  Predicting the behavior of surrounding traffic participants is crucial for
advanced driver assistance systems and autonomous driving. Most researchers
however do not consider contextual knowledge when predicting vehicle motion.
Extending former studies, we investigate how predictions are affected by
external conditions. To do so, we categorize different kinds of contextual
information and provide a carefully chosen definition as well as examples for
external conditions. More precisely, we investigate how a state-of-the-art
approach for lateral motion prediction is influenced by one selected external
condition, namely the traffic density. Our investigations demonstrate that this
kind of information is highly relevant in order to improve the performance of
prediction algorithms. Therefore, this study constitutes the first step towards
the integration of such information into automated vehicles. Moreover, our
motion prediction approach is evaluated based on the public highD data set
showing a maneuver prediction performance with areas under the ROC curve above
97% and a median lateral prediction error of only 0.18m on a prediction horizon
of 5s.


  The human brain is a complex organ, still completely undiscovered, that
controls almost all the parts of the body. Apart from survival, the human brain
stimulates emotions. Recent research indicates that brain signals can be very
effective for emotion recognition. However, which parts of the brain exhibit
most of the emotions is still under-explored. In this study, we empirically
analyze the contribution of each part of the brain in exhibiting emotions. We
use the DEAP dataset to find the most optimal electrode set which eventually
leads to the effective brain part associated with emotions. We use Fast Fourier
Transformation for effective feature extraction and a 1D-CNN with residual
connection for classification. Though 32 electrodes from the DEAP dataset got
an accuracy of 97.34%, only 12 electrodes (F7, P8, O1, F8, C4, T7, PO3, Fp1,
Fp2, O2, P3, and Fz) achieve 95.81% accuracy. This study also shows that adding
more than 10 electrodes does not improve performance significantly. Moreover,
the frontal lobe is the most important for recognizing emotion.


  The neutron population in a nuclear reactor is subject to fluctuations in
time and in space due to the competition of diffusion by scattering, births by
fission events, and deaths by absorptions. As such, fission chains provide a
prototype model for the study of spatial clustering phenomena. In order for the
reactor to be operated in stationary conditions at the critical point, the
population of prompt neutrons instantaneously emitted at fission must be in
equilibrium with the much smaller population of delayed neutrons, emitted after
a Poissonian time by nuclear decay of the fissioned nuclei. In this work, we
will show that the delayed neutrons, although representing a tiny fraction of
the total number of neutrons in the reactor, have actually a key impact on the
fluctuations, and their contribution is very effective in quenching the spatial
clustering.


  We consider localization of a random walk (RW) when attracted or repelled by
multiple extended manifolds of different dimensionalities. In particular, we
focus on $(d-1)$- and $(d-2)$-dimensional manifolds in $d$-dimensional space,
where attractive interactions are (fully or marginally) relevant. The RW can
then be in one of four phases where it is localized to neither, one, or both
manifolds. The four phases merge at a special multi-critical point where (away
from the manifolds) the RW spreads diffusively. Extensive numerical analyses on
two dimensional RWs confined inside or outside a rectangular wedge confirm
general features expected from a continuum theory, but also exhibit unexpected
attributes, such as a reentrant localization to the corner while repelled by
it.


  Research community evaluations in information retrieval, such as NIST's Text
REtrieval Conference (TREC), build reusable test collections by pooling
document rankings submitted by many teams. Naturally, the quality of the
resulting test collection thus greatly depends on the number of participating
teams and the quality of their submitted runs. In this work, we investigate: i)
how the number of participants, coupled with other factors, affects the quality
of a test collection; and ii) whether the quality of a test collection can be
inferred prior to collecting relevance judgments from human assessors.
Experiments conducted on six TREC collections illustrate how the number of
teams interacts with various other factors to influence the resulting quality
of test collections. We also show that the reusability of a test collection can
be predicted with high accuracy when the same document collection is used for
successive years in an evaluation campaign, as is common in TREC.


  A simple graph $G$ with maximum degree $\Delta$ is overfull if $|E(G)|>\Delta
\lfloor |V(G)|/2\rfloor$. The core of $G$, denoted $G_{\Delta}$, is the
subgraph of $G$ induced by its vertices of degree $\Delta$. Clearly, the
chromatic index of $G$ equals $\Delta+1$ if $G$ is overfull. Conversely, Hilton
and Zhao in 1996 conjectured that if $G$ is a simple connected graph with
$\Delta\ge 3$ and $\Delta(G_\Delta)\le 2$, then $\chi'(G)=\Delta+1$ implies
that $G$ is overfull or $G=P^*$, where $P^*$ is obtained from the Petersen
graph by deleting a vertex. Cariolaro and Cariolaro settled the base case
$\Delta=3$ in 2003, and Cranston and Rabern proved the next case $\Delta=4$ in
2019. In this paper, we give a proof of this conjecture for all $\Delta\ge 4$.


  The detection of long-lived radionuclides through ultra-sensitive single atom
counting via accelerator mass spectrometry (AMS) offers opportunities for
precise measurements of neutron capture cross sections, e.g. for nuclear
astrophysics. The technique represents a truly complementary approach,
completely independent of previous experimental methods. The potential of this
technique is highlighted at the example of the $^{54}$Fe($n, \gamma$)$^{55}$Fe
reaction. Following a series of irradiations with neutrons from cold and
thermal to keV energies, the produced long-lived $^{55}$Fe nuclei
($t_{1/2}=2.744(9)$ yr) were analyzed at the Vienna Environmental Research
Accelerator (VERA). A reproducibility of about 1% could be achieved for the
detection of $^{55}$Fe, yielding cross section uncertainties of less than 3%.
Thus, the new data can serve as anchor points to time-of-flight experiments. We
report significantly improved neutron capture cross sections at thermal energy
($\sigma_{th}=2.30\pm0.07$ b) as well as for a quasi-Maxwellian spectrum of
$kT=25$ keV ($\sigma=30.3\pm1.2$ mb) and for $E_n=481\pm53$ keV ($\sigma=
6.01\pm0.23$ mb). The new experimental cross sections have been used to deduce
improved Maxwellian average cross sections in the temperature regime of the
common $s$-process scenarios. The astrophysical impact is discussed using
stellar models for low-mass AGB stars.


  Image captioning, like many tasks involving vision and language, currently
relies on Transformer-based architectures for extracting the semantics in an
image and translating it into linguistically coherent descriptions. Although
successful, the attention operator only considers a weighted summation of
projections of the current input sample, therefore ignoring the relevant
semantic information which can come from the joint observation of other
samples. In this paper, we devise a network which can perform attention over
activations obtained while processing other training samples, through a
prototypical memory model. Our memory models the distribution of past keys and
values through the definition of prototype vectors which are both
discriminative and compact. Experimentally, we assess the performance of the
proposed model on the COCO dataset, in comparison with carefully designed
baselines and state-of-the-art approaches, and by investigating the role of
each of the proposed components. We demonstrate that our proposal can increase
the performance of an encoder-decoder Transformer by 3.7 CIDEr points both when
training in cross-entropy only and when fine-tuning with self-critical sequence
training. Source code and trained models are available at:
https://github.com/aimagelab/PMA-Net.


  This paper works on the structure of infinitely connected Fatou damains of
rational maps in terms of Koebe uniformization. Due to the complicated boundary
behavior, the existing uniformization results are failed to apply in general.
We proved that if the rational map is geometrically finite, then its infinitely
connected attracting Fatou damain is conformally homeomorphic to a circle
domain.


  We study constraints on f(R) dark energy models from solar system experiments
combined with experiments on the violation of equivalence principle. When the
mass of an equivalent scalar field degree of freedom is heavy in a region with
high density, a spherically symmetric body has a thin-shell so that an
effective coupling of the fifth force is suppressed through a chameleon
mechanism. We place experimental bounds on the cosmologically viable models
recently proposed in literature which have an asymptotic form f(R)=R-lambda R_c
[1-(R_c/R)^{2n}] in the regime R >> R_c. From the solar-system constraints on
the post-Newtonian parameter gamma, we derive the bound n>0.5, whereas the
constraints from the violations of weak and strong equivalence principles give
the bound n>0.9. This allows a possibility to find the deviation from the
LambdaCDM cosmological model. For the model f(R)=R-lambda R_c(R/R_c)^p with
0<p<1 the severest constraint is found to be p<10^{-10}, which shows that this
model is hardly distinguishable from the LambdaCDM cosmology.


  The ability to generate test data is often a necessary prerequisite for
automated software testing. For the generated data to be fit for its intended
purpose, the data usually has to satisfy various logical constraints. When
testing is performed at a system level, these constraints tend to be complex
and are typically captured in expressive formalisms based on first-order logic.
Motivated by improving the feasibility and scalability of data generation for
system testing, we present a novel approach, whereby we employ a combination of
metaheuristic search and Satisfiability Modulo Theories (SMT) for constraint
solving. Our approach delegates constraint solving tasks to metaheuristic
search and SMT in such a way as to take advantage of the complementary
strengths of the two techniques. We ground our work on test data models
specified in UML, with OCL used as the constraint language. We present tool
support and an evaluation of our approach over three industrial case studies.
The results indicate that, for complex system test data generation problems,
our approach presents substantial benefits over the state of the art in terms
of applicability and scalability.


  Polymer based organic photovoltaic (OPV) technology offers a relatively
inexpensive option for solar energy conversion provided its efficiency
increases beyond the current level (6-7%) along with significant improvements
in operational lifetime. The critical aspect of such solar cells is the complex
morphology of distributed bulk heterojunctions, which plays the central role in
the conversion of photo-generated excitons to electron-hole pairs. However, the
fabrication conditions that can produce the optimal morphology are still
unknown due to the lack of quantitative understanding of the effects of process
variables on the cell morphology. In this article, we develop a unique
process-device co-simulation framework based on phase-field model for phase
separation coupled with self-consistent drift-diffusion transport to
quantitatively explore the effects of the process conditions (e.g., annealing
temperature, mixing ratio, anneal duration) on the organic solar cell
performance. Our results explain experimentally observed trends of open circuit
voltage and short circuit current that would otherwise be deemed anomalous from
the perspective of conventional solar cells. In addition to providing an
optimization framework for OPV technology, our morphology-aware modeling
approach is ideally suited for a wide class of problems involving porous
materials, block co-polymers, polymer colloids, OLED devices etc.


  We examine the two-dimensional spacetimes that emerge from string theory. We
find all the solutions with no tachyons, and show that the only non-trivial
solution is the black hole spacetime. We examine the role of duality in this
picture. We then explore the thermodynamics of these solutions which is
complicated by the fact that only in two spacetime dimensions is it impossible
to redefine the dilaton field in terms of a canonical scalar field. Finally, we
extend our analysis to the heterotic string, and briefly comment on exact, as
opposed to perturbative, solutions.


  The Hamiltonian for a spin zero particle that is confined to a curve embedded
in the 3D space is constructed by squeezing the coordinates spanning a tube
normal to the curve onto the curve assuming strong normal forces. We follow the
new approach that we applied to confine a particle to a surface, in that we
start with an expression for the 3D momentum operators whose components along
and normal to the curve directions are separately Hermitian. The kinetic energy
operator expressed in terms of the momentum operator in the normal direction is
then a Hermitian operator in this case. When this operator is dropped and the
thickness of the tube surrounding the curve is set to zero, one automatically
gets the Hermitian curve Hamiltonian that contains the geometric potential term
as expected. It is demonstrated that the origin of this potential lies in the
ordering or symmetrization of the original 3D momentum operators in order to
render them Hermitian. The Hermitian momentum operator for the particle as it
is confined to the curve is also constructed and is seen to be similar to what
is known as the geometric momentum of a particle confined to a surface in that
it has a term proportional to the curvature that is along the normal to the
curve. The force operator of the particle on the curve is also derived, and is
shown to reduce, for a curve with a constant curvature and torsion, to a --
apparently -- single component normal to the curve that is a symmetrization of
the classical expression plus a quantum term. All the above quantities are then
derived for the specific case of a particle confined to a cylindrical helix
embedded in 3D space.


  Observations by the MACHO collaboration indicate that a significant fraction
of the galactic halo dark matter may be in form of compact objects with masses
$M\sim 0.5M_{\odot}$. Identification of these objects as red or white dwarfs is
problematic due to stringent observational upper limits on such dwarf
populations. Primordial black hole (PBH) formation from pre-existing density
fluctuations is facilitated during the cosmic QCD transition due to a
significant decrease in pressure forces. For generic initial density
perturbation spectra this implies that essentially all PBHs may form with
masses close to the QCD-horizon scale, $M_h^{QCD}\sim 1M_{\odot}$. It is
possible that such QCD PBHs contribute significantly to the closure density
today. I discuss the status of theoretical predictions for the properties of
QCD PBH dark matter. Observational signatures of and constraints on a cosmic
solar mass PBH population are also discussed.


  This paper describes the design of a multi-camera optical tactile sensor that
provides information about the contact force distribution applied to its soft
surface. This information is contained in the motion of spherical particles
spread within the surface, which deforms when subject to force. The small
embedded cameras capture images of the different particle patterns that are
then mapped to the three-dimensional contact force distribution through a
machine learning architecture. The design proposed in this paper exhibits a
larger contact surface and a thinner structure than most of the existing
camera-based tactile sensors, without the use of additional reflecting
components such as mirrors. A modular implementation of the learning
architecture is discussed that facilitates the scalability to larger surfaces
such as robotic skins.


  The accretion history of protostars remains widely mysterious even though it
represents one of the best ways to understand the protostellar collapse that
leads to the formation of stars. Molecular outflows are here used to
characterize the protostellar accretion phase in W43-MM1. The W43-MM1
protocluster host a sufficient number of protostars to statistically
investigate molecular outflows in a single, homogeneous region. We used the
CO(2-1) and SiO(5-4) line datacubes, taken as part of an ALMA mosaic with a
2000 AU resolution, to search for protostellar outflows, evaluate the influence
that the environment has on these outflows' characteristics and put constraints
on outflow variability in W43-MM1. We discovered a rich cluster of 46 outflow
lobes, driven by 27 protostars with masses of 1-100 Msun. The complex
environment inside which these outflow lobes develop has a definite influence
on their length, limiting the validity of using outflows' dynamical timescales
as a proxy of the ejection timescale in clouds with high dynamics and varying
conditions. We performed a detailed study of Position-Velocity (PV) diagrams of
outflows that revealed clear events of episodic ejection. The time variability
of W43-MM1 outflows is a general trend and is more generally observed than in
nearby, low- to intermediate-mass star-forming regions. The typical timescale
found between two ejecta, about 500 yr, is consistent with that found in nearby
protostars. If ejection episodicity reflects variability in the accretion
process, either protostellar accretion is more variable or episodicity is
easier to detect in high-mass star-forming regions than in nearby clouds. The
timescale found between accretion events could be resulting from disk
instabilities, associated with bursts of inflowing gas arising from the
dynamical environment of high-mass star-forming cores.


  We have studied the Dalitz plot of the e+ e- --> pi0 pi0 gamma events
collected at SQRT(s) ~ M(phi) with the KLOE detector. In the dipion invariant
mass (Mpp) region below 700 MeV, the process under study is dominated by the
non-resonant process e+ e- --> omega pi0 with omega --> pi0 gamma whereas, for
higher Mpp values, the radiative phi decay to the f0(980) is the dominant
mechanism. Different theoretical models are used to fit the Dalitz plot, taking
also into account a possible contribution of the sigma(600). For each model, we
extract the f0(980) mass and its coupling to pipi, KKbar and to the phi.


  In this article, we study the following fractional-Laplacian system with
singular nonlinearity \begin{equation*} (P_{\lambda,\mu}) \left\{
\begin{array}{lr} (-\Delta)^s u = \lambda f(x) u^{-q}+
\frac{\alpha}{\alpha+\beta}b(x) u^{\alpha-1} w^\beta\; \text{in}\;\Omega \\
(-\Delta)^s w = \mu g(x) w^{-q}+ \frac{\beta}{\alpha+\beta} b(x) u^{\alpha}
w^{\beta-1}\; \text{in}\;\Omega \\ \quad \quad u, w>0\;\text{in}\;\Omega, \quad
u = w = 0 \; \mbox{in}\; \mathbb{R}^n \setminus\Omega, \end{array} \quad
\right. \end{equation*} where $\Omega$ is a bounded domain in $\mathbb{R}^n$
with smooth boundary $\partial \Omega$, $n>2s$, $s\in(0,1)$, $0<q<1$,
$\alpha>1$, $\beta>1$ satisfy $2<\alpha+\beta< 2_{s}^*-1$ with
$2_{s}^*=\frac{2n}{n-2s}$, the pair of parameters $(\lambda,\mu) \in
\mathbb{R}^2\setminus\{(0,0)\}$. The weight functions $f,g:
\Omega\subset\mathbb{R}^n \to \mathbb{R}$ such that $0<f$, $g\in
L^{\frac{\alpha+\beta}{\alpha+\beta-1+q}}(\Omega)$, and $b:\Omega\subset
\mathbb{R}^n \to \mathbb{R}$ is a sign-changing function such that $b(x)\in
L^{\infty}(\Omega)$. Using variational methods, we show existence and
multiplicity of positive solutions of $(P_{\lambda,\mu})$ with respect to the
pair of parameters $(\lambda,\mu)$.


  Bounds for the diameter and for the expansion of long-range percolation
clusters on the cycle $\Z / N\Z$ are given.


  We study theoretically the anisotropic magneto-Peltier effect, which was
recently demonstrated experimentally. A first-principles-based Boltzmann
transport approach including the spin-orbit interaction shows that Ni has a
larger anisotropy of the Peltier coefficient ($\Delta \Pi$) than Fe, consistent
with experiments. It is clarified that spin-flip electron transitions due to
the spin-orbit interaction are the key in the mechanism of the large
anisotropic magneto-Peltier effect. Using our method, we further predict
several ferromagnetic metals with much larger $\Delta \Pi$ than that of Ni.


  Commercial video games are increasingly using sophisticated physics
simulations to create a more immersive experience for players. This also makes
them a powerful tool for engaging students in learning physics. We provide some
examples to show how commercial off-the-shelf games can be used to teach
specific topics in introductory undergraduate physics. The examples are
selected from a course taught predominantly through the medium of commercial
video games.


  We prove that for any integer $n$ there exist infinitely many different knots
in $S^3$ such that $n$-surgery on those knots yields the same 3-manifold. In
particular, when $|n|=1$ homology spheres arise from these surgeries. This
answers Problem 3.6(D) on the Kirby problem list. We construct two families of
examples, the first by a method of twisting along an annulus and the second by
a generalization of this procedure. The latter family also solves a stronger
version of Problem 3.6(D), that for any integer $n$, there exist infinitely
many mutually distinct knots such that 2-handle addition along each with
framing $n$ yields the same 4-manifold.


  By exhibiting the corresponding Lax pair representations we propose a wide
class of integrable two-dimensional (2D) fermionic Toda lattice (TL)
hierarchies which includes the 2D N=(2|2) and N=(0|2) supersymmetric TL
hierarchies as particular cases. Performing their reduction to the
one-dimensional case by imposing suitable constraints we derive the
corresponding 1D fermionic TL hierarchies. We develop the generalized graded
R-matrix formalism using the generalized graded bracket on the space of graded
operators with an involution generalizing the graded commutator in
superalgebras, which allows one to describe these hierarchies in the framework
of the Hamiltonian formalism and construct their first two Hamiltonian
structures. The first Hamiltonian structure is obtained for both bosonic and
fermionic Lax operators while the second Hamiltonian structure is established
for bosonic Lax operators only. We propose the graded modified Yang-Baxter
equation in the operator form and demonstrate that for the class of graded
antisymmetric R-matrices it is equivalent to the tensor form of the graded
classical Yang-Baxter equation.


  We argue that the photon spectra in radiative decays of various heavy
quarkonium states provide important information on their nature. If two of
these states are in the strong coupling regime, we are able to produce a
parameter-free model independent formula, which holds at next-to-leading order
and includes both direct and fragmentation contributions. When the formula is
checked against recent CLEO data it favors Upsilon (2S) and Upsilon (3S) in the
strong coupling regime and disfavors Upsilon (1S) in it.


  The vortex phases in type-II superconductors are very important since they
determine many magnetic and electric properties of the parent compound.
However, a universal tool to characterize the vortex phases is still lacking.
We demonstrate in a type-II superconductors YBa2Cu3O7-x polycrystal sample that
its vortex phases and phase boundaries can be comprehensively studied by a
magnetoelectric technique. In this method, a thin piezoelectric material
0.7Pb(Mg1/3Nb2/3)O3-0.3PbTiO3(PMN-PT) is mechanically bonded with YBa2Cu3O7-x
to form a laminate structure and act as a strain gauge. The phase diagram of
the YBa2Cu3O7-x polycrystalline was explored by this method. Surprisingly, it
can accurately estimate the Hc1, irreversible line, Hc2 and distinguish among
vortex glass, vortex liquid, non-vortex states. Moreover, it can probe the
dynamic response under different frequencies and observe the threshold
phenomena of vortex liquid phase. It can even account for the density of
vortices in the vortex solid phase. Our technique is readily extended to
investigate the vortex phases in other type-II superconductors.


  Salient object detection (SOD), which aims to identify and locate the most
salient pixels or regions in images, has been attracting more and more interest
due to its various real-world applications. However, this vision task is quite
challenging, especially under complex image scenes. Inspired by the intrinsic
reflection of natural images, in this paper we propose a novel feature learning
framework for large-scale salient object detection. Specifically, we design a
symmetrical fully convolutional network (SFCN) to effectively learn
complementary saliency features under the guidance of lossless feature
reflection. The location information, together with contextual and semantic
information, of salient objects are jointly utilized to supervise the proposed
network for more accurate saliency predictions. In addition, to overcome the
blurry boundary problem, we propose a new weighted structural loss function to
ensure clear object boundaries and spatially consistent saliency. The coarse
prediction results are effectively refined by these structural information for
performance improvements. Extensive experiments on seven saliency detection
datasets demonstrate that our approach achieves consistently superior
performance and outperforms the very recent state-of-the-art methods with a
large margin.


  This article presents an equivalent formulation of the implicit
complementarity problem. We demonstrate that solution of the equivalent
formulation is equivalent to the solution of the implicit complementarity
problem. Moreover, we provide another equivalent formulation of the implicit
complementarity problem using a strictly increasing function.


  We study constructions of vector fields with properties which are
characteristic to Reeb vector fields of contact forms. In particular, we prove
that all closed oriented odd-dimensional manifold have geodesible vector
fields.


  [abridged] This work aims to observationally investigate the history of size
growth of early-type galaxies and how the growth depends on cosmic epoch and
the mass of the halo in which they are embedded. We carried out a photometric
and structural analysis in the rest-frame $V$ band of a mass-selected ($\log
M/M_\odot >10.7$) sample of red-sequence early-type galaxies with
spectroscopic/grism redshift in the general field up to $z=2$ to complement a
previous work presenting an identical analysis but in halos 100 times more
massive and 1000 times denser. We homogeneously derived sizes (effective radii)
fully accounting for the multi-component nature of galaxies and the common
presence of isophote twists and ellipticity gradients. By using these
mass-selected samples, composed of 170 red-sequence early-type galaxies in the
general field and 224 identically selected and analyzed in clusters, we isolate
the effect on galaxy sizes of the halo in which galaxies are embedded and its
dependence on epoch. We find that the $\log$ of the galaxy size at a fixed
stellar mass, $\log M/M_\odot= 11$, has increased with epoch at a rate twice as
fast in the field than in cluster in the last 10 Gyr ($0.26\pm0.03$ versus
$0.13\pm0.02$ dex per unit redshift). Red-sequence early-type galaxies in the
general field reached the size of their cousins in denser environment by
$z=0.25\pm0.13$ in spite of being three times smaller at $z\sim2$. Data point
toward a model where size growth is epoch-independent (i.e., $\partial \log r_e
/\partial z = c$), but with a rate $c$ depending on environment, $\partial c
/\partial \log M_{halo} \approx 0.05$. Environment determines the growth rate
($d \log r_e / dz$) at all redshifts, indicating an external origin for the
galaxy growth without any clear epoch where it ceases to have an effect.


  Are we alone? Answering this ageless question will be a major focus for
astrophysics in coming decades. Our tools will include unprecedentedly large
UV-Optical-IR space telescopes working with advanced coronagraphs and
starshades. Yet, these facilities will not live up to their full potential
without better detectors than we have today. To inform detector development,
this paper provides an overview of visible and near-IR (VISIR;
$\lambda=0.4-1.8~\mu\textrm{m}$) detector needs for the Advanced Technology
Large Aperture Space Telescope (ATLAST), specifically for spectroscopic
characterization of atmospheric biosignature gasses. We also provide a brief
status update on some promising detector technologies for meeting these needs
in the context of a passively cooled ATLAST.


  We define creation and annihilation operators for any 2D non-abelian anyon
theory by studying the algebraic structure from the anyon diagrammatic
formalism. We construct the creation operators for Fibonacci anyons explicitly.
We obtain that a single creation operator per particle type is not enough; we
need an extra creation operator for every alternative fusion channel. We
express any physically allowed observable in terms of these creation and
annihilation operators. Finally, we express the 2D Fibonacci Hubbard
Hamiltonian in terms of the Fibonacci creation and annihilation operators, and
we comment on developing methods for simulation based on these creation and
annihilation operators.


  The security of deep neural networks (DNNs) has attracted increasing
attention due to their widespread use in various applications. Recently, the
deployed DNNs have been demonstrated to be vulnerable to Trojan attacks, which
manipulate model parameters with bit flips to inject a hidden behavior and
activate it by a specific trigger pattern. However, all existing Trojan attacks
adopt noticeable patch-based triggers (e.g., a square pattern), making them
perceptible to humans and easy to be spotted by machines. In this paper, we
present a novel attack, namely hardly perceptible Trojan attack (HPT). HPT
crafts hardly perceptible Trojan images by utilizing the additive noise and per
pixel flow field to tweak the pixel values and positions of the original
images, respectively. To achieve superior attack performance, we propose to
jointly optimize bit flips, additive noise, and flow field. Since the weight
bits of the DNNs are binary, this problem is very hard to be solved. We handle
the binary constraint with equivalent replacement and provide an effective
optimization algorithm. Extensive experiments on CIFAR-10, SVHN, and ImageNet
datasets show that the proposed HPT can generate hardly perceptible Trojan
images, while achieving comparable or better attack performance compared to the
state-of-the-art methods. The code is available at:
https://github.com/jiawangbai/HPT.


  Error-control-coding (ECC) techniques are widely used in modern digital
communication systems to minimize the effect of noisy channels on the quality
of received signals. Motivated by the fact that both communication and imaging
can be considered as an information transfer process, in this paper we
demonstrate that ECC could yield significant improvements in the image quality
by reducing the effect of noise in the physical process of image acquisition.
In the demonstrated approach, the object is encoded by ECC structured light
fields generated by a digital-micromirror-device (DMD) while its image is
obtained by decoding the received signal collected by a bucket-detector (BD).
By applying a Luby Transform (LT) code as an example, our proof-of-concept
experiment validates that the object image can be effectively reconstructed
while errors induced by noisy reception can be significantly reduced. The
demonstrated approach informs a new imaging technique: ECC assisted imaging,
which can be scaled into applications such as remote sensing, spectroscopy and
biomedical imaging.


  In this paper, we present a self-prior-based mesh inpainting framework that
requires only an incomplete mesh as input, without the need for any training
datasets. Additionally, our method maintains the polygonal mesh format
throughout the inpainting process without converting the shape format to an
intermediate one, such as a voxel grid, a point cloud, or an implicit function,
which are typically considered easier for deep neural networks to process. To
achieve this goal, we introduce two graph convolutional networks (GCNs):
single-resolution GCN (SGCN) and multi-resolution GCN (MGCN), both trained in a
self-supervised manner. Our approach refines a watertight mesh obtained from
the initial hole filling to generate a complete output mesh. Specifically, we
train the GCNs to deform an oversmoothed version of the input mesh into the
expected complete shape. The deformation is described by vertex displacements,
and the GCNs are supervised to obtain accurate displacements at vertices in
real holes. To this end, we specify several connected regions of the mesh as
fake holes, thereby generating meshes with various sets of fake holes. The
correct displacements of vertices are known in these fake holes, thus enabling
training GCNs with loss functions that assess the accuracy of vertex
displacements. We demonstrate that our method outperforms traditional
dataset-independent approaches and exhibits greater robustness compared with
other deep-learning-based methods for shapes that infrequently appear in shape
datasets. Our code and test data are available at
https://github.com/astaka-pe/SeMIGCN.


  Recently, there is rising interest in modelling the interactions of two
sentences with deep neural networks. However, most of the existing methods
encode two sequences with separate encoders, in which a sentence is encoded
with little or no information from the other sentence. In this paper, we
propose a deep architecture to model the strong interaction of sentence pair
with two coupled-LSTMs. Specifically, we introduce two coupled ways to model
the interdependences of two LSTMs, coupling the local contextualized
interactions of two sentences. We then aggregate these interactions and use a
dynamic pooling to select the most informative features. Experiments on two
very large datasets demonstrate the efficacy of our proposed architecture and
its superiority to state-of-the-art methods.


  A relativistic coupled-channels theory for the calculation of dissociation
cross sections of halo nuclei is developed. A comparison with non-relativistic
models is done for the dissociation of $^{8}$B projectiles. It is shown that
neglecting relativistic effects leads to seizable inaccuracies in the
extraction of the astrophysical S-factor for the proton+beryllium radiative
capture reaction.


  Gravity theory is the basis of modern cosmological models. Thirring-Feynman's
tensor field approach to gravitation is an alternative to General Relativity
(GR). Though Field Gravity (FG) approach is still developing subject, it opens
new understanding of gravitational interaction, stimulates novel experiments on
the nature of gravity and gives possibility to construct new cosmological
models in Minkowski space. According to FG, the universal gravity force is
caused by exchange of gravitons - the quanta of gravity field. Energy of this
field is well-defined and excludes the singularity. All classical relativistic
effects are the same as in GR, though there are new effects, such as free fall
of rotating bodies, scalar gravitational radiation, surface of relativistic
compact bodies, which may be tested experimentally. The intrinsic scalar (spin
0) part of gravity field corresponds to "antigravity" and only together with
the pure tensor (spin 2) part gives the usual Newtonian force. Laboratory and
astrophysical experiments for testing new predictions of FG, will be performed
in near future. In particular observations with bar and interferometric
detectors, like Explorer, Nautilus, LIGO and VIRGO, will check the predicted
scalar gravitational waves from supernova explosions.


  Partially greedy bases in Banach spaces were introduced by Dilworth et al. as
a strictly weaker notion than the (almost) greedy bases. In this paper, we
study two natural ways to strengthen the definition of partial greediness. The
first way produces what we call the consecutive almost greedy property, which
turns out to be equivalent to the almost greedy property. Meanwhile, the second
way reproduces the PG property for Schauder bases but a strictly stronger
property for general bases.


  We consider distributed computations between two parties carried out over a
noisy channel that may erase messages. Following a noise model proposed by Dani
et al. (2018), the noise level observed by the parties during the computation
in our setting is arbitrary and a priori unknown to the parties.
  We develop interactive coding schemes that adapt to the actual level of noise
and correctly execute any two-party computation. Namely, in case the channel
erases $T$ transmissions, the coding scheme will take $N+2T$ transmissions
using an alphabet of size $4$ (alternatively, using $2N+4T$ transmissions over
a binary channel) to correctly simulate any binary protocol that takes $N$
transmissions assuming a noiseless channel. We can further reduce the
communication to $N+T$ by relaxing the communication model and allowing parties
to remain silent rather than forcing them to communicate in every round of the
coding scheme.
  Our coding schemes are efficient, deterministic, have linear overhead both in
their communication and round complexity, and succeed (with probability 1)
regardless of the number of erasures $T$.


  Social media provides a critical communication platform for political
figures, but also makes them easy targets for harassment. In this paper, we
characterize users who adversarially interact with political figures on Twitter
using mixed-method techniques. The analysis is based on a dataset of
400~thousand users' 1.2~million replies to 756 candidates for the U.S. House of
Representatives in the two months leading up to the 2018 midterm elections. We
show that among moderately active users, adversarial activity is associated
with decreased centrality in the social graph and increased attention to
candidates from the opposing party. When compared to users who are similarly
active, highly adversarial users tend to engage in fewer supportive
interactions with their own party's candidates and express negativity in their
user profiles. Our results can inform the design of platform moderation
mechanisms to support political figures countering online harassment.


  While users claim to be concerned about privacy, often they do little to
protect their privacy in their online actions. One prominent explanation for
this "privacy paradox" is that when an individual shares her data, it is not
just her privacy that is compromised; the privacy of other individuals with
correlated data is also compromised. This information leakage encourages
oversharing of data and significantly impacts the incentives of individuals in
online platforms. In this paper, we study the design of mechanisms for data
acquisition in settings with information leakage and verifiable data. We design
an incentive compatible mechanism that optimizes the worst-case trade-off
between bias and variance of the estimation subject to a budget constraint,
where the worst-case is over the unknown correlation between costs and data.
Additionally, we characterize the structure of the optimal mechanism in closed
form and study monotonicity and non-monotonicity properties of the marketplace.


  We extend our BDI (birth-death-immigration) process based stochastic model of
an infectious disease to time-nonhomogeneous cases. First, we discuss the
deterministic model, and derive the expected value of the infection process.
Then as an application we consider that a government issues a decree to its
citizens to curtail their activities that may incur further infections and show
how the public's tardy response may further increase infections and prolong the
epidemic much longer than one might think. We seek to solve a partial
differential equation for the probability generating function. We find,
however, that an exact solution is obtainable only for the BD process, i.e., no
arrivals of the infected from outside. The coefficient of variation for the
nonhomogeneous BD process is found to be well over unity. This result implies
that the variations among different sample paths will be as large as in the
negative binomial distribution with r<1, which was found in Part I for the
homogeneous BDI model. In the final section, we illustrate, using our running
example, how much information we can derive from the time dependent PMF
(probability mass function) P_k(t)=Pr[I(t)=k]. We present graphical plots of
the PMF at various t's, and cross-sections of this function at various k's. A
mesh plot of the function over the (k, t) plane summarizes the above numerous
plots. The results of this paper reinforce our earlier claim (see Abstract of
Part II) that it would be a futile effort to attempt to identify all possible
reasons why environments of similar situations differ so much in their epidemic
patterns. Mere "luck" plays a more significant role than most of us may
believe. We should be prepared for a worse possible scenario, which only a
stochastic model can provide with probabilistic qualification. An empirical
validation of the above results will be given in Part III-B.


  We consider the problem of finding the Discrete Fourier Transform (DFT) of
$N-$ length signals with known frequency support of size $k$. When $N$ is a
power of 2 and the frequency support is a spectral set, we provide an $O(k \log
k)$ algorithm to compute the DFT. Our algorithm uses some recent
characterizations of spectral sets and is a generalization of the standard
radix-2 algorithm.


  In this work we investigate the problem of order batching and picker routing
in storage areas. These are labour and capital intensive problems, often
responsible for a substantial share of warehouse operating costs. In
particular, we consider the case of online grocery shopping in which orders may
be composed of dozens of items.
  We present a formulation for the problem based on an exponential number of
connectivity constraints and we introduce a significant number of valid
inequalities based on the standard layout of warehouses, composed of parallel
aisles and two or more cross-aisles. The proposed inequalities are highly
effective and greatly improve computational results.
  Instances involving up to 20 orders are solved to proven optimality when we
jointly consider order batching and picker routing. Instances involving up to
5000 orders are considered where order batching is done heuristically, but
picker routing is done optimally.


  Using the Kepler K2 data, we studied the flare-activity of young K-and
M-stars in the Upper Sco region and found that they have 10000 to 80000 times
as many super-flares with E> 5E34 erg than solar like stars. The power-law
index for flares is $N/dE~E^-1.2 for K stars, N/dE~E^-1.4 for early M-star and
dN/dE~E^-1.3 for late M stars, which is about the same as that of the Sun. We
also observed the active M-star AD Leo spectroscopy for 222 hours, detected 22
flares but no coronal mass ejections.


  Dissections of polytopes are a well-studied subject by geometers as well as
recreational mathematicians. A recent application in coding theory arises from
the problem of parameterizing binary vectors of constant Hamming weight which
has been shown previously to be equivalent to the problem of dissecting a
tetrahedron to a brick. Applications of dissections also arise in problems
related to the construction of analog codes.
  Here we consider the rectangle-to-rectangle dissection due to Montucla.
Montucla's dissection is first reinterpreted in terms of the Two Tile Theorem.
Based on this, a cube-to-brick dissection is developed in $\mathbb{R}^n$. We
present a linear time algorithm (in $n$) that computes the dissection, i.e.
determines a point in the cube given a point in a specific realization of the
brick. An application of this algorithm to a previously reported analog coding
scheme is also discussed.


  We investigate a W-Ta alloying route to reduce the auto-oscillation current
densities and the power consumption of nano-constriction based spin Hall nano
oscillators. Using spin-torque ferromagnetic resonance (ST-FMR) measurements on
microbars of W$_{\text{100-x}}$Ta$_{\text{x}}$(5 nm)/CoFeB(t)/MgO stacks with t
= 1.4, 1.8, and 2.0 nm, we measure a substantial improvement in both the
spin-orbit torque efficiency and the spin Hall conductivity. We demonstrate a
34\% reduction in threshold auto-oscillation current density, which translates
into a 64\% reduction in power consumption as compared to pure W-based SHNOs.
Our work demonstrates the promising aspects of W-Ta alloying for the
energy-efficient operation of emerging spintronic devices.


  We study the factorization of four dimensional N=1 superconformal index for
U(N) (SU(N)) SQCD with N_F fundamental and anti-fundamental chiral multiplets.
When both the anomaly free R-charge assignment and the traceless condition for
total vorticities are satisfied, we find that the superconformal index
factorizes to a pair of the elliptic uplift of the vortex partition functions.
We also study the relation between open topological string and the the elliptic
uplift of the vortex partition functions. In the three dimensional limit, we
show index for U(N) theory reduces to the factorized form of the partition
function on the three dimensional squashed sphere.


  In his previous paper (Math. Res. Letters 7(2000), 123--132) the author
proved that in characteristic zero the jacobian $J(C)$ of a hyperelliptic curve
$C: y^2=f(x)$ has only trivial endomorphisms over an algebraic closure $K_a$ of
the ground field $K$ if the Galois group $Gal(f)$ of the irreducible polynomial
$f(x) \in K[x]$ is either the symmetric group $S_n$ or the alternating group
$A_n$. Here $n>4$ is the degree of $f$. In math.AG/0003002 we extended this
result to the case of certain ``smaller'' Galois groups. In particular, we
treated the infinite series $n=2^r+1, Gal(f)=L_2(2^r)$ and $n=2^{4r+2}+1,
Gal(f)=Sz(2^{2r+1})$. In this paper we do the case of $Gal(f)=\U_3(2^m)$ and
$n=2^{3m}+1$.


  Radio relics have been discovered in many galaxy clusters. They are believed
to trace shock fronts induced by cluster mergers. Cosmological simulations
allow us to study merger shocks in detail since the intra-cluster medium is
heated by shock dissipation. Using high resolution cosmological simulations,
identifying shock fronts and applying a parametric model for the radio emission
allows us to simulate the formation of radio relics. We analyze a simulated
shock front in detail. We find a rather broad Mach number distribution. The
Mach number affects strongly the number density of relativistic electrons in
the downstream area, hence, the radio luminosity varies significantly across
the shock surface. The abundance of radio relics can be modeled with the help
of the radio power probability distribution which aims at predicting radio
relic number counts. Since the actual electron acceleration efficiency is not
known, predictions for the number counts need to be normalized by the observed
number of radio relics. For the characteristics of upcoming low frequency
surveys we find that about thousand relics are awaiting discovery.


  In this paper we discuss improved estimators for the regression and the
dispersion parameters in an extended class of dispersion models (J{\o}rgensen,
1996). This class extends the regular dispersion models by letting the
dispersion parameter vary throughout the observations, and contains the
dispersion models as particular case. General formulae for the second-order
bias are obtained explicitly in dispersion models with dispersion covariates,
which generalize previous results by Botter and Cordeiro (1998), Cordeiro and
McCullagh (1991), Cordeiro and Vasconcellos (1999), and Paula (1992). The
practical use of the formulae is that we can derive closed-form expressions for
the second-order biases of the maximum likelihood estimators of the regression
and dispersion parameters when the information matrix has a closed-form.
Various expressions for the second-order biases are given for special models.
The formulae have advantages for numerical purposes because they require only a
supplementary weighted linear regression. We also compare these bias-corrected
estimators with two different estimators which are also bias-free to the
second-order that are based on bootstrap methods. These estimators are compared
by simulation.


  We consider the Navier--Stokes--Fourier system in a bounded domain $\Omega
\subset R^d$, $d=2,3$, with physically realistic in/out flow boundary
conditions. We develop a new concept of weak solutions satisfying a general
form of relative energy inequality. The weak solutions exist globally in time
for any finite energy initial data and comply with the weak--strong uniqueness
principle.


  In a gravitational field, we analyze the Maxwell equations, the correponding
electromagnetic wave and continuity equations. A particular solution for
parellel electric and magnetic fields in a gravitational background is
presented. These solutions also satisfy the free-wave equations and the
phenomenology suggested by plasma physics.


  The purpose of this paper is to study well-posedness of the initial value
problem (IVP) for the inhomogeneous nonlinear Schr\"odinger equation (INLS) $$
i u_t +\Delta u+\lambda|x|^{-b}|u|^\alpha u = 0, $$ where $\lambda=\pm 1$ and
$\alpha$, $b>0$.
  We obtain local and global results for initial data in $H^s(\mathbb{R}^N)$,
with $0\leq s\leq 1$. To this end, we use the contraction mapping principle
based on the Strichartz estimates related to the linear problem.


  We calculate a new suite of albedo models for close-in extrasolar giant
planets and compare with the recent stringent upper limit for HD 209458b of
Rowe et al. using MOST. We find that all models without scattering clouds are
consistent with this optical limit. We explore the dependence on wavelength and
waveband, metallicity, the degree of heat redistribution, and the possible
presence of thermal inversions and find a rich diversity of behaviors.
Measurements of transiting extrasolar giant planets (EGPs) at short wavelengths
by MOST, Kepler, and CoRoT, as well as by proposed dedicated multi-band
missions, can complement measurements in the near- and mid-IR using {\it
Spitzer} and JWST. Collectively, such measurements can help determine
metallicity, compositions, atmospheric temperatures, and the cause of thermal
inversions (when they arise) for EGPs with a broad range of radii, masses,
degrees of stellar insolation, and ages. With this paper, we reappraise and
highlight the diagnostic potential of albedo measurements of hot EGPs shortward
of $\sim$1.3 $\mu$m.


  This paper describes the results of the most recent measurement of the
permanent electric dipole moment (EDM) of neutral $^{199}$Hg atoms. Fused
silica vapor cells containing enriched $^{199}$Hg are arranged in a stack in a
common magnetic field. Optical pumping is used to spin-polarize the atoms
orthogonal to the applied magnetic field, and the Faraday rotation of
near-resonant light is observed to determine an electric-field-induced
perturbation to the Larmor precession frequency. Our results for this frequency
shift are consistent with zero; we find the corresponding $^{199}$Hg EDM
$d_{Hg} = (2.20 \pm 2.75_{stat} \pm 1.48_{syst}) \times 10^{-30} e\cdot
\text{cm}$. We use this result to place a new upper limit on the $^{199}$Hg EDM
$|d_{Hg}| < 7.4\times 10^{-30} e\cdot \text{cm}$ (95\% C.L.), improving our
previous limit by a factor of 4. We also discuss the implications of this
result for various $CP$-violating observables as they relate to theories of
physics beyond the standard model.


  Fusion reactions induced by the weakly bound nucleus $^{6}$Li with targets
$^{28}$Si, $^{64}$Ni, $^{144}$Sm and $^{209}$Bi at energies around the Coulomb
barrier are investigated within a three-body model where $^{6}$Li is described
with an $\alpha + d$ cluster model. The total fusion (TF) cross sections are
calculated with the continuum-discretized coupled-channel (CDCC) method and the
complete fusion (CF) cross sections are extracted through the sum-rule model.
The calculations demonstrate that (i) for the TF cross section calculations,
the continuum states up to 40 MeV are found to be necessary, which corresponds
to the inclusion of closed channels for light and medium mass targets, such as
$^{28}$Si, $^{59}$Co and $^{144}$Sm, (ii) the converged CDCC results for TF
cross section at energies above the Coulomb barrier are almost the same as
single channel results in which the continuum coupling effect is neglected, and
(iii) the continuum coupling strongly influences partial wave fusion cross
sections and the closed channels play a significant role in the improvement of
the description of the CF cross sections at energies below the Coulomb barrier
for the $^6$Li+$^{28}$Si, $^{59}$Co and $^{144}$Sm systems.


  Let $\mathfrak{g}$ be a simple Lie algebra, and let $W_\kappa$ be the affine
${W}$-algebra associated to a principal nilpotent element of $\mathfrak{g}$ and
level $\kappa$. We explain a duality between the categories of smooth ${W}$
modules at levels $\kappa + \kappa_c$ and $-\kappa + \kappa_c$, where
$\kappa_c$ is the critical level. Their pairing amounts to a construction of
semi-infinite cohomology for the ${W}$-algebra. As an application, we determine
all homomorphisms between the Verma modules for ${W}$, verifying a conjecture
from the conformal field theory literature of de Vos--van Driel. Along the way,
we determine the linkage principle for Category $\mathscr{O}$ of the
${W}$-algebra.


  We introduce an associative algebra $\M_k(x)$ whose dimension is the $2k$-th
Motzkin number. The algebra $\M_k(x)$ has a basis of "Motzkin diagrams," which
are analogous to Brauer and Temperley-Lieb diagrams, and it contains the
Temperley-Lieb algebra $\TL_k(x)$ as a subalgebra. We prove that for a
particular value of $x$, the algebra $\M_k(x)$ is the centralizer algebra of
$\uqsl$ acting on the $k$-fold tensor power of the sum of the 1-dimensional and
2-dimensional irreducible $\uqsl$-modules. We show that $\M_k(x)$ is generated
by special diagrams $\ell_i, t_i, r_i \ (1 \le i < k)$ and $p_j \ (1 \le j \le
k)$, and that it has a factorization into three subalgebras $\M_k(x) = \RP_k
\TL_k(x)\, \LP_k$, all of which have dimensions given by Catalan numbers. We
define an action of $\M_k(x)$ on Motzkin paths of rank $r$, and in this way,
construct a set of indecomposable modules $\C_k^{(r)}$, $0 \le r \le k$. We
prove that $\M_k(x)$ is cellular in the sense of Graham and Lehrer and that the
$\C_k^{(r)}$ are the left cell representations. We compute the determinant of
the Gram matrix of a bilinear form on $\C_k^{(r)}$ for each $r$ and use these
determinants to show that $\M_k(x)$ is semisimple exactly when $x$ is not the
root of certain Chebyshev polynomials.


  We survey commutative and non-commutative analogs of uniform algebras in the
Archimedean settings and also offer some non-Archimedean examples. Constraints
on the development of non-complex uniform algebras are also discussed.


  We define the notion of infinite friezes of positive integers as a variation
of Conway-Coxeter frieze patterns and study their properties. We introduce
useful gluing and cutting operations on infinite friezes. It turns out that
triangulations of once-punctured discs give rise to periodic infinite friezes
having special properties, a notable example being that each diagonal consists
of a collection of arithmetic progressions. Furthermore, we work out a
combinatorial interpretation of the entries of infinite friezes associated to
triangulations of once-punctured discs via matching numbers for certain
combinatorial objects, namely periodic triangulations of strips. Alternatively,
we consider a known algorithm that as we show computes as well these entries.


  High accuracy and dynamic range have been some of the most prominent
challenges when it comes to fine-scale turbulence measurements. The current
commercial LDA processors, which perform the signal processing of Doppler
bursts directly using hardware components, are essentially black boxes and in
particular are renown for suffering from practical limitations that reduce the
measurement reliability and accuracy. A transparently functioning novel LDA,
utilizing advanced technologies and up-to-date hardware and software has
therefore been developed to enhance the measurement quality and the dynamic
range. In addition, the self-developed software comes with a highly flexible
functionality for the signal processing and data interpretation. The LDA setup
and the combined forward/side scattering optical alignment (to minimize the
effective measuring volume) are described first, followed by a description of
the signal processing aspects. The round turbulent jet has been used as the
test bed since it presents a wide range of degree of difficulty for the LDA
processor (accuracy, dynamic range etc.) across the different radial distances
and downstream development. The data are diagnosed for dynamic range in
residence and interarrival times, and compared to a typical hardware driven
processor. The radial profiles of measured mean streamwise velocity and
variance agree well with previous studies of the round jet. The spatial
turbulent kinetic energy spectra in the fully developed region perfectly match
the expected (and in this region well established) -5/3 power law even for the
largest measured distances from the centerline (where shear and turbulence
intensity are significant).


  The Visibility-based Persistent Monitoring (VPM) problem seeks to find a set
of trajectories (or controllers) for robots to persistently monitor a changing
environment. Each robot has a sensor, such as a camera, with a limited
field-of-view that is obstructed by obstacles in the environment. The robots
may need to coordinate with each other to ensure no point in the environment is
left unmonitored for long periods of time. We model the problem such that there
is a penalty that accrues every time step if a point is left unmonitored.
However, the dynamics of the penalty are unknown to us. We present a
Multi-Agent Reinforcement Learning (MARL) algorithm for the VPM problem.
Specifically, we present a Multi-Agent Graph Attention Proximal Policy
Optimization (MA-G-PPO) algorithm that takes as input the local observations of
all agents combined with a low resolution global map to learn a policy for each
agent. The graph attention allows agents to share their information with others
leading to an effective joint policy. Our main focus is to understand how
effective MARL is for the VPM problem. We investigate five research questions
with this broader goal. We find that MA-G-PPO is able to learn a better policy
than the non-RL baseline in most cases, the effectiveness depends on agents
sharing information with each other, and the policy learnt shows emergent
behavior for the agents.


  Co-occurrence matrices, such as co-citation, co-word, and co-link matrices,
have been used widely in the information sciences. However, confusion and
controversy have hindered the proper statistical analysis of this data. The
underlying problem, in our opinion, involved understanding the nature of
various types of matrices. This paper discusses the difference between a
symmetrical co-citation matrix and an asymmetrical citation matrix as well as
the appropriate statistical techniques that can be applied to each of these
matrices, respectively. Similarity measures (like the Pearson correlation
coefficient or the cosine) should not be applied to the symmetrical co-citation
matrix, but can be applied to the asymmetrical citation matrix to derive the
proximity matrix. The argument is illustrated with examples. The study then
extends the application of co-occurrence matrices to the Web environment where
the nature of the available data and thus data collection methods are different
from those of traditional databases such as the Science Citation Index. A set
of data collected with the Google Scholar search engine is analyzed using both
the traditional methods of multivariate analysis and the new visualization
software Pajek that is based on social network analysis and graph theory.


  We have considered the physics opportunities of future lepton-hadron
colliders and how these opportunities might be realized in a possible polarized
eRHIC facility and an e-p collider as part of a staged or final version VLHC.
We evaluated the physics priorities based on experience at HERA and, using
simulated data for e-p collisions with sqrt(s) > 1 TeV, showed how detector
designs would be impacted by the physics.


  Functorial semi-norms are semi-normed refinements of functors such as
singular (co)homology. We investigate how different types of representability
affect the (non-)triviality of finite functorial semi-norms on certain functors
or classes. In particular, we consider representable functors, generalised
cohomology theories, and so-called weakly flexible homology classes in singular
homology and l1-homology.


  The spatial inhomogeneity of the distribution of coronal mass ejection (CME)
occurrences in the solar atmosphere could provide a tool to estimate the
longitudinal position of the most probable CME-capable active regions in the
Sun. The anomaly in the longitudinal distribution of active regions themselves
is often referred to as active longitude (AL). In order to reveal the
connection between the AL and CME spatial occurrences, here we investigate the
morphological properties of active regions. The first morphological property
studied is the separateness parameter, which is able to characterize the
probability of the occurrence of an energetic event, such as a solar flare or
CME. The second morphological property is the sunspot tilt angle. The tilt
angle of sunspot groups allows us to estimate the helicity of active regions.
The increased helicity leads to a more complex buildup of the magnetic
structure and also can cause CME eruption. We found that the most complex
active regions appear near the AL and that the AL itself is associated with the
most tilted active regions. Therefore, the number of CME occurrences is higher
within the AL. The origin of the fast CMEs is also found to be associated with
this region. We concluded that the source of the most probably CME-capable
active regions is at the AL. By applying this method, we can potentially
forecast a flare and/or CME source several Carrington rotations in advance.
This finding also provides new information for solar dynamo modeling.


  Stimulated two-photon emission by Bose-condensed excitons accompanied by a
coherent two-exciton recombination, i.e., by simultaneous recombination of two
excitons with opposite momenta leaving unchanged the occupation numbers of
excitonic states with nonzero momenta, is investigated. Raman light scattering
accompanied by a similar two-exciton recombination (or generation of two
excitons) is also analyzed. The processes under consideration can occur only if
a system contains Bose condensate, therefore, their detection can be used as a
new method to reveal Bose condensation of excitons. The recoil momentum, which
corresponds to a change in the momentum of the electromagnetic field in the
processes, is transferred to phonons or impurities. If the recoil momentum is
transmitted to optical phonons with frequency $\omega_0^s$, the stimulated
two-photon emission with the coherent two-exciton recombination leads to the
appearance of a line at $2\Omega'-\omega$, where $\Omega'=\Omega-\omega_0^s$
and $\Omega$ is the light frequency corresponding to the recombination of an
exciton with zero momentum. Formulas for the cross sections at finite
temperatures are obtained for the processes under consideration. Our estimates
indicate that a spectral line, corresponding to the stimulated two-photon
emission accompanied by the coherent optical phonon-assisted two-exciton
recombination can be experimentally detected in Cu$_2$O.


  In a recent comment to the paper Chaotic Integrable transition in the SYK
model, it was claimed that, in a certain region of parameters, the Lyapunov
exponent of the N Majoranas Sachdev-Ye-Kitaev model with a quadratic
perturbation, is always positive. This implies that the model is quantum
chaotic. In this reply, we show that the employed perturbative formalism breaks
down precisely in the range of parameters investigated in the comment due to a
lack of separation of time scales. Moreover, based on recent analytical
results, we show that for any large and fixed N, the model has indeed a
chaotic-integrable transition that invalidate the results of the comment.


  HD5550 is a spectroscopic binary composed of two A stars observed with Narval
at TBL in the frame of the BinaMIcS (Binarity and Magnetic Interactions in
various classes of Stars) Large Program. One component of the system is found
to be an Ap star with a surprisingly weak dipolar field of ~65 G. The companion
is an Am star for which no magnetic field is detected, with a detection
threshold on the dipolar field of ~40 G. The system is tidally locked, the
primary component is synchronised with the orbit, but the system is probably
not completely circularised yet. This work is only the second detailed study of
magnetic fields in a hot short-period spectroscopic binary. More systems are
currently being observed with both Narval at TBL and ESPaDOnS at CFHT within
the BinaMIcS project, with the goal of understanding how magnetism can impact
binary evolution and vice versa.


  Let $X=\{X(t), t\geq 0\}$ be a Brownian motion or a spectrally negative
stable process of index $1<\a<2$. Let $E=\{E(t),t\geq 0\}$ be the hitting time
of a stable subordinator of index $0<\beta<1$ independent of $X$. We use a
connection between $X(E(t))$ and the stable subordinator of index $\beta/\a$ to
derive information on the path behavior of $X(E_t)$. This is an extension of
the connection of iterated Brownian motion and (1/4)-stable subordinator due to
  Bertoin \cite{bertoin}.
  Using this connection, we obtain various laws of the iterated logarithm for
$X(E(t))$. In particular, we establish law of the iterated logarithm for local
time Brownian motion, $X(L(t))$, where $X$ is a Brownian motion (the case
$\a=2$) and $L(t)$ is the local time at zero of a stable process $Y$ of index
$1<\gamma\leq 2$ independent of $X$. In this case $E(\rho t)=L(t)$ with
$\beta=1-1/\gamma$ for some constant $\rho>0$. This establishes the lower bound
in the law of the iterated logarithm which we could not prove with the
techniques of our paper \cite{MNX}. We also obtain exact small ball probability
for $X(E_t)$ using ideas from \cite{aurzada}.


  Several extensions to the Standard Model of particle physics, including light
dark matter candidates and unification theories, predict deviations from
Newton's law of gravitation. For macroscopic distances, the inverse-square law
of gravitation is well confirmed by astrophysical observations and laboratory
experiments. At micrometer and shorter length scales, however, even the
state-of-the-art constraints on deviations from gravitational interaction,
whether provided by neutron scattering or precise measurements of forces
between macroscopic bodies, are currently many orders of magnitude larger than
gravity itself. Here we show that precision spectroscopy of weakly bound
molecules can be used to constrain non-Newtonian interactions between atoms. A
proof-of-principle demonstration using recent data from photoassociation
spectroscopy of weakly bound Yb$_2$ molecules yields constraints on these new
interactions that are already close to state-of-the-art neutron scattering
experiments. At the same time, with the development of the recently proposed
optical molecular clocks, the neutron scattering constraints could be surpassed
by at least two orders of magnitude.


  We investigate the 2D excitation structure of the ISM in a sample of LIRGs
and Seyferts using near-IR IFS. This study extends to the near-IR the
well-known optical and mid-IR emission line diagnostics used to classify
activity in galaxies. Based on the spatially resolved spectroscopy of
prototypes, we identify in the [FeII]1.64/Br$\gamma$ - H_2 1-0S(1)/Br$\gamma$
plane regions dominated by the different heating sources, i.e. AGNs, young MS
massive stars, and evolved stars i.e. supernovae. The ISM in LIRGs occupy a
wide region in the near-IR diagnostic plane from -0.6 to +1.5 and from -1.2 to
+0.8 (in log units) for the [FeII]/Br$\gamma$ and H_2/Br$\gamma$ line ratios,
respectively. The corresponding median(mode) ratios are +0.18(0.16) and
+0.02(-0.04). Seyferts show on average larger values by factors ~2.5 and ~1.4
for the [FeII]/Br$\gamma$ and H_2/Br$\gamma$ ratios, respectively. New areas
and relations in the near-IR diagnostic plane are defined for the compact, high
surface brightness regions dominated by AGN, young ionizing stars, and SNe
explosions, respectively. In addition, the diffuse regions affected by the AGN
radiation field cover an area similar to that of Seyferts, but with high values
in [FeII]/Br$\gamma$ that are not as extreme. The extended, non-AGN diffuse
regions cover a wide area in the diagnostic diagram that overlaps that of
individual excitation mechanisms (i.e. AGN, young stars, and SNe), but with its
mode value to that of the young SF clumps. This indicates that the excitation
conditions of the diffuse ISM are likely due to a mixture of the different
ionization sources. The integrated line ratios in LIRGs show higher excitation
conditions i.e. towards AGNs, than those measured by the spatially resolved
spectroscopy. If this behaviour is representative, it would have clear
consequences when classifying high-z, SF galaxies based on their near-IR
integrated spectra.


  We study the structure of the unit sphere of polygonal Radon planes from a
geometric point of view. In particular, we prove that a $ 2 $-dimensional real
polygonal Banach space $ \mathbb{X} $ cannot be a Radon plane if the number of
vertices of its unit sphere is $ 4n, $ for some $ n \in \mathbb{N}. $ We next
obtain a complete characterization of polygonal Radon planes in terms of a
tractable geometric concept introduced in this article. It follows from our
characterization that every regular polygon with $ 4n+2 $ vertices, where $ n
\in \mathbb{N}, $ is the unit sphere of a Radon plane. We further give example
of a family of Radon planes for which the unit spheres are hexagons, but not
regular ones.


  Data-driven deep learning models are on the verge of transforming global
weather forecasting. It is an open question if this success can extend to
climate modeling, where long inference rollouts and data complexity pose
significant challenges. Here, we present the first conditional generative model
able to produce global climate ensemble simulations that are accurate and
physically consistent. Our model runs at 6-hourly time steps and is shown to be
stable for 10-year-long simulations. Our approach beats relevant baselines and
nearly reaches a gold standard for successful climate model emulation. We
discuss the key design choices behind our dynamics-informed diffusion
model-based approach which enables this significant step towards efficient,
data-driven climate simulations that can help us better understand the Earth
and adapt to a changing climate.


  Given $R \subseteq \mathbb{N}$ let ${n \brace k}_R$, ${n \brack k}_R$, and
$L(n,k)_R$ be the number of ways of partitioning the set $[n]$ into $k$
non-empty subsets, cycles and lists, respectively, with each block having
cardinality in $R$. We refer to these as the $R$-restricted Stirling numbers of
the second and first kind and the $R$-restricted Lah numbers, respectively.
Note that the classical Stirling numbers of the second kind and first kind, and
Lah numbers are ${n \brace k} = {n \brace k}_{\mathbb{N}}$, ${n \brack k} = {n
\brack k}_{\mathbb{N}} $ and $L(n,k) = L(n,k)_{\mathbb{N}}$, respectively.
  The matrices $[{n \brace k}]_{n,k \geq 1}$, $[{n \brack k}]_{n,k \geq 1}$ and
$[L(n,k)]_{n,k \geq 1}$ have inverses $[(-1)^{n-k}{n \brack k}]_{n,k \geq 1}$,
$[(-1)^{n-k} {n \brace k}]_{n,k \geq 1}$ and $[(-1)^{n-k} L(n,k)]_{n,k \geq 1}$
respectively. The inverse matrices $[{n \brace k}_R]^{-1}_{n,k \geq 1}$, $[{n
\brack k}_R]^{-1}_{n,k \geq 1}$ and $[L(n,k)_R]^{-1}_{n,k \geq 1}$ exist if and
only if $1 \in R$. We express each entry of each of these matrices as the
difference between the cardinalities of two explicitly defined families of
labeled forests. In particular the entries of $[{n \brace k}_{[r]}]^{-1}_{n,k
\geq 1}$ have combinatorial interpretations, affirmatively answering a question
of Choi, Long, Ng and Smith from 2006.
  If $1,2 \in R$ and if for all $n \in R$ with $n$ odd and $n \geq 3$, we have
$n \pm 1 \in R$, we additionally show that each entry of $[{n \brace
k}_R]^{-1}_{n,k \geq 1}$, $[{n \brack k}_R]^{-1}_{n,k \geq 1}$ and
$[L(n,k)_R]^{-1}_{n,k \geq 1}$ is up to an explicit sign the cardinality of a
single explicitly defined family of labeled forests. Our results also provide
combinatorial interpretations of the $k$th Whitney numbers of the first and
second kinds of $\Pi_n^{1,d}$, the poset of partitions of $[n]$ that have each
part size congruent to $1$ mod $d$.


  The correspondence between two geometrical descriptions of the KP-hierarchy,
one by discrete surface and another by difference analogue of differential
geometry, is given.


  A very popular problem on braid groups has recently been solved by Bigelow
and Krammer, namely, they have found a faithful linear representation for the
braid group B_n. In their papers, Bigelow and Krammer suggested that their
representation is the monodromy representation of a certain fibration. Our goal
in this paper is to understand this monodromy representation using standard
tools from the theory of hyperplane arrangements. In particular, we prove that
the representation of Bigelow and Krammer is a sub-representation of the
monodromy representation which we consider, but that it cannot be the whole
representation.


  The Tukey depth of a flat with respect to a point set is a concept that
appears in many areas of discrete and computational geometry. In particular,
the study of centerpoints, center transversals, Ham Sandwich cuts, or $k$-edges
can all be phrased in terms of depths of certain flats with respect to one or
more point sets. In this work, we introduce the Tukey depth histogram of
$k$-flats in $\mathbb{R}^d$ with respect to a point set $P$, which is a vector
$D^{k,d}(P)$, whose $i$'th entry $D^{k,d}_i(P)$ denotes the number of $k$-flats
spanned by $k+1$ points of $P$ that have Tukey depth $i$ with respect to $P$.
As our main result, we give a complete characterization of the depth histograms
of points, that is, for any dimension $d$ we give a description of all possible
histograms $D^{0,d}(P)$. This then allows us to compute the exact number of
possible such histograms.


  We study efficient deep learning training algorithms that process received
wireless signals, if a test Signal to Noise Ratio (SNR) estimate is available.
We focus on two tasks that facilitate source identification: 1- Identifying the
modulation type, 2- Identifying the wireless technology and channel in the 2.4
GHz ISM band. For benchmarking, we rely on recent literature on testing deep
learning algorithms against two well-known datasets. We first demonstrate that
using training data corresponding only to the test SNR value leads to dramatic
reductions in training time while incurring a small loss in average test
accuracy, as it improves the accuracy for low SNR values. Further, we show that
an erroneous test SNR estimate with a small positive offset is better for
training than another having the same error magnitude with a negative offset.
Secondly, we introduce a greedy training SNR Boosting algorithm that leads to
uniform improvement in accuracy across all tested SNR values, while using a
small subset of training SNR values at each test SNR. Finally, we demonstrate
the potential of bootstrap aggregating (Bagging) based on training SNR values
to improve generalization at low test SNR values with scarcity of training
data.


  Given two locally conformal symplectic (LCS) structures on manifolds $M_1$
and $M_2$, we construct a natural $\R^+$-torsor of locally conformal symplectic
structures on a certain covering space $M_1 \boxplus M_2$ of $M_1 \times M_2$.
As the smooth construction of $M_1 \boxplus M_2$ is natural from the
perspective of flat line bundles, we use this language to phrase the LCS
theory. This construction shares many properties with, and in a sense
generalizes, the standard symplectic product. Notably, for a Hamiltonian
isotopy $\phi_t$ of an LCS manifold $M$, there is an associated Lagrangian
embedding $\Gamma(\phi_1) \colon M \hookrightarrow M \boxplus M$, in which
certain fixed points of $\phi_1$ are in bijection with intersection points of
$\Gamma(\phi_1)$ with the diagonal $\Delta = \Gamma(\mathrm{id})$. Using a
Lagrangian intersection of result of the first author and E. Murphy, we may
conclude that if $\phi_t$ is a $C^0$-small Hamiltonian isotopy, then the number
of fixed points of $\phi_1$ is bounded below by the rank of the Novikov theory
associated to the Lee class of the LCS structure on $M$. Finally, we end the
paper by constructing the suspension of a Lagrangian submanifold along a
Hamiltonian isotopy in the LCS theory, again generalizing the symplectic
setting.


  We reveal the intricate impact of nonlinearity and disorder on the thermal
conductivity of acoustic chains. Disorder induces mobility edges and allows to
control the amount of extended modes which are the ballistic channels for
energy transport. Nonlinearity adds a diffusive conductivity channel through
interacting localized modes, and controls the contact resistance at the edges.
Analytical arguments and numerical results yield several crossovers between
dominating heat channels, when varying the system size and the temperature. We
demonstrate that the nonlinearity-induced interaction between the modes alters
the transport through existing conductivity channels and creates new ones,
underpinning the observed phenomena.


  We revisit the anisotropic universe model previously developed by Ackerman,
Carroll and Wise (ACW), and generalize both the theoretical and computational
framework to include polarization and various forms of systematic effects. We
apply our new tools to simulated WMAP data in order to understand the potential
impact of asymmetric beams, noise mis-estimation and potential Zodiacal light
emission. We find that neither has any significant impact on the results. We
next show that the previously reported ACW signal is also present in the 1-year
WMAP temperature sky map presented by Liu & Li, where data cuts are more
aggressive. Finally, we reanalyze the 5-year WMAP data taking into account a
previously neglected (-i)^{l-l'}-term in the signal covariance matrix. We still
find a strong detection of a preferred direction in the temperature map.
Including multipoles up to l=400, the anisotropy amplitude for the W-band is
found to be g = 0.29 +- 0.031, nonzero at 9 sigma. However, the corresponding
preferred direction is also shifted very close to the ecliptic poles at (l,b)=
(96,30), in agreement with the analysis of Hanson & Lewis, indicating that the
signal is aligned along the plane of the solar system. This strongly suggests
that the signal is not of cosmological origin, but most likely is a product of
an unknown systematic effect. Determining the nature of the systematic effect
is of vital importance, as it might affect other cosmological conclusions from
the WMAP experiment. Finally, we provide a forecast for the Planck experiment
including polarization.


  Machine learning algorithms have the capacity to discern intricate features
directly from raw data. We demonstrated the performance of top taggers built
upon three machine learning architectures: a BDT that uses jet-level variables
(high-level features, HLF) as input, while a CNN trained on the jet image, and
a GNN trained on the particle cloud representation of a jet utilizing the
4-momentum (low-level features, LLF) of the jet constituents as input. We found
significant performance enhancement for all three classes of classifiers when
trained on combined data from calorimeter towers and tracker detectors. The
high resolution of the tracking data not only improved the classifier
performance in the high transverse momentum region, but the information about
the distribution and composition of charged and neutral constituents of the fat
jets and subjets helped identify the quark/gluon origin of sub-jets and hence
enhances top tagging efficiency. The LLF-based classifiers, such as CNN and
GNN, exhibit significantly better performance when compared to HLF-based
classifiers like BDT, especially in the high transverse momentum region.
Nevertheless, the LLF-based classifiers trained on constituents' 4-momentum
data exhibit substantial dependency on the jet modeling within Monte Carlo
generators. The composite classifiers, formed by stacking a BDT on top of a
GNN/CNN, not only enhance the performance of LLF-based classifiers but also
mitigate the uncertainties stemming from the showering and hadronization model
of the event generator. We have conducted a comprehensive study on the
influence of the fat jet's reconstruction and labeling procedure on the
efficiency of the classifiers. We have shown the variation of the classifier's
performance with the transverse momentum of the fat jet.


  We compute the NSVZ beta functions for N = 1 four-dimensional quiver theories
arising from D-brane probes on singularities, complete with anomalous
dimensions, for a large set of phases in the corresponding duality tree. While
these beta functions are zero for D-brane probes, they are non-zero in the
presence of fractional branes. As a result there is a non-trivial RG behavior.
We apply this running of gauge couplings to some toric singularities such as
the cones over Hirzebruch and del Pezzo surfaces. We observe the emergence in
string theory, of ``Duality Walls,'' a finite energy scale at which the number
of degrees of freedom becomes infinite, and beyond which Seiberg duality does
not proceed. We also identify certain quiver symmetries as T-duality-like
actions in the dual holographic theory.


  Open Information Extraction (OpenIE) methods extract (noun phrase, relation
phrase, noun phrase) triples from text, resulting in the construction of large
Open Knowledge Bases (Open KBs). The noun phrases (NPs) and relation phrases in
such Open KBs are not canonicalized, leading to the storage of redundant and
ambiguous facts. Recent research has posed canonicalization of Open KBs as
clustering over manuallydefined feature spaces. Manual feature engineering is
expensive and often sub-optimal. In order to overcome this challenge, we
propose Canonicalization using Embeddings and Side Information (CESI) - a novel
approach which performs canonicalization over learned embeddings of Open KBs.
CESI extends recent advances in KB embedding by incorporating relevant NP and
relation phrase side information in a principled manner. Through extensive
experiments on multiple real-world datasets, we demonstrate CESI's
effectiveness.


  Using a combination of vertical transport measurements across and lateral
transport measurements along the LaAlO$_{3}$/SrTiO$_{3}$ heterointerface, we
demonstrate that significant potential barrier lowering and band bending are
the cause of interfacial metallicity. Barrier lowering and enhanced band
bending extends over 2.5 nm into LaAlO$_{3}$ as well as SrTiO$_{3}$. We explain
origins of high-temperature carrier saturation, lower carrier concentration,
and higher mobility in the sample with the thinnest LaAlO$_{3}$ film on a
SrTiO$_{3}$ substrate. Lateral transport results suggest that parasitic
interface scattering centers limit the low-temperature lateral electron
mobility of the metallic channel.


  This study examines the time complexities of the unbalanced optimal transport
problems from an algorithmic perspective for the first time. We reveal which
problems in unbalanced optimal transport can/cannot be solved efficiently.
Specifically, we prove that the Kantorovich Rubinstein distance and optimal
partial transport in the Euclidean metric cannot be computed in strongly
subquadratic time under the strong exponential time hypothesis. Then, we
propose an algorithm that solves a more general unbalanced optimal transport
problem exactly in quasi-linear time on a tree metric. The proposed algorithm
processes a tree with one million nodes in less than one second. Our analysis
forms a foundation for the theoretical study of unbalanced optimal transport
algorithms and opens the door to the applications of unbalanced optimal
transport to million-scale datasets.


  Generalization is an important attribute of machine learning models,
particularly for those that are to be deployed in a medical context, where
unreliable predictions can have real world consequences. While the failure of
models to generalize across datasets is typically attributed to a mismatch in
the data distributions, performance gaps are often a consequence of biases in
the 'ground-truth' label annotations. This is particularly important in the
context of medical image segmentation of pathological structures (e.g.
lesions), where the annotation process is much more subjective, and affected by
a number underlying factors, including the annotation protocol, rater
education/experience, and clinical aims, among others. In this paper, we show
that modeling annotation biases, rather than ignoring them, poses a promising
way of accounting for differences in annotation style across datasets. To this
end, we propose a generalized conditioning framework to (1) learn and account
for different annotation styles across multiple datasets using a single model,
(2) identify similar annotation styles across different datasets in order to
permit their effective aggregation, and (3) fine-tune a fully trained model to
a new annotation style with just a few samples. Next, we present an
image-conditioning approach to model annotation styles that correlate with
specific image features, potentially enabling detection biases to be more
easily identified.


  The faithful irreducible $*$-representations of the $C^*$-algebra of the
quantum symplectic sphere $S_q^{4n-1}, n\geq 2$, have been investigated by
D'Andrea and Landi. They proved that the first $n-1$ generators are all zero
inside $C^*(S_q^{4n-1})$, for $n\geq 2$. The result is a generalisation of the
case where $n=2$, which was shown by Mikkelsen and Szyma\'nski.
  We will show that $C^*(S_q^{4n-1}), n\geq 2$ is isomorphic to a graph
$C^*$-algebra. From here it follows that $C^*(S_q^{4n-1})$ is isomorphic to the
quantum $(2(n+1)-1)$-sphere by Vaksman and Soibelman.


  We have studied the strangeness changing antineutrino induced reactions
$\bar{\nu}_{l} p \rightarrow l^+ \phi B $, with $\phi B = K^-p$, $\bar{K}^0n$,
$\pi^0\Lambda$, $\pi^0\Sigma^0$, $\eta\Lambda$, $\eta\Sigma^0$,
$\pi^+\Sigma^-$, $\pi^-\Sigma^+$, $K^+\Xi^-$ and $K^0\Xi^0$, using a chiral
unitary approach. These ten coupled channels are allowed to interact strongly,
using a kernel derived from the chiral Lagrangians. This interaction generates
two $\Lambda(1405)$ poles, leading to a clear single peak in the $\pi \Sigma$
invariant mass distributions. At backward scattering angles in the center of
mass frame, $\bar{\nu}_{\mu} p \rightarrow \mu^+ \pi^0 \Sigma^0$ is dominated
by the $\Lambda(1405)$ state at around 1420~MeV while the lighter state becomes
relevant as the angle decreases, leading to an asymmetric line shape. In
addition, there are substantial differences in the shape of $\pi \Sigma$
invariant mass distributions for the three charge channels. If observed, these
differences would provide valuable information on a claimed isospin I=1,
strangeness S=-1 baryonic state around 1400 MeV. Integrated cross sections have
been obtained for the $\pi \Sigma$ and $\bar K N$ channels, investigating the
impact of unitarization in the results. The number of events with
$\Lambda(1405)$ excitation in $\bar\nu_\mu p$ collisions in the recent
antineutrino run at the MINERvA experiment has also been obtained. We find that
this reaction channel is relevant enough to be investigated experimentally and
to be taken into account in the simulation models of future experiments with
antineutrino beams.


  The gravitational wave emission from the merging binary neutron star system
GW170817 arrived full of tidal information which can be used to probe the
fundamental ultra-dense nuclear physics residing in these stars. In previous
work, we used two-dimensional correlations between nuclear matter parameters
and tidal deformabilities of neutron stars applying specifically to GW170817 to
derive constraints on the former. Here, we extend this analysis by finding
similar correlations for varying chirp masses, the dominant determining factor
in the frequency evolution of the inspiral, such that one can apply the same
method to future detections. We estimate how accurately one can measure nuclear
parameters with future gravitational wave interferometers and show how such
measurements can be improved by combining multiple events. We find that bounds
on the nuclear parameters with future observations can improve from the current
one with GW170817 only by $\sim 30\%$ due to the existence of systematic errors
caused mainly by the remaining uncertainty in the equation of state near and
just above the nuclear saturation density. We show that such systematic errors
can be reduced by considering multidimensional correlations among nuclear
parameters and tidal deformabilities with various neutron star masses.


  PSR B1259-63 is a middle-aged radio pulsar (P=48 ms, tau=330 kyr,
Edot=8.3*10^{35} erg/s) in an eccentric binary (P_orb =3.4 yr, e=0.87) with a
high-mass Be companion, SS 2883. We observed the binary near apastron with the
Chandra ACIS detector on 2009 May 14 for 28 ks. In addition to the previously
studied pointlike source at the pulsar's position, we detected extended
emission on the south-southwest side of this source. The pointlike source
spectrum can be described by the absorbed power-law model with the hydrogen
column density N_H = (2.5+/-0.6)*10^{21} cm^{-2}, photon index Gamma =
1.6+/-0.1, and luminosity L_{0.5-8 keV} = 1.3*10^{33} d_3^2 erg/s, where d_3 is
the distance scaled to 3 kpc. This emission likely includes an unresolved part
of the pulsar wind nebula (PWN) created by the colliding winds from the pulsar
and the Be companion, and a contribution from the pulsar magnetosphere. The
extended emission apparently consists of two components. The highly significant
compact component looks like a southward extension of the pointlike source
image, seen up to about 4 arcsec from the pulsar position. Its spectrum has
about the same slope as the pointlike source spectrum, while its luminosity is
a factor of 10 lower. We also detected an elongated feature extended ~15 arcsec
southwest of the pulsar, but significance of this detection is marginal. We
tentatively interpret the resolved compact PWN component as a shocked pulsar
wind blown out of the binary by the wind of the Be component, while the
elongated component could be a pulsar jet.


  We present an orientifold of a toric singularity allowing for a configuration
of fractional branes which corresponds to a gauge theory that dynamically
breaks supersymmetry in a stable vacuum. This model represents the first such
instance within the gauge/gravity duality.


  In a recent proposal [Jie and Zhang, Phys. Rev. A 95, 060701(R) (2017)], it
has been shown that center-of-mass-momentum-dependent two-body interactions can
be generated and tuned by Raman coupling the closed-channel bound states in a
magnetic Feshbach resonance. Here we investigate the universal relations in a
three-dimensional Fermi gas near such a laser modulated $s$-wave Feshbach
resonance. Using the operator-product expansion approach, we find that, to
fully describe the high-momentum tail of the density distribution up to
$q^{-6}$ ($q$ is the relative momentum), four center-of-mass-momentum-dependent
parameters are required, which we identify as contacts. These contacts appear
in various universal relations connecting microscopic and thermodynamic
properties. One contact is related to the variation of energy with respect to
the inverse scattering length and determines the leading $q^{-4}$ tail of the
high-momentum distribution. Another vector contact appears in the subleading
$q^{-5}$ tail, which is related to the velocity of closed-channel molecules.
The other two contacts emerge in the $q^{-6}$ tail and are respectively related
to the variation of energy with respect to the range parameter and to the
kinetic energy of closed-channel molecules. Particularly, we find that the
$q^{-5}$ tail and part of the $q^{-6}$ tail of the momentum distribution show
anisotropic features. We derive the universal relations and, as a concrete
example, estimate the contacts for the zero-temperature superfluid ground state
of the system using a mean-field approach.


  Relying on either deep models or physical models are two mainstream
approaches for solving inverse sample reconstruction problems in programmable
illumination computational microscopy. Solutions based on physical models
possess strong generalization capabilities while struggling with global
optimization of inverse problems due to a lack of insufficient physical
constraints. In contrast, deep learning methods have strong problem-solving
abilities, but their generalization ability is often questioned because of the
unclear physical principles. Besides, conventional deep models are difficult to
apply to some specific scenes because of the difficulty in acquiring
high-quality training data and their limited capacity to generalize across
different scenarios. In this paper, to combine the advantages of deep models
and physical models together, we propose a hybrid framework consisting of three
sub-neural networks (two deep learning networks and one physics-based network).
We first obtain a result with rich semantic information through a light deep
learning neural network and then use it as the initial value of the physical
network to make its output comply with physical process constraints. These two
results are then used as the input of a fusion deep learning neural work which
utilizes the paired features between the reconstruction results of two
different models to further enhance imaging quality. The final result
integrates the advantages of both deep models and physical models and can
quickly solve the computational reconstruction inverse problem in programmable
illumination computational microscopy and achieve better results. We verified
the feasibility and effectiveness of the proposed hybrid framework with
theoretical analysis and actual experiments on resolution targets and
biological samples.


  Since Downs proposed that the act of voting is irrational in 1957, myriad
models have been proposed to explain voting and account for observed turnout
patterns. We propose a model in which partisans consider both the instrumental
and expressive benefits of their vote when deciding whether or not to abstain
in an election, introducing an asymmetry that most other models do not
consider. Allowing learning processes within our electorate, we analyze what
turnout states are rationalizable under various conditions. Our model predicts
comparative statics that are consistent with voter behavior. Furthermore,
relaxing some of our preliminary assumptions eliminates some of the
discrepancies between our model and empirical voter behavior.


  The concept of green in a battery involves the chemical nature of electrodes
and electrolytes as well as the economic sustainability of the cell. Although
these aspects are typically discussed separately, they are deeply
interconnected: indeed, a new electrolyte can allow the use of different
cathodes with higher energy, lower cost or more pronounced environmental
compatibility. We focus on alternative class of electrolyte solutions for
lithium batteries formed by dissolving LiX salts in glyme solvents, i.e.,
organic ethers with the molecular formula CH3O[CH2CH2O]nCH3 differing by chain
length. The advantages of these electrolytes are illustrated in terms of
flammability, stability, toxicity, environmental compatibility, cell
performances and economic impact. A particular light is shed on the stability
of these systems, particularly in the polymer state, and in various
environments including oxygen, sulfur and high-energy lithium metal. The most
relevant studies on the chemical-physical features, the characteristic
structures, the favorable properties, and the electrochemical behavior of the
glyme-based solutions are discussed, and the most recent technological
achievements in terms of cell design and battery performance are described. The
use of glyme-based electrolytes in high-energy cells arranged by coupling the
lithium-metal anode with conventional insertion cathodes as well as in
alternative and new batteries exploiting the Li-S and Li-O2 conversion
processes are described in detail. The paragraphs reveal bonuses, including
safety, low cost and sustainability, that can be achieved by employing the
glyme-based electrolytes with respect to the commercially available ones, in
particular taking into account future and alternative applications. Particular
relevance is given by the glymes with long chain that reveal a remarkable
stability, high safety and very low toxicity.


  We introduce the social welfare implications of the Zenga index, a recently
proposed index of inequality. Our proposal is derived by following the seminal
book by Son (2011) and the recent working paper by Kakwani and Son (2019). We
compare the Zenga based approach with the classical one, based on the Lorenz
curve and the Gini coefficient, as well as the Bonferroni index. We show that
the social welfare specification based on the Zenga uniformity curve presents
some peculiarities that distinguish it from the other considered indexes. The
social welfare specification presented here provides a deeper understanding of
how the Zenga index evaluates the inequality in a distribution.