  Tag-based image retrieval (TBIR) has drawn much attention in recent years due
to the explosive amount of digital images and crowdsourcing tags. However, TBIR
is still suffering from the incomplete and inaccurate tags provided by users,
posing a great challenge for tag-based image management applications. In this
work, we proposed a novel method for image annotation, incorporating several
priors: Low-Rankness, Tag and Visual Correlation and Inhomogeneous Errors.
Highly representative CNN feature vectors are adopt to model the tag-visual
correlation and narrow the semantic gap. And we extract word vectors for tags
to measure similarity between tags in the semantic level, which is more
accurate than traditional frequency-based or graph-based methods. We utilize
the accelerated proximal gradient (APG) method to solve our model efficiently.
Extensive experiments conducted on multiple benchmark datasets demonstrate the
effectiveness and robustness of the proposed method.


  Inspired by the work of Paterson on $C^{\ast}$-algebras of directed graphs,
we show how to associate a groupoid $\mathfrak{G}_{\mathcal{G}}$ to an
ultragraph $\mathcal{G}$ in such a way that the $C^*$-algebra of
$\mathfrak{G}_{\mathcal{G}}$ is canonically isomorphic to Tomforde's
$C^*$-algebra $C^*(\mathcal{G})$. The groupoid $\mathfrak{G}_{\mathcal{G}}$ is
built from an inverse semigroup $S_{\mathcal{G}}$ naturally associated to
$\mathcal{G}$.


  We revisit the constraints implied by SN 1987 A observations on the decay
rate of a multi-MeV $\nu_\tau$ decaying into the visible channel $\nu_\tau
\rightarrow e^+ e^- \nu_e$, if its lifetime is more than 10 {\it sec.}. We
discuss its implication for the minimal left-right symmetric model with see-saw
mechanism for neutrino masses. We also speculate on the possible formation of a
``giant Capacitor" in intergalactic space due to the decay of "neutronization"
$\nu_\tau$'s and spin allignment possibility in the supernova.


  Recent experimental studies of the antiproton-deuteron system at low energies
have shown that the imaginary part of the antiproton-deuteron scattering length
is smaller than the antiproton-proton one. Two- and three-body systems with
strong annihilation are investigated and a mechanism explaining this unexpected
relation between the imaginary parts of the scattering lengths is proposed.


  MeV-scale magnetic fields in the interiors of magnetars suppress the pairing
of neutrons and protons in the $S$-wave state. In the case of a neutron
condensate the suppression is the consequence of the Pauli-paramagnetism of the
neutron gas, i.e., the alignment of the neutron spins along the magnetic field.
The proton $S$-wave pairing is suppressed because of the Landau diamagnetic
currents of protons induced by the field. The Ginzburg-Landau and BCS theories
of the critical magnetic fields for unpairing are reviewed. The macrophysical
implications of the suppression (unpairing) of the condensates are discussed
for the rotational crust-core coupling in magnetars and the neutrino-dominated
cooling era of their thermal evolution.


  This paper analyzes wireless network control for remote estimation of linear
time-invariant dynamical systems under various Hybrid Automatic Repeat Request
(HARQ) packet retransmission schemes. In conventional HARQ, packet reliability
increases gradually with additional packets; however, each retransmission
maximally increases the Age of Information and causes severe degradation in
estimation mean squared error (MSE) performance. We optimize standard HARQ
schemes by allowing partial retransmissions to increase the packet reliability
gradually and limit the AoI growth. In incremental redundancy HARQ, we optimize
the retransmission time to enable the early arrival of the next status updates.
In Chase combining HARQ, since packet length remains fixed, we allow
retransmission and new updates in a single time slot using non-orthogonal
signaling. Non-orthogonal retransmissions increase packet reliability without
delaying the fresh updates. We formulate bi-objective optimization with the
proposed variance of the MSE-based cost function and standard long-term average
MSE cost function to guarantee short-term performance stability. Using the
Markov decision process formulation, we find the optimal static and dynamic
policies under the proposed HARQ schemes to improve MSE performance further.
The simulation results show that the proposed HARQ-based policies are more
robust and achieve significantly better and more stable MSE performance than
standard HARQ-based policies.


  This paper presents a novel Sequence-to-Sequence (Seq2Seq) model based on a
transformer-based attention mechanism and temporal pooling for Non-Intrusive
Load Monitoring (NILM) of smart buildings. The paper aims to improve the
accuracy of NILM by using a deep learning-based method. The proposed method
uses a Seq2Seq model with a transformer-based attention mechanism to capture
the long-term dependencies of NILM data. Additionally, temporal pooling is used
to improve the model's accuracy by capturing both the steady-state and
transient behavior of appliances. The paper evaluates the proposed method on a
publicly available dataset and compares the results with other state-of-the-art
NILM techniques. The results demonstrate that the proposed method outperforms
the existing methods in terms of both accuracy and computational efficiency.


  Equipping the rototranslation group $SE(2)$ with a sub-Riemannian structure
inspired by the visual cortex V1, we propose algorithms for image inpainting
and enhancement based on hypoelliptic diffusion. We innovate on previous
implementations of the methods by Citti, Sarti, and Boscain et al., by
proposing an alternative that prevents fading and is capable of producing
sharper results in a procedure that we call WaxOn-WaxOff. We also exploit the
sub-Riemannian structure to define a completely new unsharp filter using
$SE(2)$, analogous to the classical unsharp filter for 2D image processing. We
demonstrate our method on blood vessels enhancement in retinal scans.


  With growing application of machine learning (ML) technologies in healthcare,
there have been calls for developing techniques to understand and mitigate
biases these systems may exhibit. Fair-ness considerations in the development
of ML-based solutions for health have particular implications for Africa, which
already faces inequitable power imbalances between the Global North and
South.This paper seeks to explore fairness for global health, with Africa as a
case study. We conduct a scoping review to propose axes of disparities for
fairness consideration in the African context and delineate where they may come
into play in different ML-enabled medical modalities. We then conduct
qualitative research studies with 672 general population study participants and
28 experts inML, health, and policy focused on Africa to obtain corroborative
evidence on the proposed axes of disparities. Our analysis focuses on
colonialism as the attribute of interest and examines the interplay between
artificial intelligence (AI), health, and colonialism. Among the pre-identified
attributes, we found that colonial history, country of origin, and national
income level were specific axes of disparities that participants believed would
cause an AI system to be biased.However, there was also divergence of opinion
between experts and general population participants. Whereas experts generally
expressed a shared view about the relevance of colonial history for the
development and implementation of AI technologies in Africa, the majority of
the general population participants surveyed did not think there was a direct
link between AI and colonialism. Based on these findings, we provide practical
recommendations for developing fairness-aware ML solutions for health in
Africa.


  This work presents the facility location problem for maximum coverage in an
emergency medical service called SAMU-BH, located in Belo Horizonte, Minas
Gerais, Brazil. The purpose of the proposed model is to find the best locations
for its ambulances in order to provide faster in-site assistance whenever
necessary. First, it develops a mono-objective model to maximize the coverage
rate, defined as the number of calls attended before a target time. Based on
the Facility Location and Equipment Emplacement Technique (FLEET) model, a
novel mathematical model is proposed, called FLEET-IC, which can work with
independent coverages. Secondly, it proposes a multi-objective model to
increase total coverage while reducing the number of installed bases. The
results show that the mono-objective model's application increases the coverage
rate up to 48%, considering the busy fraction factor and up to 26% without it.
It also analyzes the effect on the coverage rate of the inclusion of additional
ambulances.


  The method of constructing Hermite trigonometric polynomials, which
interpolate the values of a certain periodic function and its derivatives up to
(including ) the -th ( ) order in nodes of a uniform grid, is considered. The
proposed method is based on the properties of the periodicity of trigonometric
functions and is reduced to the solving of only two systems of the linear
algebraic equations of the --th order; solutions to these systems may be
obtained in advance. When implementing this method, it is necessary to
calculate the coefficients of interpolation trigonometric polynomials that
interpolate the values of the function itself and the values of its derivatives
in the nodes of a uniform grid; well-known algorithms of fast Fourier transform
can be applied for this purpose. The examples of construction of Hermite
trigonometric polynomials for .. are given. The proposed method may be
recommended for wide practical application.


  We investigate the double-charm and hidden-charm hexaquarks as molecules in
the framework of the one-boson-exchange potential model. The multichannel
coupling and $S-D$ wave mixing are taken into account carefully. We adopt the
complex scaling method to investigate the possible quasibound states, whose
widths are from the three-body decay channel $\Lambda_c\Lambda_c\pi$ or
$\Lambda_c\bar{\Lambda}_c\pi$. For the double-charm system of $I(J^P)=1(1^+)$,
we obtain a quasibound state, whose width is 0.50 MeV if the binding energy is
-14.27 MeV. And the $S$-wave $\Lambda_c\Sigma_c$ and $\Lambda_c\Sigma_c^*$
components give the dominant contributions. For the $1(0^+)$ double-charm
hexaquark system, we do not find any pole. We find more poles in the
hidden-charm hexaquark system. We obtain one pole as a quasibound state in the
$I^G(J^{PC})=1^+(0^{--})$ system, which only has one channel
$(\Lambda_c\bar{\Sigma}_c+\Sigma_c\bar{\Lambda}_c)/\sqrt{2}$. Its width is 1.72
MeV with a binding energy of -5.37 MeV. But, we do not find any pole for the
scalar $1^-(0^{-+})$ system. For the vector $1^-(1^{-+})$ system, we find a
quasibound state. Its energies, widths and constituents are very similar to
those of the $1(1^+)$ double-charm case. In the vector $1^+(1^{--})$ system, we
get two poles -- a quasibound state and a resonance. The quasibound state has a
width of 0.6 MeV with a binding energy of -15.37 MeV. For the resonance, its
width is 2.72 MeV with an energy of 63.55 MeV relative to the
$\Lambda_c\bar{\Sigma}_c$ threshold. And its partial width from the two-body
decay channel $(\Lambda_c\bar{\Sigma}_c-\Sigma_c\bar{\Lambda}_c)/\sqrt{2}$ is
apparently larger than the partial width from the three-body decay channel
$\Lambda_c\bar{\Lambda}_c\pi$.


  In this paper, we obtain a refined temporal asymptotic upper bound of the
global axially symmetric solution to the Boussinesq system with no thermal
diffusivity. We show the spacial $W^{1,p}$-Sobolev ($2\leq p<\infty$) norm of
the velocity can only grow at most algebraically as $t\to+\infty$. Under a
signed potential condition imposed on the initial data, we further derive that
the aforementioned norm is uniformly bounded at all times. Higher order
estimates are also given: We find the $H^1$ norm of the temperature fluctuation
grows sub-exponentially as $t\to+\infty$. Meanwhile, for any $m\geq 1$, we
deduce that the $H^m$-temporal growth of the solution is slower than a double
exponential function. As a result, these improve the results in
\cite{HR:2010AIHP} where the authors only provided rough temporal asymptotic
upper bounds while proving the global well-posedness.


  We present a two-part program for state space decomposition. States are
classified into entanglement classes based on local unitary transformations,
and then characterized as elements of topological spaces using the language of
fibre bundles.


  We propose a novel approach and an empirical procedure to test direct
contagion of growth rate in a trade credit network of firms. Our hypotheses are
that the use of trade credit contributes to contagion (from many customers to a
single supplier - "many to one" contagion) and amplification (through their
interaction with the macrocopic variables, such as interest rate) of growth
rate. In this paper we test the contagion hypothesis, measuring empirically the
mesoscopic "many-to-one" effect. The effect of amplification has been dealt
with in another paper.
  Our empirical analysis is based on the delayed payments between trading
partners across many different industrial sectors, intermediated by a large
Italian bank during the year 2007. The data is used to create a weighted and
directed trade credit network. Assuming that the linkages are static, we look
at the dynamics of the nodes/firms. On the ratio of the 2007 trade credit in
Sales and Purchases items on the profit and loss statements, we estimate the
trade credit in 2006 and 2008.
  Applying the "many to one" approach we compare such predicted growth of trade
(demand) aggregated per supplier, and compare it with the real growth of Sales
of the supplier. We analyze the correlation of these two growth rates over two
yearly periods, 2007/2006 and 2008/2007, and in this way we test our contagion
hypotheses. We could not find strong correlations between the predicted and the
actual growth rates. We provide an evidence of contagion only in restricted
sub-groups of our network, and not in the whole network. We do find a strong
macroscopic effect of the crisis, indicated by a coincident negative drift in
the growth of sales of nearly all the firms in our sample.


  Using a data sample of 2.59 x 10^7 psi(2S) decays obtained with the CLEO-c
detector, we perform amplitude analyses of the complementary decay chains
chi_c1 -> eta pi+ pi- and chi_c1 -> eta' pi+ pi-. We find evidence for a P-wave
eta' pi scattering amplitude, which, if interpreted as a resonance, would have
exotic J^PC = 1^-+ and parameters consistent with the pi_1(1600) state reported
in other production mechanisms. We also make the first observation of the decay
a_0(980) -> eta' pi and measure the ratio of branching fractions B(a_0(980) ->
eta' pi)/B(a_0(980) -> eta pi) = 0.064 +- 0.014 +- 0.014. The pi pi spectrum
produced with a recoiling eta is compared to that with eta' recoil.


  In germanium-based light detectors for scintillating bolometers, a SiO$_2$
anti-reflective coating is often applied on the side of the germanium wafer
exposed to light with the aim to improve its light collection efficiency. In
this paper, we report about a measurement, performed in the temperature range
25-35 mK, of the light-collection increase obtained thanks to this method,
which resulted to be of the order of 20%. The procedure followed has been
carefully selected in order to minimize systematic effects. The employed light
sources have the same spectral features (peaking at $\sim 630$ nm wavelength)
that will characterise future neutrinoless double beta decay experiments on the
isotope $^{82}$Se and based on ZnSe crystals, such as LUCIFER. The coupling
between source and light detector reproduces the configuration used in
scintillating bolometers. The present measurement clarifies the role of SiO$_2$
coating and describes a method and a set-up that can be extended to the study
of other types of coatings and luminescent materials.


  Park et al. [1] reported a decline in the disruptiveness of scientific and
technological knowledge over time. Their main finding is based on the
computation of CD indices, a measure of disruption in citation networks [2],
across almost 45 million papers and 3.9 million patents. Due to a factual
plotting mistake, database entries with zero references were omitted in the CD
index distributions, hiding a large number of outliers with a maximum CD index
of one, while keeping them in the analysis [1]. Our reanalysis shows that the
reported decline in disruptiveness can be attributed to a relative decline of
these database entries with zero references. Notably, this was not caught by
the robustness checks included in the manuscript. The regression adjustment
fails to control for the hidden outliers as they correspond to a discontinuity
in the CD index. Proper evaluation of the Monte-Carlo simulations reveals that,
because of the preservation of the hidden outliers, even random citation
behaviour replicates the observed decline in disruptiveness. Finally, while
these papers and patents with supposedly zero references are the hidden drivers
of the reported decline, their source documents predominantly do make
references, exposing them as pure dataset artefacts.


  In this paper we develop a theory of general selection systems with discrete
time and explore the evolution of selection systems, in particular,
inhomogeneous populations. We show that the knowledge of the initial
distribution of the selection system allows us to determine explicitly the
system distribution at the entire time interval. All statistical
characteristics of interest, such as mean values of the fitness or any trait
can be predicted effectively for indefinite time and these predictions
dramatically depend on the initial distribution. The Fisher Fundamental theorem
of natural selection (FTNS) and more general the Price equations are the famous
results of the mathematical selection theory. We show that the problem of
dynamic insufficiency for the Price equations and for the FTNS can be resolved
within the framework of selection systems. Effective formulas for solutions of
the Price equations and for the FTNS are derived. Applications of the developed
theory to some other problems of mathematical biology (dynamics of
inhomogeneous logistic and Ricker model, selection in rotifer populations) are
also given. Complex behavior of the total population size, the mean fitness (in
contrast to the plain FTNS) and other traits is possible for inhomogeneous
populations with density-dependent fitness. The temporary dynamics of these
quantities can be investigated with the help of suggested methods.


  A Gedanken experiment is presented where an excited and a ground-state atom
are positioned such that, within the former's half-life time, they exchange a
photon with 50% probability. A measurement of their energy state will therefore
indicate in 50% of the cases that no photon was exchanged. Yet other
measurements would reveal that, by the mere possibility of exchange, the two
atoms have become entangled. Consequently, the "no exchange" result, apparently
precluding entanglement, is non-locally established between the atoms by this
very entanglement. This quantum-mechanical version of the ancient Liar Paradox
can be realized with already existing transmission schemes, with the addition
of Bell's theorem applied to the no-exchange cases. Under appropriate
probabilities, the initially-excited atom, still excited, can be entangled with
additional atoms time and again, or alternatively, exert multipartite nonlocal
correlations in an interaction free manner. When densely repeated several
times, this result also gives rise to the Quantum Zeno effect, again exerted
between distant atoms without photon exchange. We discuss these experiments as
variants of Interaction-Free-Measurement, now generalized for both spatial and
temporal uncertainties. We next employ weak measurements for elucidating the
paradox. Interpretational issues are discussed in the conclusion, and a
resolution is offered within the Two-State Vector Formalism and its new
Heisenberg framework.


  Open relation extraction is the task of extracting open-domain relation facts
from natural language sentences. Existing works either utilize heuristics or
distant-supervised annotations to train a supervised classifier over
pre-defined relations, or adopt unsupervised methods with additional
assumptions that have less discriminative power. In this work, we proposed a
self-supervised framework named SelfORE, which exploits weak, self-supervised
signals by leveraging large pretrained language model for adaptive clustering
on contextualized relational features, and bootstraps the self-supervised
signals by improving contextualized features in relation classification.
Experimental results on three datasets show the effectiveness and robustness of
SelfORE on open-domain Relation Extraction when comparing with competitive
baselines.


  There is a remarkably tight relation between the observationally inferred
dust masses and star-formation rates (SFRs) of SDSS galaxies, Mdust $\propto$
SFR$^{1.11}$ (Da Cunha et al. 2010). Here we extend the Mdust-SFR relation to
the high end and show that it bends over at very large SFRs (i.e., dust masses
are lower than predicted for a given SFR). We identify several distinct
evolutionary processes in the diagram: (1) A star-bursting phase in which dust
builds up rapidly at early times. The maximum attainable dust mass in this
process is the cause of the bend-over of the relation. A high dust-formation
efficiency, a bottom-light initial mass function, and negligible supernova
shock dust destruction are required to produce sufficiently high dust masses.
(2) A quiescent star-forming phase in which the subsequent parallel decline in
dust mass and SFR gives rise to the Mdust-SFR relation, through astration and
dust destruction. The dust-to-gas ratio is approximately constant along the
relation. We show that the power-law slope of the Mdust-SFR relation is
inversely proportional to the global Schmidt-Kennicutt law exponent (i.e.,
$\sim 0.9$) in simple chemical evolution models. (3) A quenching phase which
causes star formation to drop while the dust mass stays roughly constant or
drops proportionally. Combined with merging, these processes, as well as the
range in total baryonic mass, give rise to a complex population of the diagram
which adds significant scatter to the original Mdust-SFR relation. (4) At very
high redshifts, a population of galaxies located significantly below the local
relation is predicted.


  We investigate the magnetism of the
Co$^{II}_4$(OH)$_2$(C$_1$$_0$H$_1$$_6$O$_4$)$_3$ metal-organic framework which
displays complex inorganic chains separated from each other by distances of 1
to 2 nm, and which orders at ~5.4 K. The zero-field magnetic structure is
determined using neutron powder diffraction: it is mainly antiferromagnetic but
posseses a ferromagnetic component along the $\textbf{c}$-axis. This magnetic
structure persists in presence of a magnetic field. Ac susceptibility
measurements confirm the existence of a single thermally activated regime over
7 decades in frequency ($E/k_B\approx64 K$) whereas time-dependent relaxation
of the magnetization after saturation in an external field leads to a two times
smaller energy barrier. These experiments probe the slow dynamics of domain
walls within the chains: we propose that the ac measurements are sensitive to
the motion of existing domain walls within the chains, while the magnetization
measurements are governed by the creation of domain walls.


  We explore experimentally bichromatic (frequencies $\omega_1$ and $\omega
_2$) photoresistance of a two-dimensional electron system in the regimes of
microwave-induced resistance oscillations and zero-resistance states. We find
bichromatic resistance to be well described by a superposition of $\omega_1$
and $\omega_2$ components, provided that both monochromatic resistances are
positive. This relation holds even when the oscillation amplitudes are small
and one could expect additive contributions from monochromatic
photoresistances. In contrast, whenever a zero-resistance state is formed by
one of the frequencies, such superposition relation breaks down and the
bichromatic resistance is strongly suppressed.


  Schrodinger's equation predicts something very peculiar about the electron in
the Hydrogen atom: its total energy must be equal to zero. Unfortunately, an
analysis of a zero-energy wavefunction for the electron in the Hydrogen atom
has not been attempted in the published literature. This paper provides such an
analysis for the first time and uncovers a few interesting facts, including the
fact that a "zero-energy wavefunction" is actually a quantized version of the
classical wavefunction that has been known for decades.


  We present a lattice determination of the leading-order hadronic vacuum
polarization (HVP) contribution to the muon anomalous magnetic moment,
$a_{\mu}^{\rm HVP}$, in the so-called short and intermediate time-distance
windows, $a_{\mu}^{\rm SD}$ and $a_{\mu}^{\rm W}$. We employ gauge ensembles
produced by the Extended Twisted Mass Collaboration (ETMC) with $N_f = 2 + 1 +
1$ flavours of Wilson-clover twisted-mass quarks with masses of all the
dynamical quark flavours tuned close to their physical values. The simulations
are carried out at three values of the lattice spacing equal to $\simeq 0.057,
0.068$ and $0.080$ fm with spatial lattice sizes up to $L \simeq 7.6$~fm. For
the short distance window we obtain $a_\mu^{\rm SD} = 69.27\,(34) \cdot
10^{-10}$, in agreement with the dispersive determination based on experimental
$e^+ e^-$ data. For the intermediate window we get instead $a_\mu^{\rm W} =
236.3\,(1.3) \cdot 10^{-10}$, which is consistent with recent determinations by
other lattice collaborations, but disagrees with the dispersive determination
at the level of $3.6\,\sigma$.


  We propose new methods to numerically approximate non-attracting sets
governing transiently-chaotic systems. Trajectories starting in a vicinity
$\Omega$ of these sets escape $\Omega$ in a finite time $\tau$ and the problem
is to find initial conditions ${\bf x} \in \Omega$ with increasingly large
$\tau= \tau({\bf x})$. We search points ${\bf x}'$ with $\tau({\bf
x}')>\tau({\bf x})$ in a {\it search domain} in $\Omega$. Our first method
considers a search domain with size that decreases exponentially in $\tau$,
with an exponent proportional to the largest Lyapunov exponent $\lambda_1$. Our
second method considers anisotropic search domains in the {\it tangent}
unstable manifold, where each direction scale as the inverse of the
corresponding {\it expanding} singular value of the Jacobian matrix of the
iterated map. We show that both methods outperform the state-of-the-art {\it
Stagger-and-Step} method (Sweet, Nusse, and York, Phys. Rev. Lett. {\bf 86},
2261, 2001) but that only the anisotropic method achieves an efficiency
independent of $\tau$ for the case of high-dimensional systems with multiple
positive Lyapunov exponents. We perform simulations in a chain of coupled
H\'enon maps in up to 24 dimensions ($12$ positive Lyapunov exponents). This
suggests the possibility of characterizing also non-attracting sets in
spatio-temporal systems.


  The description of chiral quantum incompressible fluids by the W-infinity
symmetry can be extended from the edge, where it encompasses the conformal
field theory approach, to the non-conformal bulk. The two regimes are
characterized by excitations with different sizes, energies and momenta within
the disk geometry. In particular, the bulk quantities have a finite limit for
large droplets. We obtain analytic results for the radial shape of excitations,
the edge reconstruction phenomenon and the energy spectrum of density
fluctuations in Laughlin states.


  Applying the sum rule approach, we investigate the energy of a soft dipole
motion in $\Lambda$ hypernuclei, which results from a dipole oscillation of a
$\Lambda$ hyperon against the core nucleus. To this end, we systematically
study single-$\Lambda$ hypernuclei, from $^{16}_{\;\,\Lambda}$O to
$^{208}_{\;\;\;\Lambda}$Pb, for which the ground state wave function is
obtained in the framework of Hartree-Fock method with several Skyrme-type
$\Lambda N$ interactions. Our results indicate that the excitation energy of
the soft dipole $\Lambda$ mode, $E_{sd\Lambda}$, decreases as the mass number
increases. We find that the excitation energy is well parametrized as
$E_{sd\Lambda}=26.6A^{-1/3}+11.2A^{-2/3}$ MeV as a function of mass number $A$.


  The non-trivial ground-state vacuum fields of QCD form the foundation of
matter. Using modern visualisation techniques, this presentation examines the
microscopic structure of these fields. Of particular interest are the centre
vortices identified within the ground-state fields of lattice QCD. Our current
focus is on understanding the manner in which dynamical fermions in the QCD
vacuum alter the centre-vortex structure. The impact of dynamical fermions is
significant and provides new insights into the role of centre vortices in
underpinning both confinement and dynamical chiral symmetry breaking in QCD.


  This paper examines the memory capacity of generalized neural networks.
Hopfield networks trained with a variety of learning techniques are
investigated for their capacity both for binary and non-binary alphabets. It is
shown that the capacity can be much increased when multilevel inputs are used.
New learning strategies are proposed to increase Hopfield network capacity, and
the scalability of these methods is also examined in respect to size of the
network. The ability to recall entire patterns from stimulation of a single
neuron is examined for the increased capacity networks.


  In-camera event denoising reduces the data rate of event cameras by filtering
out noise at the source. A lightweight multilayer perceptron denoising filter
(MLPF) provides state-of-the-art low-cost denoising accuracy. It processes a
small neighborhood of pixels from the timestamp image around each event to
discriminate signal and noise events. This paper proposes two digital logic
implementations of the MLPF denoiser and quantifies their resource cost, power,
and latency. The hardware MLPF quantizes the weights and hidden unit
activations to 4 bits and has about 1k weights with about 40% sparsity. The
Area-Under-Curve Receiver Operating Characteristic accuracy is nearly
indistinguishable from that of the floating point network. The FPGA MLPF
processes each event in 10 clock cycles. In FPGA, it uses 3.5k flip flops and
11.5k LUTs. Our ASIC implementation in 65nm digital technology for a 346x260
pixel camera occupies an area of 4.3mm^2 and consumes 4nJ of energy per event
at event rates up to 25MHz. The MLPF can be easily integrated into an event
camera using an FPGA or as an ASIC directly on the camera chip or in the same
package. This denoising could dramatically reduce the energy consumed by the
communication and host processor and open new areas of always-on event camera
application under scavenged and battery power. Code:
https://github.com/SensorsINI/dnd_hls


  The present experimental situation regarding neutrino oscillations is first
summarized, followed by an overview of selected grand unified models which have
been proposed to explain the various scenarios with three active neutrinos and
their right-handed counterparts. Special attention is given to the general
features of the models and their ability to favor some scenarios over others.


  We determined Faraday rotation measures (RMs) towards 137 pulsars in the
northern sky, using Low-Frequency Array (LOFAR) observations at 110-190 MHz.
This low-frequency RM catalogue, the largest to date, improves the precision of
existing RM measurements on average by a factor of 20 - due to the low
frequency and wide bandwidth of the data, aided by the RM synthesis method. We
report RMs towards 25 pulsars for the first time. The RMs were corrected for
ionospheric Faraday rotation to increase the accuracy of our catalogue to
approximately 0.1 rad m$^{\rm -2}$. The ionospheric RM correction is currently
the largest contributor to the measurement uncertainty. In addition, we find
that the Faraday dispersion functions towards pulsars are extremely Faraday
thin - mostly less than 0.001 rad m$^{\rm -2}$. We use these new precise RM
measurements (in combination with existing RMs, dispersion measures, and
distance estimates) to estimate the scale height of the Galactic halo magnetic
field: 2.0$\pm$0.3 kpc for Galactic quadrants I and II above and below the
Galactic plane (we also evaluate the scale height for these regions
individually). Overall, our initial low-frequency catalogue provides valuable
information about the 3-D structure of the Galactic magnetic field.


  A central goal of modern magnetic resonance imaging (MRI) is to reduce the
time required to produce high-quality images. Efforts have included hardware
and software innovations such as parallel imaging, compressed sensing, and deep
learning-based reconstruction. Here, we propose and demonstrate a Bayesian
method to build statistical libraries of magnetic resonance (MR) images in
k-space and use these libraries to identify optimal subsampling paths and
reconstruction processes. Specifically, we compute a multivariate normal
distribution based upon Gaussian processes using a publicly available library
of T1-weighted images of healthy brains. We combine this library with
physics-informed envelope functions to only retain meaningful correlations in
k-space. This covariance function is then used to select a series of
ring-shaped subsampling paths using Bayesian optimization such that they
optimally explore space while remaining practically realizable in commercial
MRI systems. Combining optimized subsampling paths found for a range of images,
we compute a generalized sampling path that, when used for novel images,
produces superlative structural similarity and error in comparison to
previously reported reconstruction processes (i.e. 96.3% structural similarity
and <0.003 normalized mean squared error from sampling only 12.5% of the
k-space data). Finally, we use this reconstruction process on pathological data
without retraining to show that reconstructed images are clinically useful for
stroke identification.


  We study the complexity of PAC learning halfspaces in the presence of Massart
noise. In this problem, we are given i.i.d. labeled examples $(\mathbf{x}, y)
\in \mathbb{R}^N \times \{ \pm 1\}$, where the distribution of $\mathbf{x}$ is
arbitrary and the label $y$ is a Massart corruption of $f(\mathbf{x})$, for an
unknown halfspace $f: \mathbb{R}^N \to \{ \pm 1\}$, with flipping probability
$\eta(\mathbf{x}) \leq \eta < 1/2$. The goal of the learner is to compute a
hypothesis with small 0-1 error. Our main result is the first computational
hardness result for this learning problem. Specifically, assuming the (widely
believed) subexponential-time hardness of the Learning with Errors (LWE)
problem, we show that no polynomial-time Massart halfspace learner can achieve
error better than $\Omega(\eta)$, even if the optimal 0-1 error is small,
namely $\mathrm{OPT} = 2^{-\log^{c} (N)}$ for any universal constant $c \in (0,
1)$. Prior work had provided qualitatively similar evidence of hardness in the
Statistical Query model. Our computational hardness result essentially resolves
the polynomial PAC learnability of Massart halfspaces, by showing that known
efficient learning algorithms for the problem are nearly best possible.


  We investigate a relationship between Ozsv\'ath and Szab\'o's bordered theory
and the algebras and bimodules constructed by Khovanov-Seidel. Specifically, we
show that (a variant of) a special case of Ozsv\'ath-Szab\'o's algebras has a
quotient which is isomorphic to the Khovanov-Seidel quiver algebra with
coefficients in $\mathbb{Z}/2\mathbb{Z}$. Furthermore, we show that after
induction and restriction of scalars, the dg bimodule over quiver algebras
associated to a crossing by Khovanov-Seidel is homotopy equivalent to
Ozsv\'ath-Szab\'o's DA bimodule for the crossing in this special case.


  We present the clustering of DEEP2 galaxies at 0.7<z<1.4 around quasars
identified using both the SDSS and DEEP2 surveys. We measure the two-point
cross-correlation of a sample of 36 optically-selected,
spectroscopically-identified quasars from the SDSS and 16 more found in the
DEEP2 survey with the full DEEP2 galaxy sample over scales 0.1 < r_p < 10
Mpc/h. The clustering amplitude is found to be similar to the auto-correlation
function of DEEP2 galaxies, with a relative bias of b=0.89 +/-0.24 between
quasars and DEEP2 galaxies at z~1. No significant dependence is found on scale,
quasar luminosity, or redshift over the ranges we probe here. The clustering
amplitude errors are comparable to those from significantly larger quasar
samples, such as the 2dF QSO Redshift Survey. This results from the statistical
power of cross-correlation techniques, which exploit the fact that galaxies are
much more numerous than quasars. We also measure the local environments of
quasars using the 3rd-nearest-neighbor surface density of surrounding DEEP2
galaxies. Quasars are found in regions of similar mean overdensity as blue
DEEP2 galaxies; they differ in environment from the red DEEP2 galaxy population
at 2 sigma significance. Our results imply that quasars do not reside in
particularly massive dark matter halos at these redshifts, with a mean dark
matter halo mass of M_200 ~ 3 10^12 solar masses in a concordance LCDM
cosmology.


  In the presence of a magnetic impurity the spin-up and down band states are
modified differently by the impurity. If the multi-electron scalar product
(MESP) between the occupied spin-up and down states approaches zero then this
defines an orthogonality catastrophe. In the present paper the MESP is
investigated for the FAIR (Friedel Artificial Iserted Resonance) solution for a
Friedel-Anderson impurity. A basis of Wilson states is used. The MESP is
numerically determined for the (enforced) magnetic, the singlet, and the
triplet states as a function of the number N of Wilson states. The magnetic and
the triplet state show an exponentially decreasing MESP as a function of N.
Surprisingly it is not the number of states which causes this decrease. It is
instead the energy separation of the highest occupied state from the Fermi
energy which determines the reduction of the MESP. In the singlet state the
ground-state requires a finite MESP to optimize its energy. As a consequence
there is no orthogonality catastrophe. The MESP approaches a saturation value
as function of N.


  In this work we present crystal structure determination of two elusive
polymorphs of furazidin, an antibacterial agent, employing a combination of
crystal structure prediction (CSP) calculations and NMR crystallography
approach. Two previously uncharacterized neat crystal forms, one of which has
two symmetry independent molecules (form I), whereas the other one has only one
molecule (form II), crystallize in P21/c and P-1 space groups, respectively,
and are both built by different conformers, displaying different intermolecular
interactions. We demonstrate that the usage of either crystal structure
prediction or NMR crystallography alone is insufficient to successfully
elucidate the mentioned crystal structures, especially in the case with two
independent molecules in the polymorph structure. In addition, cases of
serendipitous agreement in terms of 1H or 13C NMR data obtained for the crystal
structure prediction generated crystal structures different from the ones
observed in laboratory (false-positive matches) are analyzed and described.
Although for majority of analyzed crystal structures the obtained agreement
with the NMR experiment is indicative of some structural features in common
with the experimental structure, the mentioned serendipity observed in
exceptional cases points to the necessity of caution when using NMR
crystallography approach in crystal structure determination.


  There is a class of quantum Hamiltonians known as
Rokhsar-Kivelson(RK)-Hamiltonians for which static ground state properties can
be obtained by evaluating thermal expectation values for classical models. The
ground state of an RK-Hamiltonian is known explicitly, and its dynamical
properties can be obtained by performing a classical Monte Carlo simulation. We
discuss the details of a Diffusion Monte Carlo method that is a good tool for
studying statics and dynamics of perturbed RK-Hamiltonians without time
discretization errors. As a general result we point out that the relation
between the quantum dynamics and classical Monte Carlo simulations for
RK-Hamiltonians follows from the known fact that the imaginary-time evolution
operator that describes optimal importance sampling, in which the exact ground
state is used as guiding function, is Markovian. Thus quantum dynamics can be
studied by a classical Monte Carlo simulation for any Hamiltonian that is free
of the sign problem provided its ground state is known explicitly.


  We show that matter effects change the ${\rm {\nu_\mu \to \nu_\tau}}$
oscillation probability by as much as 70% for certain ranges of energies and
pathlengths. Consequently, the ${\rm {\nu_\mu \to \nu_\mu}}$ survival
probability also undergoes large changes. A proper understanding of $\nu_\mu$
survival rates must consider matter effects in $P_{\mu \tau}$ as well as
$P_{\mu e}$. We comment on a) how these matter effects may be observed and the
sign of $\Delta_{31}$ determined in atmospheric neutrino measurements and at
neutrino factories and b) how they lead to heightened sensitivity for small
$\theta_{13}$.


  In this paper, we bring together our efforts in identifying and understanding
nonequilibrium phase segregation driven by active processes in the living cell,
with special focus on the segregation of cell membrane components driven by
active contractile stresses arising from cortical actomyosin. This also has
implications for active segregation dynamics in membraneless regions within the
cytoplasm and nucleus (3d). We formulate an active version of the Flory-Huggins
theory that incorporates a contribution from fluctuating active stresses. Apart
from knitting together some of our past theoretical work in a comprehensive
narrative, we highlight some new results, and establish a correspondence with
recent studies on Active Model B/B+. We point to the many unusual aspects of
the dynamics of active phase segregation, such as (i) anomalous growth
dynamics, (ii) coarsening accompanied by propulsion and coalescence of domains
that exhibit nonreciprocal effects, (iii) segregation into mesoscale domains,
(iv) emergence of a nonequilibrium phase segregated steady state characterised
by strong macroscopic fluctuations (fluctuation dominated phase ordering
(FDPO)), and (v) mesoscale segregation even above the equilibrium Tc. Apart
from its implications for actively driven segregation of binary fluids, these
ideas are at the heart of an Active Emulsion description of the lateral
organisation of molecules on the plasma membrane of living cells, whose full
molecular elaboration appears elsewhere.


  We consider, in a string theory framework, physical processes of
phenomenological interest in models with a low string scale. The amplitudes we
study involve tree-level virtual gravitational exchange, divergent in a
field-theoretical treatment, and massive gravitons emission, which are the main
signatures of this class of models. First, we discuss the regularization of
summations appearing in virtual gravitational (closed string) Kaluza-Klein
exchanges in Type I strings. We argue that a convenient manifestly ultraviolet
convergent low energy limit of type I string theory is given by an effective
field theory with an arbitrary cutoff $\Lambda$ in the closed (gravitational)
channel and a related cutoff $M_s^2/\Lambda$ in the open (Yang-Mills) channel.
We find the leading string corrections to the field theory results. Second, we
calculate exactly string tree-level three and four-point amplitudes with gauge
bosons and one massive graviton and examine string deviations from the
field-theory result.


  Feature selection aims to select a subset of features to optimize the
performances of downstream predictive tasks. Recently, multi-agent reinforced
feature selection (MARFS) has been introduced to automate feature selection, by
creating agents for each feature to select or deselect corresponding features.
Although MARFS enjoys the automation of the selection process, MARFS suffers
from not just the data complexity in terms of contents and dimensionality, but
also the exponentially-increasing computational costs with regard to the number
of agents. The raised concern leads to a new research question: Can we simplify
the selection process of agents under reinforcement learning context so as to
improve the efficiency and costs of feature selection? To address the question,
we develop a single-agent reinforced feature selection approach integrated with
restructured choice strategy. Specifically, the restructured choice strategy
includes: 1) we exploit only one single agent to handle the selection task of
multiple features, instead of using multiple agents. 2) we develop a scanning
method to empower the single agent to make multiple selection/deselection
decisions in each round of scanning. 3) we exploit the relevance to predictive
labels of features to prioritize the scanning orders of the agent for multiple
features. 4) we propose a convolutional auto-encoder algorithm, integrated with
the encoded index information of features, to improve state representation. 5)
we design a reward scheme that take into account both prediction accuracy and
feature redundancy to facilitate the exploration process. Finally, we present
extensive experimental results to demonstrate the efficiency and effectiveness
of the proposed method.


  We report a newly found two-stage mechanism of electron acceleration near
X-lines of 3D collisionless guide-field magnetic reconnection in the
non-relativistic regime typical, e.g., for stellar coronae. We found that after
electrons are first pre-accelerated during the linear growth of reconnection,
they become additionally accelerated in the course of the nonlinear stage of 3D
guide-field magnetic reconnection. This additional acceleration is due to the
filamentation of electric and magnetic fields caused by streaming
instabilities. In addition to enhanced parallel electric fields, the
filamentation leads to additional curvature-driven electron acceleration in the
guide-field direction. As a result, part of the the accelerated electron
spectra becomes a power law with a spectral index of $\sim-1.6$ near the
X-line. This second stage of acceleration due to nonlinear reconnection is
relevant for the production of energetic electrons in, e.g., thin current
sheets of stellar coronae.


  Meta-learning has been widely used for implementing few-shot learning and
fast model adaptation. One kind of meta-learning methods attempt to learn how
to control the gradient descent process in order to make the gradient-based
learning have high speed and generalization. This work proposes a method that
controls the gradient descent process of the model parameters of a neural
network by limiting the model parameters in a low-dimensional latent space. The
main challenge of this idea is that a decoder with too many parameters is
required. This work designs a decoder with typical structure and shares a part
of weights in the decoder to reduce the number of the required parameters.
Besides, this work has introduced ensemble learning to work with the proposed
approach for improving performance. The results show that the proposed approach
is witnessed by the superior performance over the Omniglot classification and
the miniImageNet classification tasks.


  We present a simple construction for a tridiagonal matrix $T$ that commutes
with the hopping matrix for the entanglement Hamiltonian ${\cal H}$ of open
finite free-Fermion chains associated with families of discrete orthogonal
polynomials. It is based on the notion of algebraic Heun operator attached to
bispectral problems, and the parallel between entanglement studies and the
theory of time and band limiting. As examples, we consider Fermionic chains
related to the Chebychev, Krawtchouk and dual Hahn polynomials. For the former
case, which corresponds to a homogeneous chain, the outcome of our construction
coincides with a recent result of Eisler and Peschel; the latter cases yield
commuting operators for particular inhomogeneous chains. Since $T$ is
tridiagonal and non-degenerate, it can be readily diagonalized numerically,
which in turn can be used to calculate the spectrum of ${\cal H}$, and
therefore the entanglement entropy.


  This paper studies morphological properties of 103 green valley FIR active
and 2609 non-active galaxies presented in Mahoro et al. 2017. The photometric
data from the COSMOS survey were used, and the morphological parameters, such
as Abraham and Conselice-Bershady concentration indices, Gini, M20 moment of
light, and asymmetry, were analysed taking into account public catalogues.
Furthermore, a visual classification of galaxies was performed. We found that
the fraction of peculiar galaxies with clear signs of interactions and mergers
is significantly higher in AGN (38%) than non-AGN (19%) green valley galaxies,
while non-AGN galaxies from our sample are predominantly spirals (46%). We
found that the largest fraction of our green valley galaxies is located on the
main-sequence (MS) of star formation, independently on morphology, which is in
contrast with most of previous studies carried out in optical. We also found
that FIR AGN green valley galaxies have significantly higher star formation
rates in all analysed morphological types. Therefore, our results suggest that
interactions and mergers obtained in the high fraction of FIR AGN contribute
significantly to high star formation rates observed in the selected sample, but
are not the only mechanism responsible for enhancing star formation, and others
such as AGN positive feedback could contribute as well. In future we will study
in more details the possibility of AGN positive feedback through the
spectroscopic analysis of public and our SALT data.


  We study superconductivity in isolated superconducting nano-cubes and
nano-squares of size $L$ in the limit of negligible disorder, $\delta/\Delta_0
\ll 1$ and $k_F L \gg 1$ for which mean-field theory and semiclassical
techniques are applicable, with $k_F$ the Fermi wave vector, $\delta$ the mean
level spacing and $\Delta_0$ the bulk gap. By using periodic orbit theory and
number theory we find explicit analytical expressions for the size dependence
of the superconducting order parameter. Our formalism takes into account
contributions from both the spectral density and the interaction matrix
elements in a basis of one-body eigenstates. The leading size dependence of the
energy gap in three dimensions seems to be universal as it agrees with the
result for chaotic grains. In the region of parameters corresponding to
conventional metallic superconductors, and for sizes $L \gtrsim 10$nm, the
contribution to the superconducting gap from the matrix elements is substantial
($\sim 20\%$). Deviations from the bulk limit are still clearly observed even
for comparatively large grains $L \sim 50$nm. These analytical results are in
excellent agreement with the numerical solution of the mean-field gap equation.


  We have defined a new type of clustering scheme preserving the connectivity
of the nodes in network ignored by the conventional Migdal-Kadanoff bond moving
process. Our new clustering scheme performs much better for correlation length
and dynamical critical exponents in high dimensions, where the conventional
Migdal-Kadanoff bond moving scheme breaks down. In two and three dimensions we
find the dynamical critical exponents for the kinetic Ising Model to be z=2.13
and z=2.09, respectively at pure Ising fixed point. These values are in very
good agreement with recent Monte Carlo results. We investigate the phase
diagram and the critical behaviour for randomly bond diluted lattices in d=2
and 3, in the light of this new transformation. We also provide exact
correlation exponent and dynamical critical exponent values on hierarchical
lattices with power-law degree distributions, both in the pure and random
cases.


  SN 1006 (G327.6+14.6) was the brightest supernova (SN) witnessed in human
history. As of one thousand years later, it stands out as an ideal laboratory
to study Type Ia SNe and shocks in supernova remnants (SNRs). The present state
of knowledge about SN 1006 is reviewed in this article. No star consistent with
a surviving companion expected in the traditional single-degenerate scenario
has been found, which favors a double-degenerate scenario for the progenitor of
SN 1006. Both unshocked and shocked SN ejecta have been probed through
absorption lines in ultraviolet spectra of background sources and thermal X-ray
emission, respectively. The absorption studies suggest that the amount of iron
is < 0.16 M_sun, which is significantly less than the range for normal SNe Ia.
On the other hand, analyses of X-ray data reveal the distribution of shocked
ejecta to be highly asymmetric especially for iron. Therefore, most of iron
might have escaped from the ultraviolet background sources. Another important
aspect with SN 1006 is that it was the first SNR in which synchrotron X-ray
emission was detected from shells of the remnant, providing evidence that
electrons are accelerated up to ~100 TeV energies at forward shocks. The
bilateral symmetry of the synchrotron emission (bright in northeastern and
southwestern limbs) is likely due to a polar cap geometry. The broadband
(radio, X-ray, and gamma-ray) spectral energy distribution suggests that the
gamma-ray emission is predominantly leptonic. At the northwestern shock,
evidence for extreme, but less than mass proportional, temperature
non-equilibration has been found by optical, ultraviolet, and X-ray
observations.


  In this paper we analyse non-supersymmetric single centred extremal black
hole solutions in N=2 supergravity theory coupled to $n$ vector multiplets with
purely cubic pre-potential in four dimensions. We consider the algebraic
attractor equations in their most general form at the black hole horizon. We
explicitly construct a new class of solutions for these attractor equations.
These solutions are characterised by a set of involutory matrices. These
involutions are obtained from a constraint involving the parameters in the
pre-potential and generate new attractor points in the moduli space.


  This paper describes the cutting sequences of geodesic flow on the modular
surface H/PSL(2,Z) with respect to the standard fundamental domain F = {z=x+iy:
-1/2 <= x <= 1/2 and |z|>=1} of PSL(2,Z). The cutting sequence for a vertical
geodesic {\theta+it: t > 0} is related to a one-dimensional continued fraction
expansion for \theta, called the one-dimensional Minkowski geodesic continued
fraction (MGCF) expansion, which is associated to a parametrized family of
reduced bases of a family of 2-dimensional lattices. The set of cutting
sequences for all geodesics forms a two-sided shift in a symbol space {L,R,J}
which has the same set of forbidden blocks as for vertical geodesics. We show
that this shift is not a sofic shift, and that it characterizes the fundamental
domain F up to an isometry of the hyperbolic plane H. We give conversion
methods between the cutting sequence for the vertical geodesic {\theta+it: t >
0}, the MGCF expansion of \theta and the additive ordinary continued fraction
(ACF) expansion of \theta. We show that the cutting sequence and MGCF
expansions can each be computed from the other by a finite automaton, and the
ACF expansion of \theta can be computed from the cutting sequence for the
vertical geodesic \theta+it by a finite automaton. However, the cutting
sequence for a vertical geodesic cannot be computed from the ACF expansion by
any finite automaton, but there is an algorithm to compute its first l symbols
when given as input the first O(l) symbols of the ACF expansion, which takes
time O(l^2) and space O(l).


  Under specific experimental circumstances, sputter erosion on semiconductor
materials exhibits highly ordered hexagonal dot-like nanostructures. In a
recent attempt to theoretically understand this pattern forming process, Facsko
et al. [Phys. Rev. B 69, 153412 (2004)] suggested a nonlocal, damped
Kuramoto-Sivashinsky equation as a potential candidate for an adequate
continuum model of this self-organizing process. In this study we theoretically
investigate this proposal by (i) formally deriving such a nonlocal equation as
minimal model from balance considerations, (ii) showing that it can be exactly
mapped to a local, damped Kuramoto-Sivashinsky equation, and (iii) inspecting
the consequences of the resulting non-stationary erosion dynamics.


  The reduced transition probability B(E2;0 ->2+) for 28S was obtained
experimentally using Coulomb excitation at 53 MeV/nucleon. The resultant B(E2)
value 181(31) e2fm4 is smaller than the expectation based on empirical B(E2)
systematics. The double ratio |M_n/M_p|/(N/Z) of the 0+ ->2+ transition in 28S
was determined to be 1.9(2) by evaluating the M_n value from the known B(E2)
value of the mirror nucleus 28Mg, showing the hindrance of proton collectivity
relative to that of neutrons. These results indicate the emergence of the magic
number Z=16 in the |T_z|=2 nucleus 28S.


  We use simulated strongly lensed gravitational wave events from the Einstein
Telescope to demonstrate how the luminosity and angular diameter distances,
$d_L(z)$ and $d_A(z)$ respectively, can be combined to test in a model
independent manner for deviations from the cosmic distance duality relation and
the standard cosmological model. In particular, we use two machine learning
approaches, the Genetic Algorithms and Gaussian Processes, to reconstruct the
mock data and we show that both approaches are capable of correctly recovering
the underlying fiducial model and can provide percent-level constraints at
intermediate redshifts when applied to future Einstein Telescope data.


  We consider a multiobjective multiarmed bandit problem with lexicographically
ordered objectives. In this problem, the goal of the learner is to select arms
that are lexicographic optimal as much as possible without knowing the arm
reward distributions beforehand. We capture this goal by defining a
multidimensional form of regret that measures the loss of the learner due to
not selecting lexicographic optimal arms, and then, consider two settings where
the learner has prior information on the expected arm rewards. In the first
setting, the learner only knows for each objective the lexicographic optimal
expected reward. In the second setting, it only knows for each objective
near-lexicographic optimal expected rewards. For both settings we prove that
the learner achieves expected regret uniformly bounded in time. The algorithm
we propose for the second setting also attains bounded regret for the
multiarmed bandit with satisficing objectives. In addition, we also consider
the harder prior-free case, and show that the learner can still achieve
sublinear in time gap-free regret. Finally, we experimentally evaluate
performance of the proposed algorithms in a variety of multiobjective learning
problems.


  We analysed collisionless N-body simulations of intermediate and minor dry
mergers onto S0s to test whether these mergers can generate S0 galaxies with
kinematics intermediate between fast and slow rotators. We find that minor
mergers induce a lower decrease of the global rotational support than
encounters of lower mass ratios, which results in S0s with properties
intermediate between fast and slow rotators. The resulting remnants are
intrinsically more triaxial, less flattened, and span the whole range of
apparent ellipticities up to $\epsilon_\mathrm{e} \sim 0.8$. They do not show
lower apparent ellipticities in random projections than initially; on the
contrary, the formation of oval distortions and the disc thickening increase
the percentage of projections at $0.4 < \epsilon_\mathrm{e} < 0.7$. In the
experiments with S0b progenitor galaxies, minor mergers tend to spin up the
bulge and to decrease slightly its intrinsic ellipticity, whereas in the cases
of primary S0c galaxies they keep the rotational support of the bulge nearly
constant and decrease significantly its intrinsic ellipticity. The remnant
bulges remain nearly spherical ($B/A \sim C/A > 0.9$), but exhibit a wide range
of triaxialities ($0.20 < T < 1.00$). In the plane of global anisotropy of
velocities ($\delta$) vs. intrinsic ellipticity ($\epsilon_\mathrm{e,intr}$),
some of our models extend the linear trend found in previous major merger
simulations towards higher $\epsilon_\mathrm{e,intr}$ values, while others
depart from it. This is consistent with the wide dispersion exhibited by real
S0s in this diagram compared with ellipticals, which follow the linear trend
drawn by major merger simulations. The different trends exhibited by
ellipticals and S0 galaxies in the $\delta$ - $\epsilon_\mathrm{e}$ diagram may
be pointing to the different role played by major mergers in the build-up of
each morphological type.


  Maximum likelihood degree of a projective variety is the number of critical
points of a general likelihood function. In this note, we compute the Maximum
likelihood degree of Fermat hypersurfaces. We give a formula of the Maximum
likelihood degree in terms of the constants $\beta_{\mu, \nu}$, which is
defined to be the number of complex solutions to the system of equations
$z_1^\nu=z_2^\nu=\cdots=z_\mu^\nu=1$ and $z_1+\cdots +z_\mu+1=0$.


  Worst-case optimal join algorithms have gained a lot of attention in the
database literature. We now count with several algorithms that are optimal in
the worst case, and many of them have been implemented and validated in
practice. However, the implementation of these algorithms often requires an
enhanced indexing structure: to achieve optimality we either need to build
completely new indexes, or we must populate the database with several
instantiations of indexes such as B$+$-trees. Either way, this means spending
an extra amount of storage space that may be non-negligible.
  We show that optimal algorithms can be obtained directly from a
representation that regards the relations as point sets in variable-dimensional
grids, without the need of extra storage. Our representation is a compact quad
tree for the static indexes, and a dynamic quadtree sharing subtrees (which we
dub a qdag) for intermediate results. We develop a compositional algorithm to
process full join queries under this representation, and show that the running
time of this algorithm is worst-case optimal in data complexity. Remarkably, we
can extend our framework to evaluate more expressive queries from relational
algebra by introducing a lazy version of qdags (lqdags). Once again, we can
show that the running time of our algorithms is worst-case optimal.


  In this paper we study optimal advertising problems that models the
introduction of a new product into the market in the presence of carryover
effects of the advertisement and with memory effects in the level of goodwill.
In particular, we let the dynamics of the product goodwill to depend on the
past, and also on past advertising efforts. We treat the problem by means of
the stochastic Pontryagin maximum principle, that here is considered for a
class of problems where in the state equation either the state or the control
depend on the past. Moreover the control acts on the martingale term and the
space of controls can be chosen to be non-convex. The maximum principle is thus
formulated using a first-order adjoint Backward Stochastic Differential
Equations (BSDEs), which can be explicitly computed due to the specific
characteristics of the model, and a second-order adjoint relation.


  A hyperbolic group acts by homeomorphisms on its Gromov boundary. We use a
dynamical coding of boundary points to show that such actions are topologically
stable in the dynamical sense: any nearby action is semi-conjugate to (and an
extension of) the standard boundary action.
  This result was previously known in the special case that the boundary is a
topological sphere. Our proof here is independent and gives additional
information about the semiconjugacy in that case. Our techniques also give a
new proof of global stability when the boundary is a circle.


  In recent experiments bosonic [Atala et al., Nat. Phys. 10, 588 (2014), B. K.
Stuhl et al., Science 349, 1514 (2015)] as well as fermionic ladders [M.
Mancini et al., Science 349, 1510 (2015)] with a uniform flux were studied and
different interesting many-body states were observed. Motivated by these
experiments, we extend the uniform synthetic magnetic field to a periodic case
and show that a commensurate synthetic magnetic field offers an alternative
scheme to realize topological phases in many-body systems of ultra-cold Fermi
gases in ladder-like optical lattices. Using the exact diagonalization, we
numerically determine the topological band structure, edge states, non-zero
Chern numbers, Hofstadter-like-butterfly spectrum, and a complete phase diagram
of non-interacting fermionic ladders.


  This paper together with the previous one (arXiv:hep-th/0604146) presents the
detailed description of all quantum deformations of D=4 Lorentz algebra as Hopf
algebra in terms of complex and real generators. We describe here in detail two
quantum deformations of the D=4 Lorentz algebra o(3,1) obtained by twisting of
the standard q-deformation U_{q}(o(3,1)). For the first twisted q-deformation
an Abelian twist depending on Cartan generators of o(3,1) is used. The second
example of twisting provides a quantum deformation of Cremmer-Gervais type for
the Lorentz algebra. For completeness we describe also twisting of the Lorentz
algebra by standard Jordanian twist. By twist quantization techniques we obtain
for these deformations new explicit formulae for the deformed coproducts and
antipodes of the o(3,1)-generators.


  Estimating parameters of quantum systems is usually done by performing a
sequence of predetermined experiments and post-processing the resulting data.
It is known that online design, where the choice of the next experiment is
based on the most up-to-date knowledge about the system, can offer speedups to
parameter estimation. We apply online Bayesian experiment design to a Nitrogen
Vacancy (NV) in diamond to learn the values of a five-parameter model
describing its Hamiltonian and decoherence process. Comparing this to standard
pre-determined experiment sweeps, we find that we can achieve median posterior
variances on some parameters that are between 10 and 100 times better given the
same amount of data. This has applications to NV magnetometry where one of the
Hamiltonian coefficients is the parameter of interest. Furthermore, the methods
that we use are generic and can be adapted to any quantum device.


  We investigate the thermodynamical and causal consistency of cosmological
models of the cubic Quasi-Topological Gravity (QTG) in four dimensions, as well
as their phenomenological consequences. Specific restrictions on the maximal
values of the matter densities are derived by requiring the apparent horizon's
entropy to be a non-negative, non-decreasing function of time. The QTG
counterpart of the Einstein-Hilbert (EH) gravity model of linear equation of
state is studied in detail. An important feature of this particular QTG
cosmological model is the new early-time acceleration period of the evolution
of the Universe, together with the standard late-time acceleration present in
the original EH model. The QTG correction to the causal diamond's volume is
also calculated.


  Error correction is of utmost necessity for large-scale quantum computing.
Quantum error correcting codes can be degenerate, if more than one type of
error can map the input state to the same error state. In this paper, we
propose a 6-qubit degenerate CSS code. We show that our proposed code can
correct a single bit flip error, but arbitrarily many phase flip errors
occurring on the codeword. Furthermore, it follows from a bound on CSS codes
that the proposed code is the minimal binary CSS code which can encode a single
qubit of information. We also perform a comparative study of the gate count
required for a fault tolerant decomposition of the error correction circuit for
the proposed code, with that for the existing 9-qubit, 7-qubit and 5-qubit
binary QEC codes. Our results show, on an average over the different
technologies a savings of 98.14% in the gate count for the proposed code over
that for the 5-qubit code. Significant improvement of around 50% in gate count
is also obtained when compared to those for the 9-qubit and 7-qubit codes.


  We study the Semi-Inclusive Deep Inelastic Scattering (SIDIS) cross section
as a function of the transverse momentum, $q_T$. In order to describe it over a
wide region of $q_T$, soft gluon resummation has to be performed. Here we will
use the original Collins-Soper-Sterman (CSS) formalism; however, the same
procedure would hold within the improved Transverse Momentum Dependent (TMD)
framework. We study the matching between the region where fixed order
perturbative QCD can successfully be applied and the region where soft gluon
resummation is necessary. We find that the commonly used prescription of
matching through the so-called Y-factor cannot be applied in the SIDIS
kinematical configurations we examine. In particular, the non-perturbative
component of the resummed cross section turns out to play a crucial role and
should not be overlooked even at relatively high energies. Moreover, the
perturbative expansion of the resummed cross section in the matching region is
not as reliable as it is usually believed and its treatment requires special
attention.


  Both Cabibbo allowed and doubly forbidden transitions contribute coherently
to $D\rightarrow K_{S,L}+\pi 's$ decays. This leads to several intriguing and
even quantitatively significant consequences, among them: (i) A difference
between $\Gamma (D^+\rightarrow K_S \pi ^+)$ and $\Gamma (D^+\rightarrow K_L
\pi ^+)$ and between $\Gamma (D^0\rightarrow K_S \pi ^0)$ and $\Gamma
(D^0\rightarrow K_L \pi ^0)$ of roughly 10\% ; similarly $\Gamma
(D^+\rightarrow [K_S\pi ^0]_{K^*} \pi ^+) \neq \frac{1}{4}\Gamma
(D^+\rightarrow [K^-\pi ^+]_{K^*} \pi ^+)$, and more generally $\Gamma
(D\rightarrow \bar K^0+\pi 's) \neq 2\Gamma (D\rightarrow K_S+\pi 's)$. (ii) A
change in the relative phase between the isospin 3/2 and 1/2 amplitudes as
extracted from the observed branching ratios for $D^+\rightarrow K_S\pi ^+$,
$D^0\rightarrow K_S\pi ^0 ,\, K^-\pi ^+$. (iii) If New Physics intervenes to
provide the required {\em weak} phase, then CP asymmetries of up to a few per
cent can arise in $D^+\rightarrow K_S\pi ^+$ vs. $D^-\rightarrow K_S\pi ^-$,
$D^0\rightarrow K_S\pi ^0$ vs. $\bar D^0\rightarrow K_S\pi ^0$, $D^+\rightarrow
[K_S\pi ^0]_{K^*}\pi ^+$ vs. $D^-\rightarrow [K_S\pi ^0]_{K^*}\pi ^-$, etc.; an
asymmetry of the same size, but opposite in sign occurs when the $K_S$ is
replaced by a $K_L$ in the final state.


  A large class of supergravities in diverse dimensions are surveyed. This
includes maximal supergravities, their general gaugings in the framework of
embedding tensor formalism, supergravities with less than maximal
supersymmetry, their matter couplings and general gaugings. The emphasis is on
summarizing their most general form to date, and primarily in their component
formulation. A class of exceptional field theories in an extended geometric
framework are summarized briefly. For most of the supergravities surveyed, the
bosonic part of the Lagrangians and supertransformations up to leading terms in
fermions are given.


  Swirl-switching is a low-frequency oscillatory phenomenon which affects the
Dean vortices in bent pipes and may cause fatigue in piping systems. Despite
thirty years worth of research, the mechanism that causes these oscillations
and the frequencies that characterise them remain unclear. Here we show that a
three-dimensional wave-like structure is responsible for the low-frequency
switching of the dominant Dean vortex. The present study, performed via direct
numerical simulation, focuses on the turbulent flow through a 90 \degree pipe
bend preceded and followed by straight pipe segments. A pipe with curvature 0.3
(defined as ratio between pipe radius and bend radius) is studied for a bulk
Reynolds number Re = 11 700, corresponding to a friction Reynolds number
Re_\tau \approx 360. Synthetic turbulence is generated at the inflow section
and used instead of the classical recycling method in order to avoid the
interference between recycling and swirl-switching frequencies. The flow field
is analysed by three-dimensional proper orthogonal decomposition (POD) which
for the first time allows the identification of the source of swirl-switching:
a wave-like structure that originates in the pipe bend. Contrary to some
previous studies, the flow in the upstream pipe does not show any direct
influence on the swirl-switching modes. Our analysis further shows that a
three- dimensional characterisation of the modes is crucial to understand the
mechanism, and that reconstructions based on 2D POD modes are incomplete.


  Ensuring flexible and efficient manufacturing of customized products in an
increasing dynamic and turbulent environment without sacrificing cost
effectiveness, product quality and on-time delivery has become a key issue for
most industrial enterprises. A promising approach to cope with this challenge
is the integration of cognitive capabilities in systems and processes with the
aim of expanding the knowledge base used to perform managerial and operational
tasks. In this work, a novel approach to real-time rescheduling is proposed in
order to achieve sustainable improvements in flexibility and adaptability of
production systems through the integration of artificial cognitive
capabilities, involving perception, reasoning/learning and planning skills.
Moreover, an industrial example is discussed where the SOAR cognitive
architecture capabilities are integrated in a software prototype, showing that
the approach enables the rescheduling system to respond to events in an
autonomic way, and to acquire experience through intensive simulation while
performing repair tasks.


  (ABRIDGED) We present a model in which the seeds of supermassive black holes
form from the lowest angular momentum gas in proto-galaxies at high redshift.
We show that this leads to a correlation between black hole masses and spheroid
properties, as observed today. We assume that gas in early-forming, rare halos
has a distribution of specific angular momentum similar to that expected for
dark matter halos. This distribution has a significant low angular momentum
tail which implies that every proto-galaxy should contain gas that ends up in a
high-density disc. In halos more massive than a critical threshold of
\~10^8Msun, the discs are gravitationally unstable, and experience an efficient
Lin-Pringle viscosity that allows mass inflow. This process continues until the
first massive stars disrupt the disc. Black holes are created with a
characteristic mass of ~10^5 Msun, independent of the redshift of formation.
This serves as a lower bound for black-hole masses in galaxies today. The
comoving mass density of black hole seeds grows with time, and saturates when
cosmic reionization stops gas cooling in these low-mass systems. By z~15, the
comoving mass density becomes comparable to that inferred from observations,
with room for appropriate additional luminous growth during a later quasar
accretion phase. Hierarchical merging after z~15 naturally leads to a linear
correlation between black-hole mass and stellar spheroid mass, with negligible
black hole masses in disc-dominated galaxies.


  In this paper, with two-dimensional (2-D) hybrid simulations, we study the
generation mechanism of filamentary structures downstream of a quasi-parallel
shock. The results show that in the downstream both the amplitude of magnetic
field and number density exhibit obvious filamentary structures, and the
magnetic field and number density are anticorrelated. Detailed analysis find
that these downstream compressive waves propagate almost perpendicular to the
magnetic field, and the dominant wave number is around the inverse of ion
kinetic scale. Their parallel and perpendicular components roughly
satisfies(where and represent the parallel and in-plane perpendicular
components of magnetic field, is the wave number in the perpendicular
direction, and in the ion gyroradius), and their Alfven ratio also roughly
agree with the analytical relation (where and indicate the Alfven ratio and
plasma beta), while the corresponding cross helicity and compressibility show
good agreement with previous theoretical calculations. All these properties are
consistent with those of kinetic slow waves (KSWs). Therefore, we conclude that
the filamentary structures in the downstream of a quasi-parallel shock are
produced due to the excitation of KSWs.


  NiBi3 polycrystals were synthesized via a solid state method. X-ray
diffraction analysis shows that the main phase present in the sample
corresponds to NiBi3 in a weight fraction of 96.82 % according to the
refinement of the crystalline structure. SEM - EDS and XPS analysis reveal a
homogeneous composition of NiBi3, without Ni traces. The powder superconducting
samples were studied by performing magnetic measurements. The superconducting
transition temperature and critical magnetic fields were determinated as Tc =
4.05 K, Hc1 = 110 Oe and Hc2 = 3,620 Oe. The superconducting parameters were GL
coherence length= 301.5 A, Ginzburg Landau Penetration depth= 1549 A, and k =
5.136. Isothermal measurements below the transition temperature show an
anomalous behavior. Above the superconducting transition the compound presents
ferromagnetic characteristics up to 750 K, well above the Ni Curie temperature.
PACS numbers: Intermetallic Alloys; Superconductivity; Ferromagnetism;


  Leptonic \textit{CP} violation search, neutrino mass hierarchy determination,
and the precision measurement of oscillation parameters for a unitary test of
the leptonic mixing matrix are among the major targets of the ongoing and
future neutrino oscillation experiments. The work explores the physics reach
for these targets by around 2027, when the third generation of the neutrino
experiments starts operation, with a combined sensitivity of three experiments:
T2K-II, NO$\nu$A extension, and JUNO. It is shown that a joint analysis of
these three experiments can conclusively determine the neutrino mass hierarchy.
Also, at certain values of \emph{true} \dcp, it provides closely around a
$5\sigma$ confidence level (C.L.) to exclude \textit{CP}-conserving values and
more than a $50\%$ fractional region of \emph{true} $\delta_{\text{CP}}$ values
can be explored with a statistic significance of at least a $3\sigma$ C.L.
Besides, the joint analysis can provide unprecedented precision measurements of
the atmospheric neutrino oscillation parameters and a great offer to solve the
$\theta_{23}$ octant degeneracy in the case of nonmaximal mixing.


  Spiking Neural Networks (SNNs) are at the forefront of neuromorphic computing
thanks to their potential energy-efficiency, low latencies, and capacity for
continual learning. While these capabilities are well suited for robotics
tasks, SNNs have seen limited adaptation in this field thus far. This work
introduces a SNN for Visual Place Recognition (VPR) that is both trainable
within minutes and queryable in milliseconds, making it well suited for
deployment on compute-constrained robotic systems. Our proposed system,
VPRTempo, overcomes slow training and inference times using an abstracted SNN
that trades biological realism for efficiency. VPRTempo employs a temporal code
that determines the timing of a single spike based on a pixel's intensity, as
opposed to prior SNNs relying on rate coding that determined the number of
spikes; improving spike efficiency by over 100%. VPRTempo is trained using
Spike-Timing Dependent Plasticity and a supervised delta learning rule
enforcing that each output spiking neuron responds to just a single place. We
evaluate our system on the Nordland and Oxford RobotCar benchmark localization
datasets, which include up to 27k places. We found that VPRTempo's accuracy is
comparable to prior SNNs and the popular NetVLAD place recognition algorithm,
while being several orders of magnitude faster and suitable for real-time
deployment -- with inference speeds over 50 Hz on CPU. VPRTempo could be
integrated as a loop closure component for online SLAM on resource-constrained
systems such as space and underwater robots.


  Full-duplex (FD) technology is gaining popularity for integration into a wide
range of wireless networks due to its demonstrated potential in recent studies.
In contrast to half-duplex (HD) technology, the implementation of FD in
networks necessitates considering inter-node interference (INI) from various
network perspectives. When deploying FD technology in networks, several
critical factors must be taken into account. These include self-interference
(SI) and the requisite SI cancellation (SIC) processes, as well as the
selection of multiple user equipment (UE) per time slot. Additionally,
inter-node interference (INI), including cross-link interference (CLI) and
inter-cell interference (ICI), become crucial issues during concurrent uplink
(UL) and downlink (DL) transmission and reception, similar to SI. Since most
INI is challenging to eliminate, a comprehensive investigation that covers
radio resource control (RRC), medium access control (MAC), and the physical
layer (PHY) is essential in the context of FD network design, rather than
focusing on individual network layers and types. This paper covers
state-of-the-art studies, including protocols and documents from 3GPP for FD,
MAC protocol, user scheduling, and CLI handling. The methods are also compared
through a network-level system simulation based on 3D ray-tracing.


  In this article, we explore the transformative potential of integrating
generative AI, particularly Large Language Models (LLMs), into behavioral and
experimental economics to enhance internal validity. By leveraging AI tools,
researchers can improve adherence to key exclusion restrictions and in
particular ensure the internal validity measures of mental models, which often
require human intervention in the incentive mechanism. We present a case study
demonstrating how LLMs can enhance experimental design, participant engagement,
and the validity of measuring mental models.


  Brain can recognize different objects as ones that it has experienced before.
The recognition accuracy and its processing time depend on task properties such
as viewing condition, level of noise and etc. Recognition accuracy can be well
explained by different models. However, less attention has been paid to the
processing time and the ones that do, are not biologically plausible. By
extracting features temporally as well as utilizing an accumulation to bound
decision making model, an object recognition model accounting for both
recognition time and accuracy is proposed. To temporally extract informative
features in support of possible classes of stimuli, a hierarchical spiking
neural network, called spiking HMAX is modified. In the decision making part of
the model the extracted information accumulates over time using accumulator
units. The input category is determined as soon as any of the accumulators
reaches a threshold, called decision bound. Results show that not only does the
model follow human accuracy in a psychophysics task better than the classic
spiking HMAX model, but also it predicts human response time in each choice.
Results provide enough evidence that temporal representation of features are
informative since they can improve the accuracy of a biological plausible
decision maker over time. This is also in line with the well-known idea of
speed accuracy trade-off in decision making studies.


  Karolyhazy uncertainty relation, which can be viewed also as a relation
between UV and IR scales in the framework of an effective quantum field theory
satisfying a black hole entropy bound, strongly favors the existence of dark
energy with its observed value. Here we estimate the dynamics of dark energy
predicted by the Karolyhazy relation during the cosmological evolution of the
universe.


  Motivated by epidemics such as COVID-19, we study the spread of a contagious
disease when behavior responds to the disease's prevalence. We extend the SIR
epidemiological model to include endogenous meeting rates. Individuals benefit
from economic activity, but activity involves interactions with potentially
infected individuals. The main focus is a theoretical analysis of contagion
dynamics and behavioral responses to changes in risk. We obtain a simple
condition for when public-health interventions or variants of a disease will
have paradoxical effects on infection rates due to risk compensation.
Behavioral responses are most likely to undermine public-health interventions
near the peak of severe diseases.


  The key role of the orbital degree of freedom to understand the magnetic
properties of layered ruthenates is here discussed. In the G-type
antiferromagnetic phase of Ca$_2$RuO$_4$, recent X-ray experiments reported the
presence of 0.5 hole per site in the $d_{xy}$ orbital, while the $d_{\rm yz}$
and $d_{zx}$ orbitals contain 1.5 holes. This unexpected $t_{2g}$ hole
distribution is explained by a novel state with orbital ordering (OO),
stabilized by a combination of Coulomb interactions and lattice distortions. In
addition, the rich phase diagram presented here suggests the possibility of
large magnetoresistance effects, and predicts a new ferromagnetic OO phase in
ruthenates.


  GLISSANDO is a Glauber Monte-Carlo generator for early-stages of relativistic
heavy-ion collisions, written in c++ and interfaced to Root. Several models are
implemented: the wounded-nucleon model, the binary collisions model, the mixed
model, and the model with hot-spots. Subtleties of the distribution of nucleon
in the nucleus are discussed. The original geometric distribution of sources in
the transverse plane can be superimposed with a statistical distribution
simulating the dispersion in the generated transverse energy in each individual
collision. The program generates inter alia the fixed axes (standard) and
variable-axes (participant) two-dimensional profiles of the density of sources
in the transverse plane and their Fourier components. These profiles can be
used in further analyses of physical phenomena, such as the the jet quenching,
event-by-event hydrodynamics, or analysis of the elliptic flow and its
fluctuations. Characteristics of the event (multiplicities, eccentricities,
Fourier coefficients, etc.) are evaluated and stored in a file for further
off-line studies. A number of scripts is provided for that purpose. Supplied
variants of the code can also be used for the proton-nucleus and
deuteron-nucleus collisions.


  This work extends an existing virtual multi-agent platform called RoboSumo to
create TripleSumo -- a platform for investigating multi-agent cooperative
behaviors in continuous action spaces, with physical contact in an adversarial
environment. In this paper we investigate a scenario in which two agents,
namely `Bug' and `Ant', must team up and push another agent `Spider' out of the
arena. To tackle this goal, the newly added agent `Bug' is trained during an
ongoing match between `Ant' and `Spider'. `Bug' must develop awareness of the
other agents' actions, infer the strategy of both sides, and eventually learn
an action policy to cooperate. The reinforcement learning algorithm Deep
Deterministic Policy Gradient (DDPG) is implemented with a hybrid reward
structure combining dense and sparse rewards. The cooperative behavior is
quantitatively evaluated by the mean probability of winning the match and mean
number of steps needed to win.


  Link prediction is an important learning task for graph-structured data. In
this paper, we propose a novel topological approach to characterize
interactions between two nodes. Our topological feature, based on the extended
persistent homology, encodes rich structural information regarding the
multi-hop paths connecting nodes. Based on this feature, we propose a graph
neural network method that outperforms state-of-the-arts on different
benchmarks. As another contribution, we propose a novel algorithm to more
efficiently compute the extended persistence diagrams for graphs. This
algorithm can be generally applied to accelerate many other topological methods
for graph learning tasks.


  This article proposes doubly robust estimators for the average treatment
effect on the treated (ATT) in difference-in-differences (DID) research
designs. In contrast to alternative DID estimators, the proposed estimators are
consistent if either (but not necessarily both) a propensity score or outcome
regression working models are correctly specified. We also derive the
semiparametric efficiency bound for the ATT in DID designs when either panel or
repeated cross-section data are available, and show that our proposed
estimators attain the semiparametric efficiency bound when the working models
are correctly specified. Furthermore, we quantify the potential efficiency
gains of having access to panel data instead of repeated cross-section data.
Finally, by paying articular attention to the estimation method used to
estimate the nuisance parameters, we show that one can sometimes construct
doubly robust DID estimators for the ATT that are also doubly robust for
inference. Simulation studies and an empirical application illustrate the
desirable finite-sample performance of the proposed estimators. Open-source
software for implementing the proposed policy evaluation tools is available.


  The Borel summability in the distributional sense is established of the
divergent perturbation theory for the ground state resonance of the quantum
H\'enon-Heiles model.


  We report the predictions of different Monte Carlo event generators including
HIJING, Pythia, and QGSJETII in comparison with the experimental data measured
by the CMS Collaboration at CERN in proton-proton ($pp$) collisions at
center-of-mass energy $\sqrt{s}$ = 0.9 and 2.36 TeV. The CMS experimental
transverse momentum ($p_T$ or $p_{\perp}$) spectra of charged hadrons were
measured for pseudorapidity range 0 $\le$ $\eta$ $\le$ 2.4 with bin width of
$\eta$ = 0.2 (for $p_T$ from 0.1 to 2 GeV/$c$) and a single bin of $\eta$ for
$\lvert$$\eta$$\rvert$ $<$ 2.4 (for $p_T$ from 0.1 to 4 GeV/$c$). Pythia
reproduced the $p_T$ spectra with reasonable agreement for most of the $p_T$
range. It depicts better results in the case of the $|\eta|<$ 2.4 than HIJING
and QGSJETII which could reproduce the spectra in a limited $p_T$ range.
Furthermore, to analyze the $p_T$ spectra of charged hadrons measured by the
CMS Collaboration, we used a three component function (structured from the
Boltzmann distribution) and the $q$-dual function (from the $q$-dual
statistics) to extract parameter values relevant for the study of bulk
properties of hadronic matter at high energy. We have also applied the two
analytic functions over the model predictions. The values extracted by the
functions from the HIJING and Pythia models are closer to the experimental data
than the QGSJETII model. Although the models could reproduce the $p_T$ spectra
of all charged particles in some of the $p_T$ range but none of them could
reproduce the distributions over the entire $p_T$ range and in all the
pseudorapidity regions.


  Given any line bundle L of positive degree, on a compact Riemann surface, let
$M_L^\Lambda$ be the moduli space of L-twisted Higgs pairs of rank 2 with fixed
determinant isomorphic to $\Lambda$ and traceless Higgs field. We give a
description of the singular fibre of the Hitchin map $H:M^L_\Lambda\to
H^0(L^2)$, when the corresponding spectral curve has any singularity of type
$A_{m-1}$. In particular, we prove directly that this fibre is connected.


  For processes with gauge bosons in the final state we show how to
continuously connect with a single Born-improved amplitude the resonant region,
where resummation effects are important, with the asymptotic region far away
from the resonance, where the amplitude must reduce to its tree-level form.
While doing so all known field-theoretical constraints are respected, most
notably gauge-invariance, unitarity and the equivalence theorem. The
calculations presented are based on the process $f\bar{f}\to ZZ$, mediated by a
possibly resonant Higgs boson; this process captures all the essential
features, and can serve as a prototype for a variety of similar calculations.
By virtue of massive cancellations the resulting closed expressions for the
differential and total cross-sections are particularly compact.


  The first, long awaited, detection of a gravitational wave (GW) signal from
the merger of a binary neutron-star (NS-NS) system was finally achieved
(GW$\,$170817), and was also accompanied by an electromagnetic counterpart --
the short-duration GRB 170817A. It occurred in the nearby ($D\approx40\;$Mpc)
elliptical galaxy NGC$\,$4993, and showed optical, IR and UV emission from half
a day up to weeks after the event, as well as late time X-ray (at $\geq
8.9\;$days) and radio (at $\geq 16.4\;$days) emission. There was a delay of
$\Delta t \approx 1.74\;$s between the GW merger chirp signal and the
prompt-GRB emission onset, and an upper limit of $\theta_{\rm obs}<28^\circ$
was set on the viewing angle w.r.t the jet's symmetry axis from the GW signal.
In this letter we examine some of the implications of these groundbreaking
observations. The delay $\Delta t$ sets an upper limit on the prompt-GRB
emission radius, $R_\gamma\lesssim 2c\Delta t/(\theta_{\rm obs}-\theta_0)^2$,
for a jet with sharp edges at an angle $\theta_0<\theta_{\rm obs}$. GRB
170817A's relatively low isotropic equivalent $\gamma$-ray energy-output may
suggest a viewing angle slightly outside the jet's sharp edge,
$\theta_{\rm{}obs}-\theta_0\sim(0.05-0.1)(\Gamma/100)^{-1}$, but its peak
$\nu{}F_\nu$ photon energy and afterglow emission suggest instead that the jet
does not have sharp edges and the prompt emission was dominated by less
energetic material along our line of sight, at $\theta_{\rm{}obs}\gtrsim
2\theta_0$. Finally, we consider the type of remnant that is produced by the
NS-NS merger and find that a relatively long-lived ($>2\;$s) massive NS is
strongly disfavored, while a hyper-massive NS of lifetime $\sim1\;$s appears to
be somewhat favored over the direct formation of a black hole.


  The present paper is devoted to a new black bounce solution that regularize
the well-known rotating black string in $3+1$ dimensions. To do so, the
procedure pointed out by Simpson-Visser is followed, which has been already
applied successfully to other static cases of black strings, with and without
electric charge. This method implies to force a bounce on the radial
coordinate, such that a wormhole throat arises before the singularity, which
renders a regular solution. An analysis of the metric is conducted, showing the
interpolation between a regular black hole and a wormhole, what provides a much
richer family of solutions than the original metric. Different curvature
magnitudes are obtained in order to analyze the regularity of the solution,
including the Ricci and Kretschmann scalars. Finally, by following the Einstein
field equations the corresponding effective energy-momentum tensor is obtained
and the energy conditions are analyzed.


  In this note we prove the conjecture of \cite{HaWiWi} that every bipartite
multigraph with integer edge delays admits an edge colouring with $d+1$ colours
in the special case where $d=3$. A connection to the Brualdi-Ryser-Stein
conjecture is discussed.


  Social Media Site (SMS) usage has grown rapidly in the last few years. This
sudden increase in SMS usage creates an opportunity for data leakage which
could compromise personal and/or professional life. In this work, we have
reviewed traditional penetration testing process and discussed the failures of
traditional penetration testing process to test the 'People' layer of Simple
Enterprise Security Architecture (SESA) model. In order to overcome these
failures, we have developed the conceptual idea of online SMS user account
penetration testing system that could be applied to online SMS user account and
the user account could be categorised based on the rating points. This could
help us to avoid leaking information that is sensitive and/or damage their
reputation. Finally, we have also listed the best practice guidelines of online
SMS usage.


  In present work, we theoretically study the electron wave's focusing
phenomenon in a single layered graphene pn junction(PNJ) and obtain the
electric current density distribution of graphene PNJ, which is in good
agreement with the qualitative result in previous numerical calculations
[Science, 315, 1252 (2007)]. In addition, we find that for symmetric PNJ, 1/4
of total electric current radiated from source electrode can be collected by
drain electrode. Furthermore, this ratio reduces to 3/16 in a symmetric
graphene npn junction. Our results obtained by present analytical method
provide a general design rule for electric lens based on negative refractory
index systems.