  We use deep Hubble Space Telescope imaging of the Frontier Fields to
accurately measure the galaxy rest-frame ultraviolet luminosity function (UV
LF) in the redshift range $z \sim 6-8$. We combine observations in three
lensing clusters A2744, MACS0416, MACS0717 and their associated parallels
fields to select high-redshift dropout candidates. We use the latest lensing
models to estimate the flux magnification and the effective survey volume in
combination with completeness simulations performed in the source plane. We
report the detection of 227 galaxy candidates at $z=6-7$ and 25 candidates at
$z \sim 8$. While the total survey area is about 4 arcmin$^{2}$ in each
parallel field, it drops to about 0.6 to 1 arcmin$^{2}$ in the cluster core
fields because of the strong lensing. We compute the UV luminosity function at
$z \sim 7$ using the combined galaxy sample and perform Monte Carlo simulations
to determine the best fit Schechter parameters. We are able to reliably
constrain the LF down to an absolute magnitude of $M_{UV}=-15.25$, which
corresponds to 0.005$L^{\star}$. More importantly, we find that the faint-end
slope remains steep down to this magnitude limit with
$\alpha=-2.04_{-0.17}^{+0.13}$. Our results confirm the most recent results in
deep blank fields but extend the LF measurements more than two magnitudes
deeper. The UV LF at $z \sim 8$ is not very well constrained below $M_{UV}=-18$
due to the small number statistics and incompleteness uncertainties. To assess
the contribution of galaxies to cosmic reionization we derive the UV luminosity
density at $z\sim7$ by integrating the UV LF down to an observationally
constrained limit of $M_{UV} = -15$. We show that our determination of
Log($\rho_{UV}$)=$26.2\pm0.13$ (erg s$^{-1}$ Hz$^{-1}$ Mpc$^{-3}$) can be
sufficient to maintain the IGM ionized.


  We summarize the physical equations and analytic solutions of three versions
of the box model equations, suitable for the integral formulation of
axisymmetric gravity-driven particle currents with constant volume. The first
model is based on a simple constant resisting stress, while the second and
third models assume flow dilution by particle deposition. The third model is
characterized by assuming an interstitial fluid lighter than the ambient fluid.
All the calculations are performed on a flat topography. Ambient fluid
entrainment and cooling effects are not considered. All particles are assumed
to deposit at the same velocity.


  Many bacteria share the fascinating ability to sense Earth's magnetic field
-- a process known as magnetotaxis. These bacteria synthesize magnetic
nanoparticles, called magnetosomes, within their own cell body and arrange them
to form a linear magnetic chain. The chain, which behaves like a compass
needle, aligns the microorganisms with the geomagnetic field. Here, we measure
the magnetic hysteresis of an individual bacterium of the species
Magnetospirillum gryphiswaldense via ultrasensitive torque magnetometry. These
measurements, in combination with transmission electron microscopy and
micromagnetic simulations, reveal the magnetic configurations of the
magnetosomes, their progression as a function of applied field, as well as the
total remanent magnetic moment and effective magnetic anisotropy of a chain
within a single bacterium. Knowledge of magnetic properties is crucial both for
understanding the mechanisms behind magnetotaxis and for the design of systems
exploiting magnetotactic bacteria in biomedical applications.


  Inflation is the currently accepted paradigm for the beginnings of the
Universe. To explain the observed almost scale invariant spectrum of density
perturbations with only a slight spectral tilt, inflation must have been "slow
roll", that is with a potential with sufficiently small slope. While the origin
of inflationary structure is intrinsically quantum mechanical, gravity gets
treated semiclassically within inflationary models. Recent work, in terms of
the so called de-Sitter swampland conjecture, has called into question whether
slow roll inflation is consistent with a complete theory of quantum gravity in
the presence of a positive vacuum energy density, which is a key ingredient in
the inflationary paradigm. In this work, we show that, in fact, if we
understand this conjecture correctly and with another swampland conjecture, the
so-called distance conjecture, involved we get a potential mechanism for slow
roll inflation and we argue that here fine-tuning is not a technical problem.


  The treatment of both aleatory and epistemic uncertainty by recent methods
often requires an high computational effort. In this abstract, we propose a
numerical sampling method allowing to lighten the computational burden of
treating the information by means of so-called fuzzy random variables.


  Before a car-following model can be applied in practice, it must first be
validated against real data in a process known as calibration. This paper
discusses the formulation of calibration as an optimization problem, and
compares different algorithms for its solution. The optimization consists of an
arbitrary car following model, posed as either an ordinary or delay
differential equation, being calibrated to an arbitrary source of trajectory
data which may include lane changes. Typically, the calibration problem is
solved using gradient free optimization. In this work, the gradient of the
optimization problem is derived analytically using the adjoint method. The
computational cost of the adjoint method does not scale with the number of
model parameters, which makes it more efficient than evaluating the gradient
numerically using finite differences. Numerical results are presented which
show that quasi-newton algorithms using the adjoint method are significantly
faster than a genetic algorithm, and also achieve slightly better accuracy of
the calibrated model.


  A most desirable feature of a standard candle to estimate astronomical
distances is robustness against changes in metallicity and age. It is argued
that the radii of main sequence stars with spectral types from solar to A0 show
predictable changes with metallicity, and detectable changes with evolution.
Such stars populate the solar neighborhood, and therefore benefit from
measurements of angular diameters. Also, reliable determinations of their
masses and radii are available from observations of eclipsing binaries. Three
empirical relationships are defined and suggested for estimating distances to
dwarfs from only BVK photometry. Comparison with HIPPARCOS trigonometric
parallaxes shows that the method provides errors of about 15% for a particular
star, which can be reduced to roughly 1.5% when applied to young clusters (age
<~ 1-2 Gyr) with ~ 100 stars of the appropriate spectral types. If reddening is
unknown, main sequence stars with effective temperatures close to 8000 K can
constrain it, although an estimate of R=A(V)/E(B-V) is required.


  Access to large amounts of diverse design solutions can support designers
during the early stage of the design process. In this paper, we explore the
efficacy of large language models (LLM) in producing diverse design solutions,
investigating the level of impact that parameter tuning and various prompt
engineering techniques can have on the diversity of LLM-generated design
solutions. Specifically, LLMs are used to generate a total of 4,000 design
solutions across five distinct design topics, eight combinations of parameters,
and eight different types of prompt engineering techniques, comparing each
combination of parameter and prompt engineering method across four different
diversity metrics. LLM-generated solutions are compared against 100
human-crowdsourced solutions in each design topic using the same set of
diversity metrics. Results indicate that human-generated solutions consistently
have greater diversity scores across all design topics. Using a post hoc
logistic regression analysis we investigate whether these differences primarily
exist at the semantic level. Results show that there is a divide in some design
topics between humans and LLM-generated solutions, while others have no clear
divide. Taken together, these results contribute to the understanding of LLMs'
capabilities in generating a large volume of diverse design solutions and offer
insights for future research that leverages LLMs to generate diverse design
solutions for a broad range of design tasks (e.g., inspirational stimuli).


  The class of two-spin systems contains several important models, including
random independent sets and the Ising model of statistical physics. We show
that for both the hard-core (independent set) model and the anti-ferromagnetic
Ising model with arbitrary external field, it is NP-hard to approximate the
partition function or approximately sample from the model on d-regular graphs
when the model has non-uniqueness on the d-regular tree. Together with results
of Jerrum--Sinclair, Weitz, and Sinclair--Srivastava--Thurley giving FPRAS's
for all other two-spin systems except at the uniqueness threshold, this gives
an almost complete classification of the computational complexity of two-spin
systems on bounded-degree graphs.
  Our proof establishes that the normalized log-partition function of any
two-spin system on bipartite locally tree-like graphs converges to a limiting
"free energy density" which coincides with the (non-rigorous) Bethe prediction
of statistical physics. We use this result to characterize the local structure
of two-spin systems on locally tree-like bipartite expander graphs, which then
become the basic gadgets in a randomized reduction to approximate MAX-CUT. Our
approach is novel in that it makes no use of the second moment method employed
in previous works on these questions.


  We propose a sure screening approach for recovering the structure of a
transelliptical graphical model in the high dimensional setting. We estimate
the partial correlation graph by thresholding the elements of an estimator of
the sample correlation matrix obtained using Kendall's tau statistic. Under a
simple assumption on the relationship between the correlation and partial
correlation graphs, we show that with high probability, the estimated edge set
contains the true edge set, and the size of the estimated edge set is
controlled. We develop a threshold value that allows for control of the
expected false positive rate. In simulation and on an equities data set, we
show that transelliptical graphical sure screening performs quite competitively
with more computationally demanding techniques for graph estimation.


  In this paper, we investigate a time-slotted cognitive setting with buffered
primary and secondary users. In order to alleviate the negative effects of
misdetection and false alarm probabilities, a novel design of spectrum access
mechanism is proposed. We propose two schemes. First, the SU senses primary
channel to exploit the periods of silence, if the PU is declared to be idle,
the SU randomly accesses the channel with some access probability $a_s$.
Second, in addition to accessing the channel if the PU is idle, the SU possibly
accesses the channel if it is declared to be busy with some access probability
$b_s$. The access probabilities as function of the misdetection, false alarm
and average primary arrival rate are obtained via solving an optimization
problem designed to maximize the secondary service rate given a constraint on
primary queue stability. In addition, we propose a variable sensing duration
schemes where the SU optimizes over the optimal sensing time to achieve the
maximum stable throughput of the network. The results reveal the performance
gains of the proposed schemes over the conventional sensing scheme. We propose
a method to estimate the mean arrival rate and the outage probability of the PU
based on the primary feedback channel, i.e., acknowledgments (ACKs) and
negative-acknowledgments (NACKs) messages.


  The probability distribution function of column density (PDF) has become the
tool of choice for cloud structure analysis and star formation studies. Its
simplicity is attractive, and the PDF could offer access to cloud physical
parameters otherwise difficult to measure, but there has been some confusion in
the literature on the definition of its completeness limit and shape at the low
column density end. In this Letter we use the natural definition of the
completeness limit of a column density PDF, the last closed column-density
contour inside a surveyed region, and apply it to a set of large-scale maps of
nearby molecular clouds. We conclude that there is no observational evidence
for log-normal PDFs in these objects. We find that all studied molecular clouds
have PDFs well described by power-laws, including the diffuse cloud Polaris.
Our results call for a new physical interpretation for the shape of the column
density PDFs. We find that the slope of a cloud PDF is invariant to distance
but not to the spatial arrangement of cloud material, and as such it is still a
useful tool to investigate cloud structure.


  Under an electric field, chiral smectic liquid crystals transit usually to
the unwound SmC* phase where the helical structure is completely unrolled.
Sometimes the sample transits initially towards an intermediate polar state
before the total destruction of the helix. Based on the extension of the H-T
model, a theoretical study of these field-induced phase transitions was carried
out. Two hypotheses of the dynamics that give rise to the appearance of the
intermediate phase have been discussed. The results of a numerical analysis
confirm the known experimental results; the intermediate phase has a
three-layer periodicity structure.


  When compressed frictional granular media are decompressed, generically a
fragile configuration is created at low pressures. Typically this is
accompanied by a giant frictional slippage as the fragile state collapses. We
show that this instability is understood in terms of a scaling theory with
theoretically computable amplitudes and exponents. The amplitude diverges in
the thermodynamic limit hinting to the possibility of huge frictional slip
events in decompressed granular media. The physics of this slippage is
discussed in terms of the probability distribution functions of the tangential
and normal forces on the grains which are highly correlated due to the Coulomb
condition.


  We present a criterion of local Normal Embedding of a semialgebraic (or
definable in an o-minimal structure) contained in $R^n$ in terms orders of
contact of arcs. Namely, we prove that a semialgebraic set is normally embedded
at a point x if and only if for any pair of arcs, coming to this point the
inner order of contact is equal to the outer order of contact.


  Given a functor $p:E \rightarrow B$ and an object $e \in E$ , we define a
\emph{displacement} of $e$ along a morphism $\varepsilon: p(e) \rightarrow b$,
as a map $e \rightarrow \nabla_\varepsilon(e)$ satisfying a universal property
analogue to that of a \emph{cocartesian lifting} (pushforward) \emph{\`a la}
B\'enabou-Grothendieck-Street. There are many difficulties in geometry that
come from the fact that forgetful functors such as $p: Var(\mathbf{C})
\rightarrow Top $ don't have displacements of objects along arbitrary maps. And
this can be already seen abstractly, since the existence of a left adjoint to
$p$, can be reduced to the existence of all displacements of the initial
object. However some \emph{schematization functors} exist as approximations. In
a broader context, if $B$ is a model category and $p$ is a right adjoint, then
the right-induced model category on $E$ exists if and only if all displacements
along any trivial cofibration $\varepsilon$, are weak $p$-equivalences. In
these notes we provide some categorical lemmas that will be necessary for
future applications. The idea is to have a \emph{homotopy descent process} for
\emph{elementary displacements} when $p$ has a \emph{presentation} as a
$2$-pullback of a family $\{p_i: E_i \rightarrow B\}_{i\in J}$. When suitably
applied it should lead to techniques similar to Mumford's GIT through homotopy
theory (simplicial presheaves).


  The precise determination of the arrival direction of cosmic rays is a
fundamental prerequisite for the search for sources or the study of their
anisotropies on the sky. One of the most important aspects to achieve an
optimal measurement of these directions is to properly take into account the
measurement uncertainties in the estimation procedure. In this article we
present a model for the uncertainties associated with the time measurements in
the Auger surface detector array. We show that this model represents well the
measurement uncertainties and therefore provides the basis for an optimal
determination of the arrival direction. With this model and a description of
the shower front geometry it is possible to estimate, on an event by event
basis, the uncertainty associated with the determination of the arrival
directions of the cosmic rays.


  As the workforce settles into flexible work arrangements, researchers have
focused on the collaborative and psychological consequences of the shift. While
nearly a fifth of the world's population is estimated to be neurodivergent, the
implications of remote collaboration on the cognitive, sensory, and
socio-affective experiences of autistic workers are poorly understood. Prior
literature suggests that information and communication technologies (ICTs)
introduce major psychological stressors. Theoretically, these stressors ought
to be exceptionally straining considering autistic traits $\unicode{x2013}$
yet, studies describe a strong attraction to ICTs. We thus ask: how do digital
technologies alleviate autistic workers' experiences of their collaborative
work environment? Thirty-three interviews were conducted to address this
question. Findings suggest that digital media present capabilities that filter
input from the environment, turning it into a virtual stage that lets workers
"time out". The resulting "technorelief" enables autistic workers to tune into
their perceptions and regain control of their collaborative experiences.


  We introduce and study the Lyapunov numbers -- quantitative measures of the
sensitivity of a dynamical system $(X,f)$ given by a compact metric space $X$
and a continuous map $f:X \to X$. In particular, we prove that for a minimal
topologically weakly mixing system all Lyapunov numbers are the same.


  We show that the long-distance behavior of the two-body density correlation
functions and the Cooper-pair probability density of a balanced mixture of a
two-component Fermi gas at $T = 0$, is universal along the BEC-BCS crossover.
Our result is demonstrated by numerically solving the mean-field BCS model for
different finite short-range atomic interaction potentials. We find an analytic
expression for the correlation length in terms of the chemical potential and
the energy gap at zero momentum.


  This paper is devoted to tetrahedron maps, which are set-theoretical
solutions to the Zamolodchikov tetrahedron equation. We construct a family of
tetrahedron maps on associative rings. We show that matrix tetrahedron maps
presented in [arXiv:2110.05998] are a particular case of our construction. This
provides an algebraic explanation of the fact that the matrix maps from
[arXiv:2110.05998] satisfy the tetrahedron equation. Also, Liouville
integrability is established for some of the constructed maps.


  Intrinsic complexity of a relation on a given computable structure is
captured by the notion of its degree spectrum - the set of Turing degrees of
images of the relation in all computable isomorphic copies of that structure.
We investigate the intrinsic complexity of unary total recursive functions on
nonnegative integers with standard order. According to existing results,
possible spectra of such functions include three sets consisting of precisely:
the computable degree, all c.e. degrees and all $\Delta_2$ degrees. These
results, however, fall far short of the full classification. In this paper, we
obtain a more complete picture by giving a few criteria for a function to have
intrinsic complexity equal to one of the three candidate sets of degrees. Our
investigations are based on the notion of block functions and a broader class
of quasi-block functions beyond which all functions of interest have intrinsic
complexity equal to the c.e. degrees. We also answer the questions raised by
Wright and Harrison-Trainor by showing that the division between computable,
c.e. and $\Delta_2$ degrees is insufficient in this context as there is a unary
total recursive function whose spectrum contains all c.e. degrees but is
strictly contained in the $\Delta_2$ degrees.


  The "Machiavellian intelligence" hypothesis (or the "social brain"
hypothesis) posits that large brains and distinctive cognitive abilities of
humans have evolved via intense social competition in which social competitors
developed increasingly sophisticated "Machiavellian" strategies as a means to
achieve higher social and reproductive success. Here we build a mathematical
model aiming to explore this hypothesis. In the model, genes control brains
which invent and learn strategies (memes) which are used by males to gain
advantage in competition for mates. We show that the dynamics of intelligence
has three distinct phases. During the dormant phase only newly invented memes
are present in the population. During the cognitive explosion phase the
population's meme count and the learning ability, cerebral capacity
(controlling the number of different memes that the brain can learn and use),
and Machiavellian fitness of individuals increase in a runaway fashion. During
the saturation phase natural selection resulting from the costs of having large
brains checks further increases in cognitive abilities. Overall, our results
suggest that the mechanisms underlying the "Machiavellian intelligence"
hypothesis can indeed result in the evolution of significant cognitive
abilities on the time scale of 10 to 20 thousand generations. We show that
cerebral capacity evolves faster and to a larger degree than learning ability.
Our model suggests that there may be a tendency toward a reduction in cognitive
abilities (driven by the costs of having a large brain) as the reproductive
advantage of having a large brain decreases and the exposure to memes increases
in modern societies.


  The Superspinorial Dual-covariant Field Theory (SSFT) developed in papers [1,
2] is treated in terms of Riemannian coordinates (RC) [7, 8] in space of the N
dimensions unified manifold (UM). Metric tensor of UM (grand metric, GM) is
built on the split metric matrices (SM) [1] which are a proportion of the
Cartan's affinors (an extended analog of Dirac's matrices) of his Theory of
Spinors [3] as explicated in [2]. Transition to RC based on consideration of
geodesics is described. A principal property of an orthogonal RC frame (ORC)
utilized in the present paper is constancy of the rotation matrix A of the
Riemannian space of UM, while transformation matrix B of the dual
superspinorial state vector field (DSV) varies together with Cartan's affinors
according to the dynamical law of SSFT derived in [2]. The spinorial genesis of
notion of the orthogonality as aspect of irreducible SSFT is pointed out in the
present paper. The main outcome of resorting to an orthogonal RC frame (ORC) is
explication of the conformal dynamic invariance of metric i.e. constancy of
ratio between components of GM in ORC frame. This leads to possibility of
reduction of algebraic equations of SSFT for the SM [2] to equation for GM
determinant where GM signature plays a role of N discrete parameters
non-specified in advance.


  The leading contributions from heavy new physics to Higgs processes can be
captured in a model-independent way by dimension-six operators in an effective
Lagrangian approach. We present a complete analysis of how these contributions
affect Higgs couplings. Under certain well-motivated assumptions, we find that
8 CP-even plus 3 CP-odd Wilson coefficients parametrize the main impact in
Higgs physics, as all other coefficients are constrained by non-Higgs SM
measurements. We calculate the most relevant anomalous dimensions for these
Wilson coefficients, which describe operator mixing from the heavy scale down
to the electroweak scale. This allows us to find the leading-log corrections to
the predictions for the Higgs couplings in specific models, such as the MSSM or
composite Higgs, which we find to be significant in certain cases.


  Blockchain, as the basis for cryptocurrencies, has received extensive
attentions recently. Blockchain serves as an immutable distributed ledger
technology which allows transactions to be carried out credibly in a
decentralized environment. Blockchain-based applications are springing up,
covering numerous fields including financial services, reputation system and
Internet of Things (IoT), and so on. However, there are still many challenges
of blockchain technology such as scalability, security and other issues waiting
to be overcome. This article provides a comprehensive overview of blockchain
technology and its applications. We begin with a summary of the development of
blockchain, and then give an overview of the blockchain architecture and a
systematic review of the research and application of blockchain technology in
different fields from the perspective of academic research and industry
technology. Furthermore, technical challenges and recent developments are also
briefly listed. We also looked at the possible future trends of blockchain.


  We present an MatchboxNet - an end-to-end neural network for speech command
recognition. MatchboxNet is a deep residual network composed from blocks of 1D
time-channel separable convolution, batch-normalization, ReLU and dropout
layers. MatchboxNet reaches state-of-the-art accuracy on the Google Speech
Commands dataset while having significantly fewer parameters than similar
models. The small footprint of MatchboxNet makes it an attractive candidate for
devices with limited computational resources. The model is highly scalable, so
model accuracy can be improved with modest additional memory and compute.
Finally, we show how intensive data augmentation using an auxiliary noise
dataset improves robustness in the presence of background noise.


  UVCANDELS is a HST Cycle-26 Treasury Program awarded 164 orbits of primary
ultraviolet (UV) F275W imaging and coordinated parallel optical F435W imaging
in four CANDELS fields: GOODS-N, GOODS-S, EGS, and COSMOS, covering a total
area of $\sim426$ arcmin$^2$. This is $\sim2.7$ times larger than the area
covered by previous deep-field space UV data combined, reaching a depth of
about 27 and 28 ABmag ($5\sigma$ in $0.2"$ apertures) for F275W and F435W,
respectively. Along with the new photometric catalogs, we present an analysis
of the rest-frame UV luminosity function (LF), relying on our UV-optimized
aperture photometry method yielding a factor of $1.5\times$ increase than the
H-isophot aperture photometry in the signal-to-noise ratios of galaxies in our
F275W imaging. Using well tested photometric redshift measurements we identify
5810 galaxies at redshifts $0.6<z<1$, down to an absolute magnitude of
$M_\text{UV} = -14.2$. In order to minimize the effect of uncertainties in
estimating the completeness function, especially at the faint-end, we restrict
our analysis to sources above $30\%$ completeness, which provides a final
sample of 4726 galaxies at $-21.5<M_\text{UV}<-15.5$. We performed a maximum
likelihood estimate to derive the best-fit parameters of the UV LF. We report a
best-fit faint-end slope of $\alpha = -1.359^{+0.041}_{-0.041}$ at $z \sim
0.8$. Creating sub-samples at $z\sim0.7$ and $z\sim0.9$, we observe a possible
evolution of $\alpha$ with redshift. The unobscured UV luminosity density at
$M_\text{UV}<-10$ is derived as $\rho_\text{UV}=1.339^{+0.027}_{-0.030}\
(\times10^{26} \text{ergs/s/Hz/Mpc}^3)$ using our best-fit LF parameters. The
new F275W and F435 photometric catalogs from UVCANDELS have been made publicly
available on the Barbara A. Mikulski Archive for Space Telescopes (MAST).


  The idea of a graph theoretical approach to modeling the emergence of a
quantized geometry and consequently spacetime, has been proposed previously,
but not well studied. In most approaches the focus has been upon how to
generate a spacetime that possesses properties that would be desirable at the
continuum limit, and the question of how to model matter and its dynamics has
not been directly addressed. Recent advances in network science have yielded
new approaches to the mechanism by which spacetime can emerge as the ground
state of a simple Hamiltonian, based upon a multi-dimensional Ising model with
one dimensionless coupling constant. Extensions to this model have been
proposed that improve the ground state geometry, but they require additional
coupling constants. In this paper we conduct an extensive exploration of the
graph properties of the ground states of these models, and a simplification
requiring only one coupling constant. We demonstrate that the simplification is
effective at producing an acceptable ground state. Moreover we propose a scheme
for the inclusion of matter and dynamics as excitations above the ground state
of the simplified Hamiltonian. Intriguingly, enforcing locality has the
consequence of reproducing the free non-relativistic dynamics of a quantum
particle.


  Semantic Communication (SEM-COM) has emerged as one of the disruptive
technologies facilitating the evolution towards sixth-generation (6G) wireless
networks. This article presents the potential of SEM-COM to transform
Vehicle-to-Everything (V2X) communications, with a particular emphasis on its
ability to enhance communication efficiency and intelligence. We discuss the
core components and metrics that characterize SEM-COM, providing insights into
its operational framework within the context of V2X communications. We
illustrate the applicability and practicality of SEM-COM through real-world
vehicular use cases, demonstrate the potential of SEM-COM to enhance aspects of
intelligent mobility, such as communication efficiency and decision-making.
Finally, the article identifies key open research questions for SEM-COM V2X,
pointing to areas that require further exploration and thus setting a
foundation for future work in this evolving domain.


  In their recent paper ``Faraday rotation of the cosmic microwave background
polarization by a stochastic magnetic field'', Kosowsky et al. Phys.Rev. D71,
043006 (2005) have commented about our paper [C.Caprini and R.Durrer, Phys.
Rev. D65, 023517 (2002)], in which we derived very strong limits on the
amplitude of a primordial magnetic field from gravitational wave production.
They argue that our limits are erroneous. In this short comment we defend our
result.


  Patients with Frontotemporal Dementia (FTD) have impaired cognitive
abilities, executive and behavioral traits, loss of language ability, and
decreased memory capabilities. Based on the distinct patterns of cortical
atrophy and symptoms, the FTD spectrum primarily includes three variants:
behavioral variant FTD (bvFTD), non-fluent variant primary progressive aphasia
(nfvPPA), and semantic variant primary progressive aphasia (svPPA). The purpose
of this study is to classify MRI images of every single subject into one of the
spectrums of the FTD in a hierarchical order by applying data-driven techniques
of Artificial Intelligence (AI) on cortical thickness data. This data is
computed by FreeSurfer software. We used the Smallest Univalue Segment
Assimilating Nucleus (SUSAN) technique to minimize the noise in cortical
thickness data. Specifically, we took 204 subjects from the frontotemporal
lobar degeneration neuroimaging initiative (NIFTD) database to validate this
approach, and each subject was diagnosed in one of the diagnostic categories
(bvFTD, svPPA, nfvPPA and cognitively normal). Our proposed automated
classification model yielded classification accuracy of 86.5, 76, and 72.7 with
support vector machine (SVM), linear discriminant analysis (LDA), and Naive
Bayes methods, respectively, in 10-fold cross-validation analysis, which is a
significant improvement on a traditional single multi-class model with an
accuracy of 82.7, 73.4, and 69.2.


  We present a multi-wavelength photometric study of individual stars in M83
based on observations taken as part of the WFC3 Early Release Science (ERS)
program. The central region of M83 has been imaged in seven broad-band filters
to obtain multi-wavelength coverage from the near-UV to near-IR. We use four
filters- F336W, F438W, F555W, and F814W-to measure the UBVI photometric colors
and intrinsic luminosity for ~10,000 stars. These measurements are used to
determine the recent (< 1 Gyr) star formation history of M83. We selected 50
regions in the spiral arm and the inter-arm area of M83 and categorize them
based on their H? morphology. To determine ages of stars in each region, the
color-magnitude diagrams (CMD) and the color-color diagrams were used with the
Padova isochrones with a metallicity of Z=0.03 (1.5 Z{\odot}). We correct the
foreground and internal extinction of individual stars using the reddening-free
Q parameter and improve our age estimates of stars from the isochrone fitting
on the CMDs. Comparisons of stellar ages and cluster ages based on both their
H? morphology and their spectral energy distribution (SED) fitting were made
and show fairly good correlations. We also find that the regions with ages
determined younger than 10 Myr are located preferentially along the active
star-forming regions on the spiral arm.


  A longstanding problem in astrochemistry is how molecules can be maintained
in the gas phase in dense inter- and circumstellar regions. Photodesorption is
a non-thermal desorption mechanism, which may explain the small amounts of
observed cold gas in cloud cores and disk mid-planes. This paper aims to
determine the UV photodesorption yields and to constrain the photodesorption
mechanisms of three astrochemically relevant ices: CO, N2 and CO2. In addition,
the possibility of co-desorption in mixed and layered CO:N2 ices is explored.
The ice photodesorption is studied experimentally under ultra high vacuum
conditions and at 15-60 K using a hydrogen discharge lamp (7-10.5 eV). The ice
desorption during irradiation is monitored by reflection absorption infrared
spectroscopy of the ice and simultaneous mass spectrometry of the desorbed
molecules. Both the UV photodesorption yields per incident photon and the
photodesorption mechanisms are molecule specific. CO photodesorbs without
dissociation from the surface layer of the ice. N2, which lacks an electronic
transition in this wavelength range, has a photodesorption yield that is more
than an order of magnitude lower. This yield increases significantly due to
co-desorption when N2 is mixed in with or layered on top of CO ice. CO2
photodesorbs through dissociation and subsequent recombination from the top 10
layers of the ice. At low temperatures (15-18 K) the derived photodesorption
yields are 2.7x10^-3 and <2x10^-4 molecules photon-1 for pure CO and N2,
respectively. The CO2 photodesorption yield is 1.2x10^-3x(1-e^(-X/2.9)) +
1.1x10^-3x(1-e^(-X/4.6)) molecules photon-1, where X is the ice thickness in
monolayers and the two parts of the expression represent a CO2 and CO
photodesorption pathway.


  Recent results from Au+Au collisions at BNL-RHIC energy hint at explosive
hadron production at the QCD transition rather than soft hydrodynamic
evolution. We speculate that this is due to a rapid variation of the effective
potential for QCD close to Tc. Performing real-time lattice simulations of an
effective theory we show that the fast evolution of the potential leads to
``explosive'' spinodal decomposition rather than bubble nucleation or critical
slowing down.


  The nonlinear process of second harmonic generation (SHG) in monolayer (1L)
transition metal dichalcogenides (TMD), like $WS_2$, strongly depends on the
polarization state of the excitation light. Combining plasmonic nanostructures
with $1L-WS_2$ by transferring it onto a plasmonic nanoantenna array, a hybrid
metasurface is realized impacting the polarization dependency of its SHG. Here,
we investigate how plasmonic dipole resonances affect the process of SHG in
plasmonic-TMD hybrid metasurfaces by nonlinear spectroscopy. We show, that the
polarization dependency is affected by the lattice structure of plasmonic
nanoantenna arrays as well as by the relative orientation between the $1L-WS_2$
and the individual plasmonic nanoantennas. In addition, such hybrid
metasurfaces show SHG in polarization states, where SHG is usually forbidden
for either $1L-WS_2$ or plasmonic nanoantennas. By comparing the SHG in these
channels with the SHG generated by the hybrid metasurface components, we detect
an enhancement of the SHG signal by a factor of more than 40. Meanwhile, an
attenuation of the SHG signal in usually allowed polarization states is
observed. Our study provides valuable insight into hybrid systems where
symmetries strongly affecting the SHG and open up the possibility for tailoring
the SHG in $1L-WS_2$ for future applications.


  Linear programming (LP) problems are pervasive in real-life applications.
However, despite their apparent simplicity, an untrained user may find it
difficult to determine the linear model of their specific problem. We envisage
the creation of a goal-oriented conversational agent that will engage in
conversation with the user to elicit all information required so that a
subsequent agent can generate the linear model. In this paper, we present an
approach for the generation of sample dialogues that can be used to develop and
train such a conversational agent. Using prompt engineering, we develop two
agents that "talk" to each other, one acting as the conversational agent, and
the other acting as the user. Using a set of text descriptions of linear
problems from NL4Opt available to the user only, the agent and the user engage
in conversation until the agent has retrieved all key information from the
original problem description. We also propose an extrinsic evaluation of the
dialogues by assessing how well the summaries generated by the dialogues match
the original problem descriptions. We conduct human and automatic evaluations,
including an evaluation approach that uses GPT-4 to mimic the human evaluation
metrics. The evaluation results show an overall good quality of the dialogues,
though research is still needed to improve the quality of the GPT-4 evaluation
metrics. The resulting dialogues, including the human annotations of a subset,
are available to the research community. The conversational agent used for the
generation of the dialogues can be used as a baseline.


  Force-Free Electrodynamics for black holes in Anti de Sitter is considered.
We present new, energy extracting solutions of Force-Free Electrodynamics in
Anti de Sitter - Near Horizon Extremal Kerr and Super-Entropic Near Horizon
Extremal Kerr geometries. The relevant equations of motion are derived from an
action for force-free plasma surrounding spinning black holes with generic
asymptotics. We consider the energy flux of electrodynamic fields in rotating
frames to argue that the correct measure for energy extraction is the energy
flux measured by a rotating observer in the near horizon region. We illustrate
this procedure by application to near horizon solutions in Kerr, AdS-Kerr and
BTZ.


  We analyze the volume-limited subsamples extracted from the sixteenth data
release of the SDSS-IV eBOSS quasar survey spanning a redshift interval of $0.8
< z < 2.2$, to estimate the scale of transition to homogeneity in the Universe.
The multi-fractal analysis used for this purpose considers the scaling behavior
of different moments of quasar distribution in different density environments.
This analysis gives the spectrum of generalized dimension $D_q$, where positive
values of $q$ characterize the scaling behavior in over-dense regions and the
negative ones in under-dense regions. We expect fractal correlation dimension
$D_q(r) = 3$, for a homogeneous, random point distribution in 3-Dimensions. The
fractal correlation dimension $D_q(r)$, corresponding to $q=2$ obtained in our
study stabilizes in the range (2.8-2.9) for scales $r>80$ $h^{-1}$ Mpc. The
observed quasar distribution shows consistency with the simulated mock data and
the random distribution of quasars within one sigma. Further, the generalized
dimension spectrum $D_q(r)$ also reveals transition to homogeneity beyond
$>110$ $h^{-1}$ Mpc, and the dominance of clustering at small scales $r<80$
$h^{-1}$ Mpc. Consequently, our study provides strong evidence for the
homogeneity in SDSS quasar distribution, offering insights into large-scale
structure properties and, thus can play a pivotal role in scrutinizing the
clustering properties of quasars and its evolution in various upcoming surveys
such as Dark Energy Spectroscopic Instrument (DESI) and Extremely Large
Telescope (ELT).


  The oscillatory dynamics of nanoelectromechanical systems (NEMS) is at the
heart of many emerging applications in nanotechnology. For common NEMS, such as
beams and strings, the oscillatory dynamics is formulated using a
dissipationless wave equation derived from elasticity. Under a harmonic ansatz,
the wave equation gives an undamped free vibration equation; solving this
equation with the proper boundary conditions provides the undamped
eigenfunctions with the familiar standing wave patterns. Any harmonically
driven solution is expressible in terms of these undamped eigenfunctions. Here,
we show that this formalism becomes inconvenient as dissipation increases. To
this end, we experimentally map out the position- and frequency-dependent
oscillatory motion of a NEMS string resonator driven linearly by a
non-symmetric force on one end at different dissipation limits. At low
dissipation (high Q factor), we observe sharp resonances with standing wave
patterns that closely match the eigenfunctions of an undamped string. With a
slight increase in dissipation, the standing wave patterns become lost and
waves begin to propagate along the nanostructure. At large dissipation (low Q
factor), these propagating waves become strongly attenuated and display little,
if any, resemblance to the undamped string eigenfunctions. A more efficient and
intuitive description of the oscillatory dynamics of a NEMS resonator can be
obtained by superposition of waves propagating along the nanostructure.


  The bottom-charmed meson spectrum is studied in this work via an effective
version of the Coulomb gauge QCD Hamiltonian. The Tamm-Dancoff approximation is
employed to estimate the energies of the low-lying and radial-excited $B_c$
states with quantum numbers $J^P = 0^{-}, 0^{+}, 1^{-}, 1^{+}, 2^{+}, 2^{-}$.
In particular, we analyze the effects of incorporating an effective transverse
hyperfine interaction and spin mixing. The Regge trajectories and hyperfine
splitting of both $S$- and $P$-wave states are also examined. The numerical
results are compared with available experimental data and theoretical
predictions of other models.


  We consider a two-dimensional optimal dividend problem in the context of two
branches of an insurance company with compound Poisson surplus processes
dividing claims and premia in some specified proportions. We solve the
stochastic control problem of maximizing expected cumulative discounted
dividend payments (among all admissible dividend strategies) until ruin of at
least one company. We prove that the value function is the smallest viscosity
supersolution of the respective Hamilton-Jacobi-Bellman equation and we
describe the optimal strategy. We analize some numerical examples.


  X-ray phase-contrast imaging has recently led to a revolution in resolving
power and tissue contrast in biomedical imaging, microscopy and materials
science. The necessary high spatial coherence is currently provided by either
large-scale synchrotron facilities with limited beamtime access or by
microfocus X-ray tubes with rather limited flux. X-rays radiated by
relativistic electrons driven by well-controlled high-power lasers offer a
promising route to a proliferation of this powerful imaging technology. A
laser-driven plasma wave accelerates and wiggles electrons, giving rise to
brilliant keV X-ray emission. This so-called Betatron radiation is emitted in a
collimated beam with excellent spatial coherence and remarkable spectral
stability. Here we present the first phase-contrast micro-tomogram revealing
quantitative electron density values of a biological sample using betatron
X-rays, and a comprehensive source characterization. Our results suggest that
laser-based X-ray technology offers the potential for filling the large
performance gap between synchrotron- and current X-ray tube-based sources.


  We present a numerical study of quasistatic magnetoconvection in a cubic
Rayleigh-B\'enard (RB) convection cell subjected to a vertical external
magnetic field. For moderate values of the Hartmann number Ha, we find an
enhancement of heat transport. Furthermore, a maximum heat transport
enhancement is observed at certain optimal $Ha_{opt}$. The enhanced heat
transport may be understood as a result of the increased coherency of the
thermal plumes, which are elementary heat carriers of the system. To our
knowledge this is the first time that a heat transfer enhancement by the
stabilising Lorentz force in quasistatic magnetoconvection has been observed.
We further found that the optimal enhancement may be understood in terms of the
crossing between the thermal and the momentum boundary layers (BL) and the fact
that temperature fluctuations are maximum near the position where the BLs
cross. These findings demonstrate that the heat transport enhancement
phenomenon in the quasistatic magnetoconvection system belongs to the same
universality class of stabilising$-$destabilising ($S$-$D$) turbulent flows as
the systems of confined Rayleigh-B\'enard (CRB), rotating Rayleigh-B\'enard
(RRB) and double-diffusive convection (DDC). This is further supported by the
findings that the heat transport, boundary layer ratio and the temperature
fluctuations in magnetoconvection at the boundary layer crossing point are
similar to the other three cases.


  We present a general procedure to construct the first law of thermodynamics
on the apparent horizon and illustrate its validity by examining it in some
extended gravity theories. Applying this procedure, we can describe the
thermodynamics on the apparent horizon in Randall-Sundrum braneworld imbedded
in a nontrivial bulk. We discuss the mass-like function which was used to link
Friedmann equation to the first law of thermodynamics and obtain its special
case which gives the generalized Misner-Sharp mass in Lovelock gravity.


  Seyfert galaxies have not been detected by COMPTEL on the Compton Gamma Ray
Observatory (CGRO) in the energy range 0.75-3 MeV, placing upper limits on
their emission which are more than an order of magnitude below previously
reported detections. Here, we extend our previous work to the energy range 3-30
MeV. Again, we find no evidence for emission from a cumulative sample of X-ray
bright Seyfert galaxies. We use the recent results on the extragalactic
background at MeV energies to constrain the possible emission of these sources
and their contribution to the cosmic extragalactic background (CXB). The lack
of $\gamma$-rays from Seyfert galaxies strongly argues against hadronic
cascades as the underlying radiation mechanism and, consequently, against
recent claims that Seyferts might produce a high-energy neutrino background
with an energy flux similar to that of the CXB.


  When liquid droplets nucleate and grow in a polymer network, compressive
stresses can significantly increase their internal pressure, reaching values
that far exceed the Laplace pressure. When droplets have grown in a polymer
network with a stiffness gradient, droplets in relatively stiff regions of the
network tend to dissolve, favoring growth of droplets in softer regions. Here,
we show that this elastic ripening can be strong enough to reverse the
direction of Ostwald ripening: large droplets can shrink to feed the growth of
smaller ones. To numerically model these experiments, we generalize the theory
of elastic ripening to account for gradients in solubility alongside gradients
in mechanical stiffness.


  Collisions of $^6$Li$_2$ molecules with free $^6$Li atoms reveal a striking
deviation from universal predictions based on long-range van der Waals
interactions. Li$_2$ closed-channel molecules are formed in the highest
vibrational state near a narrow Feshbach resonance, and decay via two-body
collisions with Li$_2$, Li, and Na. For Li$_2$+Li$_2$ and Li$_2$+Na, the decay
rates agree with the universal predictions of the quantum Langevin model. In
contrast, the rate for Li$_2$+Li is exceptionally small, with an upper bound
ten times smaller than the universal prediction. This can be explained by the
low density of available decay states in systems of light atoms [G.
Qu\'em\'ener, J.-M. Launay, and P. Honvault, Phys. Rev. A \textbf{75}, 050701
(2007)], for which such collisions have not been studied before.


  Recently, there has been much interest in holographic computations of
two-point non-equilibrium Green functions from AdS-Vaidya backgrounds. In the
strongly coupled quantum field theory on the boundary, the dual interpretation
of the background is an equilibration process called a holographic quench. The
two dimensional AdS-Vaidya spacetime is a special case, dual to conformal
quantum mechanics. We study how the quench is incorporated into a Hamiltonian
$H + \theta(t) \Delta H$ and into correlation functions. With the help of
recent work on correlation functions in conformal quantum mechanics, we first
rederive the known two point functions, and then compute non-equilibrium 3- and
4-point functions. We also compute the 3-point function Witten diagram in the
two-dimensional AdS-Vaidya background, and find agreement with the conformal
quantum mechanics result.


  In this paper we analyze the action of the gravitational field on the
dynamical Casimir effect. We consider a massless scalar field confined in a
cuboid cavity placed in a gravitational field described by a static and
diagonal metric. With one of the plane mirrors of the cavity allowed to move,
we compute the average number of particles created inside the cavity by means
of the Bogoliubov coefficients computed through perturbative expansions. We
apply our result to the case of an oscillatory motion of the mirror, assuming a
weak gravitational field described by the Schwarzschild metric. The regime of
parametric amplification is analyzed in detail, demonstrating that our computed
result for the mean number of particles created agrees with specific associated
cases in the literature. Our results, obtained in the framework of the
perturbation theory, are restricted, under resonant conditions, to a short-time
limit.


  Machine learning systems show significant promise for forecasting patient
adverse events via risk scores. However, these risk scores implicitly encode
assumptions about future interventions that the patient is likely to receive,
based on the intervention policy present in the training data. Without this
important context, predictions from such systems are less interpretable for
clinicians. We propose a joint model of intervention policy and adverse event
risk as a means to explicitly communicate the model's assumptions about future
interventions. We develop such an intervention policy model on MIMIC-III, a
real world de-identified ICU dataset, and discuss some use cases that highlight
the utility of this approach. We show how combining typical risk scores, such
as the likelihood of mortality, with future intervention probability scores
leads to more interpretable clinical predictions.


  Here, we investigate the maximum power and corresponding efficiency of
thermoelectric generators through devising a set of protocols for the
isothermal and adiabatic processes of thermoelectricity to build a Carnot-like
thermoelectric cycle, with the analysis based on fluctuation theorem (FT).
First of all, the Carnot efficiency can be readily obtained for the
quasi-static thermoelectric cycle, with the vanishing power. Moreover, the
maximum power-efficiency pair of the finite-time thermoelectric cycle is
derived, which is found to have the identical form to that of Brownian motors
characterized by the stochastic thermodynamics. However, it is of significant
discrepancy compared to the linear-irreversible and
endoreversible-thermodynamics-based formulations. The distinction compared to
the linear-irreversible-thermodynamics case could result from the difference in
the definitions of Peltier and Seebeck coefficients in the thermoelectric
cycle. As for the endoreversible thermodynamics, we argue the applicability of
endoreversibility could be questionable for analyzing the thermoelectric cycle
here, due to the incompatibility of the endoreversible hypothesis that
attributes the irreversibility to finite heat transfer with thermal reservoirs,
though the distinction of the mathematical expressions can vanish with the
assumption that the ratio of thermoelectric power factors at the high and low
temperatures is equal to the square root of the temperature ratio (this
condition could significantly deviate from the practical case).


  The amplitude of solar p-mode oscillations is governed by stochastic
excitation and mode damping, both of which take place in the surface convection
zone. However, the time-dependent, turbulent nature of convection makes it
difficult to self-consistently study excitation and damping processes through
the use of traditional one-dimensional hydrostatic models. To this end, we
carried out \textit{ab initio} three-dimensional, hydrodynamical numerical
simulations of the solar atmosphere to investigate how p-modes are driven and
dissipated in the Sun. The description of surface convection in the simulations
is free from the tuneable parameters typically adopted in traditional
one-dimensional models. Mode excitation and damping rates are computed based on
analytical expressions whose ingredients are evaluated directly from the
three-dimensional model. With excitation and damping rates both available, we
estimate the theoretical oscillation amplitude and frequency of maximum power,
$\nu_{\max}$, for the Sun. We compare our numerical results with helioseismic
observations, finding encouraging agreement between the two. The numerical
method presented here provides a novel way to investigate the physical
processes responsible for mode driving and damping, and should be valid for all
solar-type oscillating stars.


  State minimization is a fundamental problem in automata theory. The problem
is also of great importance in the study of fuzzy automata. However, most work
in the literature considered only state reduction of fuzzy automata, whereas
the state minimization problem is almost untouched for fuzzy automata. Thus in
this paper we focus on the latter problem. Formally, the decision version of
the minimization problem of fuzzy automata is as follows: \begin{itemize}
  \item Given a fuzzy automaton $\mathcal{A}$ and a natural number $k$, that
is, a pair $\langle \mathcal{A}, k\rangle$, is there a $k$-state fuzzy
automaton equivalent to $\mathcal{A}$? \end{itemize} We prove for the first
time that the above problem is decidable for fuzzy automata over totally
ordered lattices. To this end, we first give the concept of systems of fuzzy
polynomial equations and then present a procedure to solve these systems.
Afterwards, we apply the solvability of a system of fuzzy polynomial equations
to the minimization problem mentioned above, obtaining the decidability.
Finally, we point out that the above problem is at least as hard as
PSAPCE-complete.


  The purpose of this paper is to obtain existence and uniqueness results in
weighted Sobolev spaces for transmission problems for the non-linear
Darcy-Forchheimer-Brinkman system and the linear Stokes system in two
complementary Lipschitz domains in ${\mathbb R}^3$, one of them is a bounded
Lipschitz domain $\Omega $ with connected boundary, and another one is the
exterior Lipschitz domain ${\mathbb R}^3\setminus \overline{\Omega }$. We
exploit a layer potential method for the Stokes and Brinkman systems combined
with a fixed point theorem in order to show the desired existence and
uniqueness results, whenever the given data are suitably small in some weighted
Sobolev spaces and boundary Sobolev spaces.


  We consider locally recoverable codes (LRCs) and aim to determine the
smallest possible length $n=n_q(k,d,r)$ of a linear $[n,k,d]_q$-code with
locality $r$. For $k\le 7$ we exactly determine all values of $n_2(k,d,2)$ and
for $k\le 6$ we exactly determine all values of $n_2(k,d,1)$. For the ternary
field we also state a few numerical results. As a general result we prove that
$n_q(k,d,r)$ equals the Griesmer bound if the minimum Hamming distance $d$ is
sufficiently large and all other parameters are fixed.


  In this paper, we used standard rulers and standard candles (separately and
jointly) to explore five popular dark energy models under assumption of spatial
flatness of the Universe. As standard rulers, we used a data set comprising 118
galactic-scale strong lensing systems (individual standard rulers if properly
calibrated for the mass density profile) combined with BAO diagnostics
(statistical standard ruler). Supernovae Ia served asstandard candles. Unlike
in the most of previous statistical studies involving strong lensing systems,
we relaxed the assumption of singular isothermal sphere (SIS) in favor of its
generalization: the power-law mass density profile. Therefore, along with
cosmological model parameters we fitted the power law index and its first
derivative with respect to the redshift (thus allowing for mass density profile
evolution). It turned out that the best fitted $\gamma$ parameters are in
agreement with each other irrespective of the cosmological model considered.
This demonstrates that galactic strong lensing systems may provide a
complementary probe to test the properties of dark energy. Fits for
cosmological model parameters which we obtained are in agreement with
alternative studies performed by the others. Because standard rulers and
standard candles have different parameter degeneracies, combination of standard
rulers and standard candles gives much more restrictive results for
cosmological parameters. At last, we attempted at model selection based on
information theoretic criteria (AIC and BIC). Our results support the claim,
that cosmological constant model is still the best one and there is no (at
least statistical) reason to prefer any other more complex model.


  Vanadium tetracyanoethylene (V[TCNE]$_\text{x}$) is an organic-based
ferrimagnet that exhibits robust magnetic ordering (T$_\text{C}$ of over 600
K), high quality-factor (high-Q) microwave resonance (Q up to 3,500), and
compatibility with a wide variety of substrates and encapsulation technologies.
Here, we substantially expand the potential scope and impact of this emerging
material by demonstrating the ability to produce engineered nanostructures with
tailored magnetic anisotropy that serve as a platform for the exploration of
cavity magnonics, revealing strongly coupled quantum confined standing wave
modes that can be tuned into and out of resonance with an applied magnetic
field. Specifically, time-domain micromagnetic simulations of these
nanostructures faithfully reproduce the experimentally measured spectra,
including the quasi-uniform mode and higher-order spin-wave (magnon) modes.
Finally, when the two dominant magnon modes present in the spectra are brought
into resonance by varying the orientation of the in-plane magnetic field, we
observe anti-crossing behavior indicating strong coherent coupling between
these two magnon modes at room temperature. These results position
V[TCNE]$_\text{x}$ as a leading candidate for the development of coherent
magnonics, with potential applications ranging from microwave electronics to
quantum information.


  This work identifies a class of moves on knots which translate to
$m$-equivalences of the associated $p$-fold branched cyclic covers, for a fixed
$m$ and any $p$ (with respect to the Goussarov-Habiro filtration.) These moves
are applied to give a flexible (if specialised) construction of knots for which
the Casson-Walker-Lescop invariant (for example) of their $p$-fold branched
cyclic covers may be readily calculated, for any choice of $p$. In the second
part of this paper, these operations are illustrated by some theorems
concerning the relationship of knot invariants obtained from finite type
three-manifold invariants, via the branched cyclic covering construction, with
the finite type theory of knots.


  When gravitational waves travel from their source to an observer, they
interact with matter structures along their path, causing distinct deformations
in their waveforms. In this study we introduce a novel theoretical framework
for wave optics effects in gravitational lensing, addressing the limitations of
existing approaches. We achieve this by incorporating the proper time
technique, typically used in field theory studies, into gravitational lensing.
This approach allows us to extend the standard formalism beyond the eikonal and
paraxial approximations, which are traditionally assumed, and to account for
polarization effects, which are typically neglected in the literature. We
demonstrate that our method provides a robust generalization of conventional
approaches, including them as special cases. Our findings enhance our
understanding of gravitational wave propagation, which is crucial for
accurately interpreting gravitational wave observations and extracting unbiased
information about the lenses from the gravitational wave waveforms.


  We demonstrate the construction of an explicit NSFD discretization for the
standard Lotka-Volterra equations. In contrast to previous NSFD schemes, our
representation is dynamic consistent with respect to all the essential
properties of the differential equations and their solutions.


  Deep neural networks (DNNs) have excellent representative power and are state
of the art classifiers on many tasks. However, they often do not capture their
own uncertainties well making them less robust in the real world as they
overconfidently extrapolate and do not notice domain shift. Gaussian processes
(GPs) with RBF kernels on the other hand have better calibrated uncertainties
and do not overconfidently extrapolate far from data in their training set.
However, GPs have poor representational power and do not perform as well as
DNNs on complex domains. In this paper we show that GP hybrid deep networks,
GPDNNs, (GPs on top of DNNs and trained end-to-end) inherit the nice properties
of both GPs and DNNs and are much more robust to adversarial examples. When
extrapolating to adversarial examples and testing in domain shift settings,
GPDNNs frequently output high entropy class probabilities corresponding to
essentially "don't know". GPDNNs are therefore promising as deep architectures
that know when they don't know.


  We present HOI4D, a large-scale 4D egocentric dataset with rich annotations,
to catalyze the research of category-level human-object interaction. HOI4D
consists of 2.4M RGB-D egocentric video frames over 4000 sequences collected by
4 participants interacting with 800 different object instances from 16
categories over 610 different indoor rooms. Frame-wise annotations for panoptic
segmentation, motion segmentation, 3D hand pose, category-level object pose and
hand action have also been provided, together with reconstructed object meshes
and scene point clouds. With HOI4D, we establish three benchmarking tasks to
promote category-level HOI from 4D visual signals including semantic
segmentation of 4D dynamic point cloud sequences, category-level object pose
tracking, and egocentric action segmentation with diverse interaction targets.
In-depth analysis shows HOI4D poses great challenges to existing methods and
produces great research opportunities.


  The Lema\'itre-Toman-Bondi (LTB) models have reported to suffer from
incompatibility with cosmological observations and fine-tuning of the
observer's location. Further analysis of these issues indicates that they could
be resolved by models that are compatible with the supernova Ia data, but less
inhomogeneous than those that have been presented in the literature so far. We
study if such models exist by employing the degrees of freedom of the LTB
models in a novel manner. We discovered two scenarios which may meet the
expectations, but extensive numerical and analytical investigation showed them
inviable. We extended our studies to the $\Lambda$LTB models, which generalizes
the LTB models by including a non-zero cosmological constant $\Lambda$ in
Einsteins equations. This adds an additional degree of freedom for the earlier
scenarios and introduces a new scenario capable of meeting the expectations.
However, extensive numerical and analytical investigation reveals that
inclusion of $\Lambda$ does not enhance the viability of the models. We
identify the lack of degrees of freedom to be the reason for the unviability.
However, the method presented here can be generalized to models including more
degrees of freedom, like the Szekeres models, which have more promise to
overcome the issues in the LTB models.


  High performance computing (HPC) devices is no longer exclusive for academic,
R&D, or military purposes. The use of HPC device such as supercomputer now
growing rapidly as some new area arise such as big data, and computer
simulation. It makes the use of supercomputer more inclusive. Todays
supercomputer has a huge computing power, but requires an enormous amount of
energy to operate. In contrast a single board computer (SBC) such as Raspberry
Pi has minimum computing power, but require a small amount of energy to
operate, and as a bonus it is small and cheap. This paper covers the result of
utilizing many Raspberry Pi 2 SBCs, a quad-core Cortex A7 900 MHz, as a cluster
to compensate its computing power. The high performance linpack (HPL) is used
to benchmark the computing power, and a power meter with resolution 10mV / 10mA
is used to measure the power consumption. The experiment shows that the
increase of number of cores in every SBC member in a cluster is not giving
significant increase in computing power. This experiment give a recommendation
that 4 nodes is a maximum number of nodes for SBC cluster based on the
characteristic of computing performance and power consumption.


  Statistics of classical Hamiltonian random walk of particle colliding with
atoms of ideal gas is considered from viewpoint of earlier suggested exact
pseudo-quantum path integral representation of the problem, and qualitative
agreement is demostrated between results of an naturally arising simple
approximation of this integral and results obtained by formally different
methods, thus in a new fashion showing inevitability of scaleless 1/f-type
fluctuations in rates of molecular Brownian motions and other dynamical
transport and evolution processes.


  Consider a compact Riemannian manifold in dimension $n$ with strictly convex
boundary. We show the local invertibility near a boundary point of the
transverse ray transform of $2$ tensors for $n\geq 3$ and the mixed ray
transform of $2+2$ tensors for $n=3$. When the manifold admits a strictly
convex function, this local invertibility result leads to global invertibility.


  We introduce a price impact model which accounts for finite market depth,
tightness and resilience. Its coupled bid- and ask-price dynamics induce convex
liquidity costs. We provide existence of an optimal solution to the classical
problem of maximizing expected utility from terminal liquidation wealth at a
finite planning horizon. In the specific case when market uncertainty is
generated by an arithmetic Brownian motion with drift and the investor exhibits
constant absolute risk aversion, we show that the resulting singular optimal
stochastic control problem readily reduces to a deterministic optimal tracking
problem of the optimal frictionless constant Merton portfolio in the presence
of convex costs. Rather than studying the associated Hamilton-Jacobi-Bellmann
PDE, we exploit convex analytic and calculus of variations techniques allowing
us to construct the solution explicitly and to describe the free boundaries of
the action- and non-action regions in the underlying state space. As expected,
it is optimal to trade towards the frictionless Merton position, taking into
account the initial bid-ask spread as well as the optimal liquidation of the
accrued position when approaching terminal time. It turns out that this leads
to a surprisingly rich phenomenology of possible trajectories for the optimal
share holdings.


  We introduce a notion of competitive signaling equilibrium (CSE) in
one-to-one matching markets with a continuum of heterogeneous senders and
receivers. We then study monotone CSE where equilibrium outcomes - sender
actions, receiver reactions, beliefs, and matching - are all monotone in the
stronger set order. We show that if the sender utility is monotone-supermodular
and the receiver's utility is weakly monotone-supermodular, a CSE is stronger
monotone if and only if it passes Criterion D1 (Cho and Kreps (1987), Banks and
Sobel (1987)). Given any interval of feasible reactions that receivers can
take, we fully characterize a unique stronger monotone CSE and establishes its
existence with quasilinear utility functions.


  Cognizance of gene-environment interactions may help prevent or detain the
onset of complex diseases like cardiovascular disease, cancer, type2 diabetes,
autism or asthma by adjustments to lifestyle. In this regard, we extend the
Bayesian semiparametric gene-gene interaction model of Bhattacharya &
Bhattacharya (2015) to include the possibility of influencing gene-gene
interactions by environmental variables and possible mutations caused by the
environment. Our model accounts for the unknown number of genetic
sub-populations via finite mixtures composed of Dirichlet processes, which are
related to each other through a hierarchical matrix normal structure
responsible for inducing gene-gene interactions and possible mutations in
association with environmental variables. We also extend the Bayesian
hypotheses testing procedures of Bhattacharya & Bhattacharya (2015) to detect
the roles of genes and their interactions, environment and the influence of
environment on gene-gene interactions, in case-control studies. We develop an
effective parallel computing methodology, which harnesses the power of parallel
processing technology to the efficiencies of our conditionally independent
Gibbs sampling and Transformation based MCMC (TMCMC) methods.Applications of
our model and methods to simulation studies with biologically realistic
case-control genotype datasets obtained under five distinct set-ups yield
encouraging results in each case. We followed these up by application of our
ideas to a real, case-control based genotype dataset on early onset of
myocardial infarction. Beside being in broad agreement with the reported
literature on this dataset, the results obtained give some interesting insights
to the differential effect of gender on MI.


  In the article we have obtained some estimates of the rate of convergence for
the recently proposed by Yu.E. Nesterov method of minimization of a convex
Lipschitz-continuous function of two variables on a square with a fixed side.
The method consists in solving auxiliary problems of one-dimensional
minimization along the separating segments and does not imply the calculation
of the exact value of the gradient of the objective functional. Experiments
have shown that the method under consideration can achieve the desired accuracy
of solving the problem in less time than the other methods (gradient descent
and ellipsoid method) considered, both in the case of a known exact solution
and using estimates of the convergence rate of the methods.


  Automatic and robust segmentation of the left ventricle (LV) in magnetic
resonance images (MRI) has remained challenging for many decades. With the
great success of deep learning in object detection and classification, the
research focus of LV segmentation has changed to convolutional neural network
(CNN) in recent years. However, LV segmentation is a pixel-level classification
problem and its categories are intractable compared to object detection and
classification. In this paper, we proposed a robust LV segmentation method
based on slope difference distribution (SDD) double threshold selection and
circular Hough transform (CHT). The proposed method achieved 96.51% DICE score
on the test set of automated cardiac diagnosis challenge (ACDC) which is higher
than the best accuracy reported in recently published literatures.


  Consider an $n \times n$ matrix polynomial $P(\lambda)$. A spectral norm
distance from $P(\lambda)$ to the set of $n \times n$ matrix polynomials that
have a given scalar $\mu\in\mathbb{C}$ as a multiple eigenvalue was introduced
and obtained by Papathanasiou and Psarrakos. They computed lower and upper
bounds for this distance, constructing an associated perturbation of
$P(\lambda)$. In this paper, we extend this result to the case of two given
distinct complex numbers $\mu_{1}$ and $\mu_{2}$. First, we compute a lower
bound for the spectral norm distance from $P(\lambda)$ to the set of matrix
polynomials that have $\mu_1,\mu_2$ as two eigenvalues. Then we construct an
associated perturbation of $P(\lambda)$, such that the perturbed matrix
polynomial has two given scalars $\mu_1$ and $\mu_2$ in its spectrum. Finally,
we derive an upper bound for the distance by the constructed perturbation of
$P(\lambda)$. Numerical examples are provided to illustrate the validity of the
method.


  The SCION (Scalability, Control, and Isolation on Next-generation Networks)
inter-domain network architecture was proposed to address the availability,
scalability, and security shortcomings of the current Internet. This paper
presents a retrospective of the SCION goals and design decisions, its attacker
model and limitations, and research highlights of work conducted in the 5 years
following SCION's initial publication.


  In this paper, we show how Quantitative Narrative Analysis and simple Natural
Language Processing techniques apply to the extraction and categorization of
data in a sample case study of the Diary of the former President of the Italian
Republic (PoR), Giorgio Napolitano. The Diary contains a record of all his
institutional meetings. This information, if properly handled, allows for an
analysis of how the PoR used his so-called soft-powers to influence the Italian
political system during his first mandate. In this paper, we propose a way to
use simple, yet very effective, Natural Language Processing techniques - such
as Regular Expressions and Named Entity Recognition - to extract information
from the Diary. Then, we propose an innovative way to organize the extracted
data relying on the methodological framework of Quantitative Narrative
Analysis. Finally, we show how to analyze the structured data under different
levels of detail using PC-ACE (Program for Computer-Assisted Coding of Events),
a software developed specifically for this task and for data visualization.


  Experimental data in Particle and Nuclear physics, Particle Astrophysics and
Radiation Protection Dosimetry are obtained from experimental facilities
comprising a complex array of sensors, electronics and software. Computer
simulation is used to study the measurement process. Probability Density
Functions (PDFs) of measured physical parameters deviate from true PDFs due to
resolution, bias, and efficiency effects. Good estimates of the true PDF are
necessary for testing theoretical models, comparing results from different
experiments, and combining results from various research endeavors. In the
article, the histogram method is employed to estimate both the measured and
true PDFs. The binning of histograms is determined using the K-means clustering
algorithm. The true PDF is estimated through the maximization of the likelihood
function with entropy regularization, utilizing a non-linear optimization
algorithm specially designed for this purpose. The accuracy of the results is
assessed using the Mean Integrated Square Error. To determine the optimal value
for the regularization parameter, a bootstrap method is applied. Additionally,
a mathematical model of the measurement system is formulated using system
identification methods. This approach enhances the robustness and precision of
the estimation process, providing a more reliable analysis of the system's
characteristics.


  In this expository article, we give a self-contained introduction to the
wonderfully well-behaved class of pseudocompact algebras, focusing on the
foundational classes of semisimple and separable algebras. We give
characterizations of such algebras analogous to those for finite dimensional
algebras. We give a self-contained proof of the Wedderburn-Malcev Theorem for
pseudocompact algebras.


  We discuss recent results obtained by the D0 experiment at the Fermilab
Tevatron $p\bar p$ collider and recent combinations of CDF and D0 measurements.
Regarding the top quark mass, we present recent measurements obtained at D0,
the final Run~I+Run~II D0 combination, as well as the preliminary Run~I+Run~II
CDF+D0 combination. We also discuss the combination of the CDF+D0 measurements
of the $p\bar p \to t\bar t$ forward-backward asymmetry. We present the first
measurement of the direct CP-violating charge asymmetry in $B^\pm$ mesons
decaying to $\mu^\pm D^{0} X$, and discuss the status of the recent evidence
for a four-flavor tetraquark state seen at D0.


  We calculate the background field equations for the T-duality symmetric
string building on previous work by including the effect of the Dilaton up to
two-loops. Inclusion of the Dilaton allows us to obtain the full beta
functionals of the duality symmetric sigma model. We are able to interpret the
result in terms of a dimensionally reduced O(d,d) invariant target space
effective action.


  We study the collective dynamics of colloidal suspensions in the presence of
a time-dependent potential, by means of dynamical density functional theory. We
consider a non-linear diffusion equation for the density and show that spatial
patterns emerge from a sinusoidal external potential with a time-dependent
wavelength. These patterns are characterized by a sinusoidal density with the
average wavelength and a Bessel-function envelope with an induced wavelength
that depends only on the amplitude of the temporal oscillations. As a
generalization of this result, we propose a design strategy to obtain a family
of spatial patterns using time-dependent potentials of practically arbitrary
shape.


  We show that Hamiltonians with Weyl points can be realized for ultracold
atoms using laser-assisted tunneling in three-dimensional optical lattices.
Weyl points are synthetic magnetic monopoles that exhibit a robust,
three-dimensional linear dispersion. They are associated with many interesting
topological states of matter, such as Weyl semimetals and chiral Weyl fermions.
However, Weyl points have yet to be experimentally observed in any system. We
show that this elusive goal is well-within experimental reach with an extension
of the techniques recently used to obtain the Harper Hamiltonian.


  We study momentum relaxation due to dilute, weak impurities in a strongly
coupled CFT, a truncation of the M2 brane theory. Using the AdS/CFT
correspondence, we compute the relaxation time scale as a function of the
background magnetic field B and charge density \rho. The theory admits two
different types of impurities. We find that for magnetic impurities, momentum
relaxation due to the impurity is suppressed by a background B or \rho. For
electric impurities, due to an underlying instability in the theory towards an
ordered phase, the inverse relaxation time scale increases dramatically near
\sqrt{B^2 + \rho^2/\sigma^2_0} \sim 21 T^2. We compute the Nernst response for
the impure theory, and comment on similarities with recent measurements in
superconductors.


  Quantum tasks are quantum computations with inputs and outputs occurring at
specified spacetime locations. Considering such tasks in the context of AdS/CFT
has led to novel constraints relating bulk geometry and boundary entanglement.
In this article we consider tasks where inputs and outputs are encoded into
extended spacetime regions, rather than the points previously considered. We
show that this leads to stronger constraints than have been derived in the
point based setting. In particular we improve the connected wedge theorem,
appearing earlier in 1912.05649, by finding a larger bulk region whose
existence implies large boundary correlation. As well, we show how considering
extended input and output regions leads to non-trivial statements in
Poincar\'e-AdS$_{2+1}$, a setting where the point-based connected wedge theorem
is always trivial.


  Novel view synthesis from an in-the-wild video is difficult due to challenges
like scene dynamics and lack of parallax. While existing methods have shown
promising results with implicit neural radiance fields, they are slow to train
and render. This paper revisits explicit video representations to synthesize
high-quality novel views from a monocular video efficiently. We treat static
and dynamic video content separately. Specifically, we build a global static
scene model using an extended plane-based scene representation to synthesize
temporally coherent novel video. Our plane-based scene representation is
augmented with spherical harmonics and displacement maps to capture
view-dependent effects and model non-planar complex surface geometry. We opt to
represent the dynamic content as per-frame point clouds for efficiency. While
such representations are inconsistency-prone, minor temporal inconsistencies
are perceptually masked due to motion. We develop a method to quickly estimate
such a hybrid video representation and render novel views in real time. Our
experiments show that our method can render high-quality novel views from an
in-the-wild video with comparable quality to state-of-the-art methods while
being 100x faster in training and enabling real-time rendering.


  Let H be a Hopf algebra in a rigid braided monoidal category with split
idempotents. We prove the existence of integrals on (in) H characterized by the
universal property, employing results about Hopf modules, and show that their
common target (source) object Int H is invertible. The fully braided version of
Radford's formula for the fourth power of the antipode is obtained. Connections
of integration with cross-product and transmutation are studied. The results
apply to topological Hopf algebras, e.g. a torus with a hole, which do not have
additive structure.


  Let $X$ be a separable real Hilbert space. We show that for every Lipschitz
function $f:X\rightarrow\mathbb{R}$, and for every $\epsilon>0$, there exists a
Lipschitz, real analytic function $g:X\rightarrow\mathbb{R}$ such that
$|f(x)-g(x)|\leq \epsilon$ and $\textrm{Lip}(g)\leq \textrm{Lip}(f)+\epsilon$.


  This paper introduces QOperAv v1.5, a Java application available for free.
(Source code included in the distribution.) QOperAv is a "code generator" for
generating quantum circuits. The quantum circuits generated by QOperAv can be
used to evaluate with polynomial efficiency the average of $f(A)$ for some
simple (that is, computable with polynomial efficiency) function $f$ and a
Hermitian operator $A$, provided that we know how to compile $\exp(iA)$ with
polynomial efficiency. QOperAv implements an algorithm described in earlier
papers, that combines various standard techniques such as quantum phase
estimation and quantum multiplexors.


  The $T_N$ theory is a non-Lagrangian theory with SU(N) flavor symmetry. We
argue that when mass terms are given so that two of SU(N)'s are both broken to
SU(N-1) x U(1), it becomes $T_{N-1}$ theory coupled to an SU(N-1) vector
multiplet together with N fundamentals. This implies that when two of SU(N)'s
are both broken to U(1)$^{N-1}$, the theory becomes a linear quiver.
  We perform various checks of this statement, by using the 5d partition
function, the structure of the coupling constants, the Higgs branch, and the
Seiberg-Witten curve. We also study the case with more general punctures.


  A search for the standard model Higgs boson in the \bbbar decay channel has
been carried out with the CMS detector at the LHC collider. The searched
production modes are the associated VH production, the VBF production and the
production in association with top quark pairs (ttH). The analyses are based on
pp collision data collected at centre-of-mass energies of 7 and 8 TeV,
corresponding to integrated luminosities of 5 fb$^{-1}$ and 20 fb$^{-1}$,
respectively. The strategy and results of the searches are reported.


  Let $(M,g)$ be a compact Riemannian manifold of dimension $n\geq 3$. For a
metric $g$ on $M$, we let $\la_2(g)$ be the second eigenvalue of the Yamabe
operator $L_g:= \frac{4(n-1)}{n-2} \Delta_g + \scal_g$. Then, the second Yamabe
invariant is defined as $$ \si_2(M) \definedas \sup \inf_{h \in [g]} \la_2(h)
\Vol(M,h)^{2/n}. $$ where the supremum is taken over all metrics $g$ and the
infimum is taken over the metrics in the conformal class $[g]$. Assume that
$\si_2(M)>0$. In the spirit of \cite{ammann.dahl.humbert:08}, we prove that if
$N$ is obtained from $M$ by a $k$-dimensional surgery ($0 \leq k \leq n-3$),
there exists a positive constant $\Lambda_n$ depending only on $n$ such that
$\si_2(N) \geq \min(\sigma_2(M), \Lambda_n)$. We then give some topological
conclusions of this result.


  For the first time, a global model of electromagnetic pulse (EMP) emission
connects charge separation in the laser target to quantitative measurements of
the electromagnetic field. We present a frequency-domain dipole antenna model
which predicts the quantity of charge accumulated in a laser target as well as
the EMP amplitude and frequency. The model is validated against measurements
from several high-intensity laser facilities, providing insight into target
physics and informing the design of next-generation ultra-intense laser
facilities. EMP amplitude is proportional to the total charge accumulated on
the target, but we demonstrate that it is not directly affected by target
charging time (and therefore the laser pulse duration) provided the charging
time is shorter than the antenna characteristic time. We propose two
independent methods for estimating the charging time based on the laser pulse
duration. We also investigate the impact of target holder geometry on EMPs
using cylindrical, conical and helical holders.


  The program of matrix product states on tensor powers $\mathcal A^{\otimes
\mathbb Z}$ of $C^\ast$-algebras, initiated in Comm. Math. Phys. {\bf 144},
443-490 (1992), is re-assessed in a context where $\mathcal A$ is a generic
nuclear $C^\ast$-algebra. For any shift invariant state $\omega$, we
demonstrate the existence of an order kernel ideal $\mathcal K_\omega$, whose
quotient action reduces and factorizes the initial data $(\mathcal A^{\otimes
\mathbb Z}, \omega)$ to the tuple $(\mathcal A,\mathcal B_\omega = \mathcal
A^{\otimes \mathbb N^\times}/\mathcal K_\omega, \mathbb E_\omega : \mathcal A
\otimes \mathcal B_\omega \to \mathcal B_\omega, \bar \omega : \mathcal
B_\omega \to \mathbb C)$, where $\mathcal B_\omega$ is an operator system and
$\mathbb E_\omega$ and $\bar \omega$ are unital and completely positive maps.
Reciprocally, given a (input) tuple $(\mathcal A,\mathcal S,\mathbb E,\phi)$
that shares similar attributes, we supply an algorithm that produces a
shift-invariant state on $\mathcal A^{\otimes \mathbb Z}$. We give sufficient
conditions in which the so constructed states are ergodic and they reduce back
to their input data. As examples, we formulate the input data that produces
AKLT-type states, this time in the context of infinite site algebras, such as
the group algebra of discrete amenable groups.


  I cross-correlate the galaxy counts from the Canada-France Hawaii Telescope
Lensing Survey (CFHTLenS) galaxy catalogue and Cosmic Microwave Background
(CMB) convergence from the Planck data release 1 (2013) and 2 (2015), following
the work of Omori & Holder (2015). I improve their study by computing an
analytic covariance from the Halo Model, implementing simulations to validate
the theoretically estimated error bars and the reconstruction method, fitting
both a galaxy bias and a cross-correlation amplitude using the joint cross and
galaxy auto-correlation, and performing a series of null tests. Using a
bayesian analysis, I find a galaxy bias $b=0.92_{-0.02}^{+0.02}$ and a
cross-correlation amplitude $A=0.85_{-0.16}^{+0.15}$ for the 2015 release,
whereas for the 2013 release I find $b=0.93_{-0.02}^{+0.02}$ and
$A=1.05_{-0.15}^{+0.15}$. I thus confirm the difference between the two
releases found by Omori & Holder (2015), although both values of the amplitude
now appear to be compatible with the fiducial value $A=1$.


  Solutions to Traveling salesman problem have been obtained with several
algorithms. However, few of them has discussed about the statistical
distribution of lengths for the quasi-optimal path obtained. For a random set
of cities such a distribution follows a rank 2 daisy model but our analysis on
actual distribution of cities does not show the characteristic quadratic growth
of the daisy model. The role played by the initial city distribution is
explored in this work. The importance of understanding such a behavior in the
context of electoral processes is discussed.


  By considering a simplified but exact model for realizing the ekpyrotic
scenario, we clarify various assumptions that have been used in the literature.
In particular, we discuss the new ekpyrotic prescription for passing the
perturbations through the singularity which we show to provide a spectrum
depending on a non physical normalization function. We also show that this
prescription does not reproduce the exact result for a sharp transition. Then,
more generally, we demonstrate that, in the only case where a bounce can be
obtained in Einstein General Relativity without facing singularities and/or
violation of the standard energy conditions, the bounce cannot be made
arbitrarily short. This contrasts with the standard (inflationary) situation
where the transition between two eras with different values of the equation of
state can be considered as instantaneous. We then argue that the usually
conserved quantities are not constant on a typical bounce time scale. Finally,
we also examine the case of a test scalar field (or gravitational waves) where
similar results are obtained. We conclude that the full dynamical equations of
the underlying theory should be solved in a non singular case before any
conclusion can be drawn.


  The objective is to develop a general stochastic approach to delays on
financial markets. We suggest such a concept in the context of large platonic
markets, which allow infinitely many assets and incorporate a restricted
information setting. The discussion is divided into information delays and
order execution delays. The former enables modelling of markets where the
observed information is delayed, while the latter provides the opportunity to
defer the indexed time of a received asset price. Both delays may be designed
randomly and inhomogeneously over time. We show that delayed markets are
equipped with a fundamental theorem of asset pricing and our main result is
inheritance of the no asymptotic Lp-free lunch condition under both delay
types. Eventually, we suggest an approach to verify absence of Lp-free lunch on
markets with multiple brokers endowed with deviating trading speeds.


  We consider the space $\mathcal{P}(X)$ of probability measures on arbitrary
Radon space $X$ endowed with a transportation cost $J(\mu, \nu)$ generated by a
nonnegative continuous cost function. For a probability distribution on
$\mathcal{P}(X)$ we formulate a notion of average with respect to this
transportation cost, called here the Fr\'echet barycenter, prove a version of
the law of large numbers for Fr\'echet barycenters, and discuss the structure
of $\mathcal{P}(X)$ related to the transportation cost $J$.


  We have found that there is more than one type of conducting carriers
generated in LaAlO3/SrTiO3 heterostructures by comparing the sheet carrier
density and mobility from optical transmission spectroscopy with those from
dc-transport measurements. When multiple types of carriers exist, optical
characterization dominantly reflects the contribution from the high-density
carriers whereas dc-transport measurements may exaggerate the contribution of
the high-mobility carriers even though they are present at low-density. Since
the low-temperature mobilities determined by dc-transport in the LaAlO3/SrTiO3
heterostructures are much higher than those extracted by optical method, we
attribute the origin of high-mobility transport to the low-density conducting
carriers.


  In this paper, we describe the design, construction and performance of an
apparatus installed in the Aberdeen Tunnel laboratory in Hong Kong for studying
spallation neutrons induced by cosmic-ray muons under a vertical rock
overburden of 611 meter water equivalent (m.w.e.). The apparatus comprises of
six horizontal layers of plastic-scintillator hodoscopes for determining the
direction and position of the incident cosmic-ray muons. Sandwiched between the
hodoscope planes is a neutron detector filled with 650 kg of liquid
scintillator doped with about 0.06% of Gadolinium by weight for improving the
efficiency of detecting the spallation neutrons. Performance of the apparatus
is also presented.


  Recently, an interesting phenomenon called grokking has gained much
attention, where generalization occurs long after the models have initially
overfitted the training data. We try to understand this seemingly strange
phenomenon through the robustness of the neural network. From a robustness
perspective, we show that the popular $l_2$ weight norm (metric) of the neural
network is actually a sufficient condition for grokking. Based on the previous
observations, we propose perturbation-based methods to speed up the
generalization process. In addition, we examine the standard training process
on the modulo addition dataset and find that it hardly learns other basic group
operations before grokking, for example, the commutative law. Interestingly,
the speed-up of generalization when using our proposed method can be explained
by learning the commutative law, a necessary condition when the model groks on
the test dataset. We also empirically find that $l_2$ norm correlates with
grokking on the test data not in a timely way, we propose new metrics based on
robustness and information theory and find that our new metrics correlate well
with the grokking phenomenon and may be used to predict grokking.


  We analytically and numerically investigate the 't Hooft-Bergknoff-Eller
equations, the lowest order mesonic Light-Front Tamm-Dancoff equations for
U(N_C) and SU(N_C) gauge theories. We find the wavefunction can be well
approximated by new basis functions and obtain an analytic formula for the mass
of the lightest bound state. Its value is consistent with the precedent
results.


  With the rapid growth of surveillance cameras in many public places to
mon-itor human activities such as in malls, streets, schools and, prisons,
there is a strong demand for such systems to detect violence events
automatically. Au-tomatic analysis of video to detect violence is significant
for law enforce-ment. Moreover, it helps to avoid any social, economic and
environmental damages. Mostly, all systems today require manual human
supervisors to de-tect violence scenes in the video which is inefficient and
inaccurate. in this work, we interest in physical violence that involved two
persons or more. This work proposed a novel method to detect violence using a
fusion tech-nique of two significantly different convolutional neural networks
(CNNs) which are AlexNet and SqueezeNet networks. Each network followed by
separate Convolution Long Short Term memory (ConvLSTM) to extract ro-bust and
richer features from a video in the final hidden state. Then, making a fusion
of these two obtained states and fed to the max-pooling layer. Final-ly,
features were classified using a series of fully connected layers and soft-max
classifier. The performance of the proposed method is evaluated using three
standard benchmark datasets in terms of detection accuracy: Hockey Fight
dataset, Movie dataset and Violent Flow dataset. The results show an accuracy
of 97%, 100%, and 96% respectively. A comparison of the results with the state
of the art techniques revealed the promising capability of the proposed method
in recognizing violent videos.


  For a wide family of multivariate Hausdorff operators, a new stronger
condition for the boundedness of an operator from this family on the real Hardy
space $H^1$ by means of atomic decomposition.


  The tRopIcal DEep-sea Neutrino Telescope (TRIDENT) is a future large-scale
next-generation neutrino telescope. In September 2021, the TRIDENT pathfinder
experiment (TRIDENT EXplorer, T-REX for short) completed in-situ measurements
of deep-sea water properties in the South China Sea. The T-REX apparatus
integrates two independent and complementary systems, a photomultiplier tube
(PMT) and a camera system, to measure the optical and radioactive properties of
the deep-sea water. One light emitter module and two light receiver modules
were deployed, which were synchronized by using White Rabbit (WR) technology.
The light emitter module generates nanosecond-width LED pulses, while the light
receiver module hosts three PMTs and a camera to detect photons. The submerged
apparatus and the data acquisition system (DAQ) perform real-time command and
data transmission. We report the design and performance of the readout
electronics for T-REX, including hardware modules, firmware design for digital
signal processing, and host-computer software.