  The variability of Indo-Pacific SST on seasonal to multidecadal timescales is
investigated using a recently introduced technique called nonlinear Laplacian
spectral analysis (NLSA). Through this technique, drawbacks associated with ad
hoc pre-filtering of the input data are avoided, enabling recovery of
low-frequency and intermittent modes not previously accessible via classical
approaches. Here, a multiscale hierarchy of spatiotemporal modes is identified
for Indo-Pacific SST in millennial control runs of CCSM4 and CM3 and in HadISST
data. On interannual timescales, a mode with spatiotemporal patterns
corresponding to the fundamental component of ENSO emerges, along with
ENSO-modulated annual modes consistent with combination mode theory. The ENSO
combination modes also feature prominent activity in the Indian Ocean,
explaining significant fraction of the SST variance in regions associated with
the Indian Ocean dipole. A pattern resembling the tropospheric biennial
oscillation emerges in addition to ENSO and the associated combination modes.
On multidecadal timescales, the dominant NLSA mode in the model data is
predominantly active in the western tropical Pacific. The interdecadal Pacific
oscillation also emerges as a distinct NLSA mode, though with smaller explained
variance than the western Pacific multidecadal mode. Analogous modes on
interannual and decadal timescales are also identified in HadISST data for the
industrial era, as well as in model data of comparable timespan, though decadal
modes are either absent or of degraded quality in these datasets.


  The mean spectrum and burst statistics of gravitational waves produced by a
cosmological population of cosmic string loops are estimated using analytic
approximations, calibrated with earlier simulations. Formulas are derived
showing the dependence of observables on the string tension, in the regime
where newly-formed loops are relatively large, not very much smaller than the
horizon. Large loops form earlier, are more abundant, and generate a more
intense stochastic background and more frequent bursts than assumed in earlier
background estimates, enabling experiments to probe lighter cosmic strings of
interest to string theory. Predictions are compared with instrument noise from
current and future experiments, and with confusion noise from known
astrophysical gravitational wave sources such as stellar and massive black hole
binaries. In these large-loop models, current data from millisecond pulsar
timing already suggests that the tension is less than about $10^{-10}$, a
typical value expected in strings from brane inflation. LISA will be sensitive
to stochastic backgrounds created by strings as light as $G\mu\approx
10^{-15}$, at frequencies where it is limited by confusion noise of Galactic
stellar populations; however, for those lightest detectable strings, bursts are
rarely detectable.


  Chen, Faudree, Gould, Jacobson, and Lesniak determined the minimum degree
threshold for which a balanced $k$-partite graph has a Hamiltonian cycle. We
give an asymptotically tight minimum degree condition for Hamiltonian cycles in
arbitrary $k$-partite graphs in which all parts have at most $n/2$ vertices (a
necessary condition). To do this, we first prove a general result which both
simplifies the process of checking whether a graph $G$ is a robust expander and
gives useful structural information in the case when $G$ is not a robust
expander. Then we use this result to prove that any $k$-partite graph
satisfying the minimum degree condition is either a robust expander or else
contains a Hamiltonian cycle directly.


  Fluctuations in the physical properties of biological machines are
inextricably linked to their functions. Distributions of run-lengths and
velocities of processive molecular motors, like kinesin-1, are accessible
through single molecule techniques, yet there is lack a rigorous theoretical
model for these probabilities up to now. We derive exact analytic results for a
kinetic model to predict the resistive force ($F$) dependent velocity ($P(v)$)
and run-length ($P(n)$) distribution functions of generic finitely processive
molecular motors that take forward and backward steps on a track. Our theory
quantitatively explains the zero force kinesin-1 data for both $P(n)$ and
$P(v)$ using the detachment rate as the only parameter, thus allowing us to
obtain the variations of these quantities under load. At non-zero $F$, $P(v)$
is non-Gaussian, and is bimodal with peaks at positive and negative values of
$v$. The prediction that $P(v)$ is bimodal is a consequence of the discrete
step-size of kinesin-1, and remains even when the step-size distribution is
taken into account. Although the predictions are based on analyses of kinesin-1
data, our results are general and should hold for any processive motor, which
walks on a track by taking discrete steps.


  Changes in the capital structure before and after the global financial crisis
for SMEs are studied, emphasizing their financing problems, distinguishing
between internal financing and external financing determinants. The empirical
research bears upon 158 small and medium-sized firms listed on Shenzhen and
Shanghai Stock Exchanges in China over the period of 2004-2014. A regression
analysis, along the lines of the Trade-Off Theory, shows that the leverage
decreases with profitability, non-debt tax shields and the liquidity, and
increases with firm size and tangibility. A positive relationship is found
between firm growth and debt ratio, though not highly significantly. It is
shown that the SMEs with high growth rates are those which will more easily
obtain external financing after a financial crisis. It is recognized that the
China government should reconsider SMEs taxation laws.


  This paper presents four new classes of binary quantum codes with minimum
dis- tance 3 and 4, namely Class-I, Class-II, Class-III and Class-IV. The
classes Class-I and Class-II are constructed based on self-dual orientable
embeddings of the com- plete graphs K4r+1 and K4s and by current graphs and
rotation schemes. and s are both divisible by 4.


  We have obtained maps of the molecular emission within the central five
arcminutes (12 pc) of the Galactic center (GC) in selected molecular tracers:
SiO(2-1), HNCO(5_{0,5}-4_{0,4}), and the J=1-->0 transition of H^{13}CO+,
HN^{13}C, and C^{18}O at an angular resolution of 30" (1.2 pc). The mapped
region includes the circumnuclear disk (CND) and the two surrounding giant
molecular clouds (GMCs) of the Sgr A complex, known as the 20 and 50 km s^{-1}
molecular clouds.Additionally, we simultaneously observed the J=2-1 and 3-2
transitions of SiO toward selected positions to estimate the physical
conditions of the molecular gas. The SiO(2-1) and H^{13}CO+(1-0) emission
covers the same velocity range and presents a similar distribution. In
contrast, HNCO(5-4) emission appears in a narrow velocity range mostly
concentrated in the 20 and 50 km s^{-1} GMCs. The HNCO column densities and
fractional abundances present the highest contrast, with difference factors of
$\geq$60 and 28, respectively. Their highest values are found toward the cores
of the GMCs, whereas the lowest ones are measured at the CND. SiO abundances do
not follow this trend, with high values found toward the CND, as well as the
GMCs. By comparing our abundances with those of prototypical Galactic sources
we conclude that HNCO, similar to SiO, is ejected from grain mantles into
gas-phase by nondissociative C-shocks. This results in the high abundances
measured toward the CND and the GMCs. However, the strong UV radiation from the
Central cluster utterly photodissociates HNCO as we get closer to the center,
whereas SiO seems to be more resistant against UV-photons or it is produced
more efficiently by the strong shocks in the CND. Finally, we discuss the
possible connections between the molecular gas at the CND and the GMCs using
the HNCO/SiO, SiO/CS, and HNCO/CS intensity ratios as probes of distance to the
Central cluster.


  All properties of the quasars known by the author (quietness of the BAL
quasars, Lyman forest, iron in the high-z quasars...) are explained supposing
that the kernel of the quasar is surrounded by a halo containing an accretion
disk and magnetic satellites (no dark matter or fast jet, no variation of the
fine structure constant, no strange source of iron...). The key is taking into
account the coherent light-matter interactions.


  Current network-based methods for detecting coordinated inauthentic behaviour
on social media focus primarily on inferring links between accounts based on
common "behavioural traces" [19], such as retweeting the same tweet or posting
the same URL. Assuming the goal of coordination is amplification, boosting a
message within a constrained period, most approaches use a temporal window to
ensure the co-activity occurs within a specific timeframe [9, 14, 19, 24].
Real-world application requires considering near real-time processing, creating
performance requirements, which also highlight gaps in the semantics of
coordination in the literature. These methods could all exploit temporal
elements of coordinated activity. We describe preliminary research regarding
coordination network semantics, coordination network construction, relevant
observations in three political Twitter datasets and the role of cheerleaders
in revealing social bots.


  In this paper, we present an explicit construction of list-decodable codes
for single-deletion and single-substitution with list size two and redundancy
3log n+4, where n is the block length of the code. Our construction has lower
redundancy than the best known explicit construction by Gabrys et al. (arXiv
2021), whose redundancy is 4log n+O(1).


  We give a moduli interpretation of the outer automorphism group Out of a
finite dimensional algebra similar to that of the Picard group of a scheme. We
deduce that Out^0 is invariant under derived and stable equivalences. This
allows us to transfer gradings between algebras and gives rise to conjectural
homological constructions of interesting gradings on block of finite groups
with abelian defect. We give applications to the lifting of stable equivalences
to derived equivalences.
  We give a counterpart of the invariance result for smooth projective
varieties: the product Pic^0xAut^0 is invariant under derived equivalence.


  In its daily use, the Indonesian language is riddled with informality, that
is, deviations from the standard in terms of vocabulary, spelling, and word
order. On the other hand, current available Indonesian NLP models are typically
developed with the standard Indonesian in mind. In this work, we address a
style-transfer from informal to formal Indonesian as a low-resource machine
translation problem. We build a new dataset of parallel sentences of informal
Indonesian and its formal counterpart. We benchmark several strategies to
perform style transfer from informal to formal Indonesian. We also explore
augmenting the training set with artificial forward-translated data. Since we
are dealing with an extremely low-resource setting, we find that a phrase-based
machine translation approach outperforms the Transformer-based approach.
Alternatively, a pre-trained GPT-2 fined-tuned to this task performed equally
well but costs more computational resource. Our findings show a promising step
towards leveraging machine translation models for style transfer. Our code and
data are available in https://github.com/haryoa/stif-indonesia


  We present a lattice study of the $SU(4)$ gauge theory with two Dirac
fermions in the fundamental and two in the two-index antisymmetric
representation, a model close to a theory of partial compositeness. Focus of
this work are the methodologies behind the computation of the spectrum and the
extrapolation of the chiral point for a theory with matter in multiple
representations. While being still technical, this study provides important
steps towards a non-perturbative understanding of the spectrum of theories of
partial compositeness, which present a richer dynamics compared to
single-representation theories. The multi-representation features are studied
first in perturbation theory, and then non-perturbatively by adopting a dual
outlook on lattice data through a joint analysis of time-momentum correlation
functions and smeared spectral densities.


  In this article, we give a simple and direct proof of the Yoshida-Nicolaescu
Theorem in a more general context by using the theory of partial signatures. We
do not impose the usual condition of non-degeneracy at the endpoints and use a
natural definition of the Maslov index.


  We study knockout reactions with proton probes within a theoretical framework
where {\it ab initio} Quantum Monte Carlo wave functions are combined with the
Faddeev/Alt-Grassberger-Sandhas few-body reaction formalism. New Quantum Monte
Carlo wave functions are used to describe $^{12}$C, yielding, for the first
time, results consistent with the experimental point rms radii, electron
scattering data and (p,2p) total cross sections data. Our results for
$\mathrm{A}\leq 12$ and $(N-Z) \leq 3$ nuclei show that the theoretical ratios
between the (i) {\it ab initio} and Mean Field Approximation theoretical cross
sections, $\mathcal{R}_\sigma$, (ii) corresponding ratios between the
spectroscopic factors, $\mathcal{R}_\Sigma$, summed over states below particle
emission, depend moderately on the nucleon separation energy S$_{\rm N}$. These
ratios are determined by a delicate interplay between the radii of the parent
and the residual nuclei and the nucleon separation energy, and were found to be
always smaller for the knockout of the more correlated deficient species
nucleon. In the case of the symmetric $^{12}$C nucleus, the theoretical ratios
still appear to indicate that protons are more correlated than neutrons.


  We initiate the study of parameterized complexity of $\textsf{QMA}$ problems
in terms of the number of non-Clifford gates in the problem description. We
show that for the problem of parameterized quantum circuit satisfiability,
there exists a classical algorithm solving the problem with a runtime scaling
exponentially in the number of non-Clifford gates but only polynomially with
the system size. This result follows from our main result, that for any
Clifford + $t$ $T$-gate quantum circuit satisfiability problem, the search
space of optimal witnesses can be reduced to a stabilizer subspace isomorphic
to at most $t$ qubits (independent of the system size). Furthermore, we derive
new lower bounds on the $T$-count of circuit satisfiability instances and the
$T$-count of the $W$-state assuming the classical exponential time hypothesis
($\textsf{ETH}$). Lastly, we explore the parameterized complexity of the
quantum non-identity check problem.


  Axial vector $(J^{PC}=1^{++})$ charmonium and bottomonium hybrid masses are
determined via QCD Laplace sum-rules. Previous sum-rule studies in this channel
did not incorporate the dimension-six gluon condensate, which has been shown to
be important for $1^{--}$ and $0^{-+}$ heavy quark hybrids. An updated analysis
of axial vector charmonium and bottomonium hybrids is presented, including the
effects of the dimension-six gluon condensate. The axial vector charmonium and
bottomonium hybrid masses are predicted to be 5.13 GeV and 11.32 GeV,
respectively. We discuss the implications of this result for the
charmonium-like XYZ states and the charmonium hybrid multiplet structure
observed in recent lattice calculations.


  We investigate the occurrence rate of rapidly rotating ($v\sin i$$>$10 km
s$^{-1}$), low-mass giant stars in the APOGEE-Kepler (APOKASC) fields with
asteroseismic mass and surface gravity measurements. Such stars are likely
merger products and their frequency places interesting constraints on stellar
population models. We also identify anomalous rotators, i.e. stars with 5 km
s$^{-1}$$<$$v\sin i$$<$10 km s$^{-1}$ that are rotating significantly faster
than both angular momentum evolution predictions and the measured rates of
similar stars. Our data set contains fewer rapid rotators than one would expect
given measurements of the Galactic field star population, which likely
indicates that asteroseismic detections are less common in rapidly rotating red
giants. The number of low-mass moderate (5-10 km s$^{-1}$) rotators in our
sample gives a lower limit of 7% for the rate at which low-mass stars interact
on the upper red giant branch because single stars in this mass range are
expected to rotate slowly. Finally, we classify the likely origin of the rapid
or anomalous rotation where possible. KIC 10293335 is identified as a merger
product and KIC 6501237 is a possible binary system of two oscillating red
giants.


  Although supervised image denoising networks have shown remarkable
performance on synthesized noisy images, they often fail in practice due to the
difference between real and synthesized noise. Since clean-noisy image pairs
from the real world are extremely costly to gather, self-supervised learning,
which utilizes noisy input itself as a target, has been studied. To prevent a
self-supervised denoising model from learning identical mapping, each output
pixel should not be influenced by its corresponding input pixel; This
requirement is known as J-invariance. Blind-spot networks (BSNs) have been a
prevalent choice to ensure J-invariance in self-supervised image denoising.
However, constructing variations of BSNs by injecting additional operations
such as downsampling can expose blinded information, thereby violating
J-invariance. Consequently, convolutions designed specifically for BSNs have
been allowed only, limiting architectural flexibility. To overcome this
limitation, we propose PUCA, a novel J-invariant U-Net architecture, for
self-supervised denoising. PUCA leverages patch-unshuffle/shuffle to
dramatically expand receptive fields while maintaining J-invariance and dilated
attention blocks (DABs) for global context incorporation. Experimental results
demonstrate that PUCA achieves state-of-the-art performance, outperforming
existing methods in self-supervised image denoising.


  We present the projected metallicity profiles for a sample of 17 rich galaxy
clusters observed by BeppoSAX. We find that the 8 non-cooling flow clusters
have flat metallicity profiles. On the contrary, a strong enhancement in the
abundance is found in the central regions of the cooling flow clusters. All the
non-cooling flow clusters present evidence of recent merger activity suggesting
that the merger events redistributes efficiently the metal content of the
intracluster medium. For the cooling flow clusters with better statistics and
available optical data (A85, A496, A2029 and Perseus) we have tested whether
the observed abundance excess is due to metals ejected from the galaxies
located in the cluster core. We find that at a resolution > 100 kpc the
observed projected abundance excess profiles are consistent with originating
from a deprojected metal excess distribution tracing the optical light
distribution. In the one case (i.e. Perseus) with higher resolution (~ 50 kpc),
we find that the observed metal abundance excess distribution is broader than
the predicted one. Such a difference can be reconciled if we assume that the
metals have drifted away from their parent ejecting galaxies by a few tens of
kpc, or, alternatively, if we assume that the cluster light profile has become
significantly more centrally peaked because of the formation process of the
central dominant cluster galaxy since the last major merger occurred.


  A simplified Randall-Sundrum-like model in 6 dimensions is discussed. The
extra two dimensions correspond to the cone. The effective four-dimensional
scalar self-interacting theory is studied at one-loop level. The contributions
due to 6-dimensional parameters in four-dimensional beta-functions appear.
Using such beta-functions the one-loop effective potential is calculated. The
possibility of spontaneous symmetry breaking due to extra dimensions is
demonstrated.


  We study classical solutions (ic-instantons) in N=4 SYM in 4D which, in the
strong coupling limit, correspond to complex two-dimensional manifolds.
Asymptotically in time the latter have boundaries represented by compact real
three-manifolds. Therefore they lend themselves to an interpretation in terms
of 3-brane scattering. We suggest that these solutions may represent scattering
of D3-branes of type IIB theory in 10D. In particular we show that the
world-volume theory on complex two-dimensional manifolds is the correct one for
D3-branes.


  Let $f=0$ be a plane algebraic curve of degree $d>1$ with an isolated
singular point at the origin of the complex plane. We show that the Milnor
number $\mu_0(f)$ is less than or equal to $(d-1)^2-\left[\frac{d}{2}\right]$,
unless $f=0$ is a set of $d$ concurrent lines passing through 0. Then we
characterize the curves $f=0$ for which
$\mu_0(f)=(d-1)^2-\left[\frac{d}{2}\right]$.


  A general reconstruction and calibration procedure for tracking and wire
position determination of the OPERA drift tubes is presented. The mathematics
of the pattern recognition and the track fit are explained.


  Let $B$ be a smooth projective curve of genus $g$, and $S \subset B$ be a
finite subset of cardinality $s$. We give an effective upper bound on the
number of deformation types of admissible families of canonically polarized
manifolds of dimension $n$ with canonical volume $v$ over $B$ with prescribed
degeneracy locus $S$. The effective bound only depends on the invariants $g, s,
n$ and $v$. The key new ingredient which allows for this kind of result is a
careful study of effective birationality for families of canonically polarized
manifolds.


  We present a model of public good provision with a distributor. Our main
result describes a symmetric mixed-strategy equilibrium, where all agents
contribute to a common fund with probability $p$ and the distributor provides
either a particular amount of public goods or nothing. A corollary of this
finding is the efficient public good provision equilibrium where all agents
contribute to the common fund, all agents are expected to contribute, and the
distributor spends the entire common fund for the public good provision.


  The discovery of neighbouring active nodes is one of the most challenging
problems in asynchronous ad hoc networks. Since time synchronization is
extremely costly in these networks, application of asynchronous methods like
quorum-based protocols have attracted increased interest for their suitability.
This is because Quorum-based protocols can guarantee that two nodes with
differing clock times have an intersection within at least one timeslot. A
higher neighbour discovery rate of active nodes is desired, but it also results
in a higher active ratio and consequently and adversely more overall power
consumption of the nodes and a shorter network lifetime. There must be a
trade-off between extensive neighbour discovery and active ratio in order to
design high-performance and efficient protocols. In this paper, two novel
asynchronous quorum-based protocols to maximize the neighbour discovery and
minimize the active ratio have been designed and presented. A new metric
(Quorum Efficiency Ratio: QER) has also been designed to evaluate and compare
the performance of quorum-based protocols in terms of their neighbour discovery
(the Expected Quorum Overlap Size: EQOS) and the active ratio. The EQOS has
been theoretically derived, along with the Active Ratio and the QER values for
the proposed novel protocols and the other contemporary protocols. Finally, the
proposed methods have been evaluated and compared against the other methods
based on the current metrics and the new metric.


  CyberShake (CS) is a high-performance computing workflow for Probabilistic
Seismic Hazard Assessment (PSHA) developed by the Statewide California
Earthquake Center. Here, we employ CS to generate a set of 2103 fault ruptures
and simulate the corresponding two horizontal velocity components time
histories of ground motion (GM) on a 5-km grid of 625 stations in Southwest
Iceland (SI). The ruptures were defined on a new synthetic time-independent
500-year catalog consisting of 223 hypothetical finite-fault sources of 5-7,
generated using a new physics-based bookshelf fault system model in the SI
transform zone. This fault system model and rupture realizations enable the CS
time-independent physics-based approach to PSHA in the region. The study aims
to migrate CS to SI and validate its kinematic fault rupture, anelastic wave
propagation and ground motion simulations. Toward this goal, we use CS to
generate multiple finite-fault rupture variations for each hypothetical fault.
CS exploits seismic reciprocity for wave propagation by computing Strain Green
Tensors along fault planes, which in turn are convolved with rupture models to
generate GM seismograms. For each GM recording station, every adjoint
simulation uses a 0-1 Hz Gaussian point source polarized along one horizontal
grid direction. Comparison of the results in the form of rotation-invariant
synthetic pseudo-acceleration spectral response values at 2, 3 and 5 sec
periods are in very good agreement with the Icelandic strong-motion dataset,
and a suite of new empirical Bayesian ground motion prediction equations
(GMPEs). The vast majority of the CS results fall within one standard deviation
of the mean GMPE predictions, previously estimated for the area. Importantly,
at large magnitudes for which no data exists in Iceland, the CS dataset may
play an important role in constraining the GMPEs for future applications.


  Akemann and Weaver (2014) have shown a remarkable extension of Weaver's
$KS_r$ Conjecture (2004) in the form of approximate Lyapunov's theorem. This
was made possible thanks to the breakthrough solution of the Kadison-Singer
problem by Marcus, Spielman, and Srivastava (2015). In this paper we show a
similar type of Lyapunov theorem for continuous frames on non-atomic measure
spaces. In contrast with discrete frames, the proof of this result does not
rely on the recent solution of the Kadison-Singer problem.


  Sensory perception (e.g. vision) relies on a hierarchy of cortical areas, in
which neural activity propagates in both directions, to convey information not
only about sensory inputs but also about cognitive states, expectations and
predictions. At the macroscopic scale, neurophysiological experiments have
described the corresponding neural signals as both forward and
backward-travelling waves, sometimes with characteristic oscillatory
signatures. It remains unclear, however, how such activity patterns relate to
specific functional properties of the perceptual apparatus. Here, we present a
mathematical framework, inspired by neural network models of predictive coding,
to systematically investigate neural dynamics in a hierarchical perceptual
system. We show that stability of the system can be systematically derived from
the values of hyper-parameters controlling the different signals (related to
bottom-up inputs, top-down prediction and error correction). Similarly, it is
possible to determine in which direction, and at what speed neural activity
propagates in the system. Different neural assemblies (reflecting distinct
eigenvectors of the connectivity matrices) can simultaneously and independently
display different properties in terms of stability, propagation speed or
direction. We also derive continuous-limit versions of the system, both in time
and in neural space. Finally, we analyze the possible influence of transmission
delays between layers, and reveal the emergence of oscillations at biologically
plausible frequencies.


  Brain extraction or whole brain segmentation is an important first step in
many of the neuroimage analysis pipelines. The accuracy and robustness of brain
extraction, therefore, is crucial for the accuracy of the entire brain analysis
process. With the aim of designing a learning-based, geometry-independent and
registration-free brain extraction tool in this study, we present a technique
based on an auto-context convolutional neural network (CNN), in which intrinsic
local and global image features are learned through 2D patches of different
window sizes. In this architecture three parallel 2D convolutional pathways for
three different directions (axial, coronal, and sagittal) implicitly learn 3D
image information without the need for computationally expensive 3D
convolutions. Posterior probability maps generated by the network are used
iteratively as context information along with the original image patches to
learn the local shape and connectedness of the brain, to extract it from
non-brain tissue.
  The brain extraction results we have obtained from our algorithm are superior
to the recently reported results in the literature on two publicly available
benchmark datasets, namely LPBA40 and OASIS, in which we obtained Dice overlap
coefficients of 97.42% and 95.40%, respectively. Furthermore, we evaluated the
performance of our algorithm in the challenging problem of extracting
arbitrarily-oriented fetal brains in reconstructed fetal brain magnetic
resonance imaging (MRI) datasets. In this application our algorithm performed
much better than the other methods (Dice coefficient: 95.98%), where the other
methods performed poorly due to the non-standard orientation and geometry of
the fetal brain in MRI. Our CNN-based method can provide accurate,
geometry-independent brain extraction in challenging applications.


  We consider the emission processes in the large-scale jets of powerful
quasars based on the results obtained with the VLA, Spitzer, Hubble, and
Chandra. We show that two well-known jets, 3C 273 and PKS 1136-135, have two
distinct spectral components on large-scales: (1) the low-energy (LE)
synchrotron spectrum extending from radio to infrared, and (2) the high-energy
(HE) component arising from optical and extending to X-rays. The X-ray emission
in quasar jets is often attributed to inverse-Compton scattering of cosmic
microwave background (CMB) photons by radio-emitting electrons in a highly
relativistic jet. However, recent data prefer synchrotron radiation by a second
distinct population as the origin of the HE component. We anticipate that
optical polarimetry with Hubble will establish the synchrotron nature of the HE
component. Gamma-ray observations with GLAST (renamed as the Fermi Gamma-ray
Space Telescope), as well as future TeV observations, are expected to place
important constraints on the jet models.


  We define and study square-integrable coactions of locally compact quantum
groups on Hilbert modules, generalising previous work for group actions. As
special cases, we consider square-integrable Hilbert space corepresentations
and integrable coactions on C*-algebras. Our main result is an equivariant
generalisation of Kasparov's Stabilisation Theorem.


  Sleep apnea (SA) is a significant respiratory condition that poses a major
global health challenge. Previous studies have investigated several machine and
deep learning models for electrocardiogram (ECG)-based SA diagnoses. Despite
these advancements, conventional feature extractions derived from ECG signals,
such as R-peaks and RR intervals, may fail to capture crucial information
encompassed within the complete PQRST segments. In this study, we propose an
innovative approach to address this diagnostic gap by delving deeper into the
comprehensive segments of the ECG signal. The proposed methodology draws
inspiration from Matrix Profile algorithms, which generate an Euclidean
distance profile from fixed-length signal subsequences. From this, we derived
the Min Distance Profile (MinDP), Max Distance Profile (MaxDP), and Mean
Distance Profile (MeanDP) based on the minimum, maximum, and mean of the
profile distances, respectively. To validate the effectiveness of our approach,
we use the modified LeNet-5 architecture as the primary CNN model, along with
two existing lightweight models, BAFNet and SE-MSCNN, for ECG classification
tasks. Our extensive experimental results on the PhysioNet Apnea-ECG dataset
revealed that with the new feature extraction method, we achieved a per-segment
accuracy up to 92.11 \% and a per-recording accuracy of 100\%. Moreover, it
yielded the highest correlation compared to state-of-the-art methods, with a
correlation coefficient of 0.989. By introducing a new feature extraction
method based on distance relationships, we enhanced the performance of certain
lightweight models, showing potential for home sleep apnea test (HSAT) and SA
detection in IoT devices. The source code for this work is made publicly
available in GitHub: https://github.com/vinuni-vishc/MPCNN-Sleep-Apnea.


  Strongly lensed systems are powerful probes of the distribution of dark
matter on small scales. In this paper, we show that line-of-sight haloes
between the source and the observers give rise to a distinct anisotropic
signature in the two-point function of the effective lensing deflection field.
We show in particular that the non-linear coupling between line-of-sight haloes
and the main-lens plane imprints a characteristic quadrupole moment on this
two-point function whose amplitude reflects the abundance of such haloes within
the strongly lensed field. We discuss how, by taking ratios of different
multipole moments, such observables could be made robust under the mass-sheet
transform. We also demonstrate that future extremely large telescopes have the
ability to detect the quadrupole moment due to this unique anisotropic
signature under ideal conditions. Our approach opens the door to statistically
distinguish the effect of line-of-sight haloes from that of the main-lens
substructure on lensed images, hence allowing one to probe dark matter physics
in a new way.


  We consider eigenvalues of a product of n non-Hermitian, independent random
matrices. Each matrix in this product is of size N\times N with independent
standard complex Gaussian variables. The eigenvalues of such a product form a
determinantal point process on the complex plane (Akemann and Burda J. Phys A:
Math. Theor. 45 (2012) 465201), which can be understood as a generalization of
the finite Ginibre ensemble. As N\rightarrow\infty, a generalized infinite
Ginibre ensemble arises. We show that the set of absolute values of the points
of this determinantal process has the same distribution as
{R_1^{(n)},R_2^{(n)},...}, where R_k^{(n)} are independent, and (R_k^{(n)})^2
is distributed as the product of n independent Gamma variables Gamma(k,1). This
enables us to find the asymptotics for the hole probabilities, i.e. for the
probabilities of the events that there are no points of the process in a disc
of radius r with its center at 0, as r\rightarrow\infty. In addition, we solve
the relevant overcrowding problem: we derive an asymptotic formula for the
probability that there are more than m points of the process in a fixed disk of
radius r with its center at 0, as m\rightarrow\infty.


  We analyze the effects of electron-electron interactions and disorder on a
Rashba double-nanowire setup coupled to an s-wave superconductor, which has
been recently proposed as a versatile platform to generate Kramers pairs of
Majorana bound states in the absence of magnetic fields. We identify the regime
of parameters for which these Kramers pairs are stable against interaction and
disorder effects. We use bosonization, perturbative renormalization group, and
replica techniques to derive the flow equations for various parameters of the
model and evaluate the corresponding phase diagram with topological and
disorder-dominated phases. We confirm aforementioned results by considering a
more microscopic approach which starts from the tunneling Hamiltonian between
the three-dimensional s-wave superconductor and the nanowires. We find again
that the interaction drives the system into the topological phase and, as the
strength of the source term coming from the tunneling Hamiltonian increases,
strong electron-electron interactions are required to reach the topological
phase.


  We make use of recent results in effective theory and higher-order
perturbative calculations to improve the theoretical predictions of the
top-quark pair production cross section at hadron colliders. In particular, we
supplement the fixed-order NLO calculation with higher-order corrections from
soft gluon resummation at NNLL accuracy. Uncertainties due to power corrections
to the soft limit are estimated by combining results from single-particle
inclusive and pair invariant-mass kinematics. We present our predictions as
functions of the top-quark mass in both the pole scheme and the MS(bar) scheme.
We also discuss the merits of using threshold masses as an alternative, and
calculate the cross section with the top-quark mass defined in the 1S scheme as
an illustrative example.


  Exclusive pi0 electroproduction from nucleons at large photon virtuality can
be described in terms of Generalized Parton Distributions, particularly the
chiral odd subset. Chiral odd GPDs are related to transversity and can be
accessed experimentally for various special choices of observables. This is
accomplished by choosing C-parity odd and chiral odd combinations of t-channel
exchange quantum numbers. These GPDs are calculated in a spectator model, and
are constrained by boundary functions. Alternatively, the production amplitudes
correspond to C-odd Regge exchanges with final state interactions. The helicity
structure of the virtual photoproduction amplitudes provides relations between
the partonic description via GPDs and the hadronic, Regge description of C-odd
processes, all via quark helicity flip. GPDs, in general, are analytic
functions of energy variables. Their integrals over unobservable parton momenta
thereby satisfy Dispersion Relations (DR). Using DR's could allow the real part
of the amplitudes, the integrated GPDs, to be extracted from the more easily
measured imaginary parts. However, at non-zero momentum transfer DRs require
integration over unphysical regions of the variables. We show that the relevant
unphysical region of the non-forward DRs is considerable. This will vitiate the
efforts to avoid the actual measurement of the real parts more directly.


  The disappearance of reactor antineutrinos in the Double Chooz experiment is
used to investigate the possibility of neutrino-antineutrino oscillations
arising due to the breakdown of Lorentz invariance. We find no evidence for
this phenomenon and set the first limits on 15 coefficients describing
neutrino-antineutrino mixing within the framework of the Standard-Model
Extension.


  Datalog is a powerful yet elegant language that allows expressing recursive
computation. Although Datalog evaluation has been extensively studied in the
literature, so far, only loose upper bounds are known on how fast a Datalog
program can be evaluated. In this work, we ask the following question: given a
Datalog program over a naturally-ordered semiring $\sigma$, what is the
tightest possible runtime? To this end, our main contribution is a general
two-phase framework for analyzing the data complexity of Datalog over $\sigma$:
first ground the program into an equivalent system of polynomial equations
(i.e. grounding) and then find the least fixpoint of the grounding over
$\sigma$. We present algorithms that use structure-aware query evaluation
techniques to obtain the smallest possible groundings. Next, efficient
algorithms for fixpoint evaluation are introduced over two classes of
semirings: (1) finite-rank semirings and (2) absorptive semirings of total
order. Combining both phases, we obtain state-of-the-art and new algorithmic
results. Finally, we complement our results with a matching fine-grained lower
bound.


  By applying a singular perturbation approach, canard limit cycles exhibited
by a general family of singularly perturbed planar piecewise linear (PWL)
differential systems are analyzed. The performed study involves both hyperbolic
and non-hyperbolic canard limit cycles appearing after both a supercritical and
a subcritical Hopf bifurcation.
  The obtained results are completely comparable with those obtained for smooth
vector fields. In some sense, the manuscript can be understood as an extension
towards the PWL framework of the results obtained for smooth systems by Krupa
and Szmolyan [18]. In addition, some novel slow-fast behaviors are obtained. In
particular, in the supercritical case, and under suitable conditions, it is
proved that the limit cycles are organized along a curve exhibiting two folds.
Each of these folds corresponds to a saddle-node bifurcation of canard limit
cycles, one involving headless canard cycles, whereas the other involving
canard cycles with head. This configuration allows the coexistence of three
canard limit cycles.


  The Hessian Topology is a subject having interesting relations with several
areas, for instance, differential geometry, implicit differential equations,
analysis and singularity theory. In this article we study the problem of
realization of a real plane curve as the Hessian curve of a smooth function.
The plane curves we consider are constituted either by only outer ovals or
inner ovals. We prove that some of such curves are realizable as Hessian
curves.


  We compute equilibrium strategies in multi-stage games with continuous signal
and action spaces as they are widely used in the management sciences and
economics. Examples include sequential sales via auctions, multi-stage
elimination contests, and Stackelberg competitions. In sequential auctions,
analysts performing equilibrium analysis are required to derive not just single
bids but bid functions for all possible signals or values that a bidder might
have in multiple stages. Due to the continuity of the signal and action spaces,
these bid functions come from an infinite dimensional space. While such models
are fundamental to game theory and its applications, equilibrium strategies are
rarely known. The resulting system of non-linear differential equations is
considered intractable for all but elementary models. This has been limiting
progress in game theory and is a barrier to its adoption in the field. We show
that Deep Reinforcement Learning and self-play can learn equilibrium bidding
strategies for various multi-stage games. We find equilibrium in models that
have not yet been explored analytically and new asymmetric equilibrium bid
functions for established models of sequential auctions. The verification of
equilibrium is challenging in such games due to the continuous signal and
action spaces. We introduce a verification algorithm and prove that the error
of this verifier decreases when considering Lipschitz continuous strategies
with increasing levels of discretization and sample sizes.


  This study delves into the radiation pattern synthesis of reconfigurable
intelligent surfaces (RIS) / reflection metasurfaces. Through superimposing
multiple single-reflection profiles, which comprise the amplitude and/or phase
settings of all constituent elements, a single incident wave can be effectively
reflected in multiple asymmetric directions. However, some mismatch and
interference between adjacent reflection beams may be caused by this
superposition as well. Additionally, it is constrained by the inherent
limitation that achieving linear and continuous amplitude adjustments and phase
shifts in real-world designs is challenging. Consequently, the reconfigurable
amplitude and phase must be approximated to discrete values, necessitating the
arrangement of reflection profile before and after optimization based on
integer. Therefore, in this paper, we adapt the traditional particle swarm
optimization (PSO) algorithm to discretized integer-based PSO by proposing the
concepts of 'discard rate' and 'knowledge.' With the enhancement of the
integer-based programming, the multiple asymmetric reflection pattern can be
synthesized with suppressed sidelobe levels within limited iterations and time
cost.


  With the increasing popularity of plugin-based software systems, ensuring the
security of plugins has become a critical concern. When users install plugins
or browse websites with plugins from an untrusted source, how can we be sure
that they do have any undesirable functions implicitly? In this research, we
present a comprehensive study on language-based security mechanisms for plugin
development. We aim to enhance the understanding of access control
vulnerabilities in plugins and explore effective security measures by
introducing a capability-based system. We also developed and evaluated test
plugins to assess the security mechanisms in popular development environments
such as IntelliJ IDEA and Visual Studio Code by utilising Java, JavaScript, and
associated APIs and frameworks. We also explore the concept of capability-based
module systems as an alternative approach to plugin security. A comparative
analysis is conducted to evaluate the effectiveness of capability-based systems
in addressing access control vulnerabilities identified in earlier sections.
Finally, recommendations for improving plugin security practices and tools will
be presented, emphasizing the importance of robust security measures in the
ever-evolving landscape of software plugins.


  In this paper, we study Grover walks on a line with one and two absorbing
boundaries. In particular, we present some results for the absorbing
probabilities both in a semi-finite and finite line. Analytical expressions for
these absorbing probabilities are presented by using the combinatorial
approach. These results are perfectly matched with numerical simulations. We
show that the behavior of Grover walks on a line with absorbing boundaries is
strikingly different from that of classical walks and that of Hadamard walks.


  The shortage of annotated medical images is one of the biggest challenges in
the field of medical image computing. Without a sufficient number of training
samples, deep learning based models are very likely to suffer from over-fitting
problem. The common solution is image manipulation such as image rotation,
cropping, or resizing. Those methods can help relieve the over-fitting problem
as more training samples are introduced. However, they do not really introduce
new images with additional information and may lead to data leakage as the test
set may contain similar samples which appear in the training set. To address
this challenge, we propose to generate diverse images with generative
adversarial network. In this paper, we develop a novel generative method named
generative adversarial U-Net , which utilizes both generative adversarial
network and U-Net. Different from existing approaches, our newly designed model
is domain-free and generalizable to various medical images. Extensive
experiments are conducted over eight diverse datasets including computed
tomography (CT) scan, pathology, X-ray, etc. The visualization and quantitative
results demonstrate the efficacy and good generalization of the proposed method
on generating a wide array of high-quality medical images.


  The classical approach for repairing a Description Logic ontology O in the
sense of removing an unwanted consequence $\alpha$ is to delete a minimal
number of axioms from O such that the resulting ontology O' does not have the
consequence $\alpha$. However, the complete deletion of axioms may be too
rough, in the sense that it may also remove consequences that are actually
wanted. To alleviate this problem, we propose a more gentle way of repair in
which axioms are not necessarily deleted, but only weakened. On the one hand,
we investigate general properties of this gentle repair method. On the other
hand, we propose and analyze concrete approaches for weakening axioms expressed
in the Description Logic EL.


  A graphene sheet biased with a drift electric current offers a tantalizing
opportunity to attain unidirectional, backscattering-immune, and subwavelength
light propagation, as proposed in [T. A. Morgado, M. G. Silveirinha, ACS
Photonics 5(11), 4253 (2018)]. Here, we investigate in detail the impact of the
intrinsic nonlocal response of graphene in the dispersion characteristics of
the current-driven plasmons supported by single-layer and double-layer graphene
systems. It is theoretically shown that even though the nonlocal effects weaken
the spectral asymmetry of the plasmons dispersion, the studied platforms can
support unidirectional backscattering-immune guided modes. Our analysis also
confirms that the drift-current bias can effectively pump the graphene plasmons
and enhance the propagation distance. Moreover, it is shown that the
nonreciprocity and optical isolation can be boosted by pairing two
drift-current biased graphene sheets due to the enhanced radiation drag by the
drifting electrons.


  The superconducting transition temperature, $T_{\rm{c}}$, of FeSe can be
significantly enhanced several-fold by applying pressure, electron doping,
intercalating spacing layer, and reducing dimensionality. Various ordered
electronic phases, such as nematicity and spin density waves, have also been
observed accompanying high-$T_{\rm{c}}$ superconductivity. Investigation on the
evolution of the electronic structure with $T_{\rm{c}}$ is essential to
understanding electronic behavior and high-$T_{\rm{c}}$ superconductivity in
FeSe and its derived superconductors. In this report, we have found a series of
discrete superconducting phases, with a maximum $T_{\rm{c}}$ up to 44 K, in
H$^+$-intercalated FeSe single crystals using an ionic liquid gating method.
Accompanied with the increase of $T_{\rm{c}}$, suppression of the nematic phase
and evolution from non-Fermi-liquid to Fermi-liquid behavior was observed. An
abrupt change in the Fermi surface topology was proposed to explain the
discrete superconducting phases. A band structure that favors the
high-$T_{\rm{c}}$ superconducting phase was also revealed.


  We examine a commonly used relative poverty measure called the headcount
ratio ($H_p$), defined to be the proportion of incomes falling below the
relative poverty line, which is defined to be a fraction $p$ of the median
income. We do this by considering this concept for theoretical income
populations, and its potential for determining actual changes following
transfer of incomes from the wealthy to those whose incomes fall below the
relative poverty line. In the process we derive and evaluate the performance of
large sample confidence intervals for $H_p$. Finally, we illustrate the
estimators on real income data sets.


  In the present paper the resonances of vibrational modes in one-dimensional
random Morse lattice are found and analyzed. The resonance energy exchange is
observed at some values of elongation. Resonance $2 \omega_1 = \omega_2$ is
investigated in details. The interacting modes are inequivalent: the
higher-frequency mode is much more stable in the excited state, i.e. its
life-time is larger than the life-time of lower-frequency mode under the
resonance conditions. Simple model of two nonlinearly coupled harmonic
oscillators is also considered. It allows to get analytical description and to
investigate the kinetics and the energy exchange degree vs. such parameters as
the resonance detuning and specific energy. The very similar behavior is found
in the Morse and the two-oscillatory models, and an excellent agreement between
analytical and numerical results is obtained. Analogous resonance phenomena are
also found in the random Fermi-Pasta-Ulam lattice under contraction.


  Nowadays self-paced learning (SPL) is an important machine learning paradigm
that mimics the cognitive process of humans and animals. The SPL regime
involves a self-paced regularizer and a gradually increasing age parameter,
which plays a key role in SPL but where to optimally terminate this process is
still non-trivial to determine. A natural idea is to compute the solution path
w.r.t. age parameter (i.e., age-path). However, current age-path algorithms are
either limited to the simplest regularizer, or lack solid theoretical
understanding as well as computational efficiency. To address this challenge,
we propose a novel \underline{G}eneralized \underline{Ag}e-path
\underline{A}lgorithm (GAGA) for SPL with various self-paced regularizers based
on ordinary differential equations (ODEs) and sets control, which can learn the
entire solution spectrum w.r.t. a range of age parameters. To the best of our
knowledge, GAGA is the first exact path-following algorithm tackling the
age-path for general self-paced regularizer. Finally the algorithmic steps of
classic SVM and Lasso are described in detail. We demonstrate the performance
of GAGA on real-world datasets, and find considerable speedup between our
algorithm and competing baselines.


  There is a recent trend in machine learning to increase model quality by
growing models to sizes previously thought to be unreasonable. Recent work has
shown that autoregressive generative models with cross-entropy objective
functions exhibit smooth power-law relationships, or scaling laws, that predict
model quality from model size, training set size, and the available compute
budget. These scaling laws allow one to choose nearly optimal hyper-parameters
given constraints on available training data, model parameter count, or
training computation budget. In this paper, we demonstrate that acoustic models
trained with an auto-predictive coding loss behave as if they are subject to
similar scaling laws. We extend previous work to jointly predict loss due to
model size, to training set size, and to the inherent "irreducible loss" of the
task. We find that the scaling laws accurately match model performance over two
orders of magnitude in both model size and training set size, and make
predictions about the limits of model performance.


  This paper presents PARADISE (PARAdigm for DIalogue System Evaluation), a
general framework for evaluating spoken dialogue agents. The framework
decouples task requirements from an agent's dialogue behaviors, supports
comparisons among dialogue strategies, enables the calculation of performance
over subdialogues and whole dialogues, specifies the relative contribution of
various factors to performance, and makes it possible to compare agents
performing different tasks by normalizing for task complexity.


  Shape-invariant signals under the Discrete Fourier Transform are
investigated, leading to a class of eigenfunctions for the unitary discrete
Fourier operator. Such invariant sequences (eigensequences) are suggested as
user signatures over the real adder channel (t-RAC) and a multiuser
communication system over the t-RAC is presented.


  The dense depth estimation of a 3D scene has numerous applications, mainly in
robotics and surveillance. LiDAR and radar sensors are the hardware solution
for real-time depth estimation, but these sensors produce sparse depth maps and
are sometimes unreliable. In recent years research aimed at tackling depth
estimation using single 2D image has received a lot of attention. The deep
learning based self-supervised depth estimation methods from the rectified
stereo and monocular video frames have shown promising results. We propose a
self-attention based depth and ego-motion network for unrectified images. We
also introduce non-differentiable distortion of the camera into the training
pipeline. Our approach performs competitively when compared to other
established approaches that used rectified images for depth estimation.


  Starting with the heavy fermion compound CeNi$_9$Ge$_4$, the substitution of
nickel by copper leads to a dominance of the RKKY interaction in competition
with the Kondo and crystal field interaction. Consequently, this results in an
antiferromagnetic phase transition in CeNi$_{9-x}$Cu$_x$Ge$_4$ for $x>0.4$,
which is, however, not fully completed up to a Cu-concentration of $x=1$. To
study the influence of single-ion effects on the AFM ordering by shielding the
$4f$-moments, we analyzed the spin diluted substitution series
La$_{0.5}$Ce$_{0.5}$Ni$_{9-x}$Cu$_x$Ge$_4$ by magnetic susceptibility $\chi$
and specific heat $C$ measurements. For small Cu-amounts $x\leq 0.4$ the data
reveal single-ion scaling with regard to the Ce-concentration, while for larger
Cu-concentrations the AFM transition (encountered in the
CeNi$_{9-x}$Cu$_x$Ge$_4$ series) is found to be completely depressed.
Calculation of the entropy reveal that the Kondo-effect still shields the
4$f$-moments of the Ce$^{3+}$-ions in CeNi$_8$CuGe$_4$.


  To identify potential universal cellular automata, a method is developed to
measure information processing capacity of elementary cellular automata. We
consider two features of cellular automata: Ability to store information, and
ability to process information. We define local collections of cells as
particles of cellular automata and consider information contained by particles.
By using this method, information channels and channels' intersections can be
shown. By observing these two features, potential universal cellular automata
are classified into a certain class, and all elementary cellular automata can
be classified into four groups, which correspond to S. Wolfram's four classes:
1) Homogeneous; 2) Regular; 3) Chaotic and 4) Complex. This result shows that
using abilities of store and processing information to characterize complex
systems is effective and succinct. And it is found that these abilities are
capable of quantifying the complexity of systems.


  We recall the physical features of the parton distributions in the quantum
statistical approach of the nucleon. Some predictions from a next-to-leading
order QCD analysis are compared to recent experimental results. We also
consider their extension to include their transverse momentum dependence.


  We describe how surface interactions can affect the growth of ice crystal
facets in contact with a substrate by lowering the normal nucleation barrier on
the ice surface. We also describe how the resulting enhanced growth rates can
produce systematic errors even when measuring the growth of facets not
contacting the substrate. From an analysis of the diffusion dynamics we then
develop a simple procedure for approximately correcting ice growth data, thus
substantially reducing these systematic errors. We have found this technique to
be quite useful for interpreting ice growth data and extracting the intrinsic
attachment coefficients of ice surfaces.


  We report on the exploitation of the stellar content of the Hamburg/ESO
objective prism survey by quantitative selection methods, such as automatic
spectral classification, and first results obtained.


  A local luminosity function at 15$\mu m$ is derived using the bivariate
(15$\mu m$ vs. 60$\mu m$ luminosity) method, based on the newly published
ISOCAM LW3-band (15$\mu m$) survey of the very deep IRAS 60$\mu m$ sample in
the north ecliptic pole region (NEPR). New IRAS 60$\mu m$ fluxes are obtained
using the SCANPI/SUPERSCANPI software at the new ISOCAM positions of the
sources in the sample. It is found to be in excellent agreement with the 15$\mu
m$ local luminosity function published by Xu et al (1998), which is derived
from the {\it predicted} 15$\mu m$ luminosities of a sample of IRAS 25$\mu m$
selected galaxies. Model predictions of number counts and redshift
distributions based on the local luminosity function and assumptions of its
evolution with the redshift are calculated and compared with the data of ISOCAM
15$\mu m$ surveys. Strong luminosity evolution on the order of $L\propto
(1+z)^{4.5}$ is suggested in these comparisons, while pure density evolution
can be ruled out with high confidence. The sharp peak at about 0.4mJy in the
Euclidean normalized differential counts at 15$\mu m$ can be explained by the
effects of MIR broadband emission features, eliminating the need for any
hypothesis for a 'new population'. It is found that the contribution from the
population represented by ISOCAM 15$\mu m$ sources can account for the entire
IR/submm background, leaving little room for any missing 'new population' which
can be significant energy sources of the IR/submm sky.


  We study the 3d effective field theory of a weakly coupled two Higgs-doublet
scalar model at high temperature. Our model has three scalar quartic couplings
and an $O(4)$ symmetry which is spontaneously broken by a nonzero scalar field
$vev$ at zero temperature. Using high temperature perturbation theory,
renormalization group arguments in $4-\epsilon$ dimensions, as well as $1/N$
expansion techniques in 3 dimensions, we argue that the transition from the
high temperature symmetry restoring phase to the low temperature phase is first
order for a range of scalar couplings. This result is not due to gauge
couplings. We discuss the implications of our results for baryogenesis in the
two Higgs-doublet electroweak model, especially when the lightest neutral Higgs
is heavier than the W--bosons.


  With the increasing penetration of machine learning applications in critical
decision-making areas, calls for algorithmic fairness are more prominent.
Although there have been various modalities to improve algorithmic fairness
through learning with fairness constraints, their performance does not
generalize well in the test set. A performance-promising fair algorithm with
better generalizability is needed. This paper proposes a novel adaptive
reweighing method to eliminate the impact of the distribution shifts between
training and test data on model generalizability. Most previous reweighing
methods propose to assign a unified weight for each (sub)group. Rather, our
method granularly models the distance from the sample predictions to the
decision boundary. Our adaptive reweighing method prioritizes samples closer to
the decision boundary and assigns a higher weight to improve the
generalizability of fair classifiers. Extensive experiments are performed to
validate the generalizability of our adaptive priority reweighing method for
accuracy and fairness measures (i.e., equal opportunity, equalized odds, and
demographic parity) in tabular benchmarks. We also highlight the performance of
our method in improving the fairness of language and vision models. The code is
available at https://github.com/che2198/APW.


  Radiative decays of polarized Lambda_b baryons represent an attractive
possibility to measure the helicity of the photon emitted in the b --> s gamma
quark transition and thus to subject the Standard Model to a stringent test at
existing and future hadron colliders. The most abundant mode, Lambda(1116)
gamma, is experimentally very challenging because of the long decay length of
the Lambda(1116). We show that the experimentally more accessible Lambda_b -->
p K gamma decays proceeding via Lambda resonances may be used to extract the
photon helicity for sufficient Lambda_b polarization, if the resonance spin
does not exceed 3/2. A direct comparison of the potential of such resonance
decays to assess the photon polarization at a hadron collider with respect to
the decay to Lambda(1116) is given.


  Tables have been an ever-existing structure to store data. There exist now
different approaches to store tabular data physically. PDFs, images,
spreadsheets, and CSVs are leading examples. Being able to parse table
structures and extract content bounded by these structures is of high
importance in many applications. In this paper, we devise TableParser, a system
capable of parsing tables in both native PDFs and scanned images with high
precision. We have conducted extensive experiments to show the efficacy of
domain adaptation in developing such a tool. Moreover, we create TableAnnotator
and ExcelAnnotator, which constitute a spreadsheet-based weak supervision
mechanism and a pipeline to enable table parsing. We share these resources with
the research community to facilitate further research in this interesting
direction.


  According to the long-standing received wisdom, a "small" value of the Higgs
mass - as for instance implied by general unitarity constraints - is highly
"unnatural" and essentially $\mbox{requires}$ new physics to be present at or
near currently accessible energy scales. Following the discovery of a new,
Higgslike boson at the LHC facility in 2012, but with no sign of new physics
after having explored a large region of parameter space, a dilemma thus seems
to present itself : either the newly discovered boson is indeed the long-sought
Higgs boson of the standard model of particle physics (or some appropriate
variant of that model) and the new physics at the TeV scale, supposedly
required by the naturalness argument, is still waiting to be discovered,
possibly by LHC-II, or the identification of the new boson as the Higgs cannot
be maintained. It is shown that this apparent dilemma is in fact a false one,
in that nothing in contemporary particle physics dictates that a small Higgs
mass be unnatural in any way.


  In this paper, an agent-based modeling framework to evaluate the seismic
resilience of an integrated system comprising the community and its civil
infrastructure systems is proposed. Specifically, an agent-based model of the
recovery process of civil infrastructure systems is incorporated into a
previously developed compositional supply/demand seismic resilience
quantification framework. The proposed model represents the behavior of the
operators of civil infrastructure systems as they strive to recover their
functionality in the aftermath of an earthquake as well as their mutual
interactions and the interactions with the community they provide services to.
A case study of the seismic resilience of a virtual system comprising the
electric power supply system, the transportation system and the community
(EPSS-TS-Community system) is conducted using the proposed framework. A
parametric investigation is carried out to examine the effect of different
earthquake magnitude scenarios as well as different behaviors of the involved
agents and their interaction on the seismic resilience of the virtual system.
It was demonstrated that the proposed agent-based modeling approach is
effective in representing the interactions among different participants in the
recovery process. It was also revealed that timely and well-planned
intervention in the recovery process can be effective in alleviating the
post-earthquake lack of resilience resulting from the insufficient supply of
civil infrastructure service to meet the community demands. Therefore, the
proposed framework could be employed to formulate the recovery trajectory of
the intertwined socio-technical system subjected to different earthquake
scenarios. The interplay among different agents, as well as the interdependence
between civil infrastructure systems is found to profoundly shape the recovery
path for this integrated EPSS-TS-Community system.


  Within the framework of perturbative QCD factorization, we investigate the
nonfactorizable contributions to these factorization-forbidden Quasi-two-body
decays $B_{(s)}\rightarrow h\chi_{c0}\rightarrow h\pi^+\pi^-(K^+K^-)$ with $
h=\pi, K$. We compare our predicted branching ratios for the
$B_{(s)}\rightarrow K\chi_{c0}\rightarrow K\pi^+\pi^-(K^+K^-)$ decay with
available experiment data as well as predictions by other theoretical studies.
The branching ratios of these decays are consistent with data and other
theoretical predictions. In the Cabibbo-suppressed decays $B_{(s)}\rightarrow
h\chi_{c0}\rightarrow h\pi^+\pi^-(K^+K^-)$ with $h=\bar{K}^0,\pi$, however, the
values of the branching ratios are the order of $10^{-7}$ and $10^{-8}$. The
ratio $R_{\chi_{c0}}$ between the decay $B^+\rightarrow
\pi^+\chi_{c0}\rightarrow \pi^+\pi^+\pi^-$ and $B^+\rightarrow
K^+\chi_{c0}\rightarrow K^+\pi^+\pi^-$ and the distribution of branching ratios
for different decay modes in invariant mass are considered in this work.


  Right before Nolan's movie was released, I gave a talk on Oppenheimer, trying
to anticipate what elements of Bird and Sherwin's biography on which the movie
is based would make it into the movie. In this article, written for the October
2023 edition of the newsletter of the Forum on Science and Society of the APS,
I elaborate on some of the elements I missed. I used this article as the basis
for a post-movie version of my talk. I corrected some errors and made some
additions to this article before submitting it right before Nolan's movie is
expected to clean up at the Oscars (links to recordings of the pre- and
post-movie versions of my talk are included).


  The scattering cross section associated with a two dimensional delta function
has recently been the object of considerable study. It is shown here that this
problem can be put into a field theoretical framework by the construction of an
appropriate Galilean covariant theory. The Lee model with a standard Yukawa
interaction is shown to provide such a realization. The usual results for delta
function scattering are then obtained in the case that a stable particle exists
in the scattering channel provided that a certain limit is taken in the
relevant parameter space. In the more general case in which no such limit is
taken finite corrections to the cross section are obtained which (unlike the
pure delta function case) depend on the coupling constant of the model.


  The fractional inverse $M^{-\gamma}$ (real $\gamma >0$) of a matrix $M$ is
expanded in a series of Gegenbauer polynomials. If the spectrum of $M$ is
confined to an ellipse not including the origin, convergence is exponential,
with the same rate as for Chebyshev inversion. The approximants can be improved
recursively and lead to an iterative solver for $M^\gamma x = b$ in Krylov
space. In case of $\gamma = 1/2$, the expansion is in terms of Legendre
polynomials, and rigorous bounds for the truncation error are derived.


  The variance of (relative) surprisal, also known as varentropy, so far mostly
plays a role in information theory as quantifying the leading order corrections
to asymptotic i.i.d.~limits. Here, we comprehensively study the use of it to
derive single-shot results in (quantum) information theory. We show that it
gives genuine sufficient and necessary conditions for approximate
state-transitions between pairs of quantum states in the single-shot setting,
without the need for further optimization. We also clarify its relation to
smoothed min- and max-entropies, and construct a monotone for resource theories
using only the standard (relative) entropy and variance of (relative)
surprisal. This immediately gives rise to enhanced lower bounds for entropy
production in random processes. We establish certain properties of the variance
of relative surprisal which will be useful for further investigations, such as
uniform continuity and upper bounds on the violation of sub-additivity.
Motivated by our results, we further derive a simple and physically appealing
axiomatic single-shot characterization of (relative) entropy which we believe
to be of independent interest. We illustrate our results with several
applications, ranging from interconvertibility of ergodic states, over Landauer
erasure to a bound on the necessary dimension of the catalyst for catalytic
state transitions and Boltzmann's H-theorem.


  The complete electroweak O(alpha) corrections have been calculated for the
charged-current four-fermion production processes e+e- --> nu_tau tau+ mu-
anti-nu_mu, u anti-d mu- anti-nu_mu, and u anti-d s anti-c. Here, technical
details of this calculation are presented. These include the algebraic
reduction of spinor chains to a few standard structures and the consistent
implementation of the finite width of the W boson. To this end, a
generalization of the complex-mass scheme to the one-loop level is proposed,
and the practical application of this method is described. Finally, the effects
of the complete O(alpha) corrections to various differential cross sections of
physical interest are discussed and compared to predictions based on the
double-pole approximation, revealing that the latter approximation is not
sufficient to fully exploit the potential of a future linear collider in an
analysis of W-boson pairs at high energies.


  We present observations of 86 post-Asymptotic Giant Branch (post-AGB) stars
of OH maser transitions, taken with the Parkes Telescope between September 2002
and August 2003. Post-AGB stars are the precursors of planetary nebulae, which
have a wide range of morphologies that are not well explained. By studying the
circumstellar envelopes of post-AGB stars through the masers produced in them,
we hope to shed light on the origin of planetary nebula morphologies.


  This article contains a compression of results from alg-geom/9501001, with
most proofs omitted. We prove that every two points of the connected moduli
space of holomorphically symplectic manifolds can be connected with so-called
``twistor lines'' -- projective lines holomorphically embedded to the moduli
space and corresponding to the hyperk\"ahler structures. This has interesting
implications for the geometry of compact hyperk\"ahler manifolds and of
holomorphic vector bundles over such manifolds.


  A modification of the Fokker action is proposed, which allows one to
formulate the covariant quantum theory of the charge system, in which the
proper time of each particle serves as the evolution parameter and the
particles themselves receive an additional quantum number - spin. The
modification consists in adding to the Fokker action its variation generated by
the infinitesimal shifts of the proper time parameters. As a result, the proper
time parameters become observable at the quantum level.


  We propose the first joint-task learning framework for brain and vessel
segmentation (JoB-VS) from Time-of-Flight Magnetic Resonance images. Unlike
state-of-the-art vessel segmentation methods, our approach avoids the
pre-processing step of implementing a model to extract the brain from the
volumetric input data. Skipping this additional step makes our method an
end-to-end vessel segmentation framework. JoB-VS uses a lattice architecture
that favors the segmentation of structures of different scales (e.g., the brain
and vessels). Its segmentation head allows the simultaneous prediction of the
brain and vessel mask. Moreover, we generate data augmentation with adversarial
examples, which our results demonstrate to enhance the performance. JoB-VS
achieves 70.03% mean AP and 69.09% F1-score in the OASIS-3 dataset and is
capable of generalizing the segmentation in the IXI dataset. These results show
the adequacy of JoB-VS for the challenging task of vessel segmentation in
complete TOF-MRA images.


  UCLID5 is a tool for the multi-modal formal modeling, verification, and
synthesis of systems. It enables one to tackle verification problems for
heterogeneous systems such as combinations of hardware and software, or those
that have multiple, varied specifications, or systems that require hybrid modes
of modeling. A novel aspect of \uclid is an emphasis on the use of
syntax-guided and inductive synthesis to automate steps in modeling and
verification. This tool paper presents new developments in the \uclid tool
including new language features, integration with new techniques for
syntax-guided synthesis and satisfiability solving, support for hyperproperties
and combinations of axiomatic and operational modeling, demonstrations on new
problem classes, and a robust implementation.


  We study the superconductivity of strongly coupled electron-phonon systems
where the geometry of the lattice frustrates the charge order by the
sign-problem-free Quantum Monte Carlo(QMC) method. The results suggest that
with charge order frustrated, the superconductivity can benefit from strong
electron-phonon interaction in a wide range of coupling strengths.


  Based on a large sample of 133 Galactic globular clusters we obtained a new
estimate of the frequency of globular-cluster impacts onto the Galactic plane,
which we found to be equal to three events per 1 Myr. Our computations
involving new kinematical data do not support the well-known hypothesis about
the possible origin of the open cluster Stephenson~2 as a result of the massive
globular cluster $\omega$ Cen crossing the Galactic disk. Our results also do
not support the well-known hypothesis that the globular cluster NGC6397 could
trigger the formation of the open cluster NGC6231. We found for the first time
six globular clusters, which could have triggered the formation of an open
cluster when crossing the Galactic plane. These are the globular clusters
NGC104, NGC2808, NGC6362, NGC6540, NGC6749, and NGC6752. For each of these
clusters we identify one or several open clusters, which were possibly born via
such scenario. In our opinion, of greatest interest are the pairs
NGC104-Ruprecht 129, and NGC6362-Pismis 11.


  We numerically study the three-dimensional Edwards-Anderson model with
Gaussian couplings, focusing on the heterogeneities arising in its
nonequilibrium dynamics. Results are analyzed in terms of the backbone picture,
which links strong dynamical heterogeneities to spatial heterogeneities
emerging from the correlation of local rigidity of the bond network. Different
two-times quantities as the flipping time distribution and the correlation and
response functions, are evaluated over the full system and over high- and
low-rigidity regions. We find that the nonequilibrium dynamics of the model is
highly correlated to spatial heterogeneities. Also, we observe a similar
physical behavior to that previously found in the Edwards-Anderson model with a
bimodal (discrete) bond distribution. Namely, the backbone behaves as the main
structure that supports the spin-glass phase, within which a sort of
domain-growth process develops, while the complement remains in a paramagnetic
phase, even below the critical temperature.


  The prompt emission of the gamma-ray bursts is found to be very energetic,
releasing ~10^51 ergs in a flash. However, their emission mechanism remains
unclear and understanding their spectra is a key to determining the emission
mechanism. Many GRB spectra have been analyzed in the sub-MeV energy band, and
are usually well described with a smoothly broken power-law model. We present a
spectral analysis of two bright bursts (GRB910503 and GRB930506), using BATSE
and EGRET spectra that cover more than four decades of energy (30 keV - 200
MeV). Our results show time evolutions of spectral parameters (low-energy &
high-energy photon indices and break energy) that are difficult to reconcile
with a simple shock-acceleration model.


  In a spoofing attack, a malicious actor impersonates a legitimate user to
access or manipulate data without authorization. The vulnerability of
cryptographic security mechanisms to compromised user credentials motivates
spoofing attack detection in the physical layer, which traditionally relied on
channel features, such as the received signal strength (RSS) measured by
spatially distributed receivers or access points. However, existing methods
cannot effectively cope with the dynamic nature of channels, which change over
time as a result of user mobility and other factors. To address this
limitation, this work builds upon the intuition that the temporal pattern of
changes in RSS features can be used to detect the presence of concurrent
transmissions from multiple (possibly changing) locations, which in turn
indicates the existence of an attack. Since a localization-based approach would
require costly data collection and would suffer from low spatial resolution due
to multipath, the proposed algorithm employs a deep neural network to construct
a graph embedding of a sequence of RSS features that reflects changes in the
propagation conditions. A graph neural network then classifies these embeddings
to detect spoofing attacks. The effectiveness and robustness of the proposed
scheme are corroborated by experiments with real-data.


  We report a magnetic state in GaV$_4$Se$_8$ which emerges exclusively in
samples with mesoscale polar domains and not in polar mono-domain crystals. Its
onset is accompanied with a sharp anomaly in the magnetic susceptibility and
the magnetic torque, distinct from other anomalies observed also in polar
mono-domain samples upon transitions between the cycloidal, the N\'eel-type
skyrmion lattice and the ferromagnetic states. We ascribe this additional
transition to the formation of magnetic textures localized at structural domain
walls, where the magnetic interactions change stepwise and spin textures with
different spiral planes, hosted by neighbouring domains, need to be matched. A
clear anomaly in the magneto-current indicates that the domain-wall-confined
magnetic states also have strong contributions to the magnetoelectric response.
We expect polar domain walls to commonly host such confined magnetic edge
states, especially in materials with long wavelength magnetic order.


  In this paper we investigated the possibility to use the magnetic Laplacian
to characterize directed graphs (a.k.a. networks). Many interesting results are
obtained, including the finding that community structure is related to
rotational symmetry in the spectral measurements for a type of stochastic block
model. Due the hermiticity property of the magnetic Laplacian we show here how
to scale our approach to larger networks containing hundreds of thousands of
nodes using the Kernel Polynomial Method (KPM). We also propose to combine the
KPM with the Wasserstein metric in order to measure distances between networks
even when these networks are directed, large and have different sizes, a hard
problem which cannot be tackled by previous methods presented in the
literature. In addition, our python package is publicly available at
\href{https://github.com/stdogpkg/emate}{github.com/stdogpkg/emate}. The codes
can run in both CPU and GPU and can estimate the spectral density and related
trace functions, such as entropy and Estrada index, even in directed or
undirected networks with million of nodes.


  If the universe was reionized by O and B stars in an early population of
galaxies, the associated supernovae should have enriched the universe to a mean
metallicity $\bar Z = 10^{-5} (1+ n_{rec})$, where $n_{rec}$ is the mean number
of times that each baryon recombined during the reionization era. This is
consistent with recent observations of the metallicity in the Lya forest at
$z\simeq 3$. The mean surface brightness observable at present from the
galaxies that produced these heavy elements, in the rest-frame wavelengths
$1216\AA < \lambda \lesssim 2500\AA$, should be $\sim 10^{-6} (\bar Z/10^{-4})
(\Omega_b h^2/0.02) ~ photons \cm^{-2} s^{-1} arcsec^{-2}$. Most of this
radiation was emitted at $z>5$, before reionization was complete. These
high-redshift galaxies may be detectable in near-infrared photometric surveys,
identifying them via the Gunn-Peterson trough (analogous to the use of the
Lyman limit cutoff to search for galaxies at $z\sim 3$, where the Lya forest
blanketing is smaller). Their spectrum may also be characterized by a strong
Lya emission line. However, the spectra of galaxies seen behind intervening gas
that is still neutral should show the red damping wing of the Gunn-Peterson
trough, with a predictable profile that obstructs part of the Lya emission. The
low-mass galaxies formed before reionization might constitute a distinctive
population; we discuss the signature that this population could have in the
faint number counts. Although most of these galaxies should have merged into
larger ones, those that survived to the present could be dwarf spheroidals.


  SQL queries, with the AND, OR, and NOT operators, constitute a broad class of
highly used queries. Thus, their cardinality estimation is important for query
optimization. In addition, a query planner requires the set-theoretic
cardinality (i.e., without duplicates) for queries with DISTINCT as well as in
planning; for example, when considering sorting options. Yet, despite the
importance of estimating query cardinalities in the presence of DISTINCT, AND,
OR, and NOT, many cardinality estimation methods are limited to estimating
cardinalities of only conjunctive queries with duplicates counted.
  The focus of this work is on two methods for handling this deficiency that
can be applied to any limited cardinality estimation model. First, we describe
a specialized deep learning scheme, PUNQ, which is tailored to representing
conjunctive SQL queries and predicting the percentage of unique rows in the
query's result with duplicate rows. Using the predicted percentages obtained
via PUNQ, we are able to transform any cardinality estimation method that only
estimates for conjunctive queries, and which estimates cardinalities with
duplicates (e.g., MSCN), to a method that estimates queries cardinalities
without duplicates. This enables estimating cardinalities of queries with the
DISTINCT keyword. In addition, we describe a recursive algorithm, GenCrd, for
extending any cardinality estimation method M that only handles conjunctive
queries to one that estimates cardinalities for more general queries (that
include AND, OR, and NOT), without changing the method M itself.
  Our evaluation is carried out on a challenging, real-world database with
general queries that include either the DISTINCT keyword or the AND, OR, and
NOT operators. Experimentally, we show that the proposed methods obtain
accurate cardinality estimates with the same level of accuracy as that of the
original transformed methods.


  We discuss the general structure of metric geometries, and how metricity
implies the complete antisymmetry of Cartan tensor; an application in the frame
of Lie group theory is given. Interpretations of the completely antisymmetric
torsion in physical models are reviewed.


  We present the first high-resolution X-ray spectrum of a putatively single
Wolf-Rayet star. 400 ks observations of WR 6 by the XMM-Newton-telescope
resulted in a superb quality high-resolution X-ray spectrum. Spectral analysis
reveals that the X-rays originate far out in the stellar wind, more than 30
stellar radii from the photosphere, and thus outside the wind acceleration zone
where the line-driving instability could create shocks. The X-ray emitting
plasma reaches temperatures up to 50\,MK, and is embedded within the
un-shocked, "cool" stellar wind as revealed by characteristic spectral
signatures. We detect a fluorescent Fe line at approx 6.4 keV. The presence of
fluorescence is consistent with a two-component medium, where the cool wind is
permeated with the hot X-ray emitting plasma. The wind must have a very porous
structure to allow the observed amount of X-rays to escape. We find that
neither the line-driving instability nor any alternative binary scenario can
explain the data. We suggest a scenario where X-rays are produced when the fast
wind rams into slow "sticky clumps" that resist acceleration. Our new data show
that the X-rays in single WR-star are generated by some special mechanism
different from the one operating in the O-star winds.


  We have investigated structural and magnetic phase transitions under high
pressures in a quaternary rare earth transition metal arsenide oxide NdCoAsO
compound that is isostructural to high temperature superconductor NdFeAsO.
Four-probe electrical resistance measurements carried out in a designer diamond
anvil cell show that the ferromagnetic Curie temperature and anti-ferromagnetic
Neel temperature increase with an increase in pressure. High pressure x-ray
diffraction studies using a synchrotron source show a structural phase
transition from a tetragonal phase to a new crystallographic phase at a
pressure of 23 GPa at 300 K. The NdCoAsO sample remained anti-ferromagnetic and
non-superconducting to temperatures down to 10 K and to the highest pressure
achieved in this experiment of 53 GPa. A P-T phase diagram for NdCoAsO is
presented to a pressure of 53 GPa and low temperatures of 10 K.


  The k-sample testing problem involves determining whether $k$ groups of data
points are each drawn from the same distribution. The standard method for
k-sample testing in biomedicine is Multivariate analysis of variance (MANOVA),
despite that it depends on strong, and often unsuitable, parametric
assumptions. Moreover, independence testing and k-sample testing are closely
related, and several universally consistent high-dimensional independence tests
such as distance correlation (Dcorr) and Hilbert-Schmidt-Independence-Criterion
(Hsic) enjoy solid theoretical and empirical properties. In this paper, we
prove that independence tests achieve universally consistent k-sample testing
and that k-sample statistics such as Energy and Maximum Mean Discrepancy (MMD)
are precisely equivalent to Dcorr. An empirical evaluation of nonparametric
independence tests showed that they generally perform better than the popular
MANOVA test, even in Gaussian distributed scenarios. The evaluation included
several popular independence statistics and covered a comprehensive set of
simulations. Additionally, the testing approach was extended to perform
multiway and multilevel tests, which were demonstrated in a simulated study as
well as a real-world fMRI brain scans with a set of attributes.


  It is possible that powerful and potentially dangerous artificial
intelligence (AI) might be developed in the future. An Oracle is a design which
aims to restrain the impact of a potentially dangerous AI by restricting the
agent to no actions besides answering questions. Unfortunately, most Oracles
will be motivated to gain more control over the world by manipulating users
through the content of their answers, and Oracles of potentially high
intelligence might be very successful at this
\citep{DBLP:journals/corr/AlfonsecaCACAR16}. In this paper we present two
designs for Oracles which, even under pessimistic assumptions, will not
manipulate their users into releasing them and yet will still be incentivised
to provide their users with helpful answers. The first design is the
counterfactual Oracle -- which choses its answer as if it expected nobody to
ever read it. The second design is the low-bandwidth Oracle -- which is limited
by the quantity of information it can transmit.


  An automaton is partially ordered if the only cycles in its transition
diagram are self-loops. The expressivity of partially ordered NFAs (poNFAs) can
be characterized by the Straubing-Th\'erien hierarchy. Level 3/2 is recognized
by poNFAs, level 1 by confluent, self-loop deterministic poNFAs as well as by
confluent poDFAs, and level 1/2 by saturated poNFAs. We study the universality
problem for confluent, self-loop deterministic poNFAs. It asks whether an
automaton accepts all words over its alphabet. Universality for both NFAs and
poNFAs is a PSpace-complete problem. For confluent, self-loop deterministic
poNFAs, the complexity drops to coNP-complete if the alphabet is fixed but is
open if the alphabet may grow. We solve this problem by showing that it is
PSpace-complete if the alphabet may grow polynomially. Consequently, our result
provides a lower-bound complexity for some other problems, including inclusion,
equivalence, and $k$-piecewise testability. Since universality for saturated
poNFAs is easy, confluent, self-loop deterministic poNFAs are the simplest and
natural kind of NFAs characterizing a well-known class of languages, for which
deciding universality is as difficult as for general NFAs.


  Using the representation theory of Yangians we construct the rational
R-matrix which takes values in the adjoint representation of SU(n). From this
we derive an integrable SU(n) spin chain with lattice spins transforming under
the adjoint representation. However, the resulting Hamiltonian is found to be
non-Hermitian.


  Unlike conventional frame-based sensors, event-based visual sensors output
information through spikes at a high temporal resolution. By only encoding
changes in pixel intensity, they showcase a low-power consuming, low-latency
approach to visual information sensing. To use this information for higher
sensory tasks like object recognition and tracking, an essential simplification
step is the extraction and learning of features. An ideal feature descriptor
must be robust to changes involving (i) local transformations and (ii)
re-appearances of a local event pattern. To that end, we propose a novel
spatiotemporal feature representation learning algorithm based on slow feature
analysis (SFA). Using SFA, smoothly changing linear projections are learnt
which are robust to local visual transformations. In order to determine if the
features can learn to be invariant to various visual transformations, feature
point tracking tasks are used for evaluation. Extensive experiments across two
datasets demonstrate the adaptability of the spatiotemporal feature learner to
translation, scaling and rotational transformations of the feature points. More
importantly, we find that the obtained feature representations are able to
exploit the high temporal resolution of such event-based cameras in generating
better feature tracks.


  In "IP-sets and polynomial recurrence", Bergelson, Furstenberg, and
McCutcheon established the following far reaching extension of Khintchine's
recurrence theorem:
  For any invertible probability preserving system $(X,\mathcal A,\mu,T)$, any
non-constant polynomial $p\in\mathbb Z[x]$ with $p(0)=0$, any $A\in\mathcal A$,
and any $\epsilon>0$, the set $$R_\epsilon^p(A)=\{n\in\mathbb N\,|\,\mu(A\cap
T^{-p(n)}A)>\mu^2(A)-\epsilon\}$$ is IP$^*$, meaning that for any increasing
sequence $(n_k)_{k\in\mathbb N}$ in $\mathbb N$, $$\text{FS}((n_k)_{k\in\mathbb
N})\cap R_\epsilon^p(A)\neq \emptyset,$$ where $$\text{FS}((n_k)_{k\in\mathbb
N})=\{\sum_{j\in F}n_j\,|\,F\subseteq \mathbb N\,\text{ is finite}\text{ and
}F\neq\emptyset\}=\{n_{k_1}+\cdots+n_{k_t}\,|\,k_1<\cdots<k_t,\,t\in\mathbb
N\}.$$ In view of the potential new applications to combinatorics, this result
has led to the question of whether a further strengthening of Khintchine's
recurrence theorem holds, namely whether the set $R_\epsilon^p(A)$ is IP$_0^*$
meaning that there exists a $t\in\mathbb N$ such that for any finite sequence
$n_1<\cdots<n_t$ in $\mathbb N$, $$\{\sum_{j\in F}n_j\,|\,F\subseteq
\{1,...,t\}\text{ and }F\neq \emptyset\}\cap R_\epsilon^p(A)\neq \emptyset.$$
In this paper we give a negative answer to this question by showing that for
any given polynomial $p\in\mathbb Z[x]$ with deg$(p)>1$ and $p(0)=0$ there is
an invertible probability preserving system $(X,\mathcal A,\mu,T)$, a set
$A\in\mathcal A$, and an $\epsilon>0$ for which the set $R_\epsilon^p(A)$ is
not IP$_0^*$.


  Simulations of galaxy growth need to invoke strong negative feedback from
active galactic nuclei (AGN) to suppress the formation of stars and thus
prevent the over-production of very massive systems. While some observations
provide evidence for such negative feedback, other studies find either no
feedback, or even positive feedback, with increased star formation associated
with higher AGN luminosities. Here we report an analysis of several hundred AGN
and their host galaxies in the Chandra Deep Field South using X-ray and radio
data for sample selection. Combined with archival far infrared data as a
reliable tracer of star formation activity in the AGN host galaxies, we find
that AGN with pronounced radio jets exhibit a much higher star formation rate
than the purely X-ray selected ones, even at the same X-ray luminosities. This
difference implies that positive AGN feedback plays an important role, too, and
therefore has to be accounted for in all future simulation work. We interpret
this to indicate that the enhanced star formation rate of radio selected AGN
arises because of jet-induced star formation, as is hinted by the different jet
powers among our AGN samples, while the suppressed star formation rate of X-ray
selected AGN is caused by heating and photo-dissociation of molecular gas by
the hot AGN accretion disc.


  We present results from a campaign of multiple epoch echelle spectroscopy of
relatively faint (V = 9.5-13.5 mag) red giants observed as potential
astrometric grid stars for the Space Interferometry Mission (SIM PlanetQuest).
Data are analyzed for 775 stars selected from the Grid Giant Star Survey
spanning a wide range of effective temperatures (Teff), gravities and
metallicities. The spectra are used to determine these stellar parameters and
to monitor radial velocity (RV) variability at the 100 m/s level. The degree of
RV variation measured for 489 stars observed two or more times is explored as a
function of the inferred stellar parameters. The percentage of radial velocity
unstable stars is found to be very high -- about 2/3 of our sample. It is found
that the fraction of RV-stable red giants (at the 100 m/s level) is higher
among stars with Teff \sim 4500 K, corresponding to the calibration-independent
range of infrared colors 0.59 < (J-K_s)_0 < 0.73. A higher percentage of
RV-stable stars is found if the additional constraints of surface gravity and
metallicity ranges 2.3< log g < 3.2 and -0.5 < [Fe/H] < -0.1, respectively, are
applied. Selection of stars based on only photometric values of effective
temperature (4300 K < Teff < 4700 K) is a simple and effective way to increase
the fraction of RV-stable stars. The optimal selection of RV-stable stars,
especially in the case when the Washington photometry is unavailable, can rely
effectively on 2MASS colors constraint 0.59 < (J-K_s)_0 < 0.73. These results
have important ramifications for the use of giant stars as astrometric
references for the SIM PlanetQuest.


  Health insurance companies in Brazil have their data about claims organized
having the view only for providers. In this way, they loose the physician view
and how they share patients. Partnership between physicians can view as a
fruitful work in most of the cases but sometimes this could be a problem for
health insurance companies and patients, for example a recommendation to visit
another physician only because they work in same clinic. The focus of the work
is to better understand physicians activities and how these activities are
represented in the data. Our approach considers three aspects: the
relationships among physicians, the relationships between physicians and
patients, and the relationships between physicians and health providers. We
present the results of an analysis of a claims database (detailing 18 months of
activity) from a large health insurance company in Brazil. The main
contribution presented in this paper is a set of models to represent: mutual
referral between physicians, patient retention, and physician centrality in the
health insurance network. Our results show the proposed models based on social
network frameworks, extracted surprising insights about physicians from real
health insurance claims data.