  We present direct evidence, from Adaptive-Optics near-infra-red imaging, of
the jets in the Galactic microquasar SS433 interacting with enhanced
wind-outflow off the accretion disc that surrounds the black hole in this
system. Radiant quantities of gas are transported significant distances away
from the black hole approximately perpendicular to the accretion disc from
which the wind emanates. We suggest that the material that comprised the
resulting "bow-tie" structure is associated with a major flare that the system
exhibited ten months prior to the observations. During this flare, excess
matter was expelled by the accretion disc as an enhanced wind, which in turn is
"snow-ploughed", or propelled, out by the much faster jets that move at
approximately a quarter of the speed of light. Successive instances of such
bow-ties may be responsible for the large-scale X-ray cones observed across the
W50 nebula by ROSAT.


  In this work we revisit five different point sources within or behind galaxy
clusters in order to constrain the coupling constant between axion-like
particles (ALPs) and photons. We use three distinct machine learning (ML)
techniques and compare our results with a standard $\chi^2$ analysis. For the
first time we apply approximate Bayesian computation to searches for ALPs and
find consistently good performance across ML classifiers. Further, we apply
more realistic 3D magnetic field simulations of galaxy clusters and compare our
results with previously used 1D simulations. We find constraints on the
ALP-photon coupling at the level of state-of-the-art bounds with
$g_{a\gamma\gamma} \lesssim 0.6 \times 10^{-12}$ GeV${}^{-1}$, hence improving
on previous constraints obtained from the same observations.


  Recently, a new and efficient algorithm (the LLR method) has been proposed
for computing densities of states in statistical systems and gauge theories. In
this talk, we explore whether this novel density of states method can be
applied to numerical computations of observables in systems for which the
action is complex. To this purpose, we introduce a generalised density of
states, in terms of which integrals of oscillating observables can be
determined semi-analytically, and we define a strategy to compute it with the
LLR method. As a case study, we apply these ideas to the Z(3) spin model at
finite density, finding a remarkable agreement of our results for the phase
twist with those obtained with the worm algorithm for all explored chemical
potentials, including values for which there are cancellations over sixteen
orders of magnitude. These findings open new perspectives for dealing with the
sign problem on physically more relevant systems.


  The decohering environment of a quantum bit is often described by the
coupling to a large bath of spins. The quantum bit itself can be seen as a spin
$S=1/2$ which is commonly called the central spin. The resulting central spin
model describes an important mechanism of decoherence. We provide
mathematically rigorous bounds for a persisting magnetization of the central
spin in this model with and without magnetic field. In particular, we show that
there is a well defined limit of infinite number of bath spins. Only if the
fraction of very weakly coupled bath spins tends to 100\% does no magnetization
persist.


  Modern big data applications integrate data from various sources. As a
result, these datasets may not satisfy perfect constraints, leading to sparse
schema information and non-optimal query performance. The existing approach of
PatchIndexes enable the definition of approximate constraints and improve query
performance by exploiting the materialized constraint information. As real
world data warehouse workloads are often not limited to read-only queries, we
enhance the PatchIndex structure towards an update-conscious design in this
paper. Therefore, we present a sharded bitmap as the underlying data structure
which offers efficient update operations, and describe approaches to maintain
approximate constraints under updates, avoiding index recomputations and full
table scans. In our evaluation, we prove that PatchIndexes significantly impact
query performance while achieving lightweight update support.


  We study the top forward-backward asymmetry (FBA $\equiv A_{\rm FB}$)
reported by CDF and D0 Collaborations in the effective lagrangian approach.
Using dimension-6 effective largrangians for $q \bar{q} \rightarrow t \bar{t}$,
we study the $t\bar{t}$ production cross section and the $A_{\rm FB}$, and a
few observables: the FB spin-spin correlation that is strongly correlated with
the $A_{\rm FB}$, and longitudinal top polarization as a new probe of chiral
structures for possible new physics scenarios.


  Sonodynamic therapy (SDT) has received a lot of interest due to its deep
tissue penetration and lack of invasiveness. However, SDT still prioritizes the
creation of highly effective, multifunctional, and biocompatible
sonosensitizers to improve the therapeutic efficiency. In this study, sodium
niobate (NaNbO3) nanosonosensitizers are rationed synthesized for SDT for the
first time. NaNbO3 nanosonosensitizers with semiconductor characteristics are
proved to generate large amounts of reactive oxygen species and induce cell
apoptosis under ultrasound irradiation. In vitro anti-tumor theranostic results
confirm the mitochondrial dysfunction-dependent death pathway. In vivo tumor
xenograft evaluation demonstrates that NaNbO3 will massively induce
cytotoxicity and tumor eradication under ultrasound irradiation. These results
provide the paradigm of the utilization of novel nanosonosensitizers as a
therapeutic nanoplatform in treating breast cancer cells.


  Corresponding to the concept of $p$-angular distance
$\alpha_p[x,y]:=\left\lVert\lVert x\rVert^{p-1}x-\lVert
y\rVert^{p-1}y\right\rVert$, we first introduce the notion of skew $p$-angular
distance $\beta_p[x,y]:=\left\lVert \lVert y\rVert^{p-1}x-\lVert
x\rVert^{p-1}y\right\rVert$ for non-zero elements of $x, y$ in a real normed
linear space and study some of significant geometric properties of the
$p$-angular and the skew $p$-angular distances. We then give some results
comparing two different $p$-angular distances with each other. Finally, we
present some characterizations of inner product spaces related to the
$p$-angular and the skew $p$-angular distances. In particular, we show that if
$p>1$ is a real number, then a real normed space $\mathcal{X}$ is an inner
product space, if and only if for any $x,y\in \mathcal{X}\smallsetminus{\lbrace
0\rbrace}$, it holds that $\alpha_p[x,y]\geq\beta_p[x,y]$.


  For over a decade, scientists at NASA's Jet Propulsion Laboratory (JPL) have
been recording measurements from the Martian surface as a part of the Mars
Exploration Rovers mission. One quantity of interest has been the opacity of
Mars's atmosphere for its importance in day-to-day estimations of the amount of
power available to the rover from its solar arrays. This paper proposes the use
of neural networks as a method for forecasting Martian atmospheric opacity that
is more effective than the current empirical model. The more accurate
prediction provided by these networks would allow operators at JPL to make more
accurate predictions of the amount of energy available to the rover when they
plan activities for coming sols.


  Here, we employ a numerical approach to investigate the transport and
conductance characteristics of a quantum point contact. A quantum point contact
is a narrow constriction of a width comparable to the electron wavelength
defined in a two-dimensional electron gas (2DEG) by means of split-gate or
etching technique. Their properties have been widely investigated in the
experiments. We define a quantum Hall based split-gate quantum point contact
with standard gate geometry. Firstly, we obtain the spatial distribution of
incompressible strips (current channels) by applying a self consistent
Thomas-Fermi method to a realistic heterostructure under quantized Hall
conditions. Later, time-dependent Schrodinger equation is solved for electrons
injected in the current channels. The transport characteristics and
time-evolutions are analyzed in the integer filling factor regime ({\nu} = 1)
with the single electron density. The results confirm that the current
direction in a realistic quantum point contact can be controllable with the
external interventions.


  Global Markov properties in mixed graphs are usually formulated in terms of
the path-oriented m-separation or by use of augmented graphs (similar to moral
graphs in the case of directed acyclic graphs). We provide an alternative
characterization that can be easily implemented.


  Deep learning models for semantic segmentation of images require large
amounts of data. In the medical imaging domain, acquiring sufficient data is a
significant challenge. Labeling medical image data requires expert knowledge.
Collaboration between institutions could address this challenge, but sharing
medical data to a centralized location faces various legal, privacy, technical,
and data-ownership challenges, especially among international institutions. In
this study, we introduce the first use of federated learning for
multi-institutional collaboration, enabling deep learning modeling without
sharing patient data. Our quantitative results demonstrate that the performance
of federated semantic segmentation models (Dice=0.852) on multimodal brain
scans is similar to that of models trained by sharing data (Dice=0.862). We
compare federated learning with two alternative collaborative learning methods
and find that they fail to match the performance of federated learning.


  Deep convolutional networks have achieved great success for visual
recognition in still images. However, for action recognition in videos, the
advantage over traditional methods is not so evident. This paper aims to
discover the principles to design effective ConvNet architectures for action
recognition in videos and learn these models given limited training samples.
Our first contribution is temporal segment network (TSN), a novel framework for
video-based action recognition. which is based on the idea of long-range
temporal structure modeling. It combines a sparse temporal sampling strategy
and video-level supervision to enable efficient and effective learning using
the whole action video. The other contribution is our study on a series of good
practices in learning ConvNets on video data with the help of temporal segment
network. Our approach obtains the state-the-of-art performance on the datasets
of HMDB51 ( $ 69.4\% $) and UCF101 ($ 94.2\% $). We also visualize the learned
ConvNet models, which qualitatively demonstrates the effectiveness of temporal
segment network and the proposed good practices.


  We perform a systematic study of commutative $SO(p)$ invariant matrix models
with quadratic and quartic potentials in the large $N$ limit. We find that the
physics of these systems depends crucially on the number of matrices with a
critical r\^ole played by $p=4$. For $p\leq4$ the system undergoes a phase
transition accompanied by a topology change transition. For $p> 4$ the system
is always in the topologically non-trivial phase and the eigenvalue
distribution is a Dirac delta function spherical shell. We verify our analytic
work with Monte Carlo simulations.


  Terahertz pulse generation by ultra-intense two-color laser fields ionizing
gases with near- to far-infrared carrier wavelength is studied from
particle-in-cell (PIC) simulations. For long wavelength ($10.6\ \mu$m)
promoting a large ratio of electron density over critical, photoionization is
shown to catastrophically enhance the plasma wakefield, causing a net downshift
in the optical spectrum and exciting THz fields with tens of GV/m amplitude in
the laser direction. This emission is accompanied by coherent transition
radiation (CTR) of comparable amplitude due to wakefield-driven electron
acceleration. We analytically evaluate the fraction of CTR energy up to 30 % of
the total radiated emission including the particle self-field and numerically
calibrate the efficiency of the matched blowout regime for electron densities
varied over three orders of magnitude.


  Tensor parameters that are amortized or regularized over large tensor powers,
often called "asymptotic" tensor parameters, play a central role in several
areas including algebraic complexity theory (constructing fast matrix
multiplication algorithms), quantum information (entanglement cost and
distillable entanglement), and additive combinatorics (bounds on cap sets,
sunflower-free sets, etc.). Examples are the asymptotic tensor rank, asymptotic
slice rank and asymptotic subrank. Recent works (Costa-Dalai,
Blatter-Draisma-Rupniewski, Christandl-Gesmundo-Zuiddam) have investigated
notions of discreteness (no accumulation points) or "gaps" in the values of
such tensor parameters.
  We prove a general discreteness theorem for asymptotic tensor parameters of
order-three tensors and use this to prove that (1) over any finite field (and
in fact any finite set of coefficients in any field), the asymptotic subrank
and the asymptotic slice rank have no accumulation points, and (2) over the
complex numbers, the asymptotic slice rank has no accumulation points.
  Central to our approach are two new general lower bounds on the asymptotic
subrank of tensors, which measures how much a tensor can be diagonalized. The
first lower bound says that the asymptotic subrank of any concise three-tensor
is at least the cube-root of the smallest dimension. The second lower bound
says that any concise three-tensor that is "narrow enough" (has one dimension
much smaller than the other two) has maximal asymptotic subrank.
  Our proofs rely on new lower bounds on the maximum rank in matrix subspaces
that are obtained by slicing a three-tensor in the three different directions.
We prove that for any concise tensor, the product of any two such maximum ranks
must be large, and as a consequence there are always two distinct directions
with large max-rank.


  Cosmic dust is a key tracer of structure formation and evolution in the
universe. In active galactic nuclei (AGN) the origin and role of dust are
uncertain. Here, we have studied dust in the X-ray bright and reddened type-1
quasar IC 4329A, which exhibits an ionised AGN wind. We incorporated
high-resolution X-ray and mid-IR spectroscopy, combined with broad-band
continuum modelling, to investigate the properties of dust in this AGN. We used
new Chandra HETGS observations taken in June 2017, as well as archival data
from XMM-Newton, Swift, HST, Spitzer, IRAS, and Herschel for our
IR-optical-UV-X-ray modelling. Two distinct components of dust in IC 4329A are
found. One component is in the interstellar medium (ISM) of the host galaxy,
and the other is a nuclear component in the AGN torus and its associated wind.
The emitting dust in the torus is evident in mid-IR emission (9.7 and 18 micron
features), while dust in the wind is present through both reddening and X-ray
absorption (O, Si, and Fe edge features). The gas depletion factors into dust
for O, Si, and Fe are measured. We derive an intrinsic reddening E(B-V) ~ 1.0,
which is most consistent with a grey (flat) extinction law. The AGN wind
consists of three ionisation components. From analysis of long-term changes in
the wind, we determine limits on the location of the wind components. The two
lowest ionisation components are likely carriers of dust from the AGN torus. We
find that the dust in the nuclear component of IC 4329A is different from dust
in the Milky Way. The dust grains in the AGN torus and wind are likely larger
than the standard Galactic dust, and are in a porous composite form (containing
amorphous silicate with iron and oxygen). This can be a consequence of grain
coagulation in the dense nuclear environment of the AGN.


  Inspired by our earlier semi-stochastic work aimed at converging high-level
coupled-cluster (CC) energetics [J. E. Deustua, J. Shen, and P. Piecuch, Phys.
Rev. Lett. 119, 223003 (2017); J. Chem. Phys. 154, 124103 (2021)], we propose a
novel form of the CC($P$;$Q$) theory in which the stochastic Quantum Monte
Carlo propagations, used to identify dominant higher-than-doubly excited
determinants, are replaced by the selected configuration interaction (CI)
approach using the CIPSI algorithm. The advantages of the resulting
CIPSI-driven CC($P$;$Q$) methodology are illustrated by a few molecular
examples, including the dissociation of $\mathrm{F_2}$ and the automerization
of cyclobutadiene, where we recover the electronic energies corresponding to
the CC calculations with a full treatment of singles, doubles, and triples
based on the information extracted from compact CI wave functions originating
from relatively inexpensive Hamiltonian diagonalizations.


  Inspired by the seminal, ground-breaking work of Abrikosov in 1957, we
developed a new approximation to the interaction between two widely separated
superconducting vortices. In contrast with Abrikosov's, we take into account
the finite size of the vortices and their internal magnetic profile. We
consider the vortices to be embedded within a superconducting, infinitely long
hollow cylinder, in order to simplify the symmetry and boundary conditions for
the mathematical analysis. We study this system in the context of a magnetic
Ginzburg-Landau functional theory, by solving for the magnetic field profile
inside each vortex, as well as in the superconducting region, subject to
physical boundary conditions inspired by the classical analogue of two mutually
inducting coils. Under isothermal conditions, the effective force between these
vortices is given by the gradient of the Helmholtz free energy constructed from
the Ginzburg-Landau functional. From our results, we explicitly show that, in
agreement with well established theoretical arguments and experiments, the
interaction between widely separated vortices is repulsive in this context, and
their equilibrium positions are constrained by the fluxoid's conservation.
Moreover, we find that the equilibrium positions of the vortices centers are
stable due to the convexity of the Helmholtz free energy profile. Remarkably,
the effect of the boundaries of the region over the effective interaction
between the vortices is important in the chosen geometric configuration.


  We present an overview of our ongoing systematic search for wide (sub)stellar
companions around the stars known to host rad-vel planets. By using a
relatively large field of view and going very deep our survey can find all
directly detectable stellar and brown dwarf companions (m>40 Mjup) within a
1000 AU orbit.


  We classify six-dimensional F-theory compactifications in terms of simple
features of the divisor structure of the base surface of the elliptic
fibration. This structure controls the minimal spectrum of the theory. We
determine all irreducible configurations of divisors ("clusters") that are
required to carry nonabelian gauge group factors based on the intersections of
the divisors with one another and with the canonical class of the base. All 6D
F-theory models are built from combinations of these irreducible
configurations. Physically, this geometric structure characterizes the gauge
algebra and matter that can remain in a 6D theory after maximal Higgsing. These
results suggest that all 6D supergravity theories realized in F-theory have a
maximally Higgsed phase in which the gauge algebra is built out of summands of
the types su(3), so(8), f_4, e_6, e_8, e_7, (g_2 + su(2)), and su(2) + so(7) +
su(2), with minimal matter content charged only under the last three types of
summands, corresponding to the non-Higgsable cluster types identified through
F-theory geometry. Although we have identified all such geometric clusters, we
have not proven that there cannot be an obstruction to Higgsing to the minimal
gauge and matter configuration for any possible F-theory model. We also
identify bounds on the number of tensor fields allowed in a theory with any
fixed gauge algebra; we use this to bound the size of the gauge group (or
algebra) in a simple class of F-theory bases.


  A pulse-and-hold technique is used to measure the switching of small critical
current Josephson junctions. This technique allows one to achieve a good binary
detection and therefore measure switching probabilities. The technique
overcomes limitations on simple square pulses and allows for the measurement of
junctions with critical currents of the order of 10nA with bias pulses of the
order of 100ns. A correlation analysis of the switching events is performed to
show how the switching probability depends on the wait time between repeated
bias pulses.


  An analysis on the damped quantum search by exploring the rate at which the
target state is obtained. The results were compared with that of the classical
search since the standard Grover's algorithm does not give a convergent result
if the number of target state is unknown. For a large number of target states,
the classical and the damped quantum search give a similar result. However, for
intermediate values of the target size the damped quantum search gives a higher
probability of success than the classical search. Furthermore, we also made an
analysis on the average number of iterations needed to obtain at least one of
the target states. As the number of target states is reduced, the damped
quantum search gives a better result than the classical search. The results
coincide if the size of target state is comparable to the size of the sample.


  The past two decades have witnessed the rapid growth of our knowledge of the
X-ray Universe thanks to flagship X-ray space observatories like XMM-Newton and
Chandra. A significant portion of discoveries would have been impossible
without the X-ray diffractive grating spectrometers aboard these two space
observatories. We briefly overview the physical principles of diffractive
grating spectrometers as the background to the beginning of a new era with the
next-generation (diffractive and non-diffractive) high-resolution X-ray
spectrometers. This chapter focuses on the Reflection Grating Spectrometer
aboard XMM-Newton, which provides high-quality high-resolution spectra in the
soft X-ray band. Its performance and excellent calibration quality have allowed
breakthrough advancements in a wide range of astrophysical topics. For the
benefit of new learners, we illustrate how to reduce RGS imaging, timing, and
spectral data.


  We study linear contextual bandits with access to a large, confounded,
offline dataset that was sampled from some fixed policy. We show that this
problem is closely related to a variant of the bandit problem with side
information. We construct a linear bandit algorithm that takes advantage of the
projected information, and prove regret bounds. Our results demonstrate the
ability to take advantage of confounded offline data. Particularly, we prove
regret bounds that improve current bounds by a factor related to the visible
dimensionality of the contexts in the data. Our results indicate that
confounded offline data can significantly improve online learning algorithms.
Finally, we demonstrate various characteristics of our approach through
synthetic simulations.


  The most efficient way to pack equally sized spheres isotropically in 3D is
known as the random close packed state, which provides a starting point for
many approximations in physics and engineering. However, the particle size
distribution of a real granular material is never monodisperse. Here we present
a simple but accurate approximation for the random close packing density of
hard spheres of any size distribution, based upon a mapping onto a
one-dimensional problem. To test this theory we performed extensive simulations
for mixtures of elastic spheres with hydrodynamic friction. The simulations
show a general (but weak) dependence of the final (essentially hard sphere)
packing density on fluid viscosity and on particle size, but this can be
eliminated by choosing a specific relation between mass and particle size,
making the random close packed volume fraction well-defined. Our theory agrees
well with the simulations for bidisperse, tridisperse and log-normal
distributions, and correctly reproduces the exact limits for large size ratios.


  Sequence theories are an extension of theories of strings with an infinite
alphabet of letters, together with a corresponding alphabet theory (e.g. linear
integer arithmetic). Sequences are natural abstractions of extendable arrays,
which permit a wealth of operations including append, map, split, and
concatenation. In spite of the growing amount of tool support for theories of
sequences by leading SMT-solvers, little is known about the decidability of
sequence theories, which is in stark contrast to the state of the theories of
strings. We show that the decidable theory of strings with concatenation and
regular constraints can be extended to the world of sequences over an alphabet
theory that forms a Boolean algebra, while preserving decidability. In
particular, decidability holds when regular constraints are interpreted as
parametric automata (which extend both symbolic automata and variable
automata), but fails when interpreted as register automata (even over the
alphabet theory of equality). When length constraints are added, the problem is
Turing-equivalent to word equations with length (and regular) constraints.
Similar investigations are conducted in the presence of symbolic transducers,
which naturally model sequence functions like map, split, filter, etc. We have
developed a new sequence solver, SeCo, based on parametric automata, and show
its efficacy on two classes of benchmarks: (i) invariant checking on
array-manipulating programs and parameterized systems, and (ii) benchmarks on
symbolic register automata.


  We define new invariants of knots by means of quandle colorings and
longitudinal information. These invariants can be applied to a tangle embedding
problem and recognizing non-classical virtual knots.


  This paper describes a series of automated data validation tests for datasets
detailing charity financial information, political donations, and government
lobbying in Canada. We motivate and document a series of 200 tests that check
the validity, internal consistency, and external consistency of these datasets.
We present preliminary findings after application of these tests to the
political donations ($\approx10.1$ million observations) and lobbying
($\approx711,200$ observations) datasets, and to a sample of $\approx380,880$
observations from the charities datasets. We conclude with areas for future
work and lessons learnt for others looking to implement automated data
validation in their own workflows.


  We study heterogeneous quantities that efficiently cross-correlate the
lensing information encoded in CMB polarization and large-scale structures
recovered from weak lensing galaxy surveys. These quantities allow us to take
advantage of the special features of weak lensing effect on CMB B-polarization
and of the high (40%) cross-correlation between the two data sets. We show that
these objects are robust to filtering effects, have a low intrinsic cosmic
variance (around 8% for small 100 square degrees surveys) and can be used as an
original constraint on the vacuum energy density.


  We show that centrality dependence of charged particle pseudorapidity density
at midrapidity in Au+Au collisions at RHIC is well described as proportional to
We show that centrality dependence of charged particle pseudorapidity density
at midrapidity in Au+Au collisions at RHIC is well described as proportional to
the number of participating constituent quarks. In this approach there is no
need for an additional contribution from hard processes usually considered in
the models based on the number of the nucleon participants.


  We study the impact of explicit chiral symmetry breaking of Wilson fermions
on mesonic correlators in the epsilon-regime using Wilson chiral perturbation
theory (WChPT). We generalize the epsilon-expansion of continuum ChPT to
nonzero lattice spacings for various quark mass regimes. It turns out that the
corrections due to a nonzero lattice spacing are highly suppressed for typical
quark masses of the order aLambda_QCD^2. The lattice spacing effects become
more pronounced for smaller quark masses and lead to non-trivial corrections of
the continuum ChPT results at next-to-leading order. We compute these
corrections for the standard current and density correlation functions. A fit
to lattice data shows that these corrections are small, as expected.


  Rectangular TVS-cone metric spaces are introduced and Kannan's fixed point
theorem is proved in these spaces. Two approaches are followed for the proof.
At first we prove the theorem by a direct method using the structure of the
space itself. Secondly, we use the nonlinear scalarization used recently by
Wei-Shih Du in [A note on cone metric fixed point theory and its equivalence,
{Nonlinear Analysis},72(5),2259-2261 (2010).] to prove the equivalence of the
Banach contraction principle in cone metric spaces and usual metric spaces. The
proof is done without any normality assumption on the cone of the locally
convex topological vector space, and hence generalizing several previously
obtained results.


  The spontaneous symmetry breaking of rotational O(N) symmetry in
noncommutative field theory is investigated in a 2+1 dimensional model of
scalar fields coupled through a combination of quartic and sextuple
self-interactions. There are five possible orderings of the fields in the
sextuple interaction and two for the quartic interaction. At one loop, we prove
that for some choices of these orderings there is the absence of IR/UV mixing
and the appearance of massless excitations. A supersymmetric extension of the
model is also studied. Supersymmetry puts additional constraints on the
couplings but for any given N there is a Moyal ordering of the superfields for
which the requirement for the existence of Goldstone bosons is satisfied. For
some ordering and when N goes to infinity we find evidence that the model is
renormalizable to all orders in perturbation theory. We also consider a generic
chiral model in 3+1 dimensions whose superpotential is invariant under local
gauge transformations. We find that for any value of N there is no one loop
correction to the pion mass and that, at two loops, there are no pion mass
corrections for slowly varying superfields so that Goldstone theorem holds
true. We also find a new purely noncommutative coupling which gives
contributions starting at order N-2 loops.


  This paper studies cache-aided interference networks with arbitrary number of
transmitters and receivers, whereby each transmitter has a cache memory of
finite size. Each transmitter fills its cache memory from a content library of
files in the placement phase. In the subsequent delivery phase, each receiver
requests one of the library files, and the transmitters are responsible for
delivering the requested files from their caches to the receivers. The
objective is to design schemes for the placement and delivery phases to
maximize the sum degrees of freedom (sum-DoF) which expresses the capacity of
the interference network at the high signal-to-noise ratio regime. Our work
mainly focuses on a commonly used uncoded placement strategy. We provide an
information-theoretic bound on the sum-DoF for this placement strategy. We
demonstrate by an example that the derived bound is tighter than the bounds
existing in the literature for small cache sizes. We propose a novel delivery
scheme with a higher achievable sum-DoF than those previously given in the
literature. The results reveal that the reciprocal of sum-DoF decreases
linearly as the transmitter cache size increases. Therefore, increasing cache
sizes at transmitters translates to increasing the sum-DoF and, hence, the
capacity of the interference networks.


  In this letter we point out that the massive gravity theory with a graviton
ghost mode in de Sitter background cannot possess a de Sitter invariant vacuum
state. In order to avoid a negative norm state, we must associate the creation
operator of the ghost mode with a negative-energy mode function instead of a
positive-energy one as the mode function. Namely, we have to adopt a different
procedure of quantization for a ghost. When a theory has a symmetry mixing a
ghost mode with ordinary non-ghost modes, the choice of a ghost mode is not
unique. However, quantization of a ghost is impossible without specifying a
choice of ghost mode, which breaks the symmetry. For this reason, the vacuum
state cannot respect the symmetry. In the massive gravity theory with a
graviton ghost mode in de Sitter background, the ghost is the helicity-0 mode
of the graviton. This ghost mode is mixed with the other helicity graviton
modes under the action of de Sitter symmetry. Therefore, there is no de Sitter
invariant vacuum in such models. This leads to an interesting possibility that
non-covariant cutoff of the low energy effective theory may naturally arise. As
a result, the instability due to the pair production of a ghost and normal
non-ghost particles gets much milder and that the model may escape from being
rejected.


  Neutron scattering measurements have demonstrated that the heavily Cu-doped
NaFe$_{1-x}$Cu$_{x}$As compound behaves like a Mott insulator exhibiting both
real space Fe-Cu stripes, as well as antiferromagnetism below a N\'eel
temperature for $x\lesssim 0.5$. We have investigated evolution of structural
and magnetic ordering using $^{23}$Na and $^{75}$As NMR for single crystals
($x$ = 0.39 and 0.48), confirming antiferromagnetism in the form of magnetic
stripes. We show that end-chain defects in these stripes are the principal
source of magnetic disorder and are responsible for cluster spin-glass
transitions in both compounds, in the latter case coexistent with
antiferromagnetism. Aided by our numerical simulation of the $^{75}$As spectra,
we show that a staggered magnetization at the Fe sites is induced by
non-magnetic Cu dopants.


  The MINER$\nu$A TestBeam Detector calibrations will take place in the MTEST
facility at Fermilab. It will use a beam of hadrons between 300 and 1500 MeV/c
to analyze the response of the MINERvA detector components. The aim of the
present work is to design the beam while considering radiation hazards at the
hall. To accomplish this, we are using a Monte Carlo simulation based on Geant4
and actual data taken from measurements of the elements that make up the
beamline.


  Voting and assignment are two of the most fundamental settings in social
choice theory. For both settings, random serial dictatorship (RSD) is a
well-known rule that satisfies anonymity, ex post efficiency, and
strategyproofness. Recently, it was shown that computing the resulting
probabilities is #P-complete both in the voting and assignment setting. In this
paper, we study RSD from a parametrized complexity perspective. More
specifically, we present efficient algorithms to compute the RSD probabilities
under the condition that the number of agent types, alternatives, or objects is
bounded.


  In the light of the JEF(F) European project longstanding story according to
the determination of the most exact shape of the 239Pu(n, 2n)238Pu reaction
cross section and a recent measurement by Meot et al., this paper aims to shed
another light on this topic by bringing new theoretical feedback. To achieve
this goal, the AVXSF-LNG computer program has been upgraded to model
second-chance reactions using its decay-probability module and, then chained to
the TALYS-ECIS06 nuclear reaction system of codes. Present diligent calculation
of the (n,2n) cross section over the energy range from the threshold to the
onset of third-chance fission at about 12 MeV, suggests that current
evaluations under-estimate the 239Pu(n,2n) cross section below 10 MeV;
under-estimation of the order of 7% relatively to the JEFF-3.1 evaluation. On
this ground, we propose an upward correction to the normalization of the
measurement by Meot et al. Correction factor of about 1.24 with a maximum
uncertainty on present fitted model estimated to 11.6%. Latter value is
extracted from a sensitivity analysis of the calculation route to the level
density model that is selected for the non-equilibrated residual nucleus and to
alternative choices we can make in terms of neutron fission cross section
measurement references for the 238Pu and 239Pu target nuclei.


  We compute the one-loop quantum corrections to the gravitational potentials
of a spinning point particle in a de Sitter background, due to the vacuum
polarisation induced by conformal fields in an effective field theory approach.
We consider arbitrary conformal field theories, assuming only that the theory
contains a large number $N$ of fields in order to separate their contribution
from the one induced by virtual gravitons. The corrections are described in a
gauge-invariant way, classifying the induced metric perturbations around the de
Sitter background according to their behaviour under transformations on
equal-time hypersurfaces. There are six gauge-invariant modes: two scalar
Bardeen potentials, one transverse vector and one transverse traceless tensor,
of which one scalar and the vector couple to the spinning particle. The quantum
corrections consist of three different parts: a generalisation of the
flat-space correction, which is only significant at distances of the order of
the Planck length; a constant correction depending on the undetermined
parameters of the renormalised effective action; and a term which grows
logarithmically with the distance from the particle. This last term is the most
interesting, and when resummed gives a modified power law, enhancing the
gravitational force at large distances. As a check on the accuracy of our
calculation, we recover the linearised Kerr-de Sitter metric in the classical
limit and the flat-space quantum correction in the limit of vanishing Hubble
constant.


  The discriminantal arrangement $\mathcal{B}(n,k,\mathcal{A})$ has been
introduced by Manin and Schectman in 1989 and it consists of all non-generic
translates of a generic arrangement $\mathcal{A}$ of n hyperplanes in a
$k$-dimensional space. It is known that its combinatorics depends on the
original arrangement A which, following Bayer and Brandt [3], is called very
generic if the intersection lattice of the induced discriminantal arrangement
has maximum cardinality, non-very generic otherwise. While a complete
description of the combinatorics of $\mathcal{B}(n,k,\mathcal{A})$ when
$\mathcal{A}$ is very generic is known (see [2]), very few is known in the
non-very generic case. Even to provide examples of non very generic
arrangements proved to be a non-trivial task (see [17]). In this paper, we
characterize, classify and provide examples of non-very generic arrangements in
low dimension.


  We give a characterization of the graphs with at most three trivial
characteristic ideals. This implies the complete characterization of the
regular graphs whose critical groups have at most three invariant factors equal
to 1 and the characterization of the graphs whose Smith groups have at most 3
invariant factors equal to 1. We also give an alternative and simpler way to
obtain the characterization of the graphs whose Smith groups have at most 3
invariant factors equal to 1, and a list of minimal forbidden graphs for the
family of graphs with Smith group having at most 4 invariant factors equal to
1.


  We characterize the class of probability measures on a compact Kahler
manifold such that the associated Monge-Amp\`ere equation has a solution of
finite pluricomplex energy. Our results are also valid in the big cohomology
class setting.


  We report on radio timing observations of PSR J0210+5845 which reveal large
deviations from typical pulsar spin-down behaviour. We interpret these
deviations as being due to binary motion around the $V=13.5$ star 2MASS
J02105640$+$5845176, which is coincident in celestial position and distance
with the pulsar. Archival observations and new optical spectroscopy identify
this star as a B6V star with a temperature of $T_\mathrm{eff}\approx 14\,000$K
and a mass of $M_\mathrm{c}= 3.5$ to $3.8$M$_\odot$, making it the lowest mass
main-sequence star known orbiting a non-recycled pulsar. We found that the
timing observations constrain the binary orbit to be wide and moderately
eccentric, with an orbital period of $P_\mathrm{b}=47^{+40}_{-14}$yr and
eccentricity $e=0.46^{+0.10}_{-0.07}$. We predict that the next periastron
passage will occur between 2030 and 2034. Due to the low companion mass, we
find that the probability for a system with the properties of PSR J0210+5845
and its binary companion to survive the supernova is low. We show that a low
velocity and fortuitously directed natal kick is required for the binary to
remain bound during the supernova explosion, and argue that an electron-capture
supernova is a plausible formation scenario for the pulsar.


  In today's era of information disorder, many organizations are moving to
verify the veracity of news published on the web and social media. In
particular, some agencies are exploring the world of online media and, through
a largely manual process, ranking the credibility and transparency of news
sources around the world. In this paper, we evaluate two procedures for
assessing the risk of online media exposing their readers to m/disinformation.
The procedures have been dictated by NewsGuard and The Global Disinformation
Index, two well-known organizations combating d/misinformation via practices of
good journalism. Specifically, considering a fixed set of media outlets, we
examine how many of them were rated equally by the two procedures, and which
aspects led to disagreement in the assessment. The result of our analysis shows
a good degree of agreement, which in our opinion has a double value: it
fortifies the correctness of the procedures and lays the groundwork for their
automation.


  In this paper we review the current predictions of numerical simulations for
the origin and observability of the warm hot intergalactic medium (WHIM), the
diffuse gas that contains up to 50 per cent of the baryons at z~0. During
structure formation, gravitational accretion shocks emerging from collapsing
regions gradually heat the intergalactic medium (IGM) to temperatures in the
range T~10^5-10^7 K. The WHIM is predicted to radiate most of its energy in the
ultraviolet (UV) and X-ray bands and to contribute a significant fraction of
the soft X-ray background emission. While O VI and C IV absorption systems
arising in the cooler fraction of the WHIM with T~10^5-10^5.5 K are seen in
FUSE and HST observations, models agree that current X-ray telescopes such as
Chandra and XMM-Newton do not have enough sensitivity to detect the hotter
WHIM. However, future missions such as Constellation-X and XEUS might be able
to detect both emission lines and absorption systems from highly ionised atoms
such as O VII, O VIII and Fe XVII.


  We proved a conjecture of D. Freed that there are no non-trivial complete
special Kaehler manifolds.


  We study linearly ordered spaces which are Valdivia compact in their order
topology. We find an internal characterization of these spaces and we present a
counter-example disproving a conjecture posed earlier by the first author. The
conjecture asserted that a compact line is Valdivia compact if its weight does
not exceed aleph one, every point of uncountable character is isolated from one
side and every closed first countable subspace is metrizable. It turns out that
the last condition is not sufficient. On the other hand, we show that the
conjecture is valid if the closure of the set of points of uncountable
character is scattered. This improves an earlier result of the first author.


  Can the laws of physics be unified. One of the most puzzling challenges is to
reconcile physics and chemistry, where molecular physics meets condensed-matter
physics, resulting from the scaling effect and dynamic fluctuation of glassy
matter at the glass transition temperature. Pioneer of condensed-matter
physics, the Nobel Prize-winning physicist Philip Warren Anderson, wrote in
1995: The deepest and most interesting unsolved problem in condensed-matter
physics is probably the theory of the nature of glassy state and the glass
transition. In 2005, the question of 'what is the nature of glassy state' was
suggested as one of the greatest scientific conundrums over the next
quarter-century for Science's 125th anniversary. However, the nature of glassy
state and its connection to the glass transition have not been fully understood
owing to the interdisciplinary complexity of physics and chemistry, where they
are governed by the physical laws at condensed-matter and molecular scales,
respectively. Therefore, study on the glass transition becomes essential to
explore the working principles of scaling effect and dynamic fluctuation in
glassy matter, as well as further reconcile the interdisciplinary complexity of
physics and chemistry.


  We compare the dynamical properties of two galaxies at identical positions on
the Tully-Fisher relation, but with different surface brightnesses. We find
that the low surface brightness galaxy UGC 128 has a higher mass-to-light
ratio, and yet has lower mass densities than the high surface brightness galaxy
NGC 2403. This is true for the gas surface density, the stellar surface
density, and the total mass density.


  We show that non-Abelian lattice gauge fields can be simulated with a single
component ultra-cold atomic gas in an optical lattice potential. An optical
lattice can be viewed as a Bravais lattice with a $N$-point basis. An atom
located at different points of the basis can be considered as a {\it particle}
in different internal states. The appropriate engineering of tunneling
amplitudes of atoms in an optical lattice allows one to realize U$(N)$ gauge
potentials and control a mass of {\it particles} that experience such
non-Abelian gauge fields. We provide and analyze a concrete example of an
optical lattice configuration that allows for simulation of a static U(2) gauge
model with a constant Wilson loop and an adjustable mass of {\it particles}. In
particular, we observe that the non-zero mass creates large conductive gaps in
the energy spectrum, which could be important in the experimental detection of
the transverse Hall conductivity.


  We show that twisted doubled tori can be used to construct a general class of
worldsheet models describing non-geometric string backgrounds. By employing a
first order formulation of interacting chiral bosons, we first refine the
analysis on the general conditions of worldsheet Lorentz invariance and then
prove that twisted doubled tori provide good duality symmetric backgrounds.
Subsequently we apply our general analysis to several examples which enable us
to gain new insight on the difference between geometric, locally geometric and
genuine non-geometric backgrounds.


  The complementarity experiment reported in Bertet [{\it{et al.}} (2001),
{\it{Nature}} {\bf{411}}, 166.] is discussed. The role played by entanglement
in reaching the classical limit is pointed out. Dissipative and thermal effects
of the cavity are calculated and a simple modification of the experiment is
proposed in order to observe the progressive loss of the capacity of ``quantum
erasing''as a manifestation of the classical limit of quantum mechanics.


  This paper focuses on the joint multi-object tracking (MOT) and the estimate
of detection probability with the \emph{Poisson multi-Bernoulli mixture} (PMBM)
filter. In a majority of multi-object scenarios, the knowledge of detection
probability is usually uncertain, which is often estimated offline from the
training data. In such cases, online filtering is not allowed or believable,
otherwise, significate parameter mismatch will result in biased estimates
(state and cardinality of objects). Consequently, the ability of adaptively
estimating the detection probability is essential in practice. In this paper,
we detail how the detection probability can be estimated accompanied with the
state estimates. Besides, closed-form solutions to the proposed method are
derived by approximating the intensity of Poisson random finite set (RFS) to a
Beta-Gaussian mixture form and density of Bernoulli RFS to a single
Beta-Gaussian form. Simulation results show the effectiveness and superiority
of the proposed method.


  Let $G=Sp_{2n}(\mathbb{C})$, and $\mathfrak{N}$ be Kato's exotic nilpotent
cone. Following techniques used by Bezrukavnikov in [5] to establish a
bijection between $\Lambda^+$, the dominant weights for a simple algebraic
group $H$, and $\textbf{O}$, the set of pairs consisting of a nilpotent orbit
and a finite-dimensional irreducible representation of the isotropy group of
the orbit, we prove an analogous statement for the exotic nilpotent cone. First
we prove that dominant line bundles on the exotic Springer resolution
$\widetilde{\mathfrak{N}}$ have vanishing higher cohomology, and compute their
global sections using techniques of Broer. This allows to show that the direct
images of these dominant line bundles constitute a quasi-exceptional set
generating the category $D^b(Coh^G(\mathfrak{N}))$, and deduce that the
resulting $t$-structure on $D^b(Coh^G(\mathfrak{N}))$ coincides with the
perverse coherent $t$-structure. The desired result now follows from the
bijection between costandard objects and simple objects in the heart of this
$t$-structure on $D^b(Coh^G(\mathfrak{N}))$.


  Research on stochastic differential equations (SDE) involving both additive
and multiplicative noise has been extensive. In situations where the primary
process is driven by a multiplicative stochastic process, additive white noise
typically represents an intrinsic and unavoidable fast factor, including
phenomena like thermal fluctuations, inherent uncertainties in measurement
processes, or rapid wind forcing in ocean dynamics. This work focuses on a
significant class of such systems, particularly those characterized by linear
drift and multiplicative noise, extensively explored in the literature.
Conventionally, multiplicative stochastic processes are also treated as white
noise in existing studies. However, when considering colored multiplicative
noise, the emphasis has been on characterizing the far tails of the probability
density function (PDF), regardless of the spectral properties of the noise. In
the absence of additive noise and with a general colored multiplicative SDE,
standard perturbation approaches lead to a second-order PDE known as the
Fokker-Planck Equation (FPE), consistent with Fick's law. This investigation
unveils a notable departure from this standard behavior when introducing
additive white noise. At the leading order of the stochastic process strength,
perturbation approaches yield a \textit{third-order PDE}, irrespective of the
white noise intensity. The breakdown of the FPE further signifies the breakdown
of Fick's law. Additionally, we derive the explicit solution for the
equilibrium PDF corresponding to this third-order PDE Master Equation. Through
numerical simulations, we demonstrate significant deviations from outcomes
derived using the FPE obtained through the application of Fick's law.


  The purpose of this paper is to report on recent approaches to reconstruction
problems based on analog, or in other words, infinite-dimensional, image and
signal models. We describe three main contributions to this problem. First,
linear reconstructions from sampled measurements via so-called generalized
sampling (GS). Second, the extension of generalized sampling to inverse and
ill-posed problems. And third, the combination of generalized sampling with
sparse recovery techniques. This final contribution leads to a theory and set
of methods for infinite-dimensional compressed sensing, or as we shall also
refer to it, compressed sensing over the continuum.


  In this paper, we construct families of nonisometric hyperbolic orbifolds
that contain the same isometry classes of nonflat totally geodesic subspaces.
The main tool is a variant of the well-known Sunada method for constructing
length-isospectral Riemannian manifolds that handles totally geodesic
submanifolds of multiple codimensions simultaneously.


  Let $M$ be a surface with a Riemannian metric and $UM$ the unit tangent
bundle over $M$ with the canonical contact sub-Riemannian structure $D$ on
$UM$. In this paper, the complete local classification of singularities, under
the Legendre fibration $UM$ over $M$, is given for sub-Riemannian geodesics of
$(UM, D)$. Legendre singularities of sub-Riemannian geodesics are classified
completely also for another Legendre fibration from $UM$ to the space of
Riemannian geodesics on $M$. The duality on Legendre singularities is observed
related to the pendulum motion.


  Given a field $\{B(x)\}_{x\in\mathbf{Z}^d}$ of independent standard Brownian
motions, indexed by $\mathbf{Z}^d$, the generator of a suitable Markov process
on $\mathbf{Z}^d,\,\,\mathcal{G},$ and sufficiently nice function
$\sigma:[0,\infty)\to[0,\infty),$ we consider the influence of the parameter
$\lambda$ on the behavior of the system, \begin{align*}
  \rm{d} u_t(x) = & (\mathcal{G}u_t)(x)\,\rm{d} t + \lambda\sigma(u_t(x))\rm{d}
B_t(x)
  \qquad[t>0,\ x\in\mathbf{Z}^d],
  &u_0(x)=c_0\delta_0(x). \end{align*}
  We show that for any $\lambda>0$ in dimensions one and two the total mass
$\sum_{x\in\mathbf{Z}^d}u_t(x)\to 0$ as $t\to\infty$ while for dimensions
greater than two there is a phase transition point $\lambda_c\in(0,\infty)$
such that for $\lambda>\lambda_c,\, \sum_{\mathbf{Z}^d}u_t(x)\to 0$ as
$t\to\infty$ while for $\lambda<\lambda_c,\,\sum_{\mathbf{Z}^d}u_t(x)\not\to 0$
as $t\to\infty.$


  The astrometric and radial velocity techniques of extra-solar planet
detection attempt to detect the periodic reflex motion of the parent star by
extracting this periodic signal from a time-sampled set of observations. The
extraction is generally accomplished using periodogram analysis or the
functionally equivalent technique of Least Squares fitting of sinusoids. In
this paper, we use a Frequentist approach to examine the sensitivity of Least
Squares technique when applied to a combination of radial velocity and
astrometric observations. We derive a semi-analytical expression for the
sensitivity and show that the combined approach yields significantly better
sensitivity than either technique on its own. We discuss the ramifications of
this result to upcoming astrometric surveys with FAME, the Keck Interferometer,
and SIM.


  We show that on compact Riemann surfaces of nonpositive curvature, the
generalized periods, i.e. the $\nu$-th order Fourier coefficients of
eigenfunctions $e_\lambda$ over a closed smooth curve $\gamma$ which satisfies
a natural curvature condition, go to 0 at the rate of
$O((\log\lambda)^{-1/2})$, if $0<|\nu|/\lambda<1-\delta$, for any fixed
$0<\delta<1$. Our result implies, for instance, the generalized periods over
geodesic circles on any surfaces with nonpositive curvature would converge to
zero at the rate of $O((\log\lambda)^{-1/2})$. A direct corollary of our
results and the QER theorem of Toth and Zelditch is that for a geodesic circle
$\gamma$ on a compact hyperbolic surface, the restriction
$e_{\lambda_j}|_\gamma$ of an orthonormal basis $\{e_{\lambda_j}\}$ has a full
density subsequence that goes to zero in weak-$L^2(\gamma)$. One key step of
our proof is a microlocal decomposition of the measure over $\gamma$ into
tangential and transversal parts.


  In this work, we study the lepton flavor and lepton number violating $B_{c}$
meson decays via two intermediate on-shell Majorana neutrinos $N_j$ into two
charged leptons and a charged pion $B_{c}^{\pm} \to \mu^{\pm} \ N_j \to
\mu^{\pm} \tau^{\pm} \pi^{\mp}$. We evaluated the possibility to measure the
modulation of the decay width along the detector length produced as a
consequence of the lepton flavor violating process, in a scenario where the
heavy neutrinos masses range between $2.0$ GeV $\leq M_N \leq 6.0$ GeV. We
study some realistic conditions which could lead to the observation of this
phenomenon at futures $B$ factories such HL-LHCb.


  I show that the recent calculation of Moffatt's regarding the viscous
dissipation of a spinning coin overlooked the importance of the finite width of
the viscous boundary layer. My new estimates are more in accord with that
observed. I also point out that the frequency ``chirp'' of the specially
designed toy ``Euler's Disk'' is similar to that expected during the last few
minutes of the life of a coalescing binary of two neutron stars. As such, this
toy is an excellent desktop demonstration for the expected phenomena.


  To obtain a better understanding of the location and mechanisms for the
production of the gamma-ray emission in jets of AGN we present a detailed study
of the HST-1 structure, 0.8 arcsec downstream the jet of M87, previously
identified as a possible candidate for TeV emission. HST-1 shows a very
peculiar structure with superluminal as well as possible stationary
sub-components, and appears to be located in the transition from a parabolic to
a conical jet shape, presumably leading to the formation of a recollimation
shock. This scenario is supported by our new RHD simulations in which the
interaction of a moving component with a recollimation shock leads to the
appearance of a new superluminal component. To discern whether HST-1 is
produced by a recollimation shock or some other MHD instability, we present new
polarimetric 2.2 and 5 GHz VLBA, as well as 15, 22 and 43 GHz JVLA observations
obtained between November 2012 and March 2013.


  The Bose-Hubbard Hamiltonian describes the competition between superfluidity
and Mott insulating behavior at zero temperature and commensurate filling as
the strength of the on-site repulsion is varied. Gapped insulating phases also
occur at non-integer densities as a consequence of longer ranged repulsive
interactions. In this paper we explore the formation of gapped phases in
coupled chains due instead to anisotropies $t_x \neq t_y$ in the bosonic
hopping, extending the work of Crepin {\it et al.} [Phys. Rev. B 84, 054517
(2011)] on two coupled chains, where a gap was shown to occur at half filling
for arbitrarily small interchain hopping $t_y$. Our main result is that, unlike
the two-leg chains, for three- and four-leg chains, a charge gap requires a
finite nonzero critical $t_y$ to open. However, these finite values are
surprisingly small, well below the analogous values required for a fermionic
band gap to open.


  We introduce a HD DCC-HEAVY class of hierarchical-type factor models for
high-dimensional covariance matrices, employing the realized measures built
from higher-frequency data. The modelling approach features straightforward
estimation and forecasting schemes, independent of the cross-sectional
dimension of the assets under consideration, and accounts for sophisticated
asymmetric dynamics in the covariances. Empirical analyses suggest that the HD
DCC-HEAVY models have a better in-sample fit and deliver statistically and
economically significant out-of-sample gains relative to the existing
hierarchical factor model and standard benchmarks. The results are robust under
different frequencies and market conditions.


  Suzaku deep observations have discovered two highly significant nonthermal
X-ray sources, Suzaku J1804$-$2142 (Src 1) and Suzaku J1804$-$2140 (Src 2),
positionally coincident with the unidentified TeV $\gamma$-ray source, HESS
J1804$-$216. The X-ray sources are not time variable and show no counterpart in
other wavebands, except for the TeV source. Src 1 is unresolved at Suzaku
spatial resolution, whereas Src 2 is extended or composed of multiple sources.
The X-ray spectra are highly absorbed, hard, and featureless, and are well
fitted by absorbed power-law models with best-fit photon indices and absorption
columns of $-0.3_{-0.5}^{+0.5}$ and $0.2_{-0.2}^{+2.0}\times 10^{22}$ cm$^{-2}$
for Src 1, and $1.7_{-1.0}^{+1.4}$ and $1.1_{-0.6}^{+1.0}\times 10^{23}$
cm$^{-2}$ for Src 2. The measured X-ray absorption to the latter source is
significantly larger than the total Galactic neutral hydrogen column in that
direction. The unabsorbed 2--10 keV band luminosities are $7.5\times
10^{32}(d/{\rm 5 kpc})^2$ ergs s$^{-1}$ (Src 1) and $1.3\times 10^{33}(d/{\rm 5
kpc})^2$ ergs s$^{-1}$ (Src 2), where $d$ is the source distance. Among the
handful of TeV sources with known X-ray counterparts, HESS J1804$-$216 has the
largest ratio of TeV $\gamma$-ray to hard X-ray fluxes. We discuss the nature
of the emission and propose the Suzaku sources as plausible counterparts to the
TeV source, although further observations are necessary to confirm this.


  This article studies in detail the solution of an integral equation due to
Rongming et al. [13]. The methods involve complex analysis. As an application,
we find the ruin probability of a given Bonus-Malus system in a steady state.
We obtain closed form solutions for the ruin probability in certain cases, and
we characterize these cases. We give conditions for the Laplace transform of a
ruin probability to extend to a meromorphic function in the complex plane, we
prove a very general and almost sharp inequality of Lundberg type, and we
extend our results to a doubly stochastic situation.


  We introduce in an arbitrary supersymmetric version of the standard model
without elementary scalars a logarithmic operator which is irrelevant in the
limit in which all symmetries are respected. However through a dynamical
mechanism of the Nambu Jona Lasinio type this operator may produce two fermion
vacuum condensates that may account for electroweak and contribute to
supersymmetry breaking. Some of the phenomenological consequences of this
set-up are discussed.


  We define the notion of a piecewise linear map from a fan $\Sigma$ to
$\tilde{\mathfrak{B}}(G)$, the cone over the Tits building of a linear
algebraic group $G$. Let $X_\Sigma$ be a toric variety with fan $\Sigma$. We
show that when $G$ is reductive the set of integral piecewise linear maps from
$\Sigma$ to $\tilde{\mathfrak{B}}(G)$ classifies the isomorphism classes of
(framed) toric principal $G$-bundles on $X_\Sigma$. This in particular recovers
Klyachko's classification of toric vector bundles, and gives new classification
results for the orthogonal and symplectic toric principal bundles.


  We demonstrate that dispersion theory allows one to deduce crucial
information on $\pi\eta$ scattering from the final-state interactions of the
light mesons visible in the spectral distributions of the decays $\bar{B}^0_d
\to J/\psi(\pi^0\eta,K^+K^-,K^0\bar{K}^0)$. Thus high-quality measurements of
these differential observables are highly desired. The corresponding rates are
predicted to be of the same order of magnitude as those for $\bar{B}^0_d \to
J/\psi\pi^+\pi^-$ measured recently at LHCb, letting the corresponding
measurement appear feasible.


  Many causal parameters are linear functionals of an underlying regression.
The Riesz representer is a key component in the asymptotic variance of a
semiparametrically estimated linear functional. We propose an adversarial
framework to estimate the Riesz representer using general function spaces. We
prove a nonasymptotic mean square rate in terms of an abstract quantity called
the critical radius, then specialize it for neural networks, random forests,
and reproducing kernel Hilbert spaces as leading cases. Our estimators are
highly compatible with targeted and debiased machine learning with sample
splitting; our guarantees directly verify general conditions for inference that
allow mis-specification. We also use our guarantees to prove inference without
sample splitting, based on stability or complexity. Our estimators achieve
nominal coverage in highly nonlinear simulations where some previous methods
break down. They shed new light on the heterogeneous effects of matching
grants.


  Let $E$ be the essential part of the exceptional locus of a good resolution
of an isolated, log canonical singularity of index one. We describe the
dimension of the dual complex of $E$ in terms of the Hodge type of $H^{n-1}(E,
O_E)$, which is one of the main results of the paper [1] of Fujino. Our proof
uses only an elementary classical method, while Fujino's argument depends on
the recent development in minimal model theory.


  The Rossby mode (r-mode) perturbations in pulsars as a steady gravitational
wave (GW) sources have been explored. The time evolution and the intensity of
the emitted GWs in terms of the strain tensor amplitude have been estimated
with the approximation of slow rotation adopting the equation of state derived
using the Skyrme effective interaction with NRAPR parameter set. The core of
the neutron star has been considered to be $\beta$-equilibrated nuclear matter
composed of neutrons, protons, electrons and muons, which is surrounded by a
solid crust. Calculations have been made for the critical frequencies, the
evolution of frequencies and frequency change rates with time as well as the
fiducial viscous and gravitational timescales, across a broad spectrum of
pulsar masses. Our findings reveal that the r-mode instability region is
associated with rotating young and hot pulsars. Furthermore, it is noteworthy
that pulsars with low $L$ value emit gravitational radiation and fall within
the r-mode instability region if the primary dissipative mechanism is shear
viscosity along the crust-core interface boundary layer. The r-mode
perturbation amplitude increases because of GW emissions, in contrast to other
non-radial perturbations which transport to infinity the star's angular
momentum. Thus the presence of these stellar perturbations implies a
non-negative rate of change in transfer of rotational angular momentum. This
observation suggests that for a glitching pulsar, the GW emission intensity
evolves increasingly with time till the angular frequency diminishes to a value
that is below a crucial threshold, after which the compact star ceases to emit
radiation.


  Automatic text summarization (ATS) is an emerging technology to assist
clinicians in providing continuous and coordinated care. This study presents an
approach to summarize doctor-patient dialogues using generative large language
models (LLMs). We developed prompt-tuning algorithms to instruct generative
LLMs to summarize clinical text. We examined the prompt-tuning strategies, the
size of soft prompts, and the few-short learning ability of GatorTronGPT, a
generative clinical LLM developed using 277 billion clinical and general
English words with up to 20 billion parameters. We compared GatorTronGPT with a
previous solution based on fine-tuning of a widely used T5 model, using a
clinical benchmark dataset MTS-DIALOG. The experimental results show that the
GatorTronGPT- 20B model achieved the best performance on all evaluation
metrics. The proposed solution has a low computing cost as the LLM parameters
are not updated during prompt-tuning. This study demonstrates the efficiency of
generative clinical LLMs for clinical ATS through prompt tuning.


  In this paper, we consider the overdetermined problem for fully non linear
singular or degenerate elliptic operators in bounded smooth domains with both
Dirichlet and Neumann condition, as in the classical result of Serrin we prove
that the existence of nontrivial constant sign solution imply that the domain
is a ball.


  We maximize the expected utility of terminal wealth in an incomplete market
where there are cone constraints on the investor's portfolio process and the
utility function is not assumed to be strictly concave or differentiable. We
establish the existence of the optimal solutions to the primal and dual
problems and their dual relationship. We simplify the present proofs in this
area and extend the existing duality theory to the constrained nonsmooth
setting.


  A Convolutional Recurrent Neural Network (CRNN) is trained to reproduce the
evolution of the spinodal decomposition process in three dimensions as
described by the Cahn-Hilliard equation. A specialized, physics-inspired
architecture is proven to provide close accordance between the predicted
evolutions and the ground truth ones obtained via conventional integration
schemes. The method can closely reproduce the evolution of microstructures not
represented in the training set at a fraction of the computational costs.
Extremely long-time extrapolation capabilities are achieved, up to reaching the
theoretically expected equilibrium state of the system, despite the training
set containing only relatively-short, initial phases of the evolution.
Quantitative accordance with the decay rate of the Free energy is also
demonstrated up to late coarsening stages, providing an example of a
data-driven, physically consistent and high-accuracy Machine Learning method
for the long timescale simulation of materials.


  We study boundary conditions in N=4 super Yang-Mills theory that preserve
one-half the supersymmetry. The obvious Dirichlet boundary conditions can be
modified to allow some of the scalar fields to have a ``pole'' at the boundary.
The obvious Neumann boundary conditions can be modified by coupling to
additional fields supported at the boundary. The obvious boundary conditions
associated with orientifolds can also be generalized. In preparation for a
separate study of how electric-magnetic duality acts on these boundary
conditions, we explore moduli spaces of solutions of Nahm's equations that
appear in the presence of a boundary. Though our main interest is in boundary
conditions that are Lorentz-invariant (to the extent possible in the presence
of a boundary), we also explore non-Lorentz-invariant but half-BPS deformations
of Neumann boundary conditions. We make preliminary comments on the action of
electric-magnetic duality, deferring a more serious study to a later paper.


  We study the \k{appa}-Poincare and the Magueijo-Smolin (MS) DSR in the
context of the relative locality theory. This theory assigns connection,
torsion and curvature to momentum space of every modified theory beyond special
relativity. We obtain these quantities for the \k{appa}-Poincare and the MS DSR
in all order of the Planck length, at the every point of the momentum space.
The connection for the \k{appa}-Poincare theory and the MS DSR can be non-zero.
The torsion for the \k{appa}-Poincare theory can also be non-zero, but it is
zero for the MS DSR. The curvature for the \k{appa}-Poincare theory and the MS
DSR are zero. We will find that the non-zero torsion and curvature of the
momentum space implies a non-commutative spactime which is tangent to this
momentum space. Also, we show that the torsion for every Abelian DSR theory is
zero at the origin of the momentum space. At the end, we will discus dual
spacetime transformations for the \k{appa}-Poincare theory and MS-DSR.


  Communication between agents in collaborative multi-agent settings is in
general implicit or a direct data stream. This paper considers text-based
natural language as a novel form of communication between multiple agents
trained with reinforcement learning. This could be considered first steps
toward a truly autonomous communication without the need to define a limited
set of instructions, and natural collaboration between humans and robots.
Inspired by the game of Blind Leads, we propose an environment where one agent
uses natural language instructions to guide another through a maze. We test the
ability of reinforcement learning agents to effectively communicate through
discrete word-level symbols and show that the agents are able to sufficiently
communicate through natural language with a limited vocabulary. Although the
communication is not always perfect English, the agents are still able to
navigate the maze. We achieve a BLEU score of 0.85, which is an improvement of
0.61 over randomly generated sequences while maintaining a 100% maze completion
rate. This is a 3.5 times the performance of the random baseline using our
reference set.


  We study the large-volume-$L$ limit of form factors of the longitudinal spin
operators for the XXZ spin-$1/2$ chain in the massive regime. We find that the
individual form factors decay as $L^{-n}$, $n$ being an even integer counting
the number of physical excitations -- the holes -- that constitute the excited
state. Our expression allows us to derive the form-factor expansion of
two-point spin-spin correlation functions in the thermodynamic limit
$L\rightarrow +\infty$. The staggered magnetisation appears naturally as the
first term in this expansion. We show that all other contributions to the
two-point correlation function are exponentially small in the large-distance
regime.


  In this paper we prove that the compact Lie group $G_2$ admits a
left-invariant Einstein metric that is not geodesic orbit. In order to prove
the required assertion, we develop some special tools for geodesic orbit
Riemannian manifolds. It should be noted that a suitable metric is discovered
in a recent paper by I. Chrysikos and Y. Sakane, where the authors proved also
that this metric is not naturally reductive.


  In point cloud compression, exploiting temporal redundancy for inter
predictive coding is challenging because of the irregular geometry. This paper
proposes an efficient block-based inter-coding scheme for color attribute
compression. The scheme includes integer-precision motion estimation and an
adaptive graph based in-loop filtering scheme for improved attribute
prediction. The proposed block-based motion estimation scheme consists of an
initial motion search that exploits geometric and color attributes, followed by
a motion refinement that only minimizes color prediction error. To further
improve color prediction, we propose a vertex-domain low-pass graph filtering
scheme that can adaptively remove noise from predictors computed from motion
estimation with different accuracy. Our experiments demonstrate significant
coding gain over state-of-the-art coding methods.


  This paper proposes a method for fast scene radiance field reconstruction
with strong novel view synthesis performance and convenient scene editing
functionality. The key idea is to fully utilize semantic parsing and primitive
extraction for constraining and accelerating the radiance field reconstruction
process. To fulfill this goal, a primitive-aware hybrid rendering strategy was
proposed to enjoy the best of both volumetric and primitive rendering. We
further contribute a reconstruction pipeline conducts primitive parsing and
radiance field learning iteratively for each input frame which successfully
fuses semantic, primitive, and radiance information into a single framework.
Extensive evaluations demonstrate the fast reconstruction ability, high
rendering quality, and convenient editing functionality of our method.


  More than two years after its outbreak, the COVID-19 pandemic continues to
plague medical systems around the world, putting a strain on scarce resources,
and claiming human lives. From the very beginning, various AI-based COVID-19
detection and monitoring tools have been pursued in an attempt to stem the tide
of infections through timely diagnosis. In particular, computer audition has
been suggested as a non-invasive, cost-efficient, and eco-friendly alternative
for detecting COVID-19 infections through vocal sounds. However, like all AI
methods, also computer audition is heavily dependent on the quantity and
quality of available data, and large-scale COVID-19 sound datasets are
difficult to acquire -- amongst other reasons -- due to the sensitive nature of
such data. To that end, we introduce the COVYT dataset -- a novel COVID-19
dataset collected from public sources containing more than 8 hours of speech
from 65 speakers. As compared to other existing COVID-19 sound datasets, the
unique feature of the COVYT dataset is that it comprises both COVID-19 positive
and negative samples from all 65 speakers. We analyse the acoustic
manifestation of COVID-19 on the basis of these perfectly speaker
characteristic balanced `in-the-wild' data using interpretable audio
descriptors, and investigate several classification scenarios that shed light
into proper partitioning strategies for a fair speech-based COVID-19 detection.


  We study the dynamics of color fields as generated by simple configurations
of relativistic particles with Abelian and non-Abelian (SU(2)) charges in the
classical limit. We find that chromodynamic (non-Abelian) systems generally
show Coulomb-like features by analogy with electrodynamics. A peculiar feature
in the non-Abelian case is the additional strength of the chromoelectric and
chromomagnetic fields caused by the contribution of changing the color charge.
This change of color SU(2) charges results in a rotation of the color vector
which is getting very fast at close partonic distances. The presence of this
non-Abelian additional term in the chromoelectric and chromomagnetic fields
creates a 'color charge glow', which is manifested as a distinct color wave
disturbance arising due to the finite distance at which the color interaction
becomes active. This situation may be relevant to the hadronization phase in
ultrarelativistic heavy-ion collisions, where the partonic state is governed by
strong local color fluctuations.


  The PICASSO project is using superheated droplets of C$_4$F$_{10}$ for the
direct detection of Dark Matter candidates in the {\it spin-dependent} (SD)
sector. The total setup includes 32 detectors installed in the SNOLAB
underground laboratory in Sudbury (Ontario, Canada). With a concentrated effort
in detector purification and with new discrimination tools now available for
analysis, Picasso published competitive results in June 2009 \cite{publi2009}
and became the leading experiment in the SD sector of direct dark matter
searches. The present level of sensitivity is at 0.16 pb on protons at 90% C.L.
(M$_W$= 24GeV/c$^2$) following an analysis of two detectors only. The rest of
the detectors are now in the process of being analyzed and the experimental
search continues in order to further improve the limits or hopefully discover a
signal of dark matter. The status of the experiment and the ongoing analysis
will be presented.


  The Nambu-Gorkov generalized Hartree-Fock theory of superconductivity is
further generalized to treat simultaneously two kinds of correlations: the
correlations that lead to superconductivity, as well as the correlations that
produce the pseudogap in the normal state. The treatment of these simultaneous
double correlations is done by enlarging the dimension of the propagator and
self-energy matrices, from two to four. The off-diagonal self-energies and the
DOS are calculated. The results are compatible with tunneling and PES
experiments.


  The nuclear symmetry energy is intimately connected with nuclear
astrophysics. This contribution focuses on the estimation of the symmetry
energy from experiment and how it is related to the structure of neutron stars.
The most important connection is between the radii of neutron stars and the
pressure of neutron star matter in the vicinity of the nuclear saturation
density $n_s$. This pressure is essentially controlled by the nuclear symmetry
energy parameters $S_v$ and $L$, the first two coefficients of a Taylor
expansion of the symmetry energy around $n_s$. We discuss constraints on these
parameters that can be found from nuclear experiments. We demonstrate that
these constraints are largely model-independent by deriving them qualitatively
from a simple nuclear model. We also summarize how recent theoretical studies
of pure neutron matter can reinforce these constraints. To date, several
different astrophysical measurements of neutron star radii have been attempted.
Attention is focused on photospheric radius expansion bursts and on thermal
emissions from quiescent low-mass X-ray binaries. While none of these
observations can, at the present time, determine individual neutron star radii
to better than 20% accuracy, the body of observations can be used with Bayesian
techniques to effectively constrain them to higher precision. These techniques
invert the structure equations and obtain estimates of the pressure-density
relation of neutron star matter, not only near $n_s$, but up to the highest
densities found in neutron star interiors. The estimates we derive for neutron
star radii are in concordance with predictions from nuclear experiment and
theory.


  As COVID-19 ravages the world, social media analytics could augment
traditional surveys in assessing how the pandemic evolves and capturing
consumer chatter that could help healthcare agencies in addressing it. This
typically involves mining disclosure events that mention testing positive for
the disease or discussions surrounding perceptions and beliefs in preventative
or treatment options. The 2020 shared task on COVID-19 event extraction
(conducted as part of the W-NUT workshop during the EMNLP conference)
introduced a new Twitter dataset for benchmarking event extraction from
COVID-19 tweets. In this paper, we cast the problem of event extraction as
extractive question answering using recent advances in continuous prompting in
language models. On the shared task test dataset, our approach leads to over 5%
absolute micro-averaged F1-score improvement over prior best results, across
all COVID-19 event slots. Our ablation study shows that continuous prompts have
a major impact on the eventual performance.


  We ask whether the recently discovered superstring and superfivebrane
solutions of D=10 supergravity admit the interpretation of non-singular
solitons even though, in the absence of Yang-Mills fields, they exhibit
curvature singularities at the origin. We answer the question using a test
probe/source approach, and find that the nature of the singularity is
probe-dependent. If the test probe and source are both superstrings or both
superfivebranes, one falls into the other in a finite proper time and the
singularity is real, whereas if one is a superstring and the other a
superfivebrane it takes an infinite proper time (the force is repulsive!) and
the singularity is harmless. Black strings and fivebranes, on the other hand,
always display real singularities.


  Full suite of the present day Cosmic Microwave background (CMB) data, when
combined with weak prior information on the Hubble constant and the age of the
Universe, or the Large-Scale structure, provides strong indication for a
non-zero density of the vacuum-like dark energy in our universe. This result
independently supports the conclusions from Supernovae Ia (SN1a) data. When the
model parameter space is extended to allow for the range of the equation of
state parameter w_Q for the dynamical field Q which gives rise to dark energy,
the CMB data is found to give a weak upper bound w_Q < -0.4 at 95% CL, however
combined with SN1a data it strongly favours w_Q < -0.8, consistent with
Lambda-term like behaviour.


  Despite abundant negotiation strategies in literature, the complexity of
automated negotiation forbids a single strategy from being dominant against all
others in different negotiation scenarios. To overcome this, one approach is to
use mixture of experts, but at the same time, one problem of this method is the
selection of experts, as this approach is limited by the competency of the
experts selected. Another problem with most negotiation strategies is their
incapability of adapting to dynamic variation of the opponent's behaviour
within a single negotiation session resulting in poor performance. This work
focuses on both, solving the problem of expert selection and adapting to the
opponent's behaviour with our Autonomous Negotiating Agent Framework. This
framework allows real-time classification of opponent's behaviour and provides
a mechanism to select, switch or combine strategies within a single negotiation
session. Additionally, our framework has a reviewer component which enables
self-enhancement capability by deciding to include new strategies or replace
old ones with better strategies periodically. We demonstrate an instance of our
framework by implementing maximum entropy reinforcement learning based
strategies with a deep learning based opponent classifier. Finally, we evaluate
the performance of our agent against state-of-the-art negotiators under varied
negotiation scenarios.


  In this paper we describe a class of codes called {\it permutation codes}.
This class of codes is a generalization of cyclic codes and quasi-cyclic codes.
We also give some examples of optimal permutation codes over binary, ternary,
and $5$-ary. Then, we describe its structure as submodules over a polynomial
ring.


  Vision Transformer (ViT) has become one of the most popular neural
architectures due to its great scalability, computational efficiency, and
compelling performance in many vision tasks. However, ViT has shown inferior
performance to Convolutional Neural Network (CNN) on medical tasks due to its
data-hungry nature and the lack of annotated medical data. In this paper, we
pre-train ViTs on 266,340 chest X-rays using Masked Autoencoders (MAE) which
reconstruct missing pixels from a small part of each image. For comparison,
CNNs are also pre-trained on the same 266,340 X-rays using advanced
self-supervised methods (e.g., MoCo v2). The results show that our pre-trained
ViT performs comparably (sometimes better) to the state-of-the-art CNN
(DenseNet-121) for multi-label thorax disease classification. This performance
is attributed to the strong recipes extracted from our empirical studies for
pre-training and fine-tuning ViT. The pre-training recipe signifies that
medical reconstruction requires a much smaller proportion of an image (10% vs.
25%) and a more moderate random resized crop range (0.5~1.0 vs. 0.2~1.0)
compared with natural imaging. Furthermore, we remark that in-domain transfer
learning is preferred whenever possible. The fine-tuning recipe discloses that
layer-wise LR decay, RandAug magnitude, and DropPath rate are significant
factors to consider. We hope that this study can direct future research on the
application of Transformers to a larger variety of medical imaging tasks.


  The diffuse intracluster light (ICL) contains a significant fraction of the
total stellar mass in clusters of galaxies, and contributes in roughly equal
proportion as the hot intra-cluster medium (ICM) to the total baryon content of
clusters. Because of the potential importance of understanding the origin of
the ICL in the context of the formation and evolution of structure in the
Universe, the field has recently undergone a revival both in the quality and
quantity of observational and theoretical investigations. Due to cosmological
dimming, the observational work has mostly concentrated on low redshift
clusters, but clearly observations at higher redshifts can provide interesting
clues about the evolution of the diffuse component. In this paper we present
the first results of a program to characterize the ICL of intermediate redshift
clusters. We find that at z ~ 0.3, the X-ray cluster RX J0054.0-2823 already
has a significant ICL and that the fraction of the total light in the ICL and
the brightest cluster galaxy (BCG) is comparable to that of similar clusters at
lower redshift. We also find that the kinematics of the ICL is consistent with
it being the remnant of tidally destroyed galaxies streaming in the central
regions of the cluster, which has three central giant elliptical galaxies
acting as an efficient "grinding machine". Our cluster has a bi-modal
radial-velocity distribution and thus two possible values for the velocity
dispersion. We find that the cluster fits well in the correlation between
BCG+ICL fraction and cluster mass for a range of velocity dispersions, leading
us to question the validity of a relevant correlation between these two
quantities.


  A lattice reduction is an algorithm that transforms the given basis of the
lattice to another lattice basis such that problems like finding a shortest
vector and closest vector become easier to solve. Some of the famous lattice
reduction algorithms are LLL and BKZ reductions. We define a class of bases
called \emph{obtuse bases} and show that any lattice basis can be transformed
to an obtuse basis in $\mathcal{O}(n^4)$ time. A shortest vector s can be
written as $v_1b_1+\cdots+v_nb_n$ where $b_1,\dots,b_n$ are the input basis
vectors and $v_1,\dots,v_n$ are integers. When the input basis is obtuse, all
these integers can be chosen to be positive for a shortest vector. This
property of the obtuse basis makes lattice enumeration algorithm for finding a
shortest vector exponentially faster. Moreover, extreme pruning, the current
fastest algorithm for lattice enumeration, can be run on an obtuse basis.


  Although spatio-temporal graph neural networks have achieved great empirical
success in handling multiple correlated time series, they may be impractical in
some real-world scenarios due to a lack of sufficient high-quality training
data. Furthermore, spatio-temporal graph neural networks lack theoretical
interpretation. To address these issues, we put forth a novel mathematically
designed framework to analyze spatio-temporal data. Our proposed
spatio-temporal graph scattering transform (ST-GST) extends traditional
scattering transforms to the spatio-temporal domain. It performs iterative
applications of spatio-temporal graph wavelets and nonlinear activation
functions, which can be viewed as a forward pass of spatio-temporal graph
convolutional networks without training. Since all the filter coefficients in
ST-GST are mathematically designed, it is promising for the real-world
scenarios with limited training data, and also allows for a theoretical
analysis, which shows that the proposed ST-GST is stable to small perturbations
of input signals and structures. Finally, our experiments show that i) ST-GST
outperforms spatio-temporal graph convolutional networks by an increase of 35%
in accuracy for MSR Action3D dataset; ii) it is better and computationally more
efficient to design the transform based on separable spatio-temporal graphs
than the joint ones; and iii) the nonlinearity in ST-GST is critical to
empirical performance.


  Event or Neuromorphic cameras are novel biologically inspired sensors that
record data based on the change in light intensity at each pixel
asynchronously. They have a temporal resolution of microseconds. This is useful
for scenes with fast moving objects that can cause motion blur in traditional
cameras, which record the average light intensity over an exposure time for
each pixel synchronously. This paper presents a bilevel inverse problem
framework for neuromorphic imaging. Existence of solution to the inverse
problem is established. Second order sufficient conditions are derived under
special situations for this nonconvex problem. A second order Newton type
solver is derived to solve the problem. The efficacy of the approach is shown
on several examples.


  We consider the problem of an agent/robot with non-holonomic kinematics
avoiding many dynamic obstacles. State and velocity noise of both the robot and
obstacles as well as the robot's control noise are modelled as non-parametric
distributions as often the Gaussian assumptions of noise models are violated in
real-world scenarios. Under these assumptions, we formulate a robust MPC that
samples robotic controls effectively in a manner that aligns the robot to the
goal state while avoiding obstacles under the duress of such non-parametric
noise. In particular, the MPC incorporates a distribution matching cost that
effectively aligns the distribution of the current collision cone to a certain
desired distribution whose samples are collision-free. This cost is posed as a
distance function in the Hilbert Space, whose minimization typically results in
the collision cone samples becoming collision-free. We compare and show
tangible performance gain with methods that model the collision cone
distribution by linearizing the Gaussian approximations of the original
non-parametric state and obstacle distributions. We also show superior
performance with methods that pose a chance constraint formulation of the
Gaussian approximations of non-parametric noise without subjecting such
approximations to further linearizations. The performance gain is shown both in
terms of trajectory length and control costs that vindicates the efficacy of
the proposed method. To the best of our knowledge, this is the first
presentation of non-holonomic collision avoidance of moving obstacles in the
presence of non-parametric state, velocity and actuator noise models.


  Recently, it was shown that differential rotation is an unavoidable feature
of nonlinear r-modes. We investigate the influence of this differential
rotation on the detectability of gravitational waves emitted by a newly born,
hot, rapidly-rotating neutron star, as it spins down due to the r-mode
instability. We conclude that gravitational radiation may be detected by the
advanced laser interferometer detector LIGO if the amount of differential
rotation at the time the r-mode instability becomes active is not very high.


  TLA+ is a specification language based on standard set theory and temporal
logic that has constructs for hierarchical proofs. We describe how to write
TLA+ proofs and check them with TLAPS, the TLA+ Proof System. We use Peterson's
mutual exclusion algorithm as a simple example to describe the features of
TLAPS and show how it and the Toolbox (an IDE for TLA+) help users to manage
large, complex proofs.


  Demand forecasts are the crucial basis for numerous business decisions,
ranging from inventory management to strategic facility planning. While machine
learning (ML) approaches offer accuracy gains, their interpretability and
acceptance are notoriously lacking. Addressing this dilemma, we introduce
Hierarchical Neural Additive Models for time series (HNAM). HNAM expands upon
Neural Additive Models (NAM) by introducing a time-series specific additive
model with a level and interacting covariate components.
  Covariate interactions are only allowed according to a user-specified
interaction hierarchy. For example, weekday effects may be estimated
independently of other covariates, whereas a holiday effect may depend on the
weekday and an additional promotion may depend on both former covariates that
are lower in the interaction hierarchy.
  Thereby, HNAM yields an intuitive forecasting interface in which analysts can
observe the contribution for each known covariate. We evaluate the proposed
approach and benchmark its performance against other state-of-the-art machine
learning and statistical models extensively on real-world retail data. The
results reveal that HNAM offers competitive prediction performance whilst
providing plausible explanations.


  The entropy definition is deduced by means of (re)deriving the generalized
non-linear Langevin equation using Zwanzig projector operator formalism. It is
shown to be necessarily related to an invariant measure which, in classical
mechanics, can always be taken to be the Liouville measure. It is not true that
one is free to choose a ``relevant'' probability density independently as is
done in other flavors of projection operator formalism. This observation
induces an entropy expression which is valid also outside the thermodynamic
limit and in far from equilibrium situations. The Zwanzig projection operator
formalism therefore gives a deductive derivation of non-equilibrium, and
equilibrium, thermodynamics. The entropy definition found is closely related to
the (generalized) microcanonical Boltzmann-Planck definition but with some
subtle differences. No ``shell thickness'' arguments are needed, nor desirable,
for a rigorous definition. The entropy expression depends on the choice of
macroscopic variables and does not exactly transform as a scalar quantity. The
relation with expressions used in the GENERIC formalism are discussed.


  Microservices architectures are a departure from traditional Service Oriented
Architecture (SOA). Influenced by Domain Driven Design (DDD), microservices
architectures aim to help business analysts and enterprise architects develop
scalable applications that embody flexibility for new functionalities as
businesses develop, such as scenarios in the Internet of Things (IoT) domain.
This article compares microservices architecture with SOA and identifies key
characteristics that will assist application designers to select the most
appropriate approach.


  We present simulations of an imaging mechanism that reveals the trajectories
of electrons in a two-dimensional electron gas (2DEG), as well as simulations
of the electron flow in zero and small magnetic fields. The end goal of this
work is to implement the proposed mechanism to image the flow of electrons
inside a ballistic electron device from one specific point (A) to another (B)
in a 2DEG, using a low temperature scanning probe microscope with a charged
tip. The tip changes the electron density in the 2DEG beneath it and deflects
the electrons traveling nearby, thereby changing the conductance from point A
to point B. The simulations presented here show that by measuring the
transmission of electrons from A to B versus tip position, one can image the
electron flow. This forward scattering mechanism is well suited for imaging in
a magnetic field, in contrast to previous probes that depended on
backscattering. One could use this technique to image cyclotron orbits in an
electron focusing geometry, in which electrons travel from point A to point B
in semi-circular paths bouncing along a wall. Imaging the motion of electrons
in magnetic fields is useful for the development of devices for spintronics and
quantum information processing.


  Ideal point models analyze lawmakers' votes to quantify their political
positions, or ideal points. But votes are not the only way to express a
political position. Lawmakers also give speeches, release press statements, and
post tweets. In this paper, we introduce the text-based ideal point model
(TBIP), an unsupervised probabilistic topic model that analyzes texts to
quantify the political positions of its authors. We demonstrate the TBIP with
two types of politicized text data: U.S. Senate speeches and senator tweets.
Though the model does not analyze their votes or political affiliations, the
TBIP separates lawmakers by party, learns interpretable politicized topics, and
infers ideal points close to the classical vote-based ideal points. One benefit
of analyzing texts, as opposed to votes, is that the TBIP can estimate ideal
points of anyone who authors political texts, including non-voting actors. To
this end, we use it to study tweets from the 2020 Democratic presidential
candidates. Using only the texts of their tweets, it identifies them along an
interpretable progressive-to-moderate spectrum.