  In this paper, we examine the physical layer security for cooperative
wireless networks with multiple intermediate nodes, where the
decode-and-forward (DF) protocol is considered. We propose a new joint relay
and jammer selection (JRJS) scheme for protecting wireless communications
against eavesdropping, where an intermediate node is selected as the relay for
the sake of forwarding the source signal to the destination and meanwhile, the
remaining intermediate nodes are employed to act as friendly jammers which
broadcast the artificial noise for disturbing the eavesdropper. We further
investigate the power allocation among the source, relay and friendly jammers
for maximizing the secrecy rate of proposed JRJS scheme and derive a
closed-form sub-optimal solution. Specificially, all the intermediate nodes
which successfully decode the source signal are considered as relay candidates.
For each candidate, we derive the sub-optimal closed-form power allocation
solution and obtain the secrecy rate result of the corresponding JRJS scheme.
Then, the candidate which is capable of achieving the highest secrecy rate is
selected as the relay. Two assumptions about the channel state information
(CSI), namely the full CSI (FCSI) and partial CSI (PCSI), are considered.
Simulation results show that the proposed JRJS scheme outperforms the
conventional pure relay selection, pure jamming and GSVD based beamforming
schemes in terms of secrecy rate. Additionally, the proposed FCSI based power
allocation (FCSI-PA) and PCSI based power allocation (PCSI-PA) schemes both
achieve higher secrecy rates than the equal power allocation (EPA) scheme.


  In heavy fermion systems, higher-rank multipole operators are active thanks
to the strong spin-orbit interaction (SOI), and the role of diverse multipole
fluctuations on the pairing mechanism attracts a lot of attention. Here, we
study a mechanism of superconductivity in heavy fermion systems, by focusing on
the impact of vertex corrections (VCs) for the pairing interaction going beyond
the Migdal approximation. In heavy fermion systems, strong interference between
multipole fluctuations cause significant VCs, that represent many-body effects
beyond mean-field-type approximations. Especially, the coupling constants
between electrons and charged-bosons, including the electron-phonon coupling
constant, are strongly magnified by the VCs. For this reason, moderate
even-rank (=electric) multipole fluctuations give large attractive interaction,
and therefore s-wave superconductivity can emerge in heavy-fermion systems. In
particular, phonon-mediated superconductivity is expected to be realized near
the magnetic criticality, thanks to the VCs due to magnetic multipole
fluctuations. The present mechanism may be responsible for the fully gapped
s-wave superconducting state realized in CeCu2Si2.


  We give in this paper an example of infinitary rational relation, accepted by
a 2-tape B\"{u}chi automaton, which is Pi^0_3-complete in the Borel hierarchy.
Moreover the example of infinitary rational relation given in this paper has a
very simple structure and can be easily described by its sections.


  The axially symmetric solutions to the Navier-Stokes equations in a periodic
cylinder with boundary slip conditions on the lateral part of its boundary are
considered. A priori estimates for solutions with large swirl necessary for a
proof of global regular solutions are derived.


  In this work we show the results for numerical solutions of the relativistic
Grad-Shafranov equation for a typical neutron star with 1.4 solar masses. We
have studied the internal magnetic field considering both the poloidal and
toroidal components, as well as the behavior of the field lines parametrized by
the ratio between these components of the field.


  We provide a coherent, uniform measurement of the evolution of the
logarithmic star formation rate (SFR) - stellar mass ($M_*$) relation, called
the main sequence of star-forming galaxies (MS), for galaxies out to $z\sim5$.
We measure the MS using mean stacks of 3 GHz radio continuum images to derive
average SFRs for $\sim$200,000 mass-selected galaxies at $z>0.3$ in the COSMOS
field. We describe the MS relation adopting a new model that incorporates a
linear relation at low stellar mass (log($M_*$/M$_\odot$)$<$10) and a
flattening at high stellar mass that becomes more prominent at low redshift
($z<1.5$). We find that the SFR density peaks at $1.5<z<2$ and at each epoch
there is a characteristic stellar mass ($M_* = 1 - 4 \times
10^{10}\mathrm{M}_\odot$) that contributes the most to the overall SFR density.
This characteristic mass increases with redshift, at least to $z\sim2.5$. We
find no significant evidence for variations in the MS relation for galaxies in
different environments traced by the galaxy number density at $0.3<z<3$, nor
for galaxies in X-ray groups at $z\sim0.75$. We confirm that massive
bulge-dominated galaxies have lower SFRs than disk-dominated galaxies at a
fixed stellar mass at $z<1.2$. As a consequence, the increase in
bulge-dominated galaxies in the local star-forming population leads to a
flattening of the MS at high stellar masses. This indicates that
"mass-quenching" is linked with changes in the morphological composition of
galaxies at a fixed stellar mass.


  Quantization of superflow-circulation and of magnetic-flux are considered for
systems, such as superfluid $^3$He-A and unconventional superconductors, having
nonscalar order parameters. The circulation is shown to be the anholonomy in
the parallel transport of the order parameter. For multiply-connected samples
free of distributed vorticity, circulation and flux are predicted to be
quantized, but generically to nonintegral values that are tunably offset from
integers. This amounts to a version of Aharonov-Bohm physics. Experimental
settings for testing these issues are discussed.


  We present, as a case study, a description of the partnership between an
observatory (JCMT) and a data centre (CADC) that led to the development of the
JCMT Science Archive (JSA). The JSA is a successful example of a service
designed to use Virtual Observatory (VO) technologies from the start. We
describe the motivation, process and lessons learned from this approach.


  Let $(F_n)_{n\ge 1}$ be the Fibonacci sequence. Define $P(F_n): =
(\sum_{i=1}^n F_i)_{n\ge 1}$; that is, the function $P$ gives the sequence of
partial sums of $(F_n)$. In this paper, we first give an identity involving
$P^k(F_n)$, which is the resulting sequence from applying $P$ to $(F_n)$ $k$
times. Second, we provide a combinatorial interpretation of the numbers in
$P^k(F_n)$.


  Liquid-phase exfoliation is one of the most promising routes for large scale
production of multilayer graphene dispersions. These dispersions, which may be
used in coatings, composites or paints, are believed to contain disorder-free
graphene multilayers. Here we address the nature of defects in such samples
obtained by liquid-phase exfoliation of graphite powder in
N-methyl--2--pyrrolidone. Our Raman spectroscopy data challenges the assumption
that these multilayers are free of bulk defects, revealing that defect
localization strongly depends on the sonication time. For short ultrasound
times, defects are located mainly at the layer edges but they turn out to build
up in the bulk for ultrasonic times above 2 h. This knowledge may help to
devise better strategies to achieve high-quality graphene dispersions.


  Aims: Flip-flops are top-hat-like X-ray flux variations which occur in some
transient accreting black hole binary systems and feature simultaneous changes
in the spectral hardness and the Power Density Spectrum (PDS). They occur at a
crucial time in the evolution of these systems, when the accretion disk
emission starts to dominate over coronal emission. Flip-flops have only rarely
been observed and are poorly understood.
  Methods: We detect 15 flip-flops in the 2018 outburst of Swift J1658.2-4242,
in observations by XMM-Newton, NuSTAR, Astrosat, Swift, Insight-HXMT, INTEGRAL,
and ATCA. We analyse their light curves, search for periodicities, compute
their PDS, and fit their X-ray spectra, to investigate the source behaviour
during flip-flop transitions, and how the interval featuring flip-flops differs
from the rest of the outburst.
  Results: The flip-flops of Swift J1658.2-4242 are of an extreme variety,
exhibiting flux differences of up to 77% within ~100s, much larger than has
been seen so far. We observe radical changes in the PDS simultaneous with the
sharp flux variations, featuring transitions between the Quasi-Periodic
Oscillation types C and A, which have never been observed before. Changes to
the PDS are delayed, but more rapid than changes in the light curve. Flip-flops
occur in two intervals, separated by two weeks in which these phenomena were
not seen. Transitions between the two flip-flop states occurred at random
integer multiples of a fundamental period, of 2.761ks in the first interval,
and 2.61ks in the second. Spectral analysis reveals the high and low flux
flip-flop states to be similar, but distinct from intervals lacking flip-flops.
A change in the inner temperature of the accretion disk is responsible for most
of the flux difference in the flip-flops. We highlight the importance of
correcting for the influence of the dust scattering halo on the X-ray spectra.


  Recent researches demonstrate that Deep Neural Networks (DNN) models are
vulnerable to backdoor attacks. The backdoored DNN model will behave
maliciously when images containing backdoor triggers arrive. To date, existing
backdoor attacks are single-trigger and single-target attacks, and the triggers
of most existing backdoor attacks are obvious thus are easy to be detected or
noticed. In this paper, we propose a novel imperceptible and multi-channel
backdoor attack against Deep Neural Networks by exploiting Discrete Cosine
Transform (DCT) steganography. Based on the proposed backdoor attack method, we
implement two variants of backdoor attacks, i.e., N-to-N backdoor attack and
N-to-One backdoor attack. Specifically, for a colored image, we utilize DCT
steganography to construct the trigger on different channels of the image. As a
result, the trigger is stealthy and natural. Based on the proposed method, we
implement multi-target and multi-trigger backdoor attacks. Experimental results
demonstrate that the average attack success rate of the N-to-N backdoor attack
is 93.95% on CIFAR-10 dataset and 91.55% on TinyImageNet dataset, respectively.
The average attack success rate of N-to-One attack is 90.22% and 89.53% on
CIFAR-10 and TinyImageNet datasets, respectively. Meanwhile, the proposed
backdoor attack does not affect the classification accuracy of the DNN model.
Moreover, the proposed attack is demonstrated to be robust to the
state-of-the-art backdoor defense (Neural Cleanse).


  The function $y=\Phi_\alpha(x)$, the solution of $y^\alpha e^y=x$ for $x$ and
$y$ large enough, has a series expansion in terms of $\ln x$ and $\ln\ln x$,
with coefficients given in terms of Stirling cycle numbers. It is shown that
this expansion converges for $x>(\alpha e)^\alpha$ for $\alpha \ge 1$. It is
also shown that new expansions can be obtained for $\Phi_\alpha$ in terms of
associated Stirling numbers. The new expansions converge more rapidly and on a
larger domain.


  We investigate the detectability of single-event coalescing black hole
binaries with total mass of $100-600 M_{\odot}$ at cosmological distances ($5
\lesssim z \lesssim 20$) with the next generation of terrestrial gravitational
wave observatories, specifically Einstein Telescope and Cosmic Explorer. Our
ability to observe these binaries is limited by the low-frequency performance
of the detectors. Higher-order Multipoles of the gravitational wave signal are
observable in these systems, and detection of such multipoles serves to both b
the mass range over which black hole binaries are observable and improve the
recovery of their individual masses and redshift. For high redshift systems of
$\sim 200 M_{\odot}$ we will be able to confidently infer that the redshift is
at least $z=12$, and for systems of $\sim 400 M_{\odot}$ we can infer a minimum
redshift of at least $z=8$. We discuss the impact that these observations will
have in narrowing uncertainties on the existence of the pair-instability
mass-gap, and their implications on the formation of the first stellar black
holes that could be seeds for the growth of supermassive black holes powering
high-$z$ quasars.


  This paper considers the uplink of a distributed Massive MIMO network where
$N$ base stations (BSs), each equipped with $M$ antennas, receive data from
$K=2$ users. We study the asymptotic spectral efficiency (as $M\to \infty$)
with spatial correlated channels, pilot contamination, and different degrees of
channel state information (CSI) and statistical knowledge at the BSs. By
considering a two-user setup, we can simply derive fundamental asymptotic
behaviors and provide novel insights into the structure of the optimal
combining schemes. In line with [1], when global CSI is available at all BSs,
the optimal minimum-mean squared error combining has an unbounded capacity as
$M\to \infty$, if the global channel covariance matrices of the users are
asymptotically linearly independent. This result is instrumental to derive a
suboptimal combining scheme that provides unbounded capacity as $M\to \infty$
using only local CSI and global channel statistics. The latter scheme is shown
to outperform a generalized matched filter scheme, which also achieves
asymptotic unbounded capacity by using only local CSI and global channel
statistics, but is derived following [2] on the basis of a more conservative
capacity bound.


  The counter-intuitive rotational motion of the propeller of a devil's stick
when the agitator is rubbed against the pylon has long intrigued performers,
audiences and scientists. The apparently unrelated phenomenon of
self-stabilization of a Kapitza pendulum at the inverted position, once again
an amazing lecture demonstration, has on the other hand been subjected to years
of investigation and research. Here we show that the two systems are in fact
identical, and obtain a previously unreported, friction-stabilized
synchronously rotating state in the Kapitza pendulum, which in fact explains
the rotational motion of the Devil's stick.


  The Interface Region Imaging Spectrograph (IRIS) has routinely observed the
flaring Mg II NUV spectrum, offering excellent diagnostic potential and a
window into the location of energy deposition. A number of studies have forward
modelled both the general properties of these lines and specific flare
observations. Generally these have forward modelled radiation via
post-processing of snapshots from hydrodynamic flare simulations through
radiation transfer codes. There has, however, not been a study of how the
physics included in these radiation transport codes affects the solution. A
baseline setup for forward modelling MgII in flares is presented and contrasted
with approaches that add or remove complexity. It is shown for Mg II: (1) PRD
is still required during flare simulations despite the increased densities, (2)
using full angle-dependent PRD affects the solution but takes significantly
longer to process a snapshot, (3) including Mg I in NLTE results in negligible
differences to the Mg II lines but does affect the NUV quasi-continuum, (4)
only hydrogen and Mg II need to be included in NLTE, (5) ideally the
non-equilibrium hydrogen populations, with non-thermal collisional rates,
should be used rather than the statistical equilibrium populations, (6) an atom
consisting of only the ground state, h & k upper levels, and continuum level is
insufficient to model the resonance lines, and (7) irradiation from a hot,
dense flaring transition region can affect the formation of Mg II. We discuss
modifications to the RH code allowing straightforward inclusion of transition
region and coronal irradiation in flares.


  The $U(1)_A$ boson mass is calculated through the phenomenological
characteristics of the vacuum related to spontaneous breaking of chiral
symmetry in QCD. The mass is determined by the mixed quark-gluon condensate
$\langle \bar q G q \rangle$ that emerges in an appropriate correlation
function due to triangle anomaly. For three flavor QCD in chiral limit we find
the numerical value for the $U(1)_A$ boson mass to be $M_0=310\pm 50~{\rm
MeV}$.


  Drawing inspiration from biology, we describe the way in which visual sensing
with a monocular camera can provide a reliable signal for navigation of mobile
robots. The work takes inspiration from a classic paper by Lee and Reddish
(Nature, 1981, https://doi.org/10.1038/293293a0) in which they outline a
behavioral strategy pursued by diving sea birds based on a visual cue called
time-to-contact. A closely related concept of time-to-transit, tau, is defined,
and it is shown that idealized steering laws based on monocular camera
perceptions of tau can reliably and robustly steer a mobile vehicle within a
wide variety of spaces in which features perceived to lie on walls and other
objects in the environment provide adequate visual cues. The contribution of
the paper is two-fold. It provides a simple theory of robust vision-based
steering control. It goes on to show how the theory guides the implementation
of robust visual navigation using ROS-Gazebo simulations as well as deployment
and experiments with a camera-equipped Jackal robot. As far as we know, the
experiments described below are the first to demonstrate visual navigation
based on tau.


  In this paper, we address the design of high spectral-efficiency Barnes-Wall
(BW) lattice codes which are amenable to low-complexity decoding in additive
white Gaussian noise (AWGN) channels. We propose a new method of constructing
complex BW lattice codes from linear codes over polynomial rings, and show that
the proposed construction provides an explicit method of bit-labeling complex
BW lattice codes. To decode the code, we adapt the low-complexity sequential BW
lattice decoder (SBWD) recently proposed by Micciancio and Nicolosi. First, we
study the error performance of SBWD in decoding the infinite lattice, wherein
we analyze the noise statistics in the algorithm, and propose a new upper bound
on its error performance. We show that the SBWD is powerful in making correct
decisions well beyond the packing radius. Subsequently, we use the SBWD to
decode lattice codes through a novel noise-trimming technique. This is the
first work that showcases the error performance of SBWD in decoding BW lattice
codes of large block lengths.


  Channel capacities of quantum channels can be nonadditive even if one of two
quantum channels has no channel capacity. We call this phenomenon
\emph{activation} of the channel capacity. In this paper, we show that when we
use a quantum channel on a qubit system, only a noiseless qubit channel can
generate the activation of the zero-error classical capacity. In particular, we
show that the zero-error classical capacity of two quantum channels on qubit
systems cannot be activated. Furthermore, we present a class of examples
showing the activation of the zero-error classical capacity in low-dimensional
systems.


  In 2+1 dimensional gauge thories with $SU(N_c)$ color and $2N_f$ flavors of
quarks in the fundamental representation, sphalerons, if present may lead to
quark condensation and chiral symmetry breaking. The effect is similar to
instanton induced chiral symmetry breaking in 3+1 dimensions and is due to the
interaction of quark propagators with sphalerons. The existence of sphalerons
requires that color symmetries be broken by a Higgs in the fundamental
representation. We show that the sphaleron effect may persist for arbitrarily
large $N_f$ but vanishes along with the mass of the gauge fields corresponding
to broken generators of $SU(N_c)$. The effect is inherently non-Abelian and
absent for QED.


  In this paper, we generalize Schur-Weyl duality and Morita Theorem on
associative algebras to those on associative $H$-pseudoalgebras. Meanwhile, we
get a plenty of associative $H$-pseudoalgebras over a cocommutative Hopf
algebra $H$.


  The rotation curve of a magnetized plasma cloud orbiting in the gravitational
potential of a galaxy is calculated by statistical arguments. The working
assumption is that a mild magnetic field, decreasing with distance from the
galactic center, permeates space. It is shown that the resulting probability
density is compatible with a flat rotation curve.


  The spectra of, e.g. open quantum systems are typically given as the
superposition of resonances with a Lorentzian line shape, where each resonance
is related to a simple pole in the complex energy domain. However, at
exceptional points two or more resonances are degenerate and the resulting
non-Lorentzian line shapes are related to higher order poles in the complex
energy domain. In the Fourier-transform time domain an $n$-th order exceptional
point is characterised by a non-exponentially decaying time signal given as the
product of an exponential function and a polynomial of degree $n-1$. The
complex positions and amplitudes of the non-degenerate resonances can be
determined with high accuracy by application of the nonlinear harmonic
inversion method to the real-valued resonance spectra. We extend the harmonic
inversion method to include the analysis of exceptional points. The technique
yields, in the energy domain, the amplitudes of the higher order poles
contributing to the spectra, and, in the time domain, the coefficients of the
polynomial characterising the non-exponential decay of the time signal. The
extended harmonic inversion method is demonstrated on two examples, viz. the
analysis of exceptional points in resonance spectra of the hydrogen atom in
crossed magnetic and electric fields, and an exceptional point occurring in the
dynamics of a single particle in a time-dependent harmonic trap.


  We study the relation between the global topology of the Hofstadter butterfly
of a multiband insulator and the topological invariants of the underlying
Hamiltonian. The global topology of the butterfly, i.e., the displacement of
the energy gaps as the magnetic field is varied by one flux quantum, is
determined by the spectral flow of energy eigenstates crossing gaps as the
field is tuned. We find that for each gap this spectral flow is equal to the
topological invariant of the gap, i.e., the net number of edge modes traversing
the gap. For periodically driven systems, our results apply to the spectrum of
quasienergies. In this case, the spectral flow of the sum of all the
quasienergies gives directly the Rudner invariant.


  Interstellar magnetic fields are strong: up to 25 muG in spiral arms and 40
muG in nuclear regions. In the spiral galaxy NGC 6946 the average magnetic
energy density exceeds that of the thermal gas. Magnetic fields control the
evolution of dense clouds and possibly the global star formation efficiency in
galaxies. Gas flows and shocks in spiral arms and bars are modified by magnetic
fields. Magnetic forces in star-forming circumnuclear regions are able to drive
mass inflow towards the active nucleus. Magnetic fields are essential for the
propagation of cosmic rays and the formation of galactic winds and halos.


  Since clicks usually contain heavy noise, increasing research efforts have
been devoted to modeling implicit negative user behaviors (i.e., non-clicks).
However, they either rely on explicit negative user behaviors (e.g., dislikes)
or simply treat non-clicks as negative feedback, failing to learn negative user
interests comprehensively. In such situations, users may experience fatigue
because of seeing too many similar recommendations. In this paper, we propose
Fatigue-Aware Network (FAN), a novel CTR model that directly perceives user
fatigue from non-clicks. Specifically, we first apply Fourier Transformation to
the time series generated from non-clicks, obtaining its frequency spectrum
which contains comprehensive information about user fatigue. Then the frequency
spectrum is modulated by category information of the target item to model the
bias that both the upper bound of fatigue and users' patience is different for
different categories. Moreover, a gating network is adopted to model the
confidence of user fatigue and an auxiliary task is designed to guide the
learning of user fatigue, so we can obtain a well-learned fatigue
representation and combine it with user interests for the final CTR prediction.
Experimental results on real-world datasets validate the superiority of FAN and
online A/B tests also show FAN outperforms representative CTR models
significantly.


  Numerical discretizations of the Generalized Porous Medium Equation (GPME)
with discontinuous coefficients are analyzed with respect to the formation of
numerical artifacts. In addition to the degeneracy and self-sharpening of the
GPME with continuous coefficients, detailed in [1], increased numerical
challenges occur in the discontinuous coefficients case. These numerical
challenges manifest themselves in spurious temporal oscillations in second
order finite volume discretizations with both arithmetic and harmonic
averaging. The integral average, developed in [2] leads to improved solutions
with monotone and reduced amplitude temporal oscillations. In this paper, we
propose a new method called the Shock-Based Averaging Method (SAM) that
incorporates the shock position into the numerical scheme. The shock position
is numerically calculated by discretizing the theoretical speed of the front
from the GPME theory. The speed satisfies the jump condition for integral
conservation laws. SAM results in a non-oscillatory temporal profile, producing
physically valid numerical results. We use SAM to demonstrate that the choice
of averaging alone is not the cause of the oscillations, and that the shock
position must be a part of the numerical scheme to avoid the artifacts.


  We determine a formula for the average values of L-series associated to
eigenforms at complex values.


  We theoretically investigate a three-dimensional weakly interacting Bose gas
with one-dimensional Raman-type spin-orbit coupling at zero temperature. By
employing an improved ansatz, including high-order harmonics in the stripe
phase, we show that the critical transition from the stripe to the plane-wave
phases is shifted to a relatively larger Rabi frequency compared to the
prediction by previous work [Li $\textit{et al.}$, Phys. Rev. Lett.
$\textbf{108}$, 225301 (2012)] using a first-order stripe ansatz. We also
determine the quantum depletion and superfluid density over a large range of
Rabi frequency in different phases. The depletion exhibits an intriguing
behavior with a discontinuous jump at the transition between the stripe and
plane-wave phases, and a maximum at the transition between the plane-wave and
zero-momentum phases. The superfluid density is derived through a phase-twist
method. In the plane-wave and zero-momentum phases, it is significantly
suppressed along the spin-orbit-coupling direction and vanishes at the
transition, consistent with a recent work [Zhang $\textit{et al.}$, Phys. Rev.
A $\textbf{94}$, 033635 (2016)], while in the stripe phase, it smoothly
decreases with increasing Rabi frequency. Our predictions would be useful for
further theoretical and experimental studies of the exotic supersolid stripe
phase.


  In the realm of causal inference, Potential Outcomes (PO) and Structural
Causal Models (SCM) are recognized as the principal frameworks.However, when it
comes to Layer 3 valuations -- counterfactual queries deeply entwined with
individual-level semantics -- both frameworks encounter limitations due to the
degenerative issues brought forth by the consistency rule. This paper advocates
for the Distribution-consistency Structural Causal Models (DiscoSCM) framework
as a pioneering approach to counterfactual inference, skillfully integrating
the strengths of both PO and SCM. The DiscoSCM framework distinctively
incorporates a unit selection variable $U$ and embraces the concept of
uncontrollable exogenous noise realization. Through personalized incentive
scenarios, we demonstrate the inadequacies of PO and SCM frameworks in
representing the probability of a user being a complier (a Layer 3 event)
without degeneration, an issue adeptly resolved by adopting the assumption of
independent counterfactual noises within DiscoSCM. This innovative assumption
broadens the foundational counterfactual theory, facilitating the extension of
numerous theoretical results regarding the probability of causation to an
individual granularity level and leading to a comprehensive set of theories on
heterogeneous counterfactual bounds. Ultimately, our paper posits that if one
acknowledges and wishes to leverage the ubiquitous heterogeneity, understanding
causality as invariance across heterogeneous units, then DiscoSCM stands as a
significant advancement in the methodology of counterfactual inference.


  We introduce a class of interest rate models, called the $\alpha$-CIR model,
which gives a natural extension of the standard CIR model by adopting the
$\alpha$-stable L{\'e}vy process and preserving the branching property. This
model allows to describe in a unified and parsimonious way several recent
observations on the sovereign bond market such as the persistency of low
interest rate together with the presence of large jumps at local extent. We
emphasize on a general integral representation of the model by using random
fields, with which we establish the link to the CBI processes and the affine
models. Finally we analyze the jump behaviors and in particular the large
jumps, and we provide numerical illustrations.


  The limitations for the coherent manipulation of neutral atoms with
fabricated solid state devices, so-called `atom chips', are addressed.
Specifically, we examine the dominant decoherence mechanism, which is due to
the magnetic noise originating from the surface of the atom chip. It is shown
that the contribution of fluctuations in the chip wires at the shot noise level
is not negligible. We estimate the coherence times and discuss ways to increase
them. Our main conclusion is that future advances should allow for coherence
times as long as one second, a few micrometers away from the surface.


  We study the problem of recovering a signal $x\in\mathbb{C}^N$ from samples
of its phaseless periodic short-time Fourier transform (STFT): the magnitude of
the Fourier transform of the signal multiplied by a sliding window $w\in
\mathbb{C}^W$. We show that if the window $w$ is known, then a generic signal
can be recovered, up to a global phase, from less than 4N phaseless STFT
measurements. In the blind case, when the window is unknown, we show that the
signal and the window can be determined simultaneously, up to a group of
unavoidable ambiguities, from less than 4N+2W measurements. In both cases, our
bounds are optimal, up to a constant smaller than two.


  This article proposes a "cross-forming" control concept for grid-forming
inverters operating against grid faults. Cross-forming refers to voltage angle
forming and current magnitude forming. It differs from classical grid-forming
and grid-following paradigms that feature voltage magnitude-and-angle forming
and voltage magnitude-and-angle following (or current magnitude-and-angle
forming), respectively. The cross-forming concept addresses the need for
inverters to remain grid-forming (particularly voltage angle forming, as
required by grid codes) while managing fault current limitation. Simple and
feasible cross-forming control implementations are proposed, enabling inverters
to quickly limit fault currents to a prescribed level while preserving voltage
angle forming for grid-forming synchronization and providing dynamic ancillary
services, during symmetrical or asymmetrical fault ride-through. Moreover, the
cross-forming control yields an equivalent system featuring a constant virtual
impedance and a "normal form" representation, allowing for the extension of
previously established transient stability results to include scenarios
involving current saturation. Simulations and experiments validate the efficacy
of the proposed cross-forming control implementations.


  A two-ray multipath model for frequency diverse array (FDA)-based directional
modulation (DM) is proposed in multi-input single-output multi-eavesdropper
(MISOME) wiretap channels for the first time. The excitation factors of the FDA
and the weighting coefficients of the inserted artificial noise (AN) are
jointly designed in a way which imposes no impact on the desired receiver while
simultaneously distorting the received signals of eavesdroppers. Secrecy rate
is analyzed for the proposed two-ray multipath FDA-based DM model. Numerical
simulations verify the capability of physical layer secure (PLS) transmissions
of the proposed FDA-DM model in two-ray multipath MISOME wiretap channels.


  In recent years, generative diffusion models have achieved a rapid paradigm
shift in deep generative models by showing groundbreaking performance across
various applications. Meanwhile, structured data, encompassing tabular and time
series data, has been received comparatively limited attention from the deep
learning research community, despite its omnipresence and extensive
applications. Thus, there is still a lack of literature and its reviews on
structured data modelling via diffusion models, compared to other data
modalities such as visual and textual data. To address this gap, we present a
comprehensive review of recently proposed diffusion models in the field of
structured data. First, this survey provides a concise overview of the
score-based diffusion model theory, subsequently proceeding to the technical
descriptions of the majority of pioneering works that used structured data in
both data-driven general tasks and domain-specific applications. Thereafter, we
analyse and discuss the limitations and challenges shown in existing works and
suggest potential research directions. We hope this review serves as a catalyst
for the research community, promoting developments in generative diffusion
models for structured data.


  For every hyperbolic group and more general hyperbolic graphs, we construct
an equivariant ideal bicombing: this is a homological analogue of the geodesic
flow on negatively curved manifolds. We then construct a cohomological
invariant which implies that several Measure Equivalence and Orbit Equivalence
rigidity results established by Monod-Shalom hold for all non-elementary
hyperbolic groups and their non-elementary subgroups. We also derive
superrigidity results for actions of general irreducible lattices on a large
class of hyperbolic metric spaces.


  Single-Photon Emission Computed Tomography (SPECT) left ventricular
assessment protocols are important for detecting ischemia in high-risk
patients. To quantitatively measure myocardial function, clinicians depend on
commercially available solutions to segment and reorient the left ventricle
(LV) for evaluation. Based on large normal datasets, the segmentation
performance and the high price of these solutions can hinder the availability
of reliable and precise localization of the LV delineation. To overcome the
aforementioned shortcomings this paper aims to give a recipe for diagnostic
centers as well as for clinics to automatically segment the myocardium based on
small and low-quality labels on reconstructed SPECT, complete field-of-view
(FOV) volumes. A combination of Continuous Max-Flow (CMF) with prior shape
information is developed to augment the 3D U-Net self-supervised learning (SSL)
approach on various geometries of SPECT apparatus. Experimental results on the
acquired dataset have shown a 5-10\% increase in quantitative metrics based on
the previous State-of-the-Art (SOTA) solutions, suggesting a good plausible way
to tackle the few-shot SSL problem on high-noise SPECT cardiac datasets.


  Catastrophic forgetting is the notorious vulnerability of neural networks to
the change of the data distribution while learning. This phenomenon has long
been considered a major obstacle for allowing the use of learning agents in
realistic continual learning settings. A large body of continual learning
research assumes that task boundaries are known during training. However,
research for scenarios in which task boundaries are unknown during training has
been lacking. In this paper we present, for the first time, a method for
preventing catastrophic forgetting (BGD) for scenarios with task boundaries
that are unknown during training --- task-agnostic continual learning. Code of
our algorithm is available at https://github.com/igolan/bgd.


  We consider a class of singular foliations in the sense of Androulidakis and
Skandalis that we call transverse order $k$ foliations. These have a finite
number of leaves: one hypersurface (the singular leaf) together with the
components of its complement (open leaves). The positive integer parameter $k$
encodes the "order of tangency" of the leafwise vector fields to $L$. We show
that a loop in the singular leaf induces a well-defined holonomy transformation
at the level of $(k-1)$-jets. The resulting holonomy invariant can be used to
give a complete classification of these foliations and obtain concrete
descriptions of their associated groupoids and algebras.


  We apply the dynamical systems tools to study the linear dynamics of a
self-interacting scalar field trapped in the braneworld, for a wide variety of
self-interaction potentials. We focus on Randall-Sundrum (RS) and on
Dvali-Gabadadze-Porrati (DGP) braneworld models exclusively. These models are
complementary to each other: while the RS brane produces ultra-violet (UV)
corrections to general relativity, the DGP braneworld modifies Einstein's
theory at large scales, i. e., produces infra-red (IR) modifications of general
relativity. This study of the asymptotic properties of both braneworld models,
shows -- in the phase space -- the way the dynamics of a scalar field trapped
in the brane departs from standard general relativity behaviour.


  This paper considers a multigateway multibeam satellite system with multiple
feeds per beam. In these systems, each gateway serves a set of beams (cluster)
so that the overall data traffic is generated at different geographical areas.
Full frequency reuse among beams is considered so that interference mitigation
techniques are mandatory. Precisely, this paper aims at designing the precoding
scheme which, in contrast to single gateway schemes, entails two main
challenges. First, the precoding matrix shall be separated into feed groups
assigned to each gateway. Second, complete channel state information (CSI) is
required at each gateway, leading to a large communication overhead. In order
to solve these problems, a design based on a regularized singular value block
decomposition of the channel matrix is presented so that both inter-cluster
(i.e. beams of different clusters) and intra-cluster (i.e. beams of the same
cluster) interference is minimized. In addition, different gateway cooperative
schemes are analysed in order to keep the inter-gateway communication low.
Furthermore, the impact of the feeder link interference (i.e. interference
between different feeder links) is analysed and it is shown both numerically
and analytically that the system performance is reduced severally whenever this
interference occurs even though precoding reverts this additional interference.
Finally, numerical simulations are shown considering the latest fixed broadband
communication standard DVB-S2X so that the quantized feedback effect is
evaluated. The proposed precoding technique results to achieve a performance
close to the single gateway operation even when the cooperation among gateways
is low.


  The self consistent effective medium approximation (SEMA) is used to study
three-dimensional random conducting composites under the influence of a strong
magnetic field {\bf B}, in the case where all constituents exhibit isotropic
response. Asymptotic analysis is used to obtain almost closed form results for
the strong field magnetoresistance and Hall resistance in various types of two-
and three-constituent isotropic mixtures for the entire range of compositions.
Numerical solutions of the SEMA equations are also obtained, in some cases, and
compared with those results. In two-constituent
free-electron-metal/perfect-insulator mixtures, the magnetoresistance is
asymptotically proportional to $|{\bf B}|$ at {\em all concentrations above the
percolation threshold}. In three-constituent metal/insulator/superconductor
mixtures a line of critical points is found, where the strong field
magnetoresistance switches abruptly from saturating to non-saturating
dependence on $|{\bf B}|$, at a certain value of the
insulator-to-superconductor concentration ratio. This transition appears to be
related to the phenomenon of anisotropic percolation.


  An embedding of a graph in a book consists of a linear order of its vertices
along the spine of the book and of an assignment of its edges to the pages of
the book, so that no two edges on the same page cross. The book thickness of a
graph is the minimum number of pages over all its book embeddings. Accordingly,
the book thickness of a class of graphs is the maximum book thickness over all
its members. In this paper, we address a long-standing open problem regarding
the exact book thickness of the class of planar graphs, which previously was
known to be either three or four. We settle this problem by demonstrating
planar graphs that require four pages in any of their book embeddings, thus
establishing that the book thickness of the class of planar graphs is four.


  In this paper we study the quantum wave packet and the Feynman_de
Broglie_Bohm propagator of the linearized Kostin equation along a classical
trajetory.


  Recently it has been shown that fluorescence telescopes with a large field of
view can indirectly probe the scale of supersymmetry breaking. Here we show
that depending on their ability to fight a large background, multi-Km3 volume
neutrino telescopes might independently probe a similar breaking scale region,
which lies between \sim 10^5 and \sim 5 x 10^6 GeV. The scenarios we consider
have the gravitino as the lightest supersymmetric particle, and the next to
lightest (NLSP) is a long lived slepton. Indirect probes complement a proposal
that demonstrates that 1 Km3 telescopes can directly probe this breaking scale.
A high energy flux of neutrinos might interact in the Earth producing NLSPs
which decay into taus. We estimate the rate of taus, taking into account the
regeneration process, and the rate of secondary muons, which are produced in
tau decays, in multi-km3 detectors.


  We consider a compact CR manifold with a transversal CR locally free circle
action endowed with a rigid positive CR line bundle. We prove that a certain
weighted Fourier-Szeg\H{o} kernel of the CR sections in the high tensor powers
admits a full asymptotic expansion. As a consequence, we establish an
equivariant Kodaira embedding theorem.


  With the increasing capabilities of large language models (LLMs), in-context
learning (ICL) has emerged as a new paradigm for natural language processing
(NLP), where LLMs make predictions based on contexts augmented with a few
examples. It has been a significant trend to explore ICL to evaluate and
extrapolate the ability of LLMs. In this paper, we aim to survey and summarize
the progress and challenges of ICL. We first present a formal definition of ICL
and clarify its correlation to related studies. Then, we organize and discuss
advanced techniques, including training strategies, prompt designing
strategies, and related analysis. Additionally, we explore various ICL
application scenarios, such as data engineering and knowledge updating.
Finally, we address the challenges of ICL and suggest potential directions for
further research. We hope that our work can encourage more research on
uncovering how ICL works and improving ICL.


  For the given regular plane polygon and an arbitrary point in the plane of
the polygon, the distances from the point to the vertices of the polygon are
defined. We proved that there is one more non-congruent regular polygon having
the vertices at the same distances from the point. The sizes of both regular
polygons are uniquely determined by these distances. In general case,
geometrical construction of the second regular polygon is given. It is proved
that there are two points in the plane, which separately have the same set of
the distances to the vertices of two non-congruent regular polygons with a
shared vertex.


  It this paper we present the results obtained with the newly created Standard
SANC modules for calculation of the NLO QCD corrections to single top
production processes in s and t channels at the partonic level, as well as
top-decays. The main aim of these results is to prove the correct work of
modules. A comprehensive comparison with results of the CompHEP system is
given, where possible. These modules are intended to be used in Monte Carlo
generators for single top production processes at the LHC. As in our recent
paper, devoted to the electroweak corrections to these processes, we study the
regularization of the top-legs associated infrared divergences with aid of the
complex mass of the top quark. A comparison of QCD corrections with those
computed by the conventional method is presented both for top production and
decays. For s channel production we give an analytic proof of equivalence of
the two methods in the limit of low top width.


  We use atomistic-based simulations to investigate the behavior of
ferromagnetic skyrmions being continuously compressed against a rigid wall
under dc and ac drives. The compressed skyrmions can be annihilated close to
the wall and form a conformal crystal with both a size and a density gradient,
making it distinct from conformal crystals observed previously for
superconducting vortices and colloidal particles. For both dc and ac driving,
the skyrmions can move transverse to the compression direction due to a
combination of density and size gradients. Forces in the compression direction
are converted by the Magnus force into transverse motion. Under ac driving, the
amount of skyrmion annihilation is reduced and we find a skyrmion Magnus
ratchet pump. We also observe shear banding in which skyrmions near the wall
move up to twice as fast as skyrmions further from the wall. When we vary the
magnitude of the applied drive, we find a critical current above which the
skyrmions are completely annihilated during a time scale that depends on the
magnitude of the drive. By varying the magnetic parameters, we find that the
transverse motion is strongly dependent on the skyrmion size. Smaller skyrmions
are more rigid, which interferes with the size gradient and destroys the
transverse motion. We also confirm the role of the size gradient by comparing
our atomistic simulations with a particle-based model, where we find that the
transverse motion is only transient. Our results are relevant for applications
where skyrmions encounter repulsive magnetic walls, domain walls, or
interfaces.


  We study the orbit of a single particle moving under the Yukawa potential and
observe the precessing ellipse type orbits. The amount of precession can be
tuned through the coupling parameter $\alpha$. With a suitable choice of the
coupling parameter; we can get a closed bound orbit. In some cases we have
observed some petals which can also have a closed bound nature with an
appropriate choice of the coupling constant. A threshold energy has also been
calculated for the boundness of the orbits.


  The consistent theory of the Heisenberg quantum antiferromagnet in the
disordered phase with short range antiferromagnetic order was developed on the
basis of the path integral for the spin coherent states. We have presented the
Lagrangian of the theory in a form which is explicitly invariant under
rotations and have found natural variables in the term of which one can
construct a natural perturbation theory. The short wave spin fluctuations are
similar to the spin wave theory ones, and the long wave spin fluctuations are
governed by the nonlinear sigma model. We have also demonstrated that the short
wave spin fluctuations have to be considered accurately in the framework of the
discrete version in time of the path integral. In the framework of our approach
we have obtained the response function for the spin fluctuations for the whole
region of the frequency $\omega$ and the wave vector ${\bf k}$ and have
calculated the free energy of the system.


  The relaxation rate of a Maxwellian velocity distribution function that has
an initially anisotropic temperature $(T_\parallel \neq T_\perp)$ is an
important physical process in space and laboratory plasmas. It is also a
canonical example of an energy transport process that can be used to test
theory. Here, this rate is evaluated using molecular dynamics simulations of
the one-component plasma. Results are compared with the predictions of four
kinetic theories; two treating the weakly coupled regime (1) the Landau
equation, and (2) the Lenard-Balescu equation, and two that attempt to extend
the theory into the strongly coupled regime (3) the effective potential theory
and (4) the generalized Lenard-Balescu theory. The role of dynamic screening is
studied, and is found to have a negligible influence on this transport rate.
Oscillations and a delayed relaxation onset in the temperature profiles are
observed at strong coupling, which are not described by the kinetic theories.


  There are many analogies between codes, lattices, and vertex operator
algebras. For example, extremal objects are good examples of combinatorial,
spherical, and conformal designs. In this study, we investigated these objects
from the aspect of design theory.


  We study analytically and experimentally certain symplectic and
time-reversible N-body integrators which employ a Kepler solver for each
pair-wise interaction, including the method of Hernandez & Bertschinger (2015).
Owing to the Kepler solver, these methods treat close two-body interactions
correctly, while close three-body encounters contribute to the truncation error
at second order and above. The second-order errors can be corrected to obtain a
fourth-order scheme with little computational overhead. We generalise this map
to an integrator which employs a Kepler solver only for selected interactions
and yet retains fourth-order accuracy without backward steps. In this case,
however, two-body encounters not treated via a Kepler solver contribute to the
truncation error.


  This thesis deals with shape optimization for contact mechanics. More
specifically, the linear elasticity model is considered under the small
deformations hypothesis, and the elastic body is assumed to be in contact
(sliding or with Tresca friction) with a rigid foundation. The mathematical
formulations studied are two regularized versions of the original variational
inequality: the penalty formulation and the augmented Lagrangian formulation.
In order to get the shape derivatives associated to those two
non-differentiable formulations, we suggest an approach based on directional
derivatives. Especially, we derive sufficient conditions for the solution to be
shape differentiable. This allows to develop a gradient-based topology
optimization algorithm, built on these derivatives and a level-set
representation of shapes. The algorithm also benefits from a mesh-cutting
technique, which gives an explicit representation of the shape at each
iteration, and enables to apply the boundary conditions strongly on the contact
zone. The different steps of the method are detailed. Then, to validate the
approach, some numerical results on two-dimensional and three-dimensional
benchmarks are presented.


  Computational modeling is widely used to study how humans and organizations
search and solve problems in fields such as economics, management, cultural
evolution, and computer science. We argue that current computational modeling
research on human problem-solving needs to address several fundamental issues
in order to generate more meaningful and falsifiable contributions. Based on
comparative simulations and a new type of visualization of how to assess the
nature of the fitness landscape, we address two key assumptions that approaches
such as the NK framework rely on: that the NK captures the continuum of the
complexity of empirical fitness landscapes, and that search behavior is a
distinct component, independent from the topology of the fitness landscape. We
show the limitations of the most common approach to conceptualize how complex,
or rugged, a landscape is, as well as how the nature of the fitness landscape
is fundamentally intertwined with search behavior. Finally, we outline broader
implications for how to simulate problem-solving.


  In a multiple testing framework, we propose a method that identifies the
interval with the highest estimated false discovery rate of P-values and
rejects the corresponding null hypotheses. Unlike the Benjamini-Hochberg
method, which does the same but over intervals with an endpoint at the origin,
the new procedure `scans' all intervals. In parallel with
\citep*{storey2004strong}, we show that this scan procedure provides strong
control of asymptotic false discovery rate. In addition, we investigate its
asymptotic false non-discovery rate, deriving conditions under which it
outperforms the Benjamini-Hochberg procedure. For example, the scan procedure
is superior in power-law location models.


  We propose minimum empirical divergence (MED) policy for the multiarmed
bandit problem. We prove asymptotic optimality of the proposed policy for the
case of finite support models. In our setting, Burnetas and Katehakis has
already proposed an asymptotically optimal policy. For choosing an arm our
policy uses a criterion which is dual to the quantity used in Burnetas and
Katehakis. Our criterion is easily computed by a convex optimization technique
and has an advantage in practical implementation. We confirm by simulations
that MED policy demonstrates good performance in finite time in comparison to
other currently popular policies.


  Searching for controllable topological phase by means of external stimuli in
two-dimensional (2D) material-based van der Waals (vdW) heterostructures is
currently an active field for both the underlying physics and practical
applications. Here, using first-principles calculations, we investigate
electric-field-modulated topological phase transition in a vdW heterobilayer
formed by vertically stacking 2D AlSb and InSe monolayers. The AlSb/InSe
heterobilayer studied possesses both dynamical and thermal stabilities, which
is a direct bandgap semiconductor and forms a Z-scheme heterojunction. With
inclusion of spin-orbit coupling (SOC) and applying external electric field,
the bandgap decreases at first and then increase, and a trivial insulator to
topological insulator phase transition is observed. For the topological
insulator phase, band inversion is ascribed to the strong SOC of p orbitals of
Sb. Our work paves the way for the design and application of multifunctional
nanoscale devices such as topological field effect transistor.


  Factor graphs are graphical models used to represent a wide variety of
problems across robotics, such as Structure from Motion (SfM), Simultaneous
Localization and Mapping (SLAM) and calibration. Typically, at their core, they
have an optimization problem whose terms only depend on a small subset of
variables. Factor graph solvers exploit the locality of problems to drastically
reduce the computational time of the Iterative Least-Squares (ILS) methodology.
Although extremely powerful, their application is usually limited to
unconstrained problems. In this paper, we model constraints over variables
within factor graphs by introducing a factor graph version of the method of
Lagrange Multipliers. We show the potential of our method by presenting a full
navigation stack based on factor graphs. Differently from standard navigation
stacks, we can model both optimal control for local planning and localization
with factor graphs, and solve the two problems using the standard ILS
methodology. We validate our approach in real-world autonomous navigation
scenarios, comparing it with the de facto standard navigation stack implemented
in ROS. Comparative experiments show that for the application at hand our
system outperforms the standard nonlinear programming solver Interior-Point
Optimizer (IPOPT) in runtime, while achieving similar solutions.


  The well established macroscopic-microscopic (mac-mic) description of nuclear
fission enables the prediction of fission fragment yields for a broad range of
fissioning systems. In this work, we present several key enhancements to this
approach. We improve upon the microscopic sector of nuclear potential energy
surfaces by magnifying the resolution of the Lipkin-Nogami equations and
strengthening the Strutinsky procedure, thus reducing spurious effects from the
continuum. We further present a novel deterministic method for calculating
fission dynamics under the assumption of strongly damped nucleonic motion. Our
technique directly determines the evolution of the scissioned shape
distribution according to the number of random walk steps rather than the
statistical accumulation of fission events. We show that our new technique is
equivalent to the Metropolis random walk pioneered over the past decade by
Randrup and colleagues. It further improves upon it, as we remove the need for
altering the nuclear landscape via a biased potential. With our final
improvement, we calculate fission fragments mass and charge distributions using
particle number projection, which affords the simultaneous calculation of both
mass and charge yield distributions. Fission fragments are thus calculated from
the quantum mechanical $A$-body states of the potential energy surface rather
than the collective mass asymmetry variable ($\alpha_{\rm g}$) of the
Finite-Range Liquid-Drop Model (FRLDM) used in past work. We highlight the
success of our enhancements by predicting the odd-even staggering and the
charge polarization for the neutron-induced fission of ${}^{233}$U and
${}^{235}$U.


  The analysis of complex networks permeates all sciences, from biology to
sociology. A fundamental, unsolved problem is how to characterize the community
structure of a network. Here, using both standard and novel benchmarks, we show
that maximization of a simple global parameter, which we call Surprise (S),
leads to a very efficient characterization of the community structure of
complex synthetic networks. Particularly, S qualitatively outperforms the most
commonly used criterion to define communities, Newman and Girvan's modularity
(Q). Applying S maximization to real networks often provides natural,
well-supported partitions, but also sometimes counterintuitive solutions that
expose the limitations of our previous knowledge. These results indicate that
it is possible to define an effective global criterion for community structure
and open new routes for the understanding of complex networks.


  The uncertainty on measurements, given by the Heisenberg principle, is a
quantum concept usually not taken into account in General Relativity. From a
cosmological point of view, several authors wonder how such a principle can be
reconciled with the Big Bang singularity, but, generally, not whether it may
affect the reliability of cosmological measurements. In this letter, we express
the {Compton mass} as a function of the cosmological redshift. The cosmological
application of the indetermination principle unveils the differences of the
Hubble-Lema\^{i}tre constant value, $H_0$, as measured from the Cepheids
estimates and from the Cosmic Microwave Background radiation constraints. In
conclusion, the $H_0$ tension could be related to the effect of indetermination
derived in comparing a kinematic with a dynamic measurement.


  The aim of this work is to model the evolution of the cosmic space based on
thermodynamical parameters. The universe is considered to have an apparent
horizon radius with a Kodama-Hayward temperature assigned to it. The method is
founded on the fact proposed by Padmanabhan [1,2] that the subtraction of the
surface and bulk degrees of freedom provides information on the cosmic space
emergence. The fact of the matter is that in this approach the Raychaudhuri
equation could even be obtained by the consideration of only thermodynamical
parameters. As such, the standard general relativity is taken as the starting
point where by implementing the standard cosmological equations we obtain a
generalized evolutionary equation supporting emergence of the cosmic space. The
method proposed in this work would provide basis for other cosmological models
to have an emergent perspective.


  We study soliton solutions of matrix "good" Boussinesq equations, generated
via a binary Darboux transformation. Essential features of these solutions are
revealed via their "tropical limit", as exploited in previous work about the KP
equation. This limit associates a point particle interaction picture with a
soliton (wave) solution.


  We propose that charge gradient resulting in the coexisting
magneto-resistance and-capacitance tunability in material systems. We have
experimentally observed coexisting of tunable magneto-resistance and
-capacitance in Sm2Ga2Fe2O9. Our model fits well with the experimental result.


  This paper re-introduces the network reliability polynomial - introduced by
Moore and Shannon in 1956 -- for studying the effect of network structure on
the spread of diseases. We exhibit a representation of the polynomial that is
well-suited for estimation by distributed simulation. We describe a collection
of graphs derived from Erd\H{o}s-R\'enyi and scale-free-like random graphs in
which we have manipulated assortativity-by-degree and the number of triangles.
We evaluate the network reliability for all these graphs under a reliability
rule that is related to the expected size of a connected component. Through
these extensive simulations, we show that for positively or neutrally
assortative graphs, swapping edges to increase the number of triangles does not
increase the network reliability. Also, positively assortative graphs are more
reliable than neutral or disassortative graphs with the same number of edges.
Moreover, we show the combined effect of both assortativity-by-degree and the
presence of triangles on the critical point and the size of the smallest
subgraph that is reliable.


  We trace the assembly history of red galaxies since z=1, by measuring their
evolving space density with the B-band luminosity function. Our sample of 39599
red galaxies, selected from 6.96 square degrees of imaging from the NOAO Deep
Wide-Field and Spitzer IRAC Shallow surveys, is an order of magnitude larger,
in size and volume, than comparable samples in the literature. We measure a
higher space density of z=0.9 red galaxies than some of the recent literature,
in part because we account for the faint yet significant galaxy flux which
falls outside of our photometric aperture. The B-band luminosity density of red
galaxies, which effectively measures the evolution of ~L* galaxies, increases
by only 36 percent from z=0 to z=1. If red galaxy stellar populations have
faded by 1.24 B-band magnitudes since z=1, the stellar mass contained within
the red galaxy population has roughly doubled over the past 8 Gyr. This is
consistent with star-forming galaxies being transformed into ~L* red galaxies
after a decline in their star formation rates. In contrast, the evolution of
4L* red galaxies differs only slightly from a model with negligible star
formation and no galaxy mergers since z=1. If this model approximates the
luminosity evolution of red galaxy stellar populations, then 80 percent of the
stellar mass contained within today's 4L* red galaxies was already in place at
z=0.7. While red galaxy mergers have been observed, such mergers do not produce
rapid growth of 4L* red galaxy stellar masses between z=1 and the present day.


  We report preliminary results of a search for CPT and Lorentz violation in
B0-B0bar oscillations using an inclusive dilepton sample collected by the BABAR
experiment at the PEP-II B Factory. Using a sample of 232 million BBbar pairs,
we search for time-dependent variations in the complex CPT parameter z = z0 +
z1*cos(Omega*t^ + phi) where Omega is the Earth's sidereal frequency and t^ is
sidereal time. We measure Im(z0) = (-14.1 +- 7.3(stat) +- 2.4(syst)) x 10E-3,
DeltaGamma*Re(z0) = (-7.2 +- 4.1(stat) +- 2.1(syst)) x 10E-3 ps-1, Im(z1) =
(-24.0 +- 10.7(stat) +- 5.9(syst)) x 10E-3, and DeltaGamma*Re(z1) = (-18.8 +-
5.5(stat) +- 4.0(syst)) x 10E-3 ps-1, where DeltaGamma is the difference
between the decay rates of the neutral B mass eigenstates. The statistical
correlation between the measurements of Im(z0) and DeltaGamma*Re(z0) is 76%;
between Im(z1) and DeltaGamma*Re(z1) it is 79%. These results are used to
evaluate expressions involving coefficients for Lorentz and CPT violation in
the general Lorentz-violating standard-model extension. In a complementary
approach, we examine the spectral power of periodic variations in z over a wide
range of frequencies and find no significant signal.


  Interacting particle or agent systems that display a rich variety of swarming
behaviours are ubiquitous in science and engineering. A fundamental and
challenging goal is to understand the link between individual interaction rules
and swarming. In this paper, we study the data-driven discovery of a
second-order particle swarming model that describes the evolution of $N$
particles in $\mathbb{R}^d$ under radial interactions. We propose a learning
approach that models the latent radial interaction function as Gaussian
processes, which can simultaneously fulfill two inference goals: one is the
nonparametric inference of {the} interaction function with pointwise
uncertainty quantification, and the other one is the inference of unknown
scalar parameters in the non-collective friction forces of the system. We
formulate the learning problem as a statistical inverse problem and provide a
detailed analysis of recoverability conditions, establishing that a coercivity
condition is sufficient for recoverability. Given data collected from $M$ i.i.d
trajectories with independent Gaussian observational noise, we provide a
finite-sample analysis, showing that our posterior mean estimator converges in
a Reproducing kernel Hilbert space norm, at an optimal rate in $M$ equal to the
one in the classical 1-dimensional Kernel Ridge regression. As a byproduct, we
show we can obtain a parametric learning rate in $M$ for the posterior marginal
variance using $L^{\infty}$ norm, and the rate could also involve $N$ and $L$
(the number of observation time instances for each trajectory), depending on
the condition number of the inverse problem. Numerical results on systems that
exhibit different swarming behaviors demonstrate efficient learning of our
approach from scarce noisy trajectory data.


  The formation of clusters in nuclear matter is investigated, which occurs
e.g. in low energy heavy ion collisions or core-collapse supernovae. In
astrophysical applications, the excluded volume concept is commonly used for
the description of light clusters. Here we compare a phenomenological excluded
volume approach to two quantum many-body models, the quantum statistical model
and the generalized relativistic mean field model. All three models contain
bound states of nuclei with mass number A <= 4. It is explored to which extent
the complex medium effects can be mimicked by the simpler excluded volume
model, regarding the chemical composition and thermodynamic variables.
Furthermore, the role of heavy nuclei and excited states is investigated by use
of the excluded volume model. At temperatures of a few MeV the excluded volume
model gives a poor description of the medium effects on the light clusters, but
there the composition is actually dominated by heavy nuclei. At larger
temperatures there is a rather good agreement, whereas some smaller differences
and model dependencies remain.


  Similarly to the interaction lagrangian, the possible boundary conditions in
quantum field theories on space-time manifolds with boundaries are strongly
constrained by the symmetry and scaling properties of the theory. Based on this
general insight, a lattice formulation of the QCD Schr\"odinger functional is
proposed for the case where the lattice Dirac operator in the bulk of the
lattice coincides with the Neuberger--Dirac operator. The construction
satisfies all basic requirements (locality, symmetries, hermiticity) and is
suitable for numerical simulations.


  A distributed denial-of-service (DDoS) attack can flood a victim site with
malicious traffic, causing service disruption or even complete failure.
Public-access sites like amazon or ebay are particularly vulnerable to such
attacks, because they have no way of a priori blocking unauthorized traffic.
  We present Active Internet Traffic Filtering (AITF), a mechanism that
protects public-access sites from highly distributed attacks by causing
undesired traffic to be blocked as close as possible to its sources. We
identify filters as a scarce resource and show that AITF protects a significant
amount of the victim's bandwidth, while requiring from each participating
router a number of filters that can be accommodated by today's routers. AITF is
incrementally deployable, because it offers a substantial benefit even to the
first sites that deploy it.


  What is the nature of tunnelling? This yet unanswered question is as
pertinent today as it was at the dawn of quantum mechanics. This article
presents a cross section of current perspectives on the interpretation,
computational modelling, and numerical investigation of tunnelling processes in
attosecond physics as debated in the Quantum Battles in Attoscience virtual
workshop 2020.


  We show the complete integrability of N=2 nonstandard KP flows establishing
the biHamiltonian structures. One of Hamiltonian structures is shown to be
isomorphic to the nonlinear N=2 $\hat W_{\infty}$ algebra with the bosonic
sector having $\hat W_{1+\infty}\oplus \hat W_{\infty}$ structure. A consistent
free field representation of the super conformal algebra is obtained. The
bosonic generators are found to be an admixture of free fermions and free
complex bosons, unlike the linear one. The fermionic generators become
exponential in free fields, in general.


  We construct, in the work, chiral $SU(3)$ Lagrangian with $D$ mesons of spin
$J^P=0^-$ and $J^P=1^-$ and charmed baryons of spin $J^P=1/2^+$ and
$J^P=3/2^+$. There are 42 leading two-body counter-terms involving two charmed
baryon fields and two $D$ meson fields in the constructed Lagrangian. The
heavy-quark spin symmetry leads to 35 sum rules while the large-$N_c$ operator
analysis predicts 29 ones at the next-to leading order of $1/N_c$ expansion.
The combination of the sum rules from both the heavy-quark symmetry and the
large-$N_c$ analysis results in 38 independent sum rules which reduces the
number of free parameters in the chiral Lagrangian down to 4 only. This is a
remarkable result demonstrating the consistency of the heavy-quark symmetry and
large-$N_c$ operator analysis.


  The Furstenberg recurrence theorem (or equivalently, Szemer\'edi's theorem)
can be formulated in the language of von Neumann algebras as follows: given an
integer $k \geq 2$, an abelian finite von Neumann algebra $(\M,\tau)$ with an
automorphism $\alpha: \M \to \M$, and a non-negative $a \in \M$ with
$\tau(a)>0$, one has $\liminf_{N \to \infty} \frac{1}{N} \sum_{n=1}^N \Re
\tau(a \alpha^n (a) ... \alpha^{(k-1)n} (a)) > 0$; a subsequent result of Host
and Kra shows that this limit exists. In particular, $\Re \tau(a \alpha^n (a)
>... \alpha^{(k-1)n} (a)) > 0$ for all $n$ in a set of positive density.
  From the von Neumann algebra perspective, it is thus natural to ask to what
extent these results remain true when the abelian hypothesis is dropped. All
three claims hold for $k = 2$, and we show in this paper that all three claims
hold for all $k$ when the von Neumann algebra is asymptotically abelian, and
that the last two claims hold for $k=3$ when the von Neumann algebra is
ergodic. However, we show that the first claim can fail for $k=3$ even with
ergodicity, the second claim can fail for $k \geq 4$ even assuming ergodicity,
and the third claim can fail for $k=3$ without ergodicity, or $k \geq 5$ and
odd assuming ergodicity. The second claim remains open for non-ergodic systems
with $k=3$, and the third claim remains open for ergodic systems with $k=4$.


  We introduce $L^2$-Alexander torsions for 3-manifolds, which can be viewed as
a generalization of the $L^2$-Alexander polynomial of Li--Zhang. We state the
$L^2$-Alexander torsions for graph manifolds and we partially compute them for
fibered manifolds. We furthermore show that given any irreducible 3-manifold
there exists a coefficient system such that the corresponding $L^2$-torsion
detects the Thurston norm.


  We give a Hecke algebra derivation of Macdonald's expansion formula for
Hall-Littlewood polynomials in terms of semistandard Young tableaux. This is
accomplished by first obtaining a Hecke algebra lift of the expansion
coefficients and then proving a generalization of Klostermann's recursions.


  We compute classical and first quantum finite-size corrections to the
recently found giant magnon solutions in two different subspaces of
$\mathbb{CP}^3$. We use the L\"{u}scher approach on the recently proposed exact
S-matrix for $\mathcal{N}=6$ superconformal Chern-Simons theory. We compare our
results with the string and algebraic curve computations and find agreement,
thus providing a non-trivial test for the new $AdS_4/CFT_3$ correspondence
within an integrability framework.


  The availability of representative datasets is an essential prerequisite for
many successful artificial intelligence and machine learning models. However,
in real life applications these models often encounter scenarios that are
inadequately represented in the data used for training. There are various
reasons for the absence of sufficient data, ranging from time and cost
constraints to ethical considerations. As a consequence, the reliable usage of
these models, especially in safety-critical applications, is still a tremendous
challenge. Leveraging additional, already existing sources of knowledge is key
to overcome the limitations of purely data-driven approaches. Knowledge
augmented machine learning approaches offer the possibility of compensating for
deficiencies, errors, or ambiguities in the data, thus increasing the
generalization capability of the applied models. Even more, predictions that
conform with knowledge are crucial for making trustworthy and safe decisions
even in underrepresented scenarios. This work provides an overview of existing
techniques and methods in the literature that combine data-driven models with
existing knowledge. The identified approaches are structured according to the
categories knowledge integration, extraction and conformity. In particular, we
address the application of the presented methods in the field of autonomous
driving.


  Recently, learned image compression techniques have achieved remarkable
performance, even surpassing the best manually designed lossy image coders.
They are promising to be large-scale adopted. For the sake of practicality, a
thorough investigation of the architecture design of learned image compression,
regarding both compression performance and running speed, is essential. In this
paper, we first propose uneven channel-conditional adaptive coding, motivated
by the observation of energy compaction in learned image compression. Combining
the proposed uneven grouping model with existing context models, we obtain a
spatial-channel contextual adaptive model to improve the coding performance
without damage to running speed. Then we study the structure of the main
transform and propose an efficient model, ELIC, to achieve state-of-the-art
speed and compression ability. With superior performance, the proposed model
also supports extremely fast preview decoding and progressive decoding, which
makes the coming application of learning-based image compression more
promising.


  Two spectral triples are introduced for a class of fractals in R^n. The
definitions of noncommutative Hausdorff dimension and noncommutative tangential
dimensions, as well as the corresponding Hausdorff and Hausdorff-Besicovitch
functionals considered in math.OA/0202108, are studied for the mentioned
fractals endowed with these spectral triples, showing in many cases their
correspondence with classical objects. In particular, for any limit fractal,
the Hausdorff-Besicovitch functionals do not depend on the generalized limit
procedure.


  We report on investigations of the chiral and deconfinement aspects of the
finite temperature transition in 2+1 flavor QCD using the Highly Improved
Staggered Quark (HISQ) action on lattices with temporal extent $N_\tau=6$ and
$N_\tau=8$. We have performed the calculations for physical values of the
strange quark mass $m_s$ and the light quark masses $m_l=0.2m_s$ and $0.05m_s$.
Several finite temperature observables, including the renormalized Polyakov
loop, the renormalized chiral condensate and the chiral susceptibility have
been calculated. We also study the fluctuations and correlations of different
conserved charges as well as the trace anomaly at finite temperature. We
compare our findings with previous calculations that use different improved
staggered fermion formulations: asqtad, p4 and stout.


  We have calculated and compared the three-body force effects on the
properties of nuclear matter under the gap and continuous choices for the
self-consistent auxiliary potential within the Brueckner-Hartree-Fock approach
by adopting the Argonne $V18$ and the Bonn B two-body potentials plus a
microscopic three-body force (TBF). The TBF provides a strong repulsive effect
on the equation of state of nuclear matter at high densities for both the gap
and continuous choices. The saturation point turns out to be much closer to the
empirical value when the continuous choice is adopted. In addition, the
dependence of the calculated symmetry energy upon the choice of the
self-consistent auxiliary potential is discussed.


  Although residential crowding has many well-being implications, its
connection to mental health is yet to be widely examined. Using survey data
from 1613 residents in Beijing, China, we find that living in a crowded place -
measured by both square metres per person and persons per bedroom - is
significantly associated with a higher risk of depression. We test for the
mechanisms of such associations and find that the residential
crowding-depression link arises through increased living space-specific stress
rather than increased life stress. We also identify the following subgroups
that have relatively stronger residential crowding-depression associations:
females, those living with children, those not living with parents, and those
living in non-market housing units. Our findings show that inequality in living
space among urban residents not only is an important social justice issue but
also has health implications.


  Given a free unitary quantum group $G=A_u(F)$, with $F$ not a unitary
$2$-by-$2$ matrix, we show that the Martin boundary of the dual of $G$ with
respect to any $G$-$\hat G$-invariant, irreducible, finite range quantum random
walk coincides with the topological boundary defined by Vaes and Vander Vennet.
This can be thought of as a quantum analogue of the fact that the Martin
boundary of a free group coincides with the space of ends of its Cayley tree.


  We investigate the topology of a double cover of a complex affine plane
branching along a nodal real line arrangement. We define certain topological
2-cycles in the double plane using the real structure of the arrangement, and
calculate their intersection numbers.


  Reconfigurable intelligent surfaces (RISs) have tremendous potential to boost
communication performance, especially when the line-of-sight (LOS) path between
the user equipment (UE) and base station (BS) is blocked. To control the RIS,
channel state information (CSI) is needed, which entails significant pilot
overhead. To reduce this overhead and the need for frequent RIS
reconfiguration, we propose a novel framework for integrated localization and
communications, where RIS configurations are fixed during location coherence
intervals, while BS precoders are optimized every channel coherence interval.
This framework leverages accurate location information obtained with the aid of
several RISs as well as novel RIS optimization and channel estimation methods.
Performance in terms of localization accuracy, channel estimation error, and
achievable rate demonstrates the effectiveness of the proposed approach.


  Connected and autonomous vehicles (CAVs) have recently attracted a
significant amount of attention both from researchers and industry. Numerous
studies targeting algorithms, software frameworks, and applications on the CAVs
scenario have emerged. Meanwhile, several pioneer efforts have focused on the
edge computing system and architecture design for the CAVs scenario and
provided various heterogeneous platform prototypes for CAVs. However, a
standard and comprehensive application benchmark for CAVs is missing, hindering
the study of these emerging computing systems. To address this challenging
problem, we present CAVBench, the first benchmark suite for the edge computing
system in the CAVs scenario. CAVBench is comprised of six typical applications
covering four dominate CAVs scenarios and takes four datasets as standard
input. CAVBench provides quantitative evaluation results via application and
system perspective output metrics. We perform a series of experiments and
acquire three systemic characteristics of the applications in CAVBench. First,
the operation intensity of the applications is polarized, which explains why
heterogeneous hardware is important for a CAVs computing system. Second, all
applications in CAVBench consume high memory bandwidth, so the system should be
equipped with high bandwidth memory or leverage good memory bandwidth
management to avoid the performance degradation caused by memory bandwidth
competition. Third, some applications have worse data/instruction locality
based on the cache miss observation, so the computing system targeting these
applications should optimize the cache architecture. Last, we use the CAVBench
to evaluate a typical edge computing platform and present the quantitative and
qualitative analysis of the benchmarking results.


  Photon-mediated interactions in subwavelength atomic arrays have numerous
applications in quantum science. In this manuscript, we explore the potential
of three-level quantum emitters, or ``impurities" embedded in a two-dimensional
atomic array to serve as a platform for quantum computation. By exploiting the
altered behavior of impurities as a result of the induced dipole-dipole
interactions mediated by subwavelength array, we design and simulate a set of
universal quantum gates consisting of the $\sqrt{\text{iSWAP}}$ and
single-qubit rotations. We demonstrate that these gates have very high
fidelities due to the long atomic dipole-dipole coherence times, as long as the
atoms remain within a proximal range. Finally, we design and simulate quantum
circuits leading to the generation of the maximally entangled two-qubit Bell
states, as well as the entangled three-qubit GHZ state. These findings
establish subwavelength emitter arrays as an alternative platform for quantum
computation and quantum simulation.


  A string is the one-dimensional generalization of a point particle. In this
sense, the analog of a cloud of dust would be a cloud of strings. In this work,
we consider a cloud of strings around a regular solution in general gelativity.
We consider the Bardeen solution and the Simpson--Visser solution, analyzing
the consequences of the cloud in the regularity and in the energy conditions.
Actually, the presence of the cloud could make the energy density positive when
compared to the Simpson--Visser case. We verify that the usual Bardeen solution
becomes singular in the presence of the cloud of string while the
Simpson--Visser solution is still regular, violating the energy conditions, as
the usual solution. We also calculate some thermodynamic quantities to evaluate
how a cloud of strings influences the thermodynamics of the solutions.


  Adiabatic quantum computers are a promising platform for approximately
solving challenging optimization problems. We present a quantum approach to
solving the balanced $k$-means clustering training problem on the D-Wave 2000Q
adiabatic quantum computer. Existing classical approaches scale poorly for
large datasets and only guarantee a locally optimal solution. We show that our
quantum approach better targets the global solution of the training problem,
while achieving better theoretic scalability on large datasets. We test our
quantum approach on a number of small problems, and observe clustering
performance similar to the best classical algorithms.


  Let L^S(\pi,s,st) be a partial L-function of degree 7 of a cuspidal
automorphic representation \pi of the exceptional group G_2. Here we construct
a Rankin-Selberg integral for representations having certain Fourier
coefficient.


  Prediction algorithms typically assume the training data are independent
samples, but in many modern applications samples come from individuals
connected by a network. For example, in adolescent health studies of
risk-taking behaviors, information on the subjects' social network is often
available and plays an important role through network cohesion, the empirically
observed phenomenon of friends behaving similarly. Taking cohesion into account
in prediction models should allow us to improve their performance. Here we
propose a network-based penalty on individual node effects to encourage
similarity between predictions for linked nodes, and show that incorporating it
into prediction leads to improvement over traditional models both theoretically
and empirically when network cohesion is present. The penalty can be used with
many loss-based prediction methods, such as regression, generalized linear
models, and Cox's proportional hazard model. Applications to predicting levels
of recreational activity and marijuana usage among teenagers from the AddHealth
study based on both demographic covariates and friendship networks are
discussed in detail and show that our approach to taking friendships into
account can significantly improve predictions of behavior while providing
interpretable estimates of covariate effects.


  We work in the setting of Zermelo-Fraenkel set theory without assuming the
Axiom of Choice. We consider sets with the Boolean operations together with the
additional structure of comparing cardinality (in the Cantorian sense of
injections). What principles does one need to add to the laws of Boolean
algebra to reason not only about intersection, union, and complementation of
sets, but also about the relative size of sets? We give a complete
axiomatization.
  A particularly interesting case is when one restricts to the Dedekind-finite
sets. In this case, one needs exactly the same principles as for reasoning
about imprecise probability comparisons, the central principle being
Generalized Finite Cancellation (which includes, as a special case,
division-by-$m$). In the general case, the central principle is a restricted
version of Generalized Finite Cancellation within Archimedean classes which we
call Covered Generalized Finite Cancellation.


  Gradient structured (GS) metals processed by severe plastic deformation
techniques can be designed to achieve simultaneously high strength and high
ductility. Significant kinematic hardening is key to their excellent strain
hardening capacity which results in a favorable strength-ductility combination.
Unfortunately, no constitutive model has been established to simulate and
analyze the characteristic kinematic hardening behavior of GS metal to
understand the relationship between their microstructure and macroscopic
response. In this work, we developed a deformation-mechanismbased strain
gradient plasticity model considering the plasticity heterogeneities from the
grain to the sample scale. A back stress model, which accounts for the
dependency of dislocation pile-ups on grain size, is established to describe
the cyclic deformation properties of GS materials. The established model
unified the geometrically necessary dislocations accommodating internal
plasticity heterogeneities, the resulting back stress and reversible
dislocations during reverse loading into a strain gradient plasticity
framework, without introducing excessive numbers of independent material
parameters. A finite element implementation of the model quantitatively
predicts the uniaxial tensile and tensile-compressive responses of a GS copper
bar as well as of a reference sample with homogeneous grain size. It is found
that GS copper exhibits enhanced kinematic hardening which results mainly from
fine grains in the GS layer and contributes to the considerable ductility of
the GS material. The model allows to investigate the mechanical response and
optimize the properties of materials with various types of spatially
heterogeneous grain microstructures.


  Understanding smart grid cyber attacks is key for developing appropriate
protection and recovery measures. Advanced attacks pursue maximized impact at
minimized costs and detectability. This paper conducts risk analysis of
combined data integrity and availability attacks against the power system state
estimation. We compare the combined attacks with pure integrity attacks - false
data injection (FDI) attacks. A security index for vulnerability assessment to
these two kinds of attacks is proposed and formulated as a mixed integer linear
programming problem. We show that such combined attacks can succeed with fewer
resources than FDI attacks. The combined attacks with limited knowledge of the
system model also expose advantages in keeping stealth against the bad data
detection. Finally, the risk of combined attacks to reliable system operation
is evaluated using the results from vulnerability assessment and attack impact
analysis. The findings in this paper are validated and supported by a detailed
case study.


  The unsteady motion of a gas-liquid interface, such as during splashing or
atomization, often results in complex liquid structures embedded in the ambient
fluid. Here we explore the use of skeletonization to identify the minimum
amount of information needed to describe their geometry. We skeletonize a
periodic liquid jet by a modification of a recently introduced approach to
coarsen multiphase flows while retaining a sharp interface. The process
consists of diffusing an index function and at the same time moving the
interfaces with it, until they "collapse" into each other and form skeletons.
The skeleton represents the basic topology of the jet and we also keep track of
how much the interface is moved (or how much volume is "accumulated") during
the process, which can be used to approximately reconstruct the jet. We explore
various quantitative measures to characterize and distinguish the skeletons.
Those include standard morphometrics such as branch length distribution, after
segmenting the skeletons into branches, and a more sophisticated representation
of the skeleton structures called Topology Morphology Descriptor (TMD), to
obtain an "equivalent" description of the skeletons by retaining information
about the topology in a compact way.


  This paper presents the first application of the direct parametrisation
method for invariant manifolds to a fully coupled multiphysics problem
involving the nonlinear vibrations of deformable structures subjected to an
electrostatic field. The formulation proposed is intended for model order
reduction of electrostatically actuated resonating Micro-Electro-Mechanical
Systems (MEMS). The continuous problem is first rewritten in a manner that can
be directly handled by the parametrisation method, which relies upon automated
asymptotic expansions. A new mixed fully Lagrangian formulation is thus
proposed which contains only explicit polynomial nonlinearities, which is then
discretised in the framework of finite element procedures. Validation is
performed on the classical parallel plate configuration, where different
formulations using either the general framework, or an approximation of the
electrostatic field due to the geometric configuration selected, are compared.
Reduced-order models along these formulations are also compared to full-order
simulations operated with a time integration approach. Numerical results show a
remarkable performance both in terms of accuracy and wealth of nonlinear
effects that can be accounted for. In particular, the transition from hardening
to softening behaviour of the primary resonance while increasing the constant
voltage component of the electric actuation, is recovered. Secondary resonances
leading to superharmonic and parametric resonances are also investigated with
the reduced-order model.


  In this note we first set up an analogy between spin and vorticity of a
perfect 2d-fluid flow, based on the Borel-Weil contruction of the irreducible
unitary representations of SU(2), and looking at the Madelung-Bohm velocity
attached to the ensuing spin wave functions. We also show that, in the
framework of finite dimensional geometric quantum mechanics, the Schr\"odinger
velocity field on projective Hilbert space is divergence-free (being Killing
with respect to the Fubini-Study metric) and fulfils the stationary Euler
equation, with pressure proportional to the Hamiltonian uncertainty (squared).
We explicitly compute the pressure gradient of this "Schr\"odinger fluid" and
determine its critical points. Its vorticity is also calculated and shown to
depend on the spacings of the energy levels. These results follow from
hydrodynamical properties of Killing vector fields valid in any (finite
dimensional) Riemannian manifold, of possible independent interest.


  We consider a classical problem in choice theory -- vote aggregation -- using
novel distance measures between permutations that arise in several practical
applications. The distance measures are derived through an axiomatic approach,
taking into account various issues arising in voting with side constraints. The
side constraints of interest include non-uniform relevance of the top and the
bottom of rankings (or equivalently, eliminating negative outliers in votes)
and similarities between candidates (or equivalently, introducing diversity in
the voting process). The proposed distance functions may be seen as weighted
versions of the Kendall $\tau$ distance and weighted versions of the Cayley
distance. In addition to proposing the distance measures and providing the
theoretical underpinnings for their applications, we also consider algorithmic
aspects associated with distance-based aggregation processes. We focus on two
methods. One method is based on approximating weighted distance measures by a
generalized version of Spearman's footrule distance, and it has provable
constant approximation guarantees. The second class of algorithms is based on a
non-uniform Markov chain method inspired by PageRank, for which currently only
heuristic guarantees are known. We illustrate the performance of the proposed
algorithms for a number of distance measures for which the optimal solution may
be easily computed.


  Serre and Stark found a basis for the space of modular forms of weight 1/2 in
terms of theta series. In this paper, we generalize their result - under
certain mild restrictions on the level and character - to the case of weight
1/2 Hilbert modular forms over a totally real field of narrow class number 1.
The methods broadly follow those of Serre-Stark; however we are forced to
overcome technical difficulties which arise when we move out of Q.


  This paper considers the problem of designating navigation goal locations for
interactive mobile robots. We propose a point-and-click interface, implemented
with an Augmented Reality (AR) headset. The cameras on the AR headset are used
to detect natural pointing gestures performed by the user. The selected goal is
visualized through the AR headset, allowing the users to adjust the goal
location if desired. We conduct a user study in which participants set
consecutive navigation goals for the robot using three different interfaces: AR
Point & Click, Person Following and Tablet (birdeye map view). Results show
that the proposed AR Point&Click interface improved the perceived accuracy,
efficiency and reduced mental load compared to the baseline tablet interface,
and it performed on-par to the Person Following method. These results show that
the AR Point\&Click is a feasible interaction model for setting navigation
goals.


  The Astro-E2 high resolution X-Ray Spectrometer (XRS) is expected to provide
a major enhancement in study of clusters of galaxies. Astro-E2 is the fifth
Japanese X-ray astronomy observatory, which is scheduled for launch in early
2005. The XRS instrument, developed under a Japan-US collaboration, is an X-ray
microcalorimeter with a capability of observing extended objects, and a high
energy resolution of about 6 eV at 6 keV. The spectral resolving power is 20
times higher than CCDs over the 0.5-10 keV energy band. We have obtained
several new results of clusters with Chandra and XMM, which show that
high-resolution imaging spectroscopy can clarify some outstanding questions.
New sciences from Astro-E2 include the first clear measurement of gas
velocities, determination of ion and electron temperatures, and electron
densities based on the resolved line features. We will describe the XRS
instrument design, and present simulations of the expected performance.


  Finite-Size-Scaling and Conformal Invariance are used in order to find the
phase diagram and critical exponents of a quantum spin chain with spin $S=3/2$.
The model has a tetracritical point besides critical lines. The conformal
anomaly and anomalous dimensions of some primary operators are calculated at
the tetracritical point.


  This article offers an empirical exploration on the use of character-level
convolutional networks (ConvNets) for text classification. We constructed
several large-scale datasets to show that character-level convolutional
networks could achieve state-of-the-art or competitive results. Comparisons are
offered against traditional models such as bag of words, n-grams and their
TFIDF variants, and deep learning models such as word-based ConvNets and
recurrent neural networks.