  We present a new selection technique of producing spectroscopic target
catalogues for massive spectroscopic surveys for cosmology. This work was
conducted in the context of the extended Baryon Oscillation Spectroscopic
Survey (eBOSS), which will use ~200 000 emission line galaxies (ELGs) at
0.6<zspec<1.0 to obtain a precise baryon acoustic oscillation measurement. Our
proposed selection technique is based on optical and near-infrared broad-band
filter photometry. We used a training sample to define a quantity, the Fisher
discriminant (linear combination of colours), which correlates best with the
desired properties of the target: redshift and [OII] flux. The proposed
selections are simply done by applying a cut on magnitudes and this Fisher
discriminant. We used public data and dedicated SDSS spectroscopy to quantify
the redshift distribution and [OII] flux of our ELG target selections. We
demonstrate that two of our selections fulfil the initial eBOSS/ELG redshift
requirements: for a target density of 180 deg^2, ~70% of the selected objects
have 0.6<zspec<1.0 and only ~1% of those galaxies in the range 0.6<zspec<1.0
are expected to have a catastrophic zspec estimate. Additionally, the stacked
spectra and stacked deep images for those two selections show characteristic
features of star-forming galaxies. The proposed approach using the Fisher
discriminant could, however, be used to efficiently select other galaxy
populations, based on multi-band photometry, providing that spectroscopic
information is available. This technique could thus be useful for other future
massive spectroscopic surveys such as PFS, DESI, and 4MOST.


  The relaxation process of a diffusive ring becomes under-damped if the bias
(so called affinity) exceeds a critical threshold value, aka delocalization
transition. This is related to the spectral properties of the pertinent
stochastic kernel. We find the dependence of the relaxation rate on the
affinity and on the length of the ring. Additionally we study the implications
of introducing a weak-link into the circuit, and illuminate some subtleties
that arise while taking the continuum limit of the discrete model.


  The black hole solutions in higher-dimensional spacetimes with the presence
of the power-Maxwell field, surrounded by quintessence, are investigated for
Einstein as well as Rastall gravity. The obtained solutions accommodate for
spherical, planar and hyperbolic symmetries with the presence of the
cosmological constant. Besides, we show that several known black hole solutions
in literature such as those for linear Maxwell theory and BTZ black hole can be
obtained as special cases. The implications of Rastall's theory related to the
present study and the thermodynamics of the black hole solutions are discussed.


  We construct a self-consistent relativistic Newtonian analogue corresponding
to gravitational static spherical symmetric spacetime geometries, staring
directly from a generalized scalar relativistic gravitational action in
Newtonian framework, which gives geodesic equations of motion identical to
those of the parent metric. Consequently, the derived velocity-dependent
relativistic scalar potential, which is a relativistic generalization of
Newtonian gravitational potential, exactly reproduces the relativistic
gravitational features corresponding to any static spherical symmetric
spacetime geometry in its entirety, including all the experimentally tested
gravitational effects in the weak field up to the present. This relativistic
analogous potential is expected to be quite useful in studying wide range of
astrophysical phenomena, especially in strong field gravity.


  Let $X$ be a locally compact abelian group with countable base and let
$\mathcal W$ be a convex cone of positive numerical functions on $X$ which is
invariant under the group action and such that $(X,\mathcal W)$ is a balayage
space or (equivalently, if $1\in \mathcal W$) such that $\mathcal W$ is the set
of excessive functions of a Hunt process on $X$, $\mathcal W$ separates points,
every function in $\mathcal W$ is the supremum of its continuous minorants in
$\mathcal W$, and there exist strictly positive continuous $u,v\in \mathcal W$
such that $u/v\to 0$ at infinity.
  Assuming that there is a Green function $G>0$ for $X$ which locally satisfies
the triangle inequality $G(x,z)\wedge G(y,z)\le C G(x,y)$ (true for many L\'evy
processes), it is shown that Hunt's hypothesis (H) holds, that is, every
semipolar set is polar.


  We describe a general method to determine dualities between supersymmetric 5d
gauge theories. The method is based on performing local S-dualities in the
geometry associated to the gauge theory. We find that often a duality can be
obtained by adding matter to both sides of a more primitive duality. This
allows us to define the notion of irreducible dualities which cannot be
obtained from more primitive dualities. More general dualities then are
obtained by adding matter to both sides of an irreducible duality. The
geometric method described in this paper allows us to systematically construct
irreducible dualities. As an application, we explicitly determine a special
class of irreducible dualities classified by removal and addition of edges into
a Dynkin diagram. This class of dualities vastly generalizes many of the known
5d dualities in the literature.


  The planet formation process and subsequent planet migration may lead to
configurations resulting in strong dynamical interactions among the various
planets. Well-studied possible outcomes include collisions between planets,
scattering events that eject one or more of the planets, and a collision of one
or more of the planets with the parent star. In this work we consider one other
possibility that has seemingly been overlooked in the various scattering
calculations presented in the literature: the tidal capture of two planets
which leads to the formation of a binary planet (or binary brown dwarf) in
orbit about the parent star. We carry out extensive numerical simulations of
such dynamical and tidal interactions to explore the parameter space for the
formation of such binary planets. We show that tidal formation of binary
planets is possible for typical planet masses and distances from the host star.
The detection (or lack thereof) of planet-planet binaries can thus be used to
constrain the properties of planetary systems, including their mutual spacing
during formation, and the fraction of close planets in very eccentric orbits
which are believed to form by a closely related process.


  The IARAI competition Traffic4cast 2021 aims to predict short-term city-wide
high-resolution traffic states given the static and dynamic traffic information
obtained previously. The aim is to build a machine learning model for
predicting the normalized average traffic speed and flow of the subregions of
multiple large-scale cities using historical data points. The model is supposed
to be generic, in a way that it can be applied to new cities. By considering
spatiotemporal feature learning and modeling efficiency, we explore 3DResNet
and Sparse-UNet approaches for the tasks in this competition. The 3DResNet
based models use 3D convolution to learn the spatiotemporal features and apply
sequential convolutional layers to enhance the temporal relationship of the
outputs. The Sparse-UNet model uses sparse convolutions as the backbone for
spatiotemporal feature learning. Since the latter algorithm mainly focuses on
non-zero data points of the inputs, it dramatically reduces the computation
time, while maintaining a competitive accuracy. Our results show that both of
the proposed models achieve much better performance than the baseline
algorithms. The codes and pretrained models are available at
https://github.com/resuly/Traffic4Cast-2021.


  A set $A$ of nonnegative integers is an asymptotic basis of order $h$ if
every sufficiently large integer can be represented as the sum of $h$ not
necessarily distinct elements of $A$. The asymptotic basis $A$ is minimal if
removing any element of $A$ destroys every representation of infinitely many
integers, and so $A\setminus \{a\}$ is not an asymptotic basis of order $h$ for
all $a\in A$. In this paper, a new class of minimal asymptotic bases is
constructed.


  A novel conceptual framework is presented in this paper with an aim to
standardize and virtualize Internet of Things(IoT) infrastructure through
deploying OpenFlow technology. The framework can receivee services based on
context information leaving the current infrastructure unchanged. This
framework allows the active collaboration of heterogeneous devices and
protocols. Moreover it is capable to model placement of physical objects,
manage the system and to collect information for services deployed on an IoT
infrastructure. Our proposed IoT virtualization is applicable to a random
topology scenario which makes it possible to 1) share flow sensors resources 2)
establish multioperational sensor networks, and 3) extend reachability within
the framework without establishing any further physical networks. Flow sensors
achieve better results comparable to the typical sensors with respect to packet
generation, reachability, simulation time, throughput, energy consumption point
of view. Even better results are possible through utilizing multicast groups in
large scale networks.


  We construct a new family of exact quantum field theories modeled on
hyperbolic geometry, called {\it quantum hyperbolic field theories} (QHFTs).
The QHFTs are defined for a $(2+1)$-bordism category based on the set of
compact oriented 3-manifolds $Y$, equipped with properly embedded framed links
$L_\Ff$ and with flat connections $\rho$ of principal $PSL(2,\C)$-bundles over
$Y \setminus L_\Ff$, with arbitrary holonomy at the link meridians. A main
point is the introduction of new parameters for the space of all
$PSL(2,\C)$-characters of a punctured surface. Each QHFT associates to a triple
$(Y,L_\Ff,\rho)$ as above with parametrized boundary components a tensor, which
is generically holomorphic w.r.t. the parameters for the restriction of $\rho$
to $\partial Y \setminus L_\Ff$. This gives new numerical invariants of
3-manifolds, such as Chern-Simons invariants of $PSL(2,\mc)$-characters of
arbitrary link complements, or quantum invariants of compact hyperbolic cone
manifolds. Also, for any $PSL(2,\mc)$-character of a surface of finite
topological type, we obtain new conjugacy classes of linear representations of
the mapping class group. Finally, we discuss some evidences showing that the
QHFTs are pertinent to 3D gravity.


  We present Neural Congealing -- a zero-shot self-supervised framework for
detecting and jointly aligning semantically-common content across a given set
of images. Our approach harnesses the power of pre-trained DINO-ViT features to
learn: (i) a joint semantic atlas -- a 2D grid that captures the mode of
DINO-ViT features in the input set, and (ii) dense mappings from the unified
atlas to each of the input images. We derive a new robust self-supervised
framework that optimizes the atlas representation and mappings per image set,
requiring only a few real-world images as input without any additional input
information (e.g., segmentation masks). Notably, we design our losses and
training paradigm to account only for the shared content under severe
variations in appearance, pose, background clutter or other distracting
objects. We demonstrate results on a plethora of challenging image sets
including sets of mixed domains (e.g., aligning images depicting sculpture and
artwork of cats), sets depicting related yet different object categories (e.g.,
dogs and tigers), or domains for which large-scale training data is scarce
(e.g., coffee mugs). We thoroughly evaluate our method and show that our
test-time optimization approach performs favorably compared to a
state-of-the-art method that requires extensive training on large-scale
datasets.


  Using a first-principles-based approach, we determine the ferroelectric
pattern in PbZr$_{0.5}$Ti$_{0.5}$O$_3$ ultrathin film. It is found that vortex
stripes are formed in the system and they are responsible for the 180$^\circ$
domains observed. When a local external field is exerted, the vortex stripe
transforms into the vortex loop structure, which leads to the formation of a
smaller domain with the polarization antiparallel to the field in the center of
the field region. This may provide a convenient way to manipulate nanodomains
in thin films.


  We define asymptotic transfers in bounded K-theory together with a context
where this can be done in great generality. Controlled algebra plays a central
role in many advances in geometric topology, including recent work on Novikov,
Borel, and Farrell-Jones conjectures. One of the features that appears in
various manifestations throughout the subject, starting with the original work
of Farrell and Jones, is an asymptotic transfer whose meaning and construction
depend on the geometric circumstances. We first develop a general framework
that allows us to construct a version of asymptotic transfer maps for any
finite aspherical complex. This framework is the equivariant parametrized
K-theory with fibred control. We also include several fibrewise excision
theorems for its computation and a discussion of where the standard tools break
down and which tools replace them.


  In this work, we prove the existence and multiplicity of positive solutions
for the following class of quasilinear elliptic equations
  $$ \left \{ \begin{array}{lll} -\epsilon^{N}\Delta_{N} u + \left(1+\mu A(x)
\right)\left| u\right|^{N-2}u= f(u)\,\,\,\, \mbox{ in } \, \RR^{N},\\ u > 0
\,\,\,\, \mbox{ in } \, \RR^{N}, \end{array} \right. $$
  \\ where $\Delta_{N}$ is the N-Laplacian operator, $N \geq 2$, $f$ is a
function with exponential critical growth, $\mu$ and $\epsilon$ are positive
parameters and $A$ is a nonnegative continuous function verifying some
hypotheses. To obtain our results, we combine variational arguments and
Lusternik-Schnirelman category theory .


  We calculate the local cohomology modules of the binomial edge ideals of the
complements of connected graphs of girth at least 5 using the tools introduced
by \`Alvarez Montaner in arXiv:1901.08645. We then use this calculation to
compute the depth, dimension, and regularity of these binomial edge ideals.


  We present the details of our embedding proof of the Atiyah-Patodi-Singer
index theorem for Dirac operators on manifolds with boundary.


  We show that the minimal free resolution of a general semi-stable sheaf $U$
on $\mathbb{P}^2$ contains a subcomplex that determines an extremal ray of the
cone of effective divisors of its moduli space. We provide evidence that this
is part of a general phenomenon in which minimal free resolutions, for distinct
Betti tables, contain subcomplexes depending on wall-crossing. From this
viewpoint, we provide new computations of the movable cones and Mori
decompositions of some moduli spaces of sheaves using syzygies.


  General-purpose computing on graphics processing units (GPGPU) has recently
gained considerable attention in various domains such as bioinformatics,
databases and distributed computing. GPGPU is based on using the GPU as a
co-processor accelerator to offload computationally-intensive tasks from the
CPU. This study starts from the observation that a number of GPU features (such
as overlapping communication and computation, short lived buffer reuse, and
harnessing multi-GPU systems) can be abstracted and reused across different
GPGPU applications. This paper describes CrystalGPU, a modular framework that
transparently enables applications to exploit a number of GPU optimizations.
Our evaluation shows that CrystalGPU enables up to 16x speedup gains on
synthetic benchmarks, while introducing negligible latency overhead.


  Consider the Cauchy problem for the radial cubic wave equation in 1+3
dimensions with either the focusing or defocusing sign. This problem is
critical in $\dot{H}^{\frac{1}{2}} \times \dot{H}^{-\frac{1}{2}}$ and
subcritical with respect to the conserved energy. Here we prove that if the
critical norm of a solution remains bounded on the maximal time-interval of
existence, then the solution must in fact be global-in-time and scatter to free
waves as $t \to \pm \infty$.


  In this paper we study asymptotic behavior of solutions for a free boundary
problem modeling the growth of tumors containing two species of cells:
proliferating cells and quiescent cells. This tumor model was proposed by
Pettet et al in {\em Bull. Math. Biol.} (2001). By using a functional approach
and the $C_0$ semigroup theory, we prove that the unique stationary solution of
this model ensured by the work of Cui and Friedman ({\em Trans. Amer. Math.
Soc.}, 2003) is locally asymptotically stable in certain function spaces. Key
techniques used in the proof include an improvement of the linear estimate
obtained by the work of Chen et al ({\em Trans. Amer. Math. Soc.}, 2005), and a
similarity transformation.


  We introduce a two-dimensional, distribution-valued field which we call the
quadratic field associated to the one-dimensional Ornstein-Uhlenbeck process.
We show that the stationary quadratic fluctuations of the simple exclusion
process, when rescaled in the diffusive scaling, converge to this quadratic
field. We show that this quadratic field evaluated at the diagonal corresponds
to the Wick-renormalized square of the Ornstein-Uhlenbeck process, and we use
this new representation in order to prove some small and large-time properties
of it.


  Deep J, H, and K' images, recorded with the ALTAIR adaptive optics system and
NIRI imager on Gemini North, are used to probe the stellar content of the disk
and bulge of the Local Group galaxy M31. With FWHM near 0.08 arcsec in K, these
are the highest angular resolution near-infrared images yet obtained of this
galaxy. Four fields that sample M31 at galactocentric radii of 62, 9, 4, and 2
arcmin were observed. The RGB-tip occurs between K = 17.0 and 17.2, and the
color of the RGB in the field closest to the center of M31 is consistent with
that of NGC 6528. After accounting for random photometric errors, the upper RGB
in each field has a width on the (K, J-K) CMD that is consistent with a +/- 0.5
dex dispersion in [Fe/H], in rough agreement with what is seen in other disk
and spheroid fields in M31. A population of very bright red stars, which we
identify as C stars, are seen in the three fields that are closest to the
center of M31. The spatial distribution of these objects suggests that they are
well mixed throughout this part of M31, and so likely did not form in a compact
region near the galactic nucleus, but more probably formed in the inner disk.
We speculate that these C stars may be the most luminous members of the
intermediate age population that has been detected previously in studies of the
integrated spectrum of the central regions of M31.


  The antiferromagnetic spin correlation function $S_{\bf Q}$, the staggered
spin susceptibility $\chi_{\bf Q}$ and the energy scale $\omega_{FL}=S_{\bf
Q}/\chi_{\bf Q}$ are studied numerically within the t-J model and the Hubbard
model, as relevant to cuprates. It is shown that $\omega_{FL}$, related to the
onset of the non-Fermi-liquid spin response at $T>\omega_{FL}$, is very low in
the regime below the 'optimum' hole doping $c_h < c_h^* \sim 0.16$, while it
shows a steep increase in the overdoped regime. A quantitative analysis of NMR
spin-spin relaxation-rate $1/T_{2G}$ for various cuprates reveals a similar
behavior, indicating on a sharp, but continuous, crossover between a
Fermi-liquid and a non-Fermi-liquid behavior as a function of doping.


  In this paper, by means of upper approximation operators in rough set theory,
we study representations for sL-domains and its special subclasses. We
introduce the concepts of sL-approximation spaces, L-approximation spaces and
bc-approximation spaces, which are special types of CF-approximation spaces. We
prove that the collection of CF-closed sets in an sL-approximation space
(resp., an L-approximation space, a bc-approximation space) ordered by
set-theoretic inclusion is an sL-domain (resp., an L-domain, a bc-domain);
conversely, every sL-domain (resp., L-domain, bc-domain) is order-isomorphic to
the collection of CF-closed sets of an sL-approximation space (resp., an
L-approximation space, a bc-approximation space). Consequently, we establish an
equivalence between the category of sL-domains (resp., L-domains) with Scott
continuous mappings and that of sL-approximation spaces (resp., L-approximation
spaces) with CF-approximable relations.


  RZ Psc is a young Sun-like star with a bright and warm infrared excess that
is occasionally dimmed significantly by circumstellar dust structures. Optical
depth arguments suggest that the dimming events do not probe a typical sight
line through the circumstellar dust, and are instead caused by structures that
appear above an optically thick mid-plane. This system may therefore be similar
to systems where an outer disk is shadowed by material closer to the star. Here
we report the discovery that RZ Psc hosts a 0.12$M_\odot$ companion at a
projected separation of 23au. We conclude that the disk must orbit the primary
star. While we do not detect orbital motion, comparison of the angle of linear
polarization of the primary with the companion's on-sky position angle provides
circumstantial evidence that the companion and disc may not share the same
orbital plane. Whether the companion severely disrupts the disc, truncates it,
or has little effect at all, will require further observations of both the
companion and disc.


  We present HST WFPC2 observations, supplemented by ground-based H-alpha data,
of the star-cluster populations in two pairs of interacting galaxies, selected
for being in very different kinds of encounters seen at different stages.
Dynamical information and n-body simulations provide the details of encounter
geometry, mass ratio, and timing. In NGC 5752/4, we see a weak encounter well
past closest approach, after about 2.5x10^8 years. The large spiral NGC 5754
has a normal population of disk clusters, while the companion NGC 5752 exhibits
a rich population of luminous clusters with a flatter luminosity function. The
strong, ongoing encounter in NGC 6621/2, seen about 10^8 years past closest
approach between roughly equal-mass galaxies, has produced a rich population of
luminous clusters, particularly young and bright in a small region between the
nuclei. This region is dynamically interesting, so strongly perturbed that the
rotation curve reverses sign. Cluster formation requires a threshold level of
perturbation, with stage of the interaction less important. The location of the
most active star formation in NGC 6621/2 draws attention to a possible role for
the Toomre stability threshold in shaping star formation in interacting
galaxies. The rich cluster populations in NGC 5752 and 6621 show that direct
contact between gas-rich galaxy disks is not a requirement to form luminous
clusters, and that they can be triggered by processes happening within a single
galaxy disk (albeit triggered by external perturbations). (Abridged)


  Traditional science searched for new objects and phenomena that led to
discoveries. Tomorrow's science will combine together the large pool of
information in scientific archives and make discoveries. Scienthists are
currently keen to federate together the existing scientific databases. The
major challenge in building a federation of these autonomous and heterogeneous
databases is system integration. Ineffective integration will result in defunct
federations and under utilized scientific data.
  Astronomy, in particular, has many autonomous archives spread over the
Internet. It is now seeking to federate these, with minimal effort, into a
Virtual Observatory that will solve complex distributed computing tasks such as
answering federated spatial join queries.
  In this paper, we present SkyQuery, a successful prototype of an evolving
federation of astronomy archives. It interoperates using the emerging Web
services standard. We describe the SkyQuery architecture and show how it
efficiently evaluates a probabilistic federated spatial join query.


  Transesophageal echocardiography (TEE) is widely used to detect left atrium
(LA)/left atrial appendage (LAA) thrombi. In this paper, the local binary
pattern variance (LBPV) features are extracted from region of interest (ROI).
And the dynamic features are formed by using the information of its neighbor
frames in the sequence. The sequence is viewed as a bag, and the images in the
sequence are considered as the instances. Multiple-instance learning (MIL)
method is employed to solve the LAA thrombi detection. The experimental results
show that the proposed method can achieve better performance than that by using
other methods.


  Decision making is still an open issue in the application of Dempster-Shafer
evidence theory. A lot of works have been presented for it. In the transferable
belief model (TBM), pignistic probabilities based on the basic probability as-
signments are used for decision making. In this paper, multiscale probability
transformation of basic probability assignment based on the belief function and
the plausibility function is proposed, which is a generalization of the
pignistic probability transformation. In the multiscale probability function, a
factor q based on the Tsallis entropy is used to make the multiscale prob-
abilities diversified. An example is shown that the multiscale probability
transformation is more reasonable in the decision making.


  Ensuring compliance of organizations to federal regulations is a growing
concern. This paper presents a framework and methods to verify whether an
implemented low-level security policy is compliant to a high-level security
policy. Our compliance checking framework is based on organizational and
security metadata to support refinement of high-level concepts to
implementation specific instances. Our work uses the results of refinement
calculus to express valid refinement patterns and their properties.
Intuitively, a low-level security policy is compliant to a high-level security
policy if there is a valid refinement path from the high-level security policy
to the low-level security policy. Our model is capable of detecting violations
of security policies, failures to meet obligations, and capability and modal
conflicts.


  Let f: X -> Y be a based map of simply connected spaces. The corresponding
evaluation map w: map(X,Y;f) -> Y induces a homomorphism of homotopy groups
whose image in pi_n(Y) is called the nth evaluation subgroup of f. The nth
Gottlieb group of X occurs as the special case in which Y = X and f = 1_X. We
identify the homomorphism induced on rational homotopy groups by this
evaluation map, in terms of a map of complexes of derivations constructed using
Sullivan minimal models. Our identification allows for the characterization of
the rationalization of the nth evaluation subgroup of f. It also allows for the
identification of several long exact sequences of rational homotopy groups,
including the long exact sequence induced on rational homotopy groups by the
evaluation fibration. As a consequence, we obtain an identification of the
rationalization of the so-called G-sequence of the map f. This is a
sequence--in general not exact--of groups and homomorphisms that includes the
Gottlieb groups of X and the evaluation subgroups of f. We use these results to
study the G-sequence in the context of rational homotopy theory. We give new
examples of non-exact G-sequences and uncover a relationship between the
homology of the rational G-sequence and negative derivations of rational
cohomology. We also relate the splitting of the rational G-sequence of a fibre
inclusion to a well-known conjecture in rational homotopy theory.


  The evolution of a small satellite inside a more massive truncated isothermal
spherical halo is studied using both the Theory of Linear Response for
dynamical friction and N-Body simulations. The analytical approach includes the
effects of the gravitational wake, of the tidal deformation and the shift of
the barycenter of the primary, so unifying the local versus global
interpretation of dynamical friction. Sizes, masses, orbital energies and
eccentricities are chosen as expected in hierarchical clustering models. We
find that in general the drag force in self-gravitating backgrounds is weaker
than in uniform media and that the orbital decay is not accompanied by a
significant circularization. We also show that the dynamical friction time
scale is weakly dependent on the initial circularity. We provide a fitting
formula for the decay time that includes the effect of mass and angular
momentum loss. Live satellites with dense cores can survive disruption up to an
Hubble time within the primary, notwithstanding the initial choice of orbital
parameters. Dwarf spheroidal satellites of the Milky Way, like Sagittarius A
and Fornax, have already suffered mass stripping and, with their present
masses, the sinking times exceed 10 Gyr even if they are on very eccentric
orbits.


  Aquaculture production -- the cultivation of aquatic plants and animals --
has grown rapidly since the 1990s, but sparse, self-reported and aggregate
production data limits the effective understanding and monitoring of the
industry's trends and potential risks. Building on a manual survey of
aquaculture production from remote sensing imagery, we train a computer vision
model to identify marine aquaculture cages from aerial and satellite imagery,
and generate a spatially explicit dataset of finfish production locations in
the French Mediterranean from 2000-2021 that includes 4,010 cages (69m2 average
cage area). We demonstrate the value of our method as an easily adaptable,
cost-effective approach that can improve the speed and reliability of
aquaculture surveys, and enables downstream analyses relevant to researchers
and regulators. We illustrate its use to compute independent estimates of
production, and develop a flexible framework to quantify uncertainty in these
estimates. Overall, our study presents an efficient, scalable and highly
adaptable method for monitoring aquaculture production from remote sensing
imagery.


  In this paper, we propose PointSeg, a real-time end-to-end semantic
segmentation method for road-objects based on spherical images. We take the
spherical image, which is transformed from the 3D LiDAR point clouds, as input
of the convolutional neural networks (CNNs) to predict the point-wise semantic
map. To make PointSeg applicable on a mobile system, we build the model based
on the light-weight network, SqueezeNet, with several improvements. It
maintains a good balance between memory cost and prediction performance. Our
model is trained on spherical images and label masks projected from the KITTI
3D object detection dataset. Experiments show that PointSeg can achieve
competitive accuracy with 90fps on a single GPU 1080ti. which makes it quite
compatible for autonomous driving applications.


  We consider codes over $\mathbb{Z}_{p^s}$ with the extended Lee weight. We
find Singleton bounds with respect to this weight and define MLDS and MLDR
codes accordingly. We also consider the kernels of these codes and the notion
of independence of vectors in this space. We investigate the linearity and
duality of the Gray images of codes over $\mathbb{Z}_{p^s}$.


  Automotive radar emerges as a crucial sensor for autonomous vehicle
perception. As more cars are equipped radars, radar interference is an
unavoidable challenge. Unlike conventional approaches such as interference
mitigation and interference-avoiding technologies, this paper introduces an
innovative collaborative sensing scheme with multiple automotive radars that
exploits constructive interference. Through collaborative sensing, our method
optimally aligns cross-path interference signals from other radars with another
radar's self-echo signals, thereby significantly augmenting its target
detection capabilities. This approach alleviates the need for extensive raw
data sharing between collaborating radars. Instead, only an optimized weighting
matrix needs to be exchanged between the radars. This approach considerably
decreases the data bandwidth requirements for the wireless channel, making it a
more feasible and practical solution for automotive radar collaboration.
Numerical results demonstrate the effectiveness of the constructive
interference approach for enhanced object detection capability.


  Research in the area of secure multi-party computation using a deck of
playing cards, often called card-based cryptography, started from the
introduction of the five-card trick protocol to compute the logical AND
function by den Boer in 1989. Since then, many card-based protocols to compute
various functions have been developed. In this paper, we propose two new
protocols that securely compute the $n$-variable equality function (determining
whether all inputs are equal) $E: \{0,1\}^n \rightarrow \{0,1\}$ using $2n$
cards. The first protocol can be generalized to compute any doubly symmetric
function $f: \{0,1\}^n \rightarrow \mathbb{Z}$ using $2n$ cards, and any
symmetric function $f: \{0,1\}^n \rightarrow \mathbb{Z}$ using $2n+2$ cards.
The second protocol can be generalized to compute the $k$-candidate
$n$-variable equality function $E: (\mathbb{Z}/k\mathbb{Z})^n \rightarrow
\{0,1\}$ using $2 \lceil \lg k \rceil n$ cards.


  An efficient method to tune the spatial coherence of a degenerate laser over
a broad range with minimum variation in the total output power is presented. It
is based on varying the diameter of a spatial filter inside the laser cavity.
The number of lasing modes supported by the degenerate laser can be controlled
from 1 to 320,000, with less than a 50% change in the total output power. We
show that a degenerate laser designed for low spatial coherence can be used as
an illumination source for speckle-free microscopy that is 9 orders of
magnitude brighter than conventional thermal light.


  Biomarkers which predict patient's survival can play an important role in
medical diagnosis and treatment. How to select the significant biomarkers from
hundreds of protein markers is a key step in survival analysis. In this paper a
novel method is proposed to detect the prognostic biomarkers of survival in
colorectal cancer patients using wavelet analysis, genetic algorithm, and Bayes
classifier. One dimensional discrete wavelet transform (DWT) is normally used
to reduce the dimensionality of biomedical data. In this study one dimensional
continuous wavelet transform (CWT) was proposed to extract the features of
colorectal cancer data. One dimensional CWT has no ability to reduce
dimensionality of data, but captures the missing features of DWT, and is
complementary part of DWT. Genetic algorithm was performed on extracted wavelet
coefficients to select the optimized features, using Bayes classifier to build
its fitness function. The corresponding protein markers were located based on
the position of optimized features. Kaplan-Meier curve and Cox regression model
were used to evaluate the performance of selected biomarkers. Experiments were
conducted on colorectal cancer dataset and several significant biomarkers were
detected. A new protein biomarker CD46 was found to significantly associate
with survival time.


  We study the conditional distribution of goodness of fit statistics of the
Cram\'{e}r--von Mises type given the complete sufficient statistics in testing
for exponential family models. We show that this distribution is close, in
large samples, to that given by parametric bootstrapping, namely, the
unconditional distribution of the statistic under the value of the parameter
given by the maximum likelihood estimate. As part of the proof, we give uniform
Edgeworth expansions of Rao--Blackwell estimates in these models.


  Using a semi-classical approach, we describe an on-chip cooling protocol for
a micro-mechanical resonator by employing a superconducting flux qubit. A
Lorentz force, generated by the passive back-action of the resonator's
displacement, can cool down the thermal motion of the mechanical resonator by
applying an appropriate microwave drive to the qubit. We show that this onchip
cooling protocol, with well-controlled cooling power and a tunable response
time of passive back-action, can be highly efficient. With feasible
experimental parameters, the effective mode temperature of a resonator could be
cooled down by several orders of magnitude.


  We consider communication in a fully cooperative multi-agent system, where
the agents have partial observation of the environment and must act jointly to
maximize the overall reward. We have a discrete-time queueing network where
agents route packets to queues based only on the partial information of the
current queue lengths. The queues have limited buffer capacity, so packet drops
happen when they are sent to a full queue. In this work, we implemented a
communication channel for the agents to share their information in order to
reduce the packet drop rate. For efficient information sharing we use an
attention-based communication model, called ATVC, to select informative
messages from other agents. The agents then infer the state of queues using a
combination of the variational auto-encoder, VAE, and product-of-experts, PoE,
model. Ultimately, the agents learn what they need to communicate and with
whom, instead of communicating all the time with everyone. We also show
empirically that ATVC is able to infer the true state of the queues and leads
to a policy which outperforms existing baselines.


  The dynamics of an electron bunch irradiated by two focused colliding
super-intense laser pulses and the resulting gamma and electron-positron
production are studied. Due to attractors of electron dynamics in a standing
wave created by colliding pulses the photon emission and pair production, in
general, are more efficient with linearly polarized pulses than with circularly
polarized ones. The dependence of the key parameters on the laser intensity and
wavelength allows to identify the conditions for the cascade development and
gamma-electron-positron plasma creation.


  The Fueter-Sce theorem provides a procedure to obtain axially monogenic
functions, which are in the kernel of generalized Cauchy-Riemann operator in $
\mathbb{R}^{n+1}$. This result is obtained by using two operators. The first
one is the slice operator, which extends holomorphic functions of one complex
variable to slice monogenic functions in $ \mathbb{R}^{n+1}$. The second one is
a suitable power of the Laplace operator in $n+1$ variables. Another way to get
axially monogenic functions is the generalized Cauchy-Kovalevskaya (CK)
extension. This characterizes axial monogenic functions by their restriction to
the real line. In this paper, using the connection between the Fueter-Sce map
and the generalized CK-extension, we explicitly compute the actions
$\Delta_{\mathbb{R}^{n+1}}^{\frac{n-1}{2}} x^k$, where $x \in
\mathbb{R}^{n+1}$. The expressions obtained is related to a well-known class of
Clifford-Appell polynomials. These are the building blocks to write a Taylor
series for axially monogenic functions. Moreover, we focus on some elementary
axially monogenic functions, where the action of the Fueter-Sce map and the
generalized CK-extension coincide. In order to get algebraic relations between
the elementary functions, as in complex analysis, we define a new product
between axially monogenic functions. By using the connections between the
Fueter-Sce map and the generalized CK extension we characterize the range and
the kernel of the Fueter-Sce map. Furthermore, we focus on studying the
Clifford-Appell-Fock space and the Clifford-Appell-Hardy space. Finally, using
the polyanalytic Fueter-Sce theorems we obtain a new family of polyanalytic
monogenic polynomials, which extends to higher dimensions the Clifford-Appell
polynomials.


  We consider the problem of finding a net that supports prescribed forces
applied at prescribed points, yet avoids certain obstacles, with all the
elements of the net under compression (strut net) or under tension (cable web).
In the case of masonry structures, for instance, this consists in finding a
strut net that supports the forces, is contained within the physical structure,
and avoids regions that may be not accessible due, for instance, to the
presence of holes. We solve such a problem in the two-dimensional case, where
the prescribed forces are applied at the vertices of a convex polygon, and we
treat the cases of both single and multiple obstacles. By approximating the
obstacles by polygonal regions, the task reduces to identifying the feasible
domain in a linear programming problem. For a single obstacle we show how the
region $\Gamma$ available to the obstacle can be enlarged as much as possible
in the sense that there is no other strut net, having a region $\Gamma_1$
available to the obstacle with $\Gamma_1 \subset\Gamma$. The case where some of
the forces are reactive, unprescribed but reacting to the other prescribed
forces, is also treated. It again reduces to identifying the feasible domain in
a linear programming problem. Finally, one may allow a subset of the reactive
forces to each act not at a prescribed point, but rather at any point on a
prescribed line segment. Then the task reduces to identifying the feasible
domain in a quadratic programming problem.


  The "colossal magnetoresistive" (CMR) manganites are highly correlated
systems with a strong coupling between spin, charge, orbital, and lattice
degrees of freedom, which leads to complex phase diagrams and to the
coexistence of various forms of ordering. For example, nanoscale charge/orbital
ordering (CO) fluctuations appear to cooperate with Jahn-Teller (JT)
distortions of the MnO$_{6} octahedra in CMR manganites and compete with the
electron itinerancy favored by double exchange. However, access to the ordered
dynamical state has been challenging, mostly due to intrinsic experimental
difficulties in measuring fast short-range correlations. Here, we report on a
strongly damped low-energy collective mode originating from fast short-range CO
fluctuations in La}$_{0.67}Ca$_{0.33}Mn{O}$_{3}(LCMO) single crystal and thin
films. We elucidate the collective mode in terms of its dispersion relation and
dependence on average A-site ion radius, r$_{A}, and hole-doping concentration.
Our results show for the first time that dynamical short-range CO correlations
in CMR manganites can be detected with high momentum resolution by coherent
ultrafast optical techniques.


  Let $p$ be an odd prime, $D_{2p}$ be the dihedral group of order 2p, and
$F_{2}$ be the finite field with two elements. If * denotes the canonical
involution of the group algebra $F_2D_{2p}$, then bicyclic units are unitary
units. In this note, we investigate the structure of the group
$\mathcal{B}(F_2D_{2p})$, generated by the bicyclic units of the group algebra
$F_2D_{2p}$. Further, we obtain the structure of the unit group
$\mathcal{U}(F_2D_{2p})$ and the unitary subgroup $\mathcal{U}_*(F_2D_{2p})$,
and we prove that both $\mathcal{B}(F_2D_{2p})$ and $\mathcal{U}_*(F_2D_{2p})$
are normal subgroups of $\mathcal{U}(F_2D_{2p})$.


  We propose a mechanism for tumor growth emphasizing the role of homeostatic
regulation and tissue stability. We show that competition between surface and
bulk effects leads to the existence of a critical size that must be overcome by
metastases to reach macroscopic sizes. This property can qualitatively explain
the observed size distributions of metastases, while size-independent growth
rates cannot account for clinical and experimental data. In addition, it
potentially explains the observed preferential growth of metastases on tissue
surfaces and membranes such as the pleural and peritoneal layers, suggests a
mechanism underlying the seed and soil hypothesis introduced by Stephen Paget
in 1889 and yields realistic values for metastatic inefficiency. We propose a
number of key experiments to test these concepts. The homeostatic pressure as
introduced in this work could constitute a quantitative, experimentally
accessible measure for the metastatic potential of early malignant growths.


  Deep Learning (DL) is one of the most common subjects when Machine Learning
and Data Science approaches are considered. There are clearly two movements
related to DL: the first aggregates researchers in quest to outperform other
algorithms from literature, trying to win contests by considering often small
decreases in the empirical risk; and the second investigates overfitting
evidences, questioning the learning capabilities of DL classifiers. Motivated
by such opposed points of view, this paper employs the Statistical Learning
Theory (SLT) to study the convergence of Deep Neural Networks, with particular
interest in Convolutional Neural Networks. In order to draw theoretical
conclusions, we propose an approach to estimate the Shattering coefficient of
those classification algorithms, providing a lower bound for the complexity of
their space of admissible functions, a.k.a. algorithm bias. Based on such
estimator, we generalize the complexity of network biases, and, next, we study
AlexNet and VGG16 architectures in the point of view of their Shattering
coefficients, and number of training examples required to provide theoretical
learning guarantees. From our theoretical formulation, we show the conditions
which Deep Neural Networks learn as well as point out another issue: DL
benchmarks may be strictly driven by empirical risks, disregarding the
complexity of algorithms biases.


  We studied the one-loop prediction for the single production of a Higgs-like
boson in association with a photon in electron-positron collisions in the
context of two Higgs doublet type-II seesaw model (2HDMcT). We explored to what
extent the new scalars in the (2HDMcT) spectrum affect its production
cross-section, the ratio $R_{\gamma h_1}$ as well as the signal strengths
$R_{\gamma Z}$ and $R_{\gamma \gamma}$ when $h_1$ is identified with the
observed $SM $ Higgs boson within the $2HDMcT$ delimited parameter space. More
specifically, we focused on $e^+e^- \to h_1\gamma$ process at one-loop, and
analyzed how it evolves under a full set of theoretical constraints and the
available experimental data, including $B\to X_s\gamma$ constraint at 95$\%$
C.L. Our analysis showed that these observables are particularly sensitive to
the parameters $\alpha_1$, $\lambda_{7}$, $\lambda_{9}$, the trilinear Higgs
couplings and to the charged Higgs masses. We found that $\sigma (e^+e^- \to
h_1\gamma)$ can significantly be enhanced up to $8.1\,\, 10^{-2}$ fb, so
exceeding the Standard Model prediction. Additionally, as a byproduct, we also
found that $R_{\gamma h_1}$ is entirely correlated with both the
$h_1\to\gamma\gamma$ and $h_1\to\gamma Z$ signal strengths.


  We prove that if $A$ is a Borel set in the plane of equal Hausdorff and
packing dimension $s>1$, then the set of pinned distances $\{ |x-y|:y\in A\}$
has full Hausdorff dimension for all $x$ outside of a set of Hausdorff
dimension $1$ (in particular, for many $x\in A$). This verifies a strong
variant of Falconer's distance set conjecture for sets of equal Hausdorff and
packing dimension, outside the endpoint $s=1$.


  We introduce a noncommutative differential calculus on the two-parameter
$h$-superplane via a contraction of the (p,q)-superplane. We manifestly show
that the differential calculus is covariant under $GL_{h_1,h_2}(1| 1)$
transformations. We also give a two-parameter deformation of the
(1+1)-dimensional phase space algebra.


  The Kaneko--Zagier conjecture describes a correspondence between finite
multiple zeta values and symmetric multiple zeta values. Its refined version
has been established by Jarossay, Rosen and Ono--Seki--Yamamoto. In this paper,
we explicate these conjectures through studies of multiple harmonic $q$-sums.
We show that the (generalized) finite/symmetric multiple zeta value are
obtained by taking an algebraic/analytic limit of multiple harmonic $q$-sums.
As applications, new proofs of reversal, duality and cyclic sum formulas for
the generalized finite/symmetric multiple zeta values are given.


  Gauging $B-L$ symmetry provides a simple realization of the seesaw mechanism
in a naturally anomaly free extension to the MSSM gauge group, $SU(3)_c\times
SU(2)_L\times U(1)_Y \times U(1)_{B-L}$. However, as we discuss in here, it
turns out that the simplest $B-L$ extension of the MSSM may change some of the
conceptions about the path for gauge unification as well as to affect the
predicted spectrum of the supersymmetric particles at low energy. For instance,
the coupling $g_{B-L}$ ended up to be smallest of all of them and the lightest
gaugino is the one related to $B-L$. RGE also help to understand the
spontaneous breaking of the $U(1)_{B-L}$ and the vacuum expectation value of
the sneutrino at low energies, which occurs in this type of models.


  We show that the quantum invariants arising from typical representations of
the quantum group $U_h\mathfrak{sl}(2|1)$ are q-holonomic. In particular, this
implies the existence of an underlying field theory for which this family of
invariants are partition functions.


  We approach the issue of exponentiation of soft gauge boson corrections to
scattering amplitudes from a path integral point of view. We show that if one
represents the amplitude as a first quantized path integral in a mixed
coordinate-momentum space representation, a charged particle interacting with a
soft gauge field is represented as a Wilson line for a semi-infinite line
segment, together with calculable fluctuations. Combining such line segments,
we show that exponentiation in an abelian field theory follows immediately from
standard path-integral combinatorics. In the non-abelian case, we consider
color singlet hard interactions with two outgoing external lines, and obtain a
new viewpoint for exponentiation in terms of ``webs'', with a closed form
solution for their corresponding color factors. We investigate and clarify the
structure of next-to-eikonal corrections.


  We introduce twisted unitary $t$-groups, a generalization of unitary
$t$-groups under a twisting by an irreducible representation. We then apply
representation theoretic methods to the Knill-Laflamme error correction
conditions to show that twisted unitary $t$-groups automatically correspond to
quantum codes with distance $d=t+1$. By construction these codes have many
transversal gates, which are naturally fault tolerant.


  Image quality assessment (IQA) algorithms aim to reproduce the human's
perception of the image quality. The growing popularity of image enhancement,
generation, and recovery models instigated the development of many methods to
assess their performance. However, most IQA solutions are designed to predict
image quality in the general domain, with the applicability to specific areas,
such as medical imaging, remaining questionable. Moreover, the selection of
these IQA metrics for a specific task typically involves intentionally induced
distortions, such as manually added noise or artificial blurring; yet, the
chosen metrics are then used to judge the output of real-life computer vision
models. In this work, we aspire to fill these gaps by carrying out the most
extensive IQA evaluation study for Magnetic Resonance Imaging (MRI) to date
(14,700 subjective scores). We use outputs of neural network models trained to
solve problems relevant to MRI, including image reconstruction in the scan
acceleration, motion correction, and denoising. Our emphasis is on reflecting
the radiologist's perception of the reconstructed images, gauging the most
diagnostically influential criteria for the quality of MRI scans:
signal-to-noise ratio, contrast-to-noise ratio, and the presence of artifacts.
Seven trained radiologists assess these distorted images, with their verdicts
then correlated with 35 different image quality metrics (full-reference,
no-reference, and distribution-based metrics considered). The top performers --
DISTS, HaarPSI, VSI, and FID-VGG16 -- are found to be efficient across three
proposed quality criteria, for all considered anatomies and the target tasks.


  Quantum computing holds promise for outperforming classical computing in
specialized applications such as optimization. With current Noisy Intermediate
Scale Quantum (NISQ) devices, only variational quantum algorithms like the
Quantum Alternating Operator Ansatz (QAOA) can be practically run. QAOA is
effective for solving Quadratic Unconstrained Binary Optimization (QUBO)
problems by approximating Quantum Annealing via Trotterization. Successful
implementation on NISQ devices requires shallow circuits, influenced by the
number of variables and the sparsity of the augmented interaction matrix. This
paper investigates the necessary sparsity levels for augmented interaction
matrices to ensure solvability with QAOA. By analyzing the Max-Cut problem with
varying sparsity, we provide insights into how the Hamiltonian density affects
the QAOA performance. Our findings highlight that, while denser matrices
complicate the energy landscape, the performance of QAOA remains largely
unaffected by sparsity variations. This study emphasizes the algorithm's
robustness and potential for optimization tasks on near-term quantum devices,
suggesting avenues for future research in enhancing QAOA for practical
applications.


  We prove dispersive estimates for the linear Schr\"odinger evolution
associated to an operator -\Delta + V, where the potential is a signed measure
of fractal dimension at least 3/2.


  In this paper, we present the design of a sample sort algorithm for manycore
GPUs. Despite being one of the most efficient comparison-based sorting
algorithms for distributed memory architectures its performance on GPUs was
previously unknown. For uniformly distributed keys our sample sort is at least
25% and on average 68% faster than the best comparison-based sorting algorithm,
GPU Thrust merge sort, and on average more than 2 times faster than GPU
quicksort. Moreover, for 64-bit integer keys it is at least 63% and on average
2 times faster than the highly optimized GPU Thrust radix sort that directly
manipulates the binary representation of keys. Our implementation is robust to
different distributions and entropy levels of keys and scales almost linearly
with the input size. These results indicate that multi-way techniques in
general and sample sort in particular achieve substantially better performance
than two-way merge sort and quicksort.


  This paper proposes a novel automatic speech recognition (ASR) framework
called Integrated Source-Channel and Attention (ISCA) that combines the
advantages of traditional systems based on the noisy source-channel model (SC)
and end-to-end style systems using attention-based sequence-to-sequence models.
The traditional SC system framework includes hidden Markov models and
connectionist temporal classification (CTC) based acoustic models, language
models (LMs), and a decoding procedure based on a lexicon, whereas the
end-to-end style attention-based system jointly models the whole process with a
single model. By rescoring the hypotheses produced by traditional systems using
end-to-end style systems based on an extended noisy source-channel model, ISCA
allows structured knowledge to be easily incorporated via the SC-based model
while exploiting the complementarity of the attention-based model. Experiments
on the AMI meeting corpus show that ISCA is able to give a relative word error
rate reduction up to 21% over an individual system, and by 13% over an
alternative method which also involves combining CTC and attention-based
models.


  Wikidata has been increasingly adopted by many communities for a wide variety
of applications, which demand high-quality knowledge to deliver successful
results. In this paper, we develop a framework to detect and analyze
low-quality statements in Wikidata by shedding light on the current practices
exercised by the community. We explore three indicators of data quality in
Wikidata, based on: 1) community consensus on the currently recorded knowledge,
assuming that statements that have been removed and not added back are
implicitly agreed to be of low quality; 2) statements that have been
deprecated; and 3) constraint violations in the data. We combine these
indicators to detect low-quality statements, revealing challenges with
duplicate entities, missing triples, violated type rules, and taxonomic
distinctions. Our findings complement ongoing efforts by the Wikidata community
to improve data quality, aiming to make it easier for users and editors to find
and correct mistakes.


  We study the family of irreducible curves with $\delta$ nodes belonging to a
free linear system $|C|$ with smooth general member on a surface $S$ such that
$|K_S|$ is ample. Under the assumption that $C$ is numerically equivalent to
$pK_S$, $p\ge 3$ rational, we give an upper bound on $\delta$ ensuring that the
family is smooth of codimension $\delta$ in $|C|$ (plus another slightly
different result of the same type). We give examples showing that the bound is
sharp. Some related results concerning linear normality of nodal curves are
proved.


  We use the POWHEG formalism in the Herwig++ event generator to match QCD
real-emission matrix elements with the parton shower for a range of decays
relevant to Beyond the Standard Model physics searches. Applying this
correction affects the shapes of experimental observables and so changes the
number of events passing selection criteria. To validate this approach, we
study the impact of the correction on Standard Model top quark decays. We then
illustrate the effect of the correction on Beyond the Standard Model scenarios
by considering the invariant-mass distribution of dijets produced in the decay
of the lightest Randall-Sundrum graviton and transverse momentum distributions
for decays in Supersymmetry. We consider only the effect of the POWHEG
correction on the simulation of the hardest emission in the shower and ignore
the normalisation factor required to correct the total widths and branching
ratios to next-to-leading order accuracy.


  Given a bounded $\mathcaligr{C}^2$ domain $G\subset{\mathbb{R}}^m$, functions
$g\in\mathcaligr{C}(\partial G,{\mathbb{R}})$ and $h\in\mathcaligr
{C}(\bar{G},{\mathbb{R}}\setminus\{0\})$, let $u$ denote the unique viscosity
solution to the equation $-2\Delta_{\infty}u=h$ in $G$ with boundary data $g$.
We provide a representation for $u$ as the value of a two-player zero-sum
stochastic differential game.


  X-ray observation of a famous Lyman-limit quasar PKS2145+067at z_em= 0.990
was carried with ASCA. The source showed a 2-10 keV flux of 1.3 E-11 erg cm^-2
sec^-1 (L_X = 2.5 E46 erg sec^-1 for H_0=50 km s^-1 Mpc^-1) described by a
power-law spectrum with a photon index Gamma=1.63 +/- 0.04 . In the ASCA energy
band, no excess absorption was detected implying the absorption column density
at z_ ab=0.791 was less than 1.6 E21 cm^-2 if absorbing medium had a metal
abundance of 0.5 solar. Comparison with previous Einstein and ROSAT
observations shows that PKS2145+067 has increased its luminosity by a factor of
2--3 between 1991 and 1998.


  We find a succinct expression for computing the sequence $x_t = a_t x_{t-1} +
b_t$ in parallel with two prefix sums, given $t = (1, 2, \dots, n)$, $a_t \in
\mathbb{R}^n$, $b_t \in \mathbb{R}^n$, and initial value $x_0 \in \mathbb{R}$.
On $n$ parallel processors, the computation of $n$ elements incurs
$\mathcal{O}(\log n)$ time and $\mathcal{O}(n)$ space. Sequences of this form
are ubiquitous in science and engineering, making efficient parallelization
useful for a vast number of applications. We implement our expression in
software, test it on parallel hardware, and verify that it executes faster than
sequential computation by a factor of $\frac{n}{\log n}$.


  We address the impact of treating the decuplet of spin-3/2 baryons as an
explicit degree of freedom in the chiral expansion of the magnetic moments of
the octet of spin-1/2 baryons. We carry out a complete calculation of the octet
moments to O(1/\lamchic), including decuplet contributions to the chiral loops.
In contrast to results of previous analyses, we find that inclusion of the
decuplet preserves the convergence behavior of the chiral expansion implied by
power counting arguments.


  In these decades, it has been revealed that there is rich
information-theoretic structure in thermodynamics of out-of-equilibrium systems
in both the classical and quantum regimes. This has led to the fruitful
interplay among statistical physics, quantum information theory, and
mathematical theories including matrix analysis and asymptotic probability
theory. The main purpose of this book is to clarify how information theory
works behind thermodynamics and to shed modern light on it. We focus on both of
purely information-theoretic concepts and their physical implications: We
present self-contained and rigorous proofs of several fundamental properties of
entropies, divergences, and majorization. We also discuss the modern
formulations of thermodynamics, especially from the perspectives of stochastic
thermodynamics and resource theory of thermodynamics. Resource theory is a
recently-developed field as a branch of quantum information theory in order to
quantify (energetically or information-theoretically) "useful resources." We
show that resource theory has an intrinsic connection to various fundamental
ideas of mathematics and information theory. This book is not intended to be a
comprehensive review of the field, but would serve as a concise introduction to
several important ingredients of the information-theoretic formulation of
thermodynamics.


  The investigation and classification of non-unique factorization phenomena
has attracted some interest in recent literature. For finitely generated
monoids, S.T. Chapman and P.A. Garc\'ia-S\'anchez, together with several
co-authors, derived a method to calculate the catenary and tame degree from the
monoid of relations. Then, in [1], the algebraic structure of this approach was
investigated and the restriction to finitely generated monoids was removed. We
now extend these ideas further to the monotone catenary degree and then apply
all these results to the explicit computation of arithmetical invariants of
semigroup rings.
  [1] A. Philipp. A characterization of arithmetical invariants by the monoid
of relations. Semigroup Forum, 81:424-434, 2010.


  The problem of low-rank matrix reconstruction arises in various applications
in communications and signal processing. The state of the art research largely
focuses on the recovery techniques that utilize affine maps satisfying the
restricted isometry property (RIP). However, the affine map design and
reconstruction under a priori information, i.e., column or row subspace
information, has not been thoroughly investigated. To this end, we present
designs of affine maps and reconstruction algorithms that fully exploit the
low-rank matrix subspace information. Compared to the randomly generated affine
map, the proposed affine map design permits an enhanced reconstruction. In
addition, we derive an optimal representation of low-rank matrices, which is
exploited to optimize the rank and subspace of the estimate by adapting them to
the noise level in order to achieve the minimum mean square error (MSE).
Moreover, in the case when the subspace information is not a priori available,
we propose a two-step algorithm, where, in the first step, it estimates the
column subspace of a low-rank matrix, and in the second step, it exploits the
estimated information to complete the reconstruction. The simulation results
show that the proposed algorithm achieves robust performance with much lower
complexity than existing reconstruction algorithms.


  A reformulation of the Schwarzschild solution of the linearised Einstein
field equations in post-Riemannian Finsler spacetime is derived. The solution
is constructed in three stages: the exterior solution, the event-horizon
solution and the interior solution. It is shown that the exterior solution is
asymptotically similar to Newtonian gravity at large distances implying that
Newtonian gravity is a low energy approximation of the solution. Application of
Eddington-Finklestein coordinates is shown to reproduce the results obtained
from standard general relativity at the event horizon. Further application of
Kruskal-Szekeres coordinates reveals that the interior solution contains
maximally extensible geodesics.


  Gamma-Ray Burst (GRB) explosions from the first generation of stars offer an
exciting opportunity to probe the epoch of reionization. Clues about how and
when the intergalactic medium was ionized can be read off their UV emission
spectrum. Roughly a percent of all GRBs should be strongly gravitationally
lensed by intervening stars. A microlensed lightcurve can be inverted to
reconstruct the surface brightness profile of the GRB image on the sky, with
micro-arcsecond resolution.


  Globular star clusters are compact and massive stellar systems old enough to
have witnessed the entire history of our Galaxy, the Milky Way. Although recent
results suggest that their formation may have been more complex than previously
thought, they still are the best approximation to a stellar population formed
over a relatively short time scale (less than 1 Gyr) and with virtually no
dispersion in the iron content. Indeed, only one cluster-like system (omega
Centauri) in the Galactic halo is known to have multiple stellar populations
with a significant spread in iron abundance and age4,5. Similar findings in the
Galactic bulge have been hampered by the obscuration arising from thick and
varying layers of interstellar dust. Here we report that Terzan 5, a
globular-cluster-like system in the Galactic bulge, has two stellar populations
with different iron content and ages. Terzan 5 could be the surviving remnant
of one of the primordial building blocks that are thought to merge and form
galaxy bulges.


  We develop a methodology to test the accuracy of lattice extrapolations of
the form factors in B decays only using experimental data. We test this
methodology by comparing the BGL parameterization proposed by Boyd, Grinstein,
and Lebed (1996) and the BCL parameterization proposed by Bourrely Caprini and
Lellouch (2008) in the context of $B \rightarrow \pi \ell \nu$. Our results
suggest that the BCL parameterization is a slightly better predictor of the low
$q^2$ region than the BGL parameterization and that this methodology can be
extended to other decays such as $B\rightarrow D\ell \nu$.


  We present a benchmark of 29687 problems derived from the On-Line
Encyclopedia of Integer Sequences (OEIS). Each problem expresses the
equivalence of two syntactically different programs generating the same OEIS
sequence. Such programs were conjectured by a learning-guided synthesis system
using a language with looping operators. The operators implement recursion, and
thus many of the proofs require induction on natural numbers. The benchmark
contains problems of varying difficulty from a wide area of mathematical
domains. We believe that these characteristics will make it an effective judge
for the progress of inductive theorem provers in this domain for years to come.


  We study the acceleration of the star HE0437-5439, to hypervelocity and
discuss its possible origin in the Large Magellanic Cloud (LMC). The star has a
radial velocity of 723 km/s and is located at a distance of 61 kpc from the
Sun. With a mass of about 8 Msun, the travel time from the Galactic centre is
of about 100 Myr, much longer than its main sequence lifetime. Given the
relatively small distance to the LMC (18 kpc), we consider it likely that
HE0437-5439 originated in the cloud rather than in the Galactic centre, like
the other hypervelocity stars. The minimum ejection velocity required to travel
from the LMC to its current location within its lifetime is of about 500 km/s.
Such a high velocity can only be obtained in a dynamical encounter with a
massive black hole. We perform 3-body scattering simulations in which a stellar
binary encounters a massive black hole and find that a black hole more massive
than 1000 Msun is necessary to explain the high velocity of HE0437-5439. We
look for possible parent clusters for HE0437-5439 and find that NGC 2100 and
NGC 2004 are young enough to host stars coeval to HE0437-5439 and dense enough
to produce an intermediate mass black hole able to eject an 8 Msun star with
hypervelocity.


  Creativity is a complex, multi-faceted concept encompassing a variety of
related aspects, abilities, properties and behaviours. If we wish to study
creativity scientifically, then a tractable and well-articulated model of
creativity is required. Such a model would be of great value to researchers
investigating the nature of creativity and in particular, those concerned with
the evaluation of creative practice. This paper describes a unique approach to
developing a suitable model of how creative behaviour emerges that is based on
the words people use to describe the concept. Using techniques from the field
of statistical natural language processing, we identify a collection of
fourteen key components of creativity through an analysis of a corpus of
academic papers on the topic. Words are identified which appear significantly
often in connection with discussions of the concept. Using a measure of lexical
similarity to help cluster these words, a number of distinct themes emerge,
which collectively contribute to a comprehensive and multi-perspective model of
creativity. The components provide an ontology of creativity: a set of building
blocks which can be used to model creative practice in a variety of domains.
The components have been employed in two case studies to evaluate the
creativity of computational systems and have proven useful in articulating
achievements of this work and directions for further research.


  Effect of energetic disorder on charge carrier transport in organic materials
has been reexamined. A reliable method for mobility calculation and subsequent
evaluation of relevant disorder parameters has been discussed. This method is
well suited for a direct calculation of the magnitude of dipolar disorder
$\sigma_\textrm{dip}$ in polar organic materials from the current transients.
Calculation of $\sigma_\textrm{dip}$ for several transport materials with
varying concentration of polar dopants gives concentration dependences that are
in reasonable agreement with theoretical predictions. A possible solution of
the puzzle concerning the disorder effect on the mobility temperature
dependence has been suggested.


  We consider the charged scalar boson phenomenology in the simplest effective
low-energy R-parity breaking model characterized by a bilinear violation of
R-parity in the superpotential. This induces a mixing between staus and the
charged Higgs boson. We show that the charged Higgs boson mass can be lower
than expected in the MSSM, even before including radiative corrections. We also
study the charged scalar boson decay branching ratios and show that the
R-parity violating decay rates can be comparable or even bigger than the
R-parity conserving ones. Moreover, if the stau is the LSP it will have only
decays into standard model fermions. These features could have important
implications for charged supersymmetric scalar boson searches at future
accelerators.


  Non-Hermitian singularities are ubiquitous in non-conservative open systems.
These singularities are often points of measure zero in the eigenspectrum of
the system which make them difficult to access without careful engineering.
Despite that, they can remotely induce observable effects when some of the
system's parameters are varied along closed trajectories in the parameter
space. To date, a general formalism for describing this process beyond simple
cases is still lacking. Here, we bridge this gap and develop a general approach
for treating this problem by utilizing the power of permutation operators and
representation theory. This in turn allows us to reveal the following
surprising result which contradicts the common belief in the field: loops that
enclose the same singularities starting from the same initial point and
traveling in the same direction, do not necessarily share the same end outcome.
Interestingly, we find that this equivalence can be formally established only
by invoking the topological notion of homotopy. Our findings are general with
far reaching implications in various fields ranging from photonics and atomic
physics to microwaves and acoustics.


  Current data from neutrino oscillation experiments are in good agreement with
$\delta =-\frac{\pi}{2}$ and $\theta_{23}^{} = \frac{\pi}{4}$. We define the
notion of "constrained maximal CP violation" (CMCPV) for predicting these
features and study their origin in flavor symmetry. We derive the
parametrization-independent solution of CMCPV and give a set of equivalent
definitions for it. We further present a theorem on how the CMCPV can be
realized. This theorem takes advantage of residual symmetries in the neutrino
and charged lepton mass matrices, and states that, up to a few minor
exceptions, $(|\delta |, \theta_{23}) =(\frac{\pi}{2}, \frac{\pi}{4})$ is
generated when those symmetries are real. The often considered $\mu$-$\tau$
reflection symmetry, as well as specific discrete subgroups of O(3), are
special cases of our theorem.


  Electromagnetic cloaks are devices that can be used to reduce the total
scattering cross section of various objects. An ideal cloak removes all
scattering from an object and thus makes this object "invisible" to the
electromagnetic fields that impinge on the object. However, ideal cloaking
appears to be possible only at a single frequency. To study cloaking from an
electromagnetic pulse we consider propagation of a pulse inside a waveguide
with a cloaked metal object inside. There are several ways to achieve cloaking
and in this paper we study three such methods, namely, the
coordinate-transformation cloak, the transmission-line cloak, and the
metal-plate cloak. In the case of the two last cloaks, pulse propagation is
studied using experimental data whereas the coordinate-transformation cloak is
studied with numerical simulations. The results show that, at least in the
studied cases where the cloaked object's diameter is smaller than the
wavelength, the cloaks based on transmission-line meshes and metal plates have
wider bandwidth than the coordinate-transformation cloak.


  Various neural-based methods have been proposed so far for joint mention
detection and coreference resolution. However, existing works on coreference
resolution are mainly dependent on filtered mention representation, while other
spans are largely neglected. In this paper, we aim at increasing the
utilization rate of data and investigating whether those eliminated spans are
totally useless, or to what extent they can improve the performance of
coreference resolution. To achieve this, we propose a mention representation
refining strategy where spans highly related to mentions are well leveraged
using a pointer network for representation enhancing. Notably, we utilize an
additional loss term in this work to encourage the diversity between entity
clusters. Experimental results on the document-level CoNLL-2012 Shared Task
English dataset show that eliminated spans are indeed much effective and our
approach can achieve competitive results when compared with previous
state-of-the-art in coreference resolution.


  In this paper we report a study of the seismic noise measured in the
underground Baksan Neutrino Observatory. The main spectral feature below 1 $Hz$
is the oceanic microseism, while for greater frequencies the measured
horizontal and vertical accelerations approaches the Peterson low noise model.
Using two synchronized seismometers we also studied the coherence in the
microseismic band ($0.1-0.5Hz$) between three underground stations located at
$0.3km$, $1.4km$ and $3.7km$ from the tunnel entrance. Finally, on the base of
our measurements we evaluate the Newtonian noise limit at this site using the
Saulson's model.


  We present experimental results and macrospin simulations of the switching
characteristics of orthogonal spin-transfer devices incorporating an
out-of-plane magnetized polarizing layer and an in-plane magnetized spin valve
device at cryogenic temperatures. At $T=4$ K we demonstrate: high speed
deterministic switching at short pulse lengths - down to 100 ps - with
sufficient measurement statistics to establish a switching error rate of
$10^{-5}$; coherent precessional switching at longer times; and ensemble
decoherence effects at even longer times. Finite temperature macrospin models
capture the precessional switching well but fail to fully reproduce all the
decoherence and switching error behavior.


  This article presents the state-of-the-art in optimal solution methods for
decentralized partially observable Markov decision processes (Dec-POMDPs),
which are general models for collaborative multiagent planning under
uncertainty. Building off the generalized multiagent A* (GMAA*) algorithm,
which reduces the problem to a tree of one-shot collaborative Bayesian games
(CBGs), we describe several advances that greatly expand the range of
Dec-POMDPs that can be solved optimally. First, we introduce lossless
incremental clustering of the CBGs solved by GMAA*, which achieves exponential
speedups without sacrificing optimality. Second, we introduce incremental
expansion of nodes in the GMAA* search tree, which avoids the need to expand
all children, the number of which is in the worst case doubly exponential in
the nodes depth. This is particularly beneficial when little clustering is
possible. In addition, we introduce new hybrid heuristic representations that
are more compact and thereby enable the solution of larger Dec-POMDPs. We
provide theoretical guarantees that, when a suitable heuristic is used, both
incremental clustering and incremental expansion yield algorithms that are both
complete and search equivalent. Finally, we present extensive empirical results
demonstrating that GMAA*-ICE, an algorithm that synthesizes these advances, can
optimally solve Dec-POMDPs of unprecedented size.


  The geographic South Pole provides unique opportunities to study cosmic
particles in the Southern Hemisphere. It represents an optimal location to
deploy large-scale neutrino telescopes in the deep Antarctic ice, such as
AMANDA or IceCube. In both cases, the presence of an array, constructed to
observe extensive air showers, enables hybrid measurements of cosmic rays.
While additional neutron monitors can provide information on solar cosmic rays,
large detector arrays, like SPASE or IceTop, allow for precise measurements of
cosmic rays with energies above several $100\,\rm{TeV}$. In coincidence with
the signals recorded in the deep ice, which are mostly due to the high-energy
muons produced in air showers, this hybrid detector setup provides important
information about the nature of cosmic rays.
  In this review, we will discuss the historical motivation and developments
towards measurements of cosmic rays at the geographic South Pole and highlight
recent results reported by the IceCube Collaboration. We will emphasize the
important contributions by Thomas K. Gaisser and his colleagues that ultimately
led to the rich Antarctic research program which today provides crucial
insights into cosmic-ray physics.


  A fundamental problem for overlay networks is to safely exclude leaving
nodes, i.e., the nodes requesting to leave the overlay network are excluded
from it without affecting its connectivity. To rigorously study self-tabilizing
solutions to this problem, the Finite Departure Problem (FDP) has been proposed
[12]. In the FDP we are given a network of processes in an arbitrary state, and
the goal is to eventually arrive at (and stay in) a state in which all leaving
processes irrevocably decided to leave the system while for all
weakly-connected components in the initial overlay network, all staying
processes in that component will still form a weakly connected component. In
the standard interconnection model, the FDP is known to be unsolvable by local
control protocols, so oracles have been investigated that allow the problem to
be solved [12]. To avoid the use of oracles, we introduce a new interconnection
model based on relays. Despite the relay model appearing to be rather
restrictive, we show that it is universal, i.e., it is possible to transform
any weakly-connected topology into any other weakly-connected topology, which
is important for being a useful interconnection model for overlay networks.
Apart from this, our model allows processes to grant and revoke access rights,
which is why we believe it to be of interest beyond the scope of this paper. We
show how to implement the relay layer in a self-stabilizing way and identify
properties protocols need to satisfy so that the relay layer can recover while
serving protocol requests.


  We develop the theory of group graded division ring parallel to the one by P.
Cohn for (ungraded) division rings.


  We propose a geometric approach for bounding average stopping times for
stopped random walks in discrete and continuous time. We consider stopping
times in the hyperspace of time indexes and stochastic processes. Our
techniques relies on exploring geometric properties of continuity or stopping
regions. Especially, we make use of the concepts of convex sets and supporting
hyperplane. Explicit formulae and efficiently computable bounds are obtained
for average stopping times. Our techniques can be applied to bound average
stopping times involving random vectors, nonlinear stopping boundary, and
constraints of time indexes. Moreover, we establish a stochastic characteristic
of convex sets and generalize Jensen's inequality, Wald's equations and
Lorden's inequality, which are useful for investigating average stopping times.


  Language models (LMs) commonly report perplexity on monolithic data held out
from training. Implicitly or explicitly, this data is composed of
domains$\unicode{x2013}$varying distributions of language. Rather than assuming
perplexity on one distribution extrapolates to others, Perplexity Analysis for
Language Model Assessment (Paloma), measures LM fit to 585 text domains,
ranging from nytimes.com to r/depression on Reddit. We invite submissions to
our benchmark and organize results by comparability based on compliance with
guidelines such as removal of benchmark contamination from pretraining.
Submissions can also record parameter and training token count to make
comparisons of Pareto efficiency for performance as a function of these
measures of cost. We populate our benchmark with results from 6 baselines
pretrained on popular corpora. In case studies, we demonstrate analyses that
are possible with Paloma, such as finding that pretraining without data beyond
Common Crawl leads to inconsistent fit to many domains.


  Researchers have long observed that the "small-world" property, which
combines the concepts of high transitivity or clustering with a low average
path length, is ubiquitous for networks obtained from a variety of disciplines
including social sciences, biology, neuroscience, and ecology. However, we find
three shortcomings of the currently popular definition and detection methods
rendering the concept less powerful. First, the classical definition combines
high transitivity with a low average path length in a rather ad-hoc fashion
which confounds the two separate aspects. We find that in several cases,
networks get flagged as "small world" by the current methodology solely because
of their high transitivity. Second, the detection methods lack a formal
statistical inference, and third, the comparison is typically performed against
simplistic random graph models as the baseline which ignores well-known network
characteristics. We propose three innovations to address these issues. First,
we decouple the properties of high transitivity and low average path length as
separate events to test for. Second, we define the property as a statistical
test between a suitable null model and a superimposed alternative model. Third,
the test is performed using parametric bootstrap with several null models to
allow a wide range of background structures in the network. In addition to the
bootstrap tests, we also propose an asymptotic test under the
Erd\"{o}s-Ren\'{y}i null model for which we provide theoretical guarantees on
the asymptotic level and power. Applying the proposed methods on a large number
of network datasets, we uncover new insights about their small-world property.


  Gauss' classical reduction theory for indefinite binary quadratic forms over
$\mathbb{Z}$ has originally been proven by means of purely algebraic and
arithmetic considerations. It was later discovered that this reduction theory
is closely related to a certain symbolic dynamics for the geodesic flow on the
modular surface, and hence can also be deduced geometrically. In this article,
we use certain symbolic dynamics for the geodesic flow on Hecke triangle
surfaces (also the non-arithmetic ones) to develop reduction theories for the
indefinite binary quadratic forms associated to Hecke triangle groups.
Moreover, we propose an algorithm to decide for any $g\in {\rm
PSL}_2(\mathbb{R})$ whether or not $g$ is contained in the Hecke triangle group
under consideration, and provide an upper estimate for its run time.


  In this work we study $d$-dimensional majorant properties. We prove that a
set of frequencies in ${\mathbb Z}^d$ satisfies the strict majorant property on
$L^p([0,1]^d)$ for all $p> 0$ if and only if the set is affinely independent.
We further construct three types of violations of the strict majorant property.
Any set of at least $d+2$ frequencies in ${\mathbb Z}^d$ violates the strict
majorant property on $L^p([0,1]^d)$ for an open interval of $p \not\in 2
{\mathbb N}$ of length 2. Any infinite set of frequencies in ${\mathbb Z}^d$
violates the strict majorant property on $L^p([0,1]^d)$ for an infinite
sequence of open intervals of $p \not\in 2 {\mathbb N}$ of length $2$. Finally,
given any $p>0$ with $p \not\in 2{\mathbb N}$, we exhibit a set of $d+2$
frequencies on the moment curve in ${\mathbb R}^d$ that violate the strict
majorant property on $L^p([0,1]^d).$


  There is an increasing need for automated support for humans monitoring the
activity of distributed teams of cooperating agents, both human and machine. We
characterize the domain-independent challenges posed by this problem, and
describe how properties of domains influence the challenges and their
solutions. We will concentrate on dynamic, data-rich domains where humans are
ultimately responsible for team behavior. Thus, the automated aid should
interactively support effective and timely decision making by the human. We
present a domain-independent categorization of the types of alerts a plan-based
monitoring system might issue to a user, where each type generally requires
different monitoring techniques. We describe a monitoring framework for
integrating many domain-specific and task-specific monitoring techniques and
then using the concept of value of an alert to avoid operator overload. We use
this framework to describe an execution monitoring approach we have used to
implement Execution Assistants (EAs) in two different dynamic, data-rich,
real-world domains to assist a human in monitoring team behavior. One domain
(Army small unit operations) has hundreds of mobile, geographically distributed
agents, a combination of humans, robots, and vehicles. The other domain (teams
of unmanned ground and air vehicles) has a handful of cooperating robots. Both
domains involve unpredictable adversaries in the vicinity. Our approach
customizes monitoring behavior for each specific task, plan, and situation, as
well as for user preferences. Our EAs alert the human controller when reported
events threaten plan execution or physically threaten team members. Alerts were
generated in a timely manner without inundating the user with too many alerts
(less than 10 percent of alerts are unwanted, as judged by domain experts).


  End-to-end speech translation poses a heavy burden on the encoder, because it
has to transcribe, understand, and learn cross-lingual semantics
simultaneously. To obtain a powerful encoder, traditional methods pre-train it
on ASR data to capture speech features. However, we argue that pre-training the
encoder only through simple speech recognition is not enough and high-level
linguistic knowledge should be considered. Inspired by this, we propose a
curriculum pre-training method that includes an elementary course for
transcription learning and two advanced courses for understanding the utterance
and mapping words in two languages. The difficulty of these courses is
gradually increasing. Experiments show that our curriculum pre-training method
leads to significant improvements on En-De and En-Fr speech translation
benchmarks.


  Translation suggestion (TS) models are used to automatically provide
alternative suggestions for incorrect spans in sentences generated by machine
translation. This paper introduces the system used in our submission to the
WMT'22 Translation Suggestion shared task. Our system is based on the ensemble
of different translation architectures, including Transformer, SA-Transformer,
and DynamicConv. We use three strategies to construct synthetic data from
parallel corpora to compensate for the lack of supervised data. In addition, we
introduce a multi-phase pre-training strategy, adding an additional
pre-training phase with in-domain data. We rank second and third on the
English-German and English-Chinese bidirectional tasks, respectively.


  In this note we connect the language of Bessis's Garisde categories with
Salvetti's metrical-hemisphere complexes in order to find new examples of weak
Garside groups. As our main example, we show that the fundamental group of the
(appropriately defined) complexified complement of a pseudohyperplane
arrangement is a weak Garside group. As a consequence of the Folkman-Lawrence
topological realization theorem, we also show that fundamental group of the
Salvetti complex of a ("simplicial") oriented matroid is a weak Garside group.
This provides novel examples of weak Garside groups.


  Large language models (LLMs) enable in-context learning (ICL) by conditioning
on a few labeled training examples as a text-based prompt, eliminating the need
for parameter updates and achieving competitive performance. In this paper, we
demonstrate that factual knowledge is imperative for the performance of ICL in
three core facets: the inherent knowledge learned in LLMs, the factual
knowledge derived from the selected in-context examples, and the knowledge
biases in LLMs for output generation. To unleash the power of LLMs in few-shot
learning scenarios, we introduce a novel Knowledgeable In-Context Tuning (KICT)
framework to further improve the performance of ICL: 1) injecting knowledge
into LLMs during continual self-supervised pre-training, 2) judiciously
selecting the examples for ICL with high knowledge relevance, and 3)
calibrating the prediction results based on prior knowledge. We evaluate the
proposed approaches on autoregressive models (e.g., GPT-style LLMs) over
multiple text classification and question-answering tasks. Experimental results
demonstrate that KICT substantially outperforms strong baselines and improves
by more than 13% and 7% on text classification and question-answering tasks,
respectively.


  Let $G$ be a finite abelian group viewed a $\mathbb{Z}$-module and let
$\mathcal{G} = (V, E)$ be a simple graph. In this paper, we consider a graph
$\Gamma(G)$ called as a \textit{group-annihilator} graph. The vertices of
$\Gamma(G)$ are all elements of $G$ and two distinct vertices $x$ and $y$ are
adjacent in $\Gamma(G)$ if and only if $[x : G][y : G]G = \{0\}$, where $x,
y\in G$ and $[x : G] = \{r\in\mathbb{Z} : rG \subseteq \mathbb{Z}x\}$ is an
ideal of a ring $\mathbb{Z}$. We discuss in detail the graph structure realised
by the group $G$. Moreover, we study the creation sequence, hyperenergeticity
and hypoenergeticity of group-annihilator graphs. Finally, we conclude the
paper with a discussion on Laplacian eigen values of the group-annhilator
graph. We show that the Laplacian eigen values are representatives of orbits of
the group action: $Aut(\Gamma(G)) \times G \rightarrow G$.


  The on-chip creation of coherent light at visible wavelengths is crucial to
field-level deployment of spectroscopy and metrology systems. Although on-chip
lasers have been implemented in specific cases, a general solution that is not
restricted by limitations of specific gain media has not been reported. Here,
we propose creating visible light from an infrared pump by widely-separated
optical parametric oscillation (OPO) using silicon nanophotonics. The OPO
creates signal and idler light in the 700 nm and 1300 nm bands, respectively,
with a 900 nm pump. It operates at a threshold power of (0.9 +/- 0.1) mW, over
50x smaller than other widely-separated microcavity OPO works, which have only
been reported in the infrared. This low threshold enables direct pumping
without need of an intermediate optical amplifier. We further show how the
device design can be modified to generate 780 nm and 1500 nm light with a
similar power efficiency. Our nanophotonic OPO shows distinct advantages in
power efficiency, operation stability, and device scalability, and is a major
advance towards flexible on-chip generation of coherent visible light.


  Classification of malware families is crucial for a comprehensive
understanding of how they can infect devices, computers, or systems. Thus,
malware identification enables security researchers and incident responders to
take precautions against malware and accelerate mitigation. API call sequences
made by malware are widely utilized features by machine and deep learning
models for malware classification as these sequences represent the behavior of
malware. However, traditional machine and deep learning models remain incapable
of capturing sequence relationships between API calls. On the other hand, the
transformer-based models process sequences as a whole and learn relationships
between API calls due to multi-head attention mechanisms and positional
embeddings. Our experiments demonstrate that the transformer model with one
transformer block layer surpassed the widely used base architecture, LSTM.
Moreover, BERT or CANINE, pre-trained transformer models, outperformed in
classifying highly imbalanced malware families according to evaluation metrics,
F1-score, and AUC score. Furthermore, the proposed bagging-based random
transformer forest (RTF), an ensemble of BERT or CANINE, has reached the
state-of-the-art evaluation scores on three out of four datasets, particularly
state-of-the-art F1-score of 0.6149 on one of the commonly used benchmark
dataset.


  A thermally induced templated synthesis for SiC nanotubes and nanofibers
using ammonia or nitrogen as a carrier gas, single wall carbon nanotubes
(SWCNT) as templates as well as gaseous Si is presented. The bundles of SWCNT
act as both the carbon source and as a nanoframe from which SiC structuctures
form. Depending on the duration of the thermally induced templated reaction,
for a fixed temperature, carrier gas, and gas pressure, various SiC
nanostructures are obtained. These structures include SiC nanorods coated in C,
SiC nanorods, SiC nanotubes, and SiC nanocrytals. From our analysis using
transmission electron microscopy (TEM) and scanning electron microscopy (SEM),
electron energy-loss spectroscopy (EELS), electron diffraction (EDX), optical
absorption spectroscopy and Raman spectroscopy as probes we prove that H has a
key role on the morphology and stochiometry of the different SiC
nanostructures.


  We propose a model for CP violating oscillations of neutral, heavy-flavored
baryons into antibaryons at rates which are within a few orders of magnitude of
their lifetimes. The flavor structure of the baryon violation suppresses
neutron oscillations and baryon number violating nuclear decays to
experimentally allowed rates. We also propose a scenario for producing such
baryons in the early Universe via the out-of-equilibrium decays of a neutral
particle, after hadronization but before nucleosynthesis. We find parameters
where CP violating baryon oscillations at a temperature of a few MeV could
result in the observed asymmetry between baryons and antibaryons. Furthermore,
part of the relevant parameter space for baryogenesis is potentially testable
at Belle II via decays of heavy flavor baryons into an exotic neutral fermion.
The model introduces four new particles: three light Majorana fermions and a
colored scalar. The lightest of these fermions is typically long lived on
collider timescales and may be produced in decays of bottom and possibly
charmed hadrons.


  This work is an introduction to the local geometric theory of Veronese webs
developed in the last twenty years. Among the different possible approach, here
one has chosen the point of view of differential forms. Moreover, in order to
make its reading easier, this text is self-contained in which directly regards
Veronese webs.


  We introduce Motion-I2V, a novel framework for consistent and controllable
image-to-video generation (I2V). In contrast to previous methods that directly
learn the complicated image-to-video mapping, Motion-I2V factorizes I2V into
two stages with explicit motion modeling. For the first stage, we propose a
diffusion-based motion field predictor, which focuses on deducing the
trajectories of the reference image's pixels. For the second stage, we propose
motion-augmented temporal attention to enhance the limited 1-D temporal
attention in video latent diffusion models. This module can effectively
propagate reference image's feature to synthesized frames with the guidance of
predicted trajectories from the first stage. Compared with existing methods,
Motion-I2V can generate more consistent videos even at the presence of large
motion and viewpoint variation. By training a sparse trajectory ControlNet for
the first stage, Motion-I2V can support users to precisely control motion
trajectories and motion regions with sparse trajectory and region annotations.
This offers more controllability of the I2V process than solely relying on
textual instructions. Additionally, Motion-I2V's second stage naturally
supports zero-shot video-to-video translation. Both qualitative and
quantitative comparisons demonstrate the advantages of Motion-I2V over prior
approaches in consistent and controllable image-to-video generation. Please see
our project page at https://xiaoyushi97.github.io/Motion-I2V/.