
distributions in obtaining the direct WIMP detection rates, including the
modulation, is studied in some detail and, in particular, the role of the
asymmetry is explored.


  This paper evaluates the use of pin and cycle accurate SystemC models for
embedded system design exploration and early software development. The target
system is MicroBlaze VanillaNet Platform running MicroBlaze uClinux operating
system. The paper compares Register Transfer Level (RTL) Hardware Description
Language (HDL) simulation speed to the simulation speed of several different
SystemC models. It is shown that simulation speed of pin and cycle accurate
models can go up to 150 kHz, compared to 100 Hz range of HDL simulation.
Furthermore, utilising techniques that temporarily compromise cycle accuracy,
effective simulation speed of up to 500 kHz can be obtained.


  PSR B1259-63 is a $\gamma$-ray emitting high mass X-ray binary system, in
which the compact object is a millisecond pulsar. The system has an orbital
period of 1236.7 d and shows peculiar $\gamma$-ray flares when the neutron star
moves out of the stellar disk of the companion star. The $\gamma$-ray flare
events were firstly discovered by using Fermi-LAT around the 2010 periastron
passage, which was repeated for the 2014 and 2017 periastron passages. We
analyze the Fermi-LAT data for all the three periastron passages and found that
in each flare the energy spectrum can be represented well by a simple power
law. The $\gamma$-ray light curves show that in 2010 and 2014 after each
periastron there are two main flares, but in 2017 there are four flares
including one precursor about 10 d after the periastron passage. The first main
flares in 2010 and 2014 are located at around 35 d after the periastron
passage, and the main flare in 2014 is delayed by roughly 1.7 d with respect to
that in 2010. In the 2017 flare, the source shows a precursor about 10 d after
the periastron passage, but the following two flares become weaker and lag
behind those in 2010 by roughly 5 d. The strongest flares in 2017 occurred 58 d
and 70 d after the periastron passage. These results challenge the previous
models.


  Virtual reality (VR) is on the edge of getting a mainstream platform for
gaming, education and product design. The feeling of being present in the
virtual world is influenced by many factors and even more intriguing a single
negative influence can destroy the illusion that was created with a lot of
effort by other measures. Therefore, it is crucial to have a balance between
the influencing factors, know the importance of the factors and have a good
estimation of how much effort it takes to bring each factor to a certain level
of fidelity. This paper collects influencing factors discussed in literature,
analyses the immersion of current off-the-shelf VR-solutions and presents
results from an empirical study on efforts and benefits from certain aspects
influencing presence in VR experiences. It turns out, that sometimes delivering
high fidelity is easier to achieve than medium fidelity and for other aspects
it is worthwhile investing more effort to achieve higher fidelity to improve
presence a lot.


  In the next few years, Blockchain will play a central role in IoT as a
technology. It enables the traceability of processes between multiple parties
independent of a central instance. Blockchain allows to make the processes more
transparent, cheaper, and safer. This research paper was conducted as
systematic literature search. Our aim is to understand current state of
implementation in context of Blockchain Technology for digital protection of
communication in industrial cyber-physical systems. We have extracted 28
primary papers from scientific databases and classified into different
categories using visualizations. The results show that the focus in around 14\%
papers is on solution proposal and implementation of use cases "Secure transfer
of order data" using Ethereum Blockchain, 7\% papers applying Hyperledger
Fabric and Multichain. The majority of research (around 43\%) is focusing on
solution development for supply chain and process traceability.


  One interesting feature of 3d $\mathcal{N}=2$ theories is that
gauge-invariant operators can decouple by strong-coupling effects, leading to
emergent flavor symmetries in the IR. The details of such decoupling, however,
depends very delicately on the gauge group and matter content of the theory. We
here systematically study the IR behavior of 3d $\mathcal{N}=2$ SQCD with $N_f$
flavors, for gauge groups $\mathrm{SU}(N_c), \mathrm{USp}(2N_c)$ and
$\mathrm{SO}(N_c)$. We apply a combination of analytical and numerical methods,
both to small values of $N_c, N_f$ and also to the Veneziano limit, where $N_c$
and $N_f$ are taken to be large with their ratio $N_f/N_c$ fixed. We highlight
the role of the monopole operators and the interplay with Aharony-type
dualities. We also discuss the effect of gauging continuous as well as discrete
flavor symmetries, and the implications of our analysis to the classification
of $1/4$--BPS co-dimension 2 defects of 6d $(2,0)$ theories.


  RDF data is often treated as incomplete, following the Open-World Assumption.
On the other hand, SPARQL, the standard query language over RDF, usually
follows the Closed-World Assumption, assuming RDF data to be complete. This
gives rise to a semantic gap between RDF and SPARQL. In this paper, we address
how to close the semantic gap between RDF and SPARQL in terms of certain
answers and possible answers using completeness statements.


  The Doran-Harder-Thompson "gluing/splitting" conjecture unifies mirror
symmetry conjectures for Calabi-Yau and Fano varieties, relating fibration
structures on Calabi-Yau varieties to the existence of certain types of
degenerations on their mirrors. This was studied for the case of Calabi-Yau
complete intersections in toric varieties by Doran, Kostiuk and You for the
Hori-Vafa mirror construction. In this paper we prove one direction of the
conjecture using a modified version of the Gross-Siebert program. This involves
a careful study of the implications within tropical geometry and applying
modern deformation theory for singular Calabi-Yau varieties.


  As part of Smart Cities initiatives, national, regional and local governments
all over the globe are under the mandate of being more open regarding how they
share their data. Under this mandate, many of these governments are publishing
data under the umbrella of open government data, which includes measurement
data from city-wide sensor networks. Furthermore, many of these data are
published in so-called data portals as documents that may be spreadsheets,
comma-separated value (CSV) data files, or plain documents in PDF or Word
documents. The sharing of these documents may be a convenient way for the data
provider to convey and publish data but it is not the ideal way for data
consumers to reuse the data. For example, the problems of reusing the data may
range from difficulty opening a document that is provided in any format that is
not plain text, to the actual problem of understanding the meaning of each
piece of knowledge inside of the document. Our proposal tackles those
challenges by identifying metadata that has been regarded to be relevant for
measurement data and providing a schema for this metadata. We further leverage
the Human-Aware Sensor Network Ontology (HASNetO) to build an architecture for
data collected in urban environments. We discuss the use of HASNetO and the
supporting infrastructure to manage both data and metadata in support of the
City of Fortaleza, a large metropolitan area in Brazil.