  We investigate Choptuik scaling in the spherically symmetric collapse of a
massless scalar field in higher dimensions using Painleve-Gullstrand (P-G)
coordinates. Our analysis confirms the presence in higher dimensions of the
cusps in the periodic scaling relationship recently observed in four
dimensional collapse. In addition, we address the issue of the asymptotic
behaviour of the critical exponent as the number of spacetime dimensions gets
large. Our results are consistent with earlier work suggesting that the
critical exponent monotonically approaches 1/2 in this limit.


  Neural Radiance Fields (NeRFs) have made great success in representing
complex 3D scenes with high-resolution details and efficient memory.
Nevertheless, current NeRF-based pose estimators have no initial pose
prediction and are prone to local optima during optimization. In this paper, we
present LATITUDE: Global Localization with Truncated Dynamic Low-pass Filter,
which introduces a two-stage localization mechanism in city-scale NeRF. In
place recognition stage, we train a regressor through images generated from
trained NeRFs, which provides an initial value for global localization. In pose
optimization stage, we minimize the residual between the observed image and
rendered image by directly optimizing the pose on tangent plane. To avoid
convergence to local optimum, we introduce a Truncated Dynamic Low-pass Filter
(TDLF) for coarse-to-fine pose registration. We evaluate our method on both
synthetic and real-world data and show its potential applications for
high-precision navigation in large-scale city scenes. Codes and data will be
publicly available at https://github.com/jike5/LATITUDE.


  A great deal of effort has been recently devoted to the study of dielectric
relaxation processes in ferroelectric nematic liquid crystals, yet their
interpretation remains unclear. In this work, we present the results of
broadband dielectric spectroscopy experiments of a prototypical ferroelectric
nematogen in the frequency range 10 Hz-110 MHz at different electrode
separations and under the application of DC bias fields. The results evidence a
complex behavior in all phases due to the magnitude of polar correlations in
these systems. The observed modes have been assigned to different relaxation
mechanisms based on existing theoretical frameworks.


  For robots to assist users with household tasks, they must first learn about
the tasks from the users. Further, performing the same task every day, in the
same way, can become boring for the robot's user(s), therefore, assistive
robots must find creative ways to perform tasks in the household. In this
paper, we present a cognitive architecture for a household assistive robot that
can learn personalized breakfast options from its users and then use the
learned knowledge to set up a table for breakfast. The architecture can also
use the learned knowledge to create new breakfast options over a longer period
of time. The proposed cognitive architecture combines state-of-the-art
perceptual learning algorithms, computational implementation of cognitive
models of memory encoding and learning, a task planner for picking and placing
objects in the household, a graphical user interface (GUI) to interact with the
user and a novel approach for creating new breakfast options using the learned
knowledge. The architecture is integrated with the Fetch mobile manipulator
robot and validated, as a proof-of-concept system evaluation in a large indoor
environment with multiple kitchen objects. Experimental results demonstrate the
effectiveness of our architecture to learn personalized breakfast options from
the user and generate new breakfast options never learned by the robot.


  We discuss the growing interest to measure associated-quarkonium production
in a number of channels at the LHC. Whereas back-to-back production of
quarkonium + isolated photon provides a unique way to extract gluon TMDs,
observables such as quarkonium + W/Z can be of great help to better understand
the quarkonium production mechanism as well as to shed light on double-parton
scatterings. Along these lines, we also argue that quarkonium-pair production
is a potentially rich source of information which only has started to be
harvested. Finally, we discuss the relevance of studying the production of
quarkonium + heavy-quark, as e.g. J/psi + charm and Upsilon + non-prompt J/psi.


  This is the first of a set of papers having the aim to provide a detailed
description of brane configurations on a family of noncompact threedimensional
Calabi-Yau manifolds. The starting point is the singular manifold C^3/Z_6,
which admits five distinct crepant resolutions. Here we apply local mirror
symmetry to partially determine the prepotential encoding the GW-invariants of
the resolved varieties. It results that such prepotential provides all numbers
but the ones corresponding to curves having null intersection with the compact
divisor. This is realized by means of a conjecture, due to S. Hosono, so that
our results provide a check confirming at least in part the conjecture.


  Power flow calculations for systems with a large number of buses, e.g. grids
with multiple voltage levels, or time series based calculations result in a
high computational effort. A common power flow solver for the efficient
analysis of power systems is the Newton-Raphson algorithm. The main
computational effort of this method results from the linearization of the
nonlinear power flow problem and solving the resulting linear equation. This
paper presents an algorithm for the fast linearization of the power flow
problem by creating the Jacobian matrix directly in CRS format. The increase in
speed is achieved by reducing the number of iterations over the nonzero
elements of the sparse Jacobian matrix. This allows to efficiently create the
Jacobian matrix without having to approximate the problem. A comparison of the
calculation time of three power grids shows that comparable open-source
implementations need 3-14x the time to create the Jacobian matrix.


  In a recent model Choudhury proposed that a collapsing matter generates an
adiabatic pressure which can be used to explain the acceleration of the
physical universe under certain approximation. In this work we superimpose the
core pressure generated through the entropy of the blackhole. We have ignored
the blackhole internal energy change during this process. We have then
calculated both Hubble parameter and the deacceleration parameter. We have
shown that the Hubble parameter is positive and the deacceleration parameter
fluctuates with time, meaning for certain period the universe accelerates and
decelerates for other time.


  Detecting people in images is a challenging problem. Differences in pose,
clothing and lighting, along with other factors, cause a lot of variation in
their appearance. To overcome these issues, we propose a system based on fused
range and thermal infrared images. These measurements show considerably less
variation and provide more meaningful information. We provide a brief
introduction to the sensor technology used and propose a calibration method.
Several data fusion algorithms are compared and their performance is assessed
on a simulated data set. The results of initial experiments on real data are
analyzed and the measurement errors and the challenges they present are
discussed. The resulting fused data are used to efficiently detect people in a
fixed camera set-up. The system is extended to include person tracking.


  An energy-limited source trying to transmit multiple packets to a destination
with possibly different sizes is considered. With limited energy, the source
cannot potentially transmit all bits of all packets. In addition, there is a
delay cost associated with each packet. Thus, the source has to choose, how
many bits to transmit for each packet, and the order in which to transmit these
bits, to minimize the cost of distortion (introduced by transmitting lower
number of bits) and queueing plus transmission delay, across all packets.
Assuming an exponential metric for distortion loss and linear delay cost, we
show that the optimization problem is jointly convex. Hence, the problem can be
exactly solved using convex solvers, however, because of the complicated
expression derived from the KKT conditions, no closed form solution can be
found even with the simplest cost function choice made in the paper, also the
optimal order in which packets should be transmitted needs to be found via
brute force. To facilitate a more structured solution, a discretized version of
the problem is also considered, where time and energy are divided in discrete
amounts. In any time slot (fixed length), bits belonging to any one packet can
be transmitted, while any discrete number of energy quanta can be used in any
slot corresponding to any one packet, such that the total energy constraint is
satisfied. The discretized problem is a special case of a multi-partitioning
problem, where each packet's utility is super-modular and the proposed greedy
solution is shown to incur cost that is at most $2$-times of the optimal cost.


  We discuss the short-time behavior of the majority vote dynamics on
scale-free networks at the critical threshold. We introduce a heterogeneous
mean-field theory on the critical short-time behavior of the majority-vote
model on scale-free networks. In addition, we also compare the heterogeneous
mean-field predictions with extensive Monte Carlo simulations of the short-time
dependencies of the order parameter and the susceptibility. We obtained a
closed expression for the dynamical exponent $z$ and the time correlation
exponent $\nu_\parallel$. Short-time scaling is compatible with a non-universal
critical behavior for $5/2 < \gamma < 7/2$, and for $\gamma \geq 7/2$, we have
the mean-field Ising criticality with additional logarithmic corrections for
$\gamma=7/2$, in the same way as the stationary scaling.


  Resistivity saturation is observed in many metallic systems with a large
resistivity, i.e., when the resistivity has reached a critical value, its
further increase with temperature is substantially reduced. This typically
happens when the apparent mean free path is comparable to the interatomic
separations - the Ioffe-Regel condition. Recently, several exceptions to this
rule have been found. Here, we review experimental results and early theories
of resistivity saturation. We then describe more recent theoretical work,
addressing cases both where the Ioffe-Regel condition is satisfied and where it
is violated. In particular we show how the (semiclassical) Ioffe-Regel
condition can be derived quantum-mechanically under certain assumptions about
the system and why these assumptions are violated for high-Tc cuprates and
alkali-doped fullerides.


  This paper studies the Degrees of Freedom (DoF) of the two-user multi-antenna
Gaussian interference channel with an {\em instantaneous relay}, or relay
without delay, where the relay transmitted signal in channel use $t$ can depend
on all received signals up to and including that at channel use $t$. It is
assumed that the two transmitters and the two receivers have $M$ antennas,
while the relay receives through $N$ antennas and transmits through $L$
antennas. An achievable DoF region is derived, for all possible values of
$(M,N,L)$, based on a memoryless linear transmission strategy at the relay that
aims to {\it neutralize} as much interference as possible at the receivers. The
proposed scheme is shown to attain the largest sum DoF among all memoryless
linear transmission strategies at the relay and to actually be optimal for
certain values of $(M,N,L)$.


  This paper describes the reclassification of DK And, formerly classified as a
RRc type star, as EW binary. 1599 CCD unfiltered and filtered (V and R band)
observations between 1999 and 2005 show, that the star is actually an eclipsing
binary star with a period of P = 0.4892224 +/- 0.0000002 [d] with epoch E0 =
2451435.4353 +/- 0.0010 (if all historic data were taken into account). From
our new observations 12 timings of minimum light are given.


  We consider statistical models driven by Gaussian and non-Gaussian
self-similar processes with long memory and we construct maximum likelihood
estimators (MLE) for the drift parameter. Our approach is based on the
approximation by random walks of the driving noise. We study the asymptotic
behavior of the estimators and we give some numerical simulations to illustrate
our results.


  In a one-dimensional lattice, the induced metric (from a noncommutative
geometry calculation) breaks translation invariance. This leads to some
inconsistencies among different spectator frames, in the observation of the
hoppings of a test particle between lattice sites. To resolve the
inconsistencies between the different spectator frames, we replace the test
particle's bare mass by an effective locally dependent mass. This effective
mass also depends on the lattice constant - i.e. it is a scale dependent
variable (a "running" mass). We also develop an alternative approach based on a
compensating potential. The induced potential between a spectator frame and the
test particle is attractive on the average. We then show that the entire
formalism holds for a quantum particle represented by a wave function, just as
it applies to the mechanics of a classical point particle.


  A fundamental quantity of interest in Shannon theory, classical or quantum,
is the error exponent of a given channel $W$ and rate $R$: the constant
$E(W,R)$ which governs the exponential decay of decoding error when using ever
larger optimal codes of fixed rate $R$ to communicate over ever more
(memoryless) instances of a given channel $W$. Nearly matching lower and upper
bounds are well-known for classical channels. Here I show a lower bound on the
error exponent of communication over arbitrary classical-quantum (CQ) channels
which matches Dalai's sphere-packing upper bound [IEEE TIT 59, 8027 (2013)] for
rates above a critical value, exactly analogous to the case of classical
channels. This proves a conjecture made by Holevo in his investigation of the
problem [IEEE TIT 46, 2256 (2000)].
  Unlike the classical case, however, the argument does not proceed via a
refined analysis of a suitable decoder, but instead by leveraging a bound by
Hayashi on the error exponent of the cryptographic task of privacy
amplification [CMP 333, 335 (2015)]. This bound is then related to the coding
problem via tight entropic uncertainty relations and Gallager's method of
constructing capacity-achieving parity-check codes for arbitrary channels.
Along the way, I find a lower bound on the error exponent of the task of
compression of classical information relative to quantum side information that
matches the sphere-packing upper bound of Cheng et al. [IEEE TIT 67, 902
(2021)]. In turn, the polynomial prefactors to the sphere-packing bound found
by Cheng et al. may be translated to the privacy amplification problem,
sharpening a recent result by Li, Yao, and Hayashi [IEEE TIT 69, 1680 (2023)],
at least for linear randomness extractors.


  Cephalometric tracing method is usually used in orthodontic diagnosis and
treatment planning. In this paper, we propose a deep learning based framework
to automatically detect anatomical landmarks in cephalometric X-ray images. We
train the deep encoder-decoder for landmark detection, and combine global
landmark configuration with local high-resolution feature responses. The
proposed frame-work is based on 2-stage u-net, regressing the multi-channel
heatmaps for land-mark detection. In this framework, we embed attention
mechanism with global stage heatmaps, guiding the local stage inferring, to
regress the local heatmap patches in a high resolution. Besides, the Expansive
Exploration strategy improves robustness while inferring, expanding the
searching scope without increasing model complexity. We have evaluated our
framework in the most widely-used public dataset of landmark detection in
cephalometric X-ray images. With less computation and manually tuning, our
framework achieves state-of-the-art results.


  We present an analysis of the X-ray properties of 35 submm galaxies(SMGs) in
the CDF-N. Using a sample of robust 850micron-selected galaxies, with accurate
positions from Spitzer and/or radio counterparts, we find 16 objects (45+/-8%)
with significant X-ray detections in the 2Ms Chandra data. 6 of these SMGs
(~17+/-6%) have measured X-ray luminosities or upper limits consistent with
those expected based on the far-infrared (FIR) or radio-derived star formation
rate (SFR), and hence with the X-rays coming solely from star formation. In
another 7 sources (20+/-7%) a dominant AGN contribution to the X-ray emission
is required, while in 3 more it is unclear whether stellar process or accretion
are responsible. Stacking of the X-ray undetected SMGs reveals a highly
significant detection. If due to star formation, this corresponds to an average
X-ray derived SFR of ~150 Msun/yr. We deduce that the AGN fraction in SMGs
based on X-ray observations is 20-29 (+/-7) %, which is towards the lower limit
of previous estimates. Spectral analysis shows that in general the SMGs are not
heavily obscured in the X-ray but most of the SMGs classfied as AGN show
absorption with N_H in excess of 10^22 cm^-2. Of the secure AGN, the bolometric
luminosity appears to be dominated by the AGN in only 3 cases. In ~85% of the
SMGs, the X-ray spectrum effectively rules out an AGN contribution that
dominates the bolometric emission, even if the AGN is Compton thick. The
evidence therefore suggests that intense star formation accounts for both the
FIR and X-ray emission in most SMGs. We argue that, rather than having an
especially high AGN fraction or duty cycle, SMGs have a high X-ray detection
rate at very faint fluxes partly because of their high star formation rates
and, in rarer cases, because the submm emission is from an AGN.(abridged)


  We present an evidence of isospin effects in nuclear fission by comparing the
fission widths for reactions involving different isospin states of the same
compound nucleus (CN). Yadrovsky suggested this possibility in 1975. Yadrovsky
obtained the fission widths for two reaction data sets, namely
$^{206}$Pb($\alpha$,f) and $^{209}$Bi(p,f), both leading to same CN, and
concluded that "a nucleus remembers the isospin value of the nuclear states
leading to fission". We obtain the fission decay widths for both the $T_0+1/2$
and $T_0-1/2$ states of CN by using two appropriate reaction data sets. We then
compare the fission widths for the two isospin states of CN. More specifically,
we have chosen the combination of $^{206}$Pb($\alpha$,f) and $^{209}$Bi(p,f)
same as presented in Yadrovsky's paper and $^{235}$U(d,f) and $^{236}$U(p,f)
reaction data sets in this study. A significant difference between the ratios
of fission decay widths to total decay widths for different isospin values
suggests that isospin plays an important role in fission.


  Visual-only speech recognition is dependent upon a number of factors that can
be difficult to control, such as: lighting; identity; motion; emotion and
expression. But some factors, such as video resolution are controllable, so it
is surprising that there is not yet a systematic study of the effect of
resolution on lip-reading. Here we use a new data set, the Rosetta Raven data,
to train and test recognizers so we can measure the affect of video resolution
on recognition accuracy. We conclude that, contrary to common practice,
resolution need not be that great for automatic lip-reading. However it is
highly unlikely that automatic lip-reading can work reliably when the distance
between the bottom of the lower lip and the top of the upper lip is less than
four pixels at rest.


  We consider the 3D Landau equation for moderately soft potentials
($\gamma\in(-2,0)$ with the usual notation) as well as a stochastic system of
$N$ particles approximating it. We first establish some strong/weak stability
estimates for the Landau equation, which are satisfying only when $\gamma \in
[-1,0)$. We next prove, under some appropriate conditions on the initial data,
the so-called propagation of molecular chaos, i.e. that the empirical measure
of the particle system converges to the unique solution of the Landau equation.
The main difficulty is the presence of a singularity in the equation. When
$\gamma \in (-1,0)$, the strong-weak uniqueness estimate allows us to use a
coupling argument and to obtain a rate of convergence. When $\gamma \in
(-2,-1]$, we use the classical martingale method introduced by McKean. To
control the singularity, we have to take advantage of the regularity provided
by the entropy dissipation. Unfortunately, this dissipation is too weak for
some (very rare) aligned configurations. We thus introduce a perturbed system
with an additional noise, show the propagation of chaos for that perturbed
system and finally prove that the additional noise is almost never used in the
limit.


  In this paper, we consider a translating soliton for the mean curvature flow
starting from a graph of a function on a domain in a unit sphere which is
constant along each leaf of isoparametric foliation. First, we show that such a
function is given as a composition of an isoparametric function on the sphere
and a function which is given as a solution of a certain ordinary differential
equation. Further, we analyze the shape of the graphs of the solutions of the
ordinary differential equation. This analysis leads to the classification of
the shape of such translating solitons. Finally, we investigate a domain of the
function which is given as a composition of the isoparametric function and the
solution of the ordinary differential equation in the case where the number of
distinct principal curvatures of the isoparametric hypersurface defined by the
regular level set for the isoparametric function is 1, 2, or 3.


  It is demonstrated that a structured material formed by nonconnected crossed
metallic wires may enable negative refraction over a wide frequency range. This
phenomenon is a consequence of the anomalous dispersion characteristics of the
material, particularly of the fact that the isofrequency contours are
hyperbolic. These properties rely on the nonlocal response of the crossed wire
mesh, and establish a different paradigm for obtaining negative refraction
without left-handed materials.


  Large language models (LLMs) are increasingly being used in Metaverse
environments to generate dynamic and realistic content and to control the
behavior of non-player characters (NPCs). However, the cybersecurity concerns
associated with LLMs have become increasingly prominent. Previous research has
primarily focused on patching system vulnerabilities to enhance cybersecurity,
but these approaches are not well-suited to the Metaverse, where the virtual
space is more complex, LLMs are vulnerable, and ethical user interaction is
critical. Moreover, the scope of cybersecurity in the Metaverse is expected to
expand significantly. This paper proposes a method for enhancing cybersecurity
through the simulation of user interaction with LLMs. Our goal is to educate
users and strengthen their defense capabilities through exposure to a
comprehensive simulation system. This system includes extensive Metaverse
cybersecurity Q&A and attack simulation scenarios. By engaging with these,
users will improve their ability to recognize and withstand risks.
Additionally, to address the ethical implications of user input, we propose
using LLMs as evaluators to assess user content across five dimensions. We
further adapt the models through vocabulary expansion training to better
understand personalized inputs and emoticons. We conduct experiments on
multiple LLMs and find that our approach is effective.


  In speech enhancement and source separation, signal-to-noise ratio is a
ubiquitous objective measure of denoising/separation quality. A decade ago, the
BSS_eval toolkit was developed to give researchers worldwide a way to evaluate
the quality of their algorithms in a simple, fair, and hopefully insightful
way: it attempted to account for channel variations, and to not only evaluate
the total distortion in the estimated signal but also split it in terms of
various factors such as remaining interference, newly added artifacts, and
channel errors. In recent years, hundreds of papers have been relying on this
toolkit to evaluate their proposed methods and compare them to previous works,
often arguing that differences on the order of 0.1 dB proved the effectiveness
of a method over others. We argue here that the signal-to-distortion ratio
(SDR) implemented in the BSS_eval toolkit has generally been improperly used
and abused, especially in the case of single-channel separation, resulting in
misleading results. We propose to use a slightly modified definition, resulting
in a simpler, more robust measure, called scale-invariant SDR (SI-SDR). We
present various examples of critical failure of the original SDR that SI-SDR
overcomes.


  Subluminous B stars (sdBs) form the extremely hot end of the horizontal
branch and are therefore related to the blue horizontal branch (BHB) stars.
While the rotational properties of BHB stars have been investigated
extensively, studies of sdB stars have concentrated on close binaries that are
influenced by tidal interactions between their components. Here we present a
study of 105 sdB stars, which are either single stars or in wide binaries where
tidal effects become negligible. The projected rotational velocities have been
determined by measuring the broadening of metal lines using high-resolution
optical spectra. All stars in our sample are slow rotators (${v_{\rm
rot}\sin{i}}<10\,{\rm km\,s^{-1}}$). Furthermore, the $v_{\rm
rot}\sin{i}$-distributions of single sdBs are similar to those of hot subdwarfs
in wide binaries with main-sequence companions as well as close binary systems
with unseen companions and periods exceeding $\simeq1.2\,{\rm d}$. We show that
blue horizontal and extreme horizontal branch stars are also related in terms
of surface rotation and angular momentum. Hot blue horizontal branch stars
($T_{\rm eff}>11\,500\,{\rm K}$) with diffusion-dominated atmospheres are slow
rotators like the hot subdwarf stars located on the extreme horizontal branch,
which lost more envelope and therefore angular momentum in the red-giant phase.
The uniform rotation distributions of single and wide binary sdBs pose a
challenge to our understanding of hot subdwarf formation. Especially the high
fraction of helium white dwarf mergers predicted by theory seems to be
inconsistent with the results presented here.


  It has been shown that traditional deep learning methods for electronic
microscopy segmentation usually suffer from low transferability when samples
and annotations are limited, while large-scale vision foundation models are
more robust when transferring between different domains but facing sub-optimal
improvement under fine-tuning. In this work, we present a new few-shot domain
adaptation framework SAMDA, which combines the Segment Anything Model(SAM) with
nnUNet in the embedding space to achieve high transferability and accuracy.
Specifically, we choose the Unet-based network as the "expert" component to
learn segmentation features efficiently and design a SAM-based adaptation
module as the "generic" component for domain transfer. By amalgamating the
"generic" and "expert" components, we mitigate the modality imbalance in the
complex pre-training knowledge inherent to large-scale Vision Foundation models
and the challenge of transferability inherent to traditional neural networks.
The effectiveness of our model is evaluated on two electron microscopic image
datasets with different modalities for mitochondria segmentation, which
improves the dice coefficient on the target domain by 6.7%. Also, the SAM-based
adaptor performs significantly better with only a single annotated image than
the 10-shot domain adaptation on nnUNet. We further verify our model on four
MRI datasets from different sources to prove its generalization ability.


  In this talk we review how effective theories of mesons and baryons become
exactly soluble in the large-N_c limit. We start with a generic hadron
Lagrangian constrained only by certain well-known large-N_c selection rules.
The bare vertices of the theory are dressed by an infinite class of UV
divergent Feynman diagrams at leading order in 1/N_c. We show how all these
leading-order diagrams can be summed exactly using semiclassical techniques.
The saddle-point field configuration is reminiscent of the chiral bag: hedgehog
pions outside a sphere of radius \Lambda^{-1} (\Lambda being the UV cutoff of
the effective theory) matched onto nucleon degrees of freedom for r <
\Lambda^{-1}. The effect of this pion cloud is to renormalize the bare nucleon
mass, nucleon-\Delta hyperfine mass splitting, and Yukawa couplings of the
theory. The corresponding large-N_c renormalization group equations for these
parameters are presented, and solved explicitly in a series of simple models.
We explain under what conditions the Skyrmion emerges as a UV fixed-point of
the RG flow as \Lambda --> \infty.


  We study, by means of a topological approach, the forced oscillations of
second order functional retarded differential equations subject to periodic
perturbations. We consider a delay-type functional dependence involving a gamma
probability distribution. By a linear chain trick we obtain a first order
system of ODE's whose $T$-periodic solutions correspond to those of the
functional equation.


  The goal of the DIRAC experiment at CERN (PS212) is to measure the
$\pi^+\pi^-$ atom lifetime with 10% precision. Such a measurement would yield a
precision of 5% on the value of the $S$-wave $\pi\pi$ scattering lengths
combination $|a_0-a_2|$. Based on part of the collected data we present a first
result on the lifetime, $\tau=[2.91 ^{+0.49}_{-0.62}]\times 10^{-15}$ s, and
discuss the major systematic errors. This lifetime corresponds to
$|a_0-a_2|=0.264 ^{+0.033}_{-0.020} m_{\pi}^{-1}$.


  Improving road safety is hugely important with the number of deaths on the
world's roads remaining unacceptably high; an estimated 1.35 million people die
each year as a result of road traffic collisions (WHO, 2020). Current practice
for treating collision hotspots is almost always reactive: once a threshold
level of collisions has been overtopped during some pre-determined observation
period, treatment is applied (e.g. road safety cameras). Traffic collisions are
rare, so prolonged observation periods are necessary. However, traffic
conflicts are more frequent and are a margin of the social cost; hence, traffic
conflict before/after studies can be conducted over shorter time periods. We
investigate the effect of implementing the leading pedestrian interval (LPI)
treatment (Van Houten et al. 2000) at signalised intersections as a safety
intervention in a city in north America. Pedestrian-vehicle traffic conflict
data were collected from treatment and control sites during the before and
after periods. We implement a before/after study on post-encroachment times
(PETs) where small PET values denote a near-miss. Hence, extreme value theory
is employed to model extremes of our PET processes, with adjustments to the
usual modelling framework to account for temporal dependence and treatment
effects.


  In this study, based on the first-principles calculations, we systematically
investigated the electronic and magnetic properties of the transition
metal-oxide-incorporated 2D g-C3N4 nanosheet (labeled C3N4-TM-O, TM = Sc-Mn).
The results suggest that the TM-O binds to g-C3N4 nanosheets strongly for all
systems. We found that the 2D C3N4-TM-O framework is ferromagnetic for TM = Sc,
Ti, V, Cr, while it is antiferromagnetic for TM = Mn. All the ferromagnetic
systems exhibit the half-metallic property. Furthermore, Monte Carlo
simulations based on the Heisenberg model suggest that the Curie temperatures
(T_c) of the C3N4-TM-O (TM = Sc, Ti, V, Cr) framework are 169 K, 68 K, 203 K,
and 190 K, respectively. Based on Bader charge analysis, we found that the
origin of the half-metallicity at Fermi energy can be partially attributed to
the transfer of electrons from TM atoms to the g-C3N4 nanosheet. In addition,
we found that not only electrons but also holes can induce half-metallicity for
2D g-C3N4 nanosheets, which may help to understand the origin of
half-metallicity for graphitic carbon nitride.


  In [arXiv:0804.2630], we have analyzed the leading logarithms of energy that
appear in the inclusive spectrum of gluons produced in heavy ion collisions,
calculated in the Color Glass Condensate framework. The main result of this
paper was that these logarithms are intrinsic properties of the colliding
projectiles, and that they can be resummed by letting the distributions of
color sources in the nuclei evolve according to the JIMWLK equation.
  An essential step in the proof of this factorization result is the
calculation of the gluon spectrum at Next-to-Leading order, and in particular a
functional relationship that expresses the NLO correction as the action of a
certain operator on the LO spectrum.
  In this paper, we show that this type of relation between spectra at LO and
NLO is not specific to the production of gluons, but that it is in fact generic
for inclusive spectra in heavy ion collisions. To illustrate this, we compute
up to NLO the inclusive spectrum of some hypothetical scalar fields, either
color neutral or colored, that couple to gluons.


  In this paper we revise and complete the photometric survey of the
instability strip of the southern open cluster NGC 2516 published by Antonello
and Mantegazza (1986). No variable stars with amplitudes larger than $0^m.02$
were found. However by means of an accurate analysis based on a new statistical
method two groups of small amplitude variables have been disentangled: one with
periods $< 0^d.25$ (probably $\delta$ Scuti stars) and one with periods
$>0^d.025$. The position in the HR diagram and the apparent time-scale may
suggest that the stars of the second group belong to a recently discovered new
class of variables, named $\gamma$ Dor variables. They certainly deserve
further study. We also present a comparison between the results of the
photometric survey and the available pointed ROSAT observations of this
cluster.


  The effective increase of the critical density associated with the
interaction of relativistically intense laser pulses with overcritical plasmas,
known as self-induced transparency, is revisited for the case of circular
polarization. A comparison of particle-in-cell simulations to the predictions
of a relativistic cold-fluid model for the transparency threshold demonstrates
that kinetic effects, such as electron heating, can lead to a substantial
increase of the effective critical density compared to cold-fluid theory. These
results are interpreted by a study of separatrices in the single-electron phase
space corresponding to dynamics in the stationary fields predicted by the
cold-fluid model. It is shown that perturbations due to electron heating
exceeding a certain finite threshold can force electrons to escape into the
vacuum, leading to laser pulse propagation. The modification of the
transparency threshold is linked to the temporal pulse profile, through its
effect on electron heating.


  In this paper, we examine various types of ${\mathcal F}$-hypercyclic
(${\mathcal F}$-topologically transitive) and disjoint ${\mathcal
F}$-hypercyclic (disjoint ${\mathcal F}$-topologically transitive) properties
of binary relations over topological spaces. We pay special attention to finite
structures like simple graphs, digraphs and tournaments, providing a great
number of illustrative examples.


  Localization and mapping are key capabilities for self-driving vehicles. In
this paper, we build on Kimera and extend it to use multiple cameras as well as
external (eg wheel) odometry sensors, to obtain accurate and robust odometry
estimates in real-world problems. Additionally, we propose an effective scheme
for closing loops that circumvents the drawbacks of common alternatives based
on the Perspective-n-Point method and also works with a single monocular
camera. Finally, we develop a method for dense 3D mapping of the free space
that combines a segmentation network for free-space detection with a
homography-based dense mapping technique. We test our system on photo-realistic
simulations and on several real datasets collected on a car prototype developed
by the Ford Motor Company, spanning both indoor and outdoor parking scenarios.
Our multi-camera system is shown to outperform state-of-the art open-source
visual-inertial-SLAM pipelines (Vins-Fusion, ORB-SLAM3), and exhibits an
average trajectory error under 1% of the trajectory length across more than 8km
of distance traveled (combined across all datasets). A video showcasing the
system is available at: youtu.be/H8CpzDpXOI8.


  A chirped-pulse quantum control scheme applicable to Coherent Anti-Stokes
Raman Scattering spectroscopy, named as C-CARS, is presented aimed at
maximizing the vibrational coherence in molecules. It implies chirping of three
incoming pulses in the four-wave mixing process of CARS, the pump, the Stokes
and the probe, to fulfil the conditions of adiabatic passage. The scheme is
derived in the framework of rotating wave approximation and adiabatic
elimination of excited state manifold simplifying the four-level model system
into a ``super-effective'' two level system. The robustness, spectral
selectivity and adiabatic nature of this method are helpful in improving the
existing methods of CARS spectroscopy for sensing, imaging and detection. We
also show that the selectivity of excitation of vibrational degrees of freedom
can be controlled by carefully choosing the spectral chirp rate of the pulses.


  We introduce a version of Stein's method for proving concentration and moment
inequalities in problems with dependence. Simple illustrative examples from
combinatorics, physics, and mathematical statistics are provided.


  Given an action $\alpha$ of a discrete group $G$ on a unital C*-algebra $A$,
we introduce a natural concept of $\alpha$-negative definiteness for functions
from $G$ to $A$, and examine some of the first consequences of such a notion.
In particular, we prove analogs of theorems due to Delorme-Guichardet and
Schoenberg in the classical case where $A$ is trivial. We also give a
characterization of the Haagerup property for the action $\alpha$ when $G$ is
countable.


  We present a proof of Minami type estimates for one dimensional random
Schr\"odinger operators valid at all energies in the localization regime
provided a Wegner estimate is known to hold. The Minami type estimates are then
applied to various models to obtain results on their spectral statistics. The
heuristics underlying our proof of Minami type estimates is that close by
eigenvalues of a one-dimensional Schr\"odinger operator correspond either to
eigenfunctions that live far away from each other in space or they come from
some tunneling phenomena. In the second case, one can undo the tunneling and
thus construct quasi-modes that live far away from each other in space.


  The procedure for Abelian conversion of second class constraints due to
Batalin, Fradkin, Fradkina and Tyutin is considered at quantum level, by using
the field-antifield formalism. It is argued that quantum effects can obstruct
the process. In this case, Wess-Zumino fields may be introduced in order to
restore the lost symmetries.


  We propose a straightforward and cost-effective method to perform diffuse
soundfield measurements for calibrating the magnitude response of a microphone
array. Typically, such calibration is performed in a diffuse soundfield created
in reverberation chambers, an expensive and time-consuming process. A method is
proposed for obtaining diffuse field measurements in untreated environments.
First, a closed-form expression for the spatial correlation of a wideband
signal in a diffuse field is derived. Next, we describe a practical procedure
for obtaining the diffuse field response of a microphone array in the presence
of a non-diffuse soundfield by the introduction of random perturbations in the
microphone location. Experimental spatial correlation data obtained is compared
with the theoretical model, confirming that it is possible to obtain diffuse
field measurements in untreated environments with relatively few loudspeakers.
A 30 second test signal played from 4-8 loudspeakers is shown to be sufficient
in obtaining a diffuse field measurement using the proposed method. An
Eigenmike is then successfully calibrated at two different geographical
locations.


  We investigate the finite temperature properties of the one-dimensional
two-component Bose gas (2CBG) with repulsive contact interaction in a harmonic
trap. Making use of a new lattice embedding for the 2CBG and the quantum
transfer matrix we derive a system of two nonlinear integral equations
characterizing the thermodynamics of the uniform system for all values of the
relevant parameters: temperature, strength of the interaction, chemical
potential and magnetic field. This system allows for an easy numerical
implementation in stark contrast with the infinite number of equations obtained
by employing the thermodynamic Bethe ansatz. We use this exact solution coupled
with the local density approximation to compute the density profiles and local
density correlation function of the inhomogeneous gas for a wide range of
coupling strengths and temperatures. Our results show that the polarization in
the center of the trap influences heavily the local correlator especially in
the experimentally accessible Tonks-Girardeau regime.


  Small molecule protonation is an important part of the preparation of small
molecules for many types of computational chemistry protocols. For this, a
correct estimation of the pKa values of the protonation sites of molecules is
required. In this work, we present pKAce, a new web application for the
prediction of micro-pKa values of the molecules' protonation sites. We adapt
the state-of-the-art, equivariant, TensorNet model originally developed for
quantum mechanics energy and force predictions to the prediction of micro-pKa
values. We show that an adapted version of this model can achieve
state-of-the-art performance comparable with established models while trained
on just a fraction of their training data.


  A giant solar filament was visible on the solar surface from 2011 Nov. 8-23.
The filament stretched over more than half a solar diameter. Multiwavelength
data from the SDO instrument AIA (171, 193, 304, and 211\AA) were used to
examine counter-streaming flows within the spine of the filament. H$\alpha$
images from the Kanzelh\"ohe Solar Observatory provided context information. We
apply local correlation tracking (LCT) to a two-hour time series on 2011 Nov.
16 of the AIA images to derive horizontal flow velocities of the filament. To
enhance the contrast of the AIA images, noise adaptive fuzzy equalization is
employed, which allows us to identify and quantify counter-streaming flows in
the filament. We detect counter-streaming flows in the filament, which are
visible in the time-lapse movies in all examined AIA wavelength bands. In the
time-lapse movies we see that these persistent flows lasted for at least two
hours. Furthermore, by applying LCT to the images we clearly determine
counter-streaming flows in time series of 171 and 193\AA\ images. In the
304\AA\ wavelength band, we only see minor indications for counter-streaming
flows with LCT, while in the 211\AA\ wavelength band the counter-streaming
flows are not detectable. The average horizontal flows reach mean flow speeds
of 0.5 km/s. The highest horizontal flow speeds are identified in the 171\AA\
band with flow speeds of up to 2.5 km/s. The results are averaged over a time
series of 90 min. Because the LCT sampling window has finite width, a spatial
degradation cannot be avoided leading to lower estimates of the flow velocities
as compared to feature tracking or Doppler measurements. The counter-streaming
flows cover about 15-20% of the whole area of the EUV filament channel and are
located in the central part of the spine. In conclusion, we confirm the
omnipresence of counter-streaming flows also in giant quiet-Sun filaments.


  MLPGradientFlow is a software package to solve numerically the gradient flow
differential equation $\dot \theta = -\nabla \mathcal L(\theta; \mathcal D)$,
where $\theta$ are the parameters of a multi-layer perceptron, $\mathcal D$ is
some data set, and $\nabla \mathcal L$ is the gradient of a loss function. We
show numerically that adaptive first- or higher-order integration methods based
on Runge-Kutta schemes have better accuracy and convergence speed than gradient
descent with the Adam optimizer. However, we find Newton's method and
approximations like BFGS preferable to find fixed points (local and global
minima of $\mathcal L$) efficiently and accurately. For small networks and data
sets, gradients are usually computed faster than in pytorch and Hessian are
computed at least $5\times$ faster. Additionally, the package features an
integrator for a teacher-student setup with bias-free, two-layer networks
trained with standard Gaussian input in the limit of infinite data. The code is
accessible at https://github.com/jbrea/MLPGradientFlow.jl.


  Half-Heusler compounds (space group Fm3m) has garnered increasing attention
in recent years in the thermoelectric community. Three decades ago, refractory
RNiSn half-Heusler compounds (R represents refractory metals such as Hf, Zr,
Ti) were found to be narrow-gap semiconductors with large Seebeck coefficients
in 100s of micro-volt per Kelvin. Today, half-Heusler (HH) compounds have
emerged as promising thermoelectric materials in the intermediate temperature
range (400-800oC). HH materials are endowed with good thermal stability and
scalability. Thermoelectric n-p modules based on HH materials demonstrate
conversion efficiency near 10% and power density output near 9 W/cm2. The
objective of this article is to present a historical account of the research
and development of thermoelectric half-Heusler compounds. Particularly, there
have been notable achievements since 2012 thanks to the emergence of new
approaches. As a result, ZT has risen from ~1 to 1.5. The various advances made
since the early 1990s to the present are recounted by categorizing half-Heusler
materials into three generations (Gen): Gen-1 Gen-2, and Gen-3 HH materials.


  Conservative bSM models with rich scalar sector, such as multi-Higgs-doublet
models, can easily accommodate the SM-like properties of the 125 GeV scalar
observed at the LHC. Possessing a variety of bSM signals, they are worth
investigating in fuller detail. Systematic study of these models is hampered by
the highly multi-dimensional parameter space and by mathematical challenges. I
outline some directions along which multi-Higgs-doublet models in the vicinity
of a large discrete symmetry can be systematically explored.


  We present a systematic study of quantum phases in a one-dimensional
spin-polarized Fermi gas. Three comparative theoretical methods are used to
explore the phase diagram at zero temperature: the mean-field theory with
either an order parameter in a single-plane-wave form or a self-consistently
determined order parameter using the Bogoliubov-de Gennes equations, as well as
the exact soluble Bethe ansatz method. We find that a spatially inhomogeneous
Fulde-Ferrell-Larkin-Ovchinnikov phase, which lies between the fully paired BCS
state and the fully polarized normal state, dominates most of the phase diagram
of a uniform gas. The phase transition from the BCS state to the
Fulde-Ferrell-Larkin-Ovchinnikov phase is of second order, and therefore there
are no phase separation states in one-dimensional homogeneous polarized gases.
This is in sharp contrast to the three-dimensional situation, where a phase
separation regime is predicted to occupy a very large space in the phase
diagram. We conjecture that the prediction of the dominance of the phase
separation phases in three dimension could be an artifact of the
non-self-consistent mean-field approximation, which is heavily used in the
study of three-dimensional polarized Fermi gases. We consider also the effect
of a harmonic trapping potential on the phase diagram, and find that in this
case the trap generally leads to phase separation, in accord with the
experimental observations for a trapped gas in three dimension. We finally
investigate the local fermionic density of states of the
Fulde-Ferrell-Larkin-Ovchinnikov ansatz. A two-energy-gap structure is shown
up, which could be used as an experimental probe of the
Fulde-Ferrell-Larkin-Ovchinnikov states.


  Although software managers are generally good at new project estimation,
their experience of scheduling rework tends to be poor. Inconsistent or
incorrect effort estimation can increase the risk that the completion time for
a project will be problematic. To continually alter software maintenance
schedules during software maintenance is a daunting task. Our proposed
framework, validated in a case study confirms that the variables resulting from
requirements changes suffer from a number of problems, e.g., the coding used,
end user involvement and user documentation. Our results clearly show a
significant impact on rework effort as a result of unexpected errors that
correlate with 1) weak characteristics and attributes as described in the
program's source lines of code, especially in data declarations and data
statements, 2) lack of communication between developers and users on a change
effects, and 3) unavailability of user documentation. To keep rework effort
under control, new criteria in change request forms are proposed. These
criteria are shown in a proposed framework; the more case studies that are
validated, the more reliable the result will be in determining the outcome of
effort rework estimation.


  Ultrasound imaging often suffers from image degradation stemming from phase
aberration, which represents a significant contributing factor to the overall
image degradation in ultrasound imaging. Frequency-space prediction filtering
or FXPF is a technique that has been applied within focused ultrasound imaging
to alleviate the phase aberration effect. It presupposes the existence of an
autoregressive (AR) model across the signals received at the transducer
elements and removes any components that do not conform to the established
model. In this study, we illustrate the challenge of applying this technique to
plane-wave imaging, where, at shallower depths, signals from more distant
elements lose relevance, and a fewer number of elements contribute to image
reconstruction. While the number of contributing signals varies, adopting a
fixed-order AR model across all depths, results in suboptimal performance. To
address this challenge, we propose an AR model with an adaptive order and
quantify its effectiveness using contrast and generalized contrast-to-noise
ratio metrics.


  Let $a$ and $b$ be positive integers with prime factorisations $a =
p_1^np_2^n$ and $b = q_1^nq_2^n$. We prove that the number of essentially
distinct $\alpha$-graceful labelings of the complete bipartite graph $K_{a, b}$
equals the alternating sum of fourth powers of binomial coefficients
$(-1)^n[\binom{2n}{0}^4 - \binom{2n}{1}^4 + \binom{2n}{2}^4 - \binom{2n}{3}^4 +
\cdots + \binom{2n}{2n}^4]$.


  Fake news often involves semantic manipulations across modalities such as
image, text, location etc and requires the development of multimodal semantic
forensics for its detection. Recent research has centered the problem around
images, calling it image repurposing -- where a digitally unmanipulated image
is semantically misrepresented by means of its accompanying multimodal metadata
such as captions, location, etc. The image and metadata together comprise a
multimedia package. The problem setup requires algorithms to perform multimodal
semantic forensics to authenticate a query multimedia package using a reference
dataset of potentially related packages as evidences. Existing methods are
limited to using a single evidence (retrieved package), which ignores potential
performance improvement from the use of multiple evidences. In this work, we
introduce a novel graph neural network based model for multimodal semantic
forensics, which effectively utilizes multiple retrieved packages as evidences
and is scalable with the number of evidences. We compare the scalability and
performance of our model against existing methods. Experimental results show
that the proposed model outperforms existing state-of-the-art algorithms with
an error reduction of up to 25%.


  Several years ago the second author playing with different "recognizers of
real constants", e.g., the LLL algorithm, the Plouffe inverter, etc. found
empirically the following formula. Let $p_n/q_n$ denote the $n$th convergent of
the continued fraction of the constant $e$, then $$ \sum_{n \geq 0} |q_n e -
p_n| = \frac{e}{4} \left(- 1 + 10 \sum_{n \geq 0} \frac{(-1)^n}{(n+1)! (2n^2 +
7n + 3)}\right). $$ The purpose of the present paper is to prove this formula
and to give similar formulas for some powers of $e$.


  We investigate the behavior of energy momentum tensor correlators in strongly
coupled large-N_c Yang-Mills theory at nonzero temperature, working within the
Improved Holographic QCD model. In particular, we determine the spectral
functions and corresponding imaginary time correlators in the bulk and shear
channels, and compare the results to recent perturbative and lattice
calculations where available. For the bulk channel imaginary time correlator,
for which all three results exist, lattice data is seen to favor the
holographic prediction over the perturbative one over a wide range of
temperatures.


  We propose a sharp-interface model for a hyperelastic material consisting of
two phases. In this model, phase interfaces are treated in the deformed
configuration, resulting in a fully Eulerian interfacial energy. In order to
penalize large curvature of the interface, we include a geometric term
featuring a curvature varifold. Equilibrium solutions are proved to exist via
minimization. We then utilize this model in an Eulerian topology optimization
problem that incorporates a curvature penalization.


  A persistent challenge in predictive molecular modeling of thermoset polymers
is to capture the effects of chemical composition and degree of crosslinking
(DC) on dynamical and mechanical properties with high computational efficiency.
We established a new coarse-graining (CG) approach that combines the energy
renormalization method with Gaussian process surrogate models of the molecular
dynamics simulations. This allows a machine-learning informed functional
calibration of DC-dependent CG force field parameters. Taking versatile epoxy
resins consisting of Bisphenol A diglycidyl ether combined with curing agent of
either 4,4-Diaminodicyclohexylmethane or polyoxypropylene diamines, we
demonstrated excellent agreement between all-atom and CG predictions for
density, Debye-Waller factor, Young's modulus and yield stress at any DC. We
further introduce a surrogate model enabled simplification of the functional
forms of 14 non-bonded calibration parameters by quantifying the uncertainty of
a candidate set of high-dimensional and flexible calibration functions. The
framework established provides an efficient methodology for chemistry-specific,
large-scale investigations of the dynamics and mechanics of epoxy resins.


  High spatial and spectral resolution observations of star formation and
kinematics in early galaxies have shown that two-thirds are massive rotating
disk galaxies with the remainder being less massive non-rotating objects. The
line of sight averaged velocity dispersions are typically five times higher
than in today's disk galaxies. This has suggested that
gravitationally-unstable, gas-rich disks in the early Universe are fuelled by
cold, dense accreting gas flowing along cosmic filaments and penetrating hot
galactic gas halos. However these accreting flows have not been observed, and
cosmic accretion cannot power the observed level of turbulence. Here we report
on a new sample of rare high-velocity-dispersion disk galaxies we have
discovered in the nearby Universe where cold accretion is unlikely to drive
their high star-formation rates. We find that the velocity dispersion is most
fundamentally correlated with their star-formation rates, and not their mass
nor gas fraction, which leads to a new picture where star formation itself is
the energetic driver of galaxy disk turbulence at all cosmic epochs.


  Heartbeat stars (HB stars) are a class of eccentric binary stars with close
periastron passages. The characteristic photometric HB signal evident in their
light curves is produced by a combination of tidal distortion, heating, and
Doppler boosting near orbital periastron. Many HB stars continue to oscillate
after periastron and along the entire orbit, indicative of the tidal excitation
of oscillation modes within one or both stars. These systems are among the most
eccentric binaries known, and they constitute astrophysical laboratories for
the study of tidal effects. We have undertaken a radial velocity (RV)
monitoring campaign of Kepler HB stars in order to measure their orbits. We
present our first results here, including a sample of 21 Kepler HB systems,
where for 19 of them we obtained the Keplerian orbit and for 3 other systems we
did not detect a statistically significant RV variability. Results presented
here are based on 218 spectra obtained with the Keck/HIRES spectrograph during
the 2015 Kepler observing season, and they have allowed us to obtain the
largest sample of HB stars with orbits measured using a single instrument,
which roughly doubles the number of HB stars with an RV measured orbit. The 19
systems measured here have orbital periods from 7 to 90 d and eccentricities
from 0.2 to 0.9. We show that HB stars draw the upper envelope of the
eccentricity - period distribution. Therefore, HB stars likely represent a
population of stars currently undergoing high eccentricity migration via tidal
orbital circularization, and they will allow for new tests of high eccentricity
migration theories.


  Milnor formulated a conjecture about rational linear independence of some
special Hurwitz zeta values. The second and third authors along with Ram Murty
studied this conjecture and suggested an extension of Milnor's conjecture. In
this note, we investigate the number field generalisation of this extended
Milnor conjecture. We indicate the motivation for considering this number field
case by noting that such a phenomenon is true in an analogous context. We also
study some new spaces related to normalised Hurwitz zeta values.


  Motivated by an early experimental study of VOSeO3, which suggested that it
is a quasi-2D system of weakly coupled spin dimers with a small spin gap, we
have investigated the electronic structure of this material via
density-functional calculations. These ab initio results indicate that the
system is better thought of as an alternating spin-1/2 chain with moderate
interchain interactions, an analog of (VO)2P2O7. The potential interest of this
system for studies in high magnetic field given the presumably small value of
the spin gap is emphasized.


  We present a systematic study that clarifies validity and limitation of
current hybrid functionals in density functional theory for structural and
electronic properties of various semiconductors and insulators. The three
hybrid functionals, PBE0 by Perdew, Ernzerhof, and Becke, HSE by Heyd,
Sucseria, and Ernzerhof, and a long-range corrected (LC) functional, are
implemented in a well-established plane-wave-basis-set scheme combined with
norm-conserving pseudopotentials, thus enabling us to assess applicability of
each functional on equal footing to the properties of the materials. The
materials we have examined in this paper range from covalent to ionic materials
as well as a rare-gas solid whose energy gaps determined by experiments are in
the range of 0.6 eV - 14.2 eV: i.e., Ge, Si, BaTiO$_3$, $\beta$-GaN, diamond,
MgO, NaCl, LiCl, Kr, and LiF. We find that the calculated bulk moduli by the
hybrid functionals show better agreement with the experiments than the
generalized gradient approximation (GGA) provides, whereas the calculated
lattice constants by the hybrid functionals and GGA show comparable accuracy.
The calculated energy band gaps and the valence-band widths for the ten
prototype materials show substantial improvement using the hybrid functional
compared with GGA. In particular, it is found that the band gaps of the ionic
materials as well as the rare-gas solid are well reproduced by the LC-hybrid
functional, whereas those of covalent materials are well described by the HSE
functional. We also examine exchange effects due to short-range and long-range
components of the Coulomb interaction and propose an optimum recipe to the
short-range and long-range separation in treating the exchange energy.


  Invariant Extended Kalman Filter (IEKF) has been successfully applied in
Visual-inertial Odometry (VIO) as an advanced achievement of Kalman filter,
showing great potential in sensor fusion. In this paper, we propose partial
IEKF (PIEKF), which only incorporates rotation-velocity state into the Lie
group structure and apply it for Visual-Inertial-Wheel Odometry (VIWO) to
improve positioning accuracy and consistency. Specifically, we derive the
rotation-velocity measurement model, which combines wheel measurements with
kinematic constraints. The model circumvents the wheel odometer's 3D
integration and covariance propagation, which is essential for filter
consistency. And a plane constraint is also introduced to enhance the position
accuracy. A dynamic outlier detection method is adopted, leveraging the
velocity state output. Through the simulation and real-world test, we validate
the effectiveness of our approach, which outperforms the standard Multi-State
Constraint Kalman Filter (MSCKF) based VIWO in consistency and accuracy.


  The scaled momentum distributions of charged particles in jets have been
measured for dijet photoproduction with the ZEUS detector at HERA using an
integrated luminosity of 359 pb-1. The distributions are compared to
predictions based on perturbative QCD carried out in the framework of the
modified leading-logarithmic approximation (MLLA) and assuming local
parton-hadron duality (LPHD). The universal MLLA scale, Lambda_eff, and the
LPHD parameter, kappa^ch, are extracted.


  Text Proposals have emerged as a class-dependent version of object proposals
- efficient approaches to reduce the search space of possible text object
locations in an image. Combined with strong word classifiers, text proposals
currently yield top state of the art results in end-to-end scene text
recognition. In this paper we propose an improvement over the original Text
Proposals algorithm of Gomez and Karatzas (2016), combining it with Fully
Convolutional Networks to improve the ranking of proposals. Results on the
ICDAR RRC and the COCO-text datasets show superior performance over current
state-of-the-art.


  High quality transcription data is crucial for training automatic speech
recognition (ASR) systems. However, the existing industry-level data collection
pipelines are expensive to researchers, while the quality of crowdsourced
transcription is low. In this paper, we propose a reliable method to collect
speech transcriptions. We introduce two mechanisms to improve transcription
quality: confidence estimation based reprocessing at labeling stage, and
automatic word error correction at post-labeling stage. We collect and release
LibriCrowd - a large-scale crowdsourced dataset of audio transcriptions on 100
hours of English speech. Experiment shows the Transcription WER is reduced by
over 50%. We further investigate the impact of transcription error on ASR model
performance and found a strong correlation. The transcription quality
improvement provides over 10% relative WER reduction for ASR models. We release
the dataset and code to benefit the research community.


  We present results of a photometric study of the young southern open cluster
Stock 14. This cluster is known to contain two eclipsing systems with presumed
beta Cephei components, HD 101794 and HD 101838. We confirm variability due to
pulsations and eclipses in both targets and announce the discovery of other
variable stars in the observed field.


  It is shown that optical geometry of the Reissner-Nordstrom exterior metric
can be embedded in a hyperbolic space all the way down to its outer horizon.
The adopted embedding procedure removes a breakdown of flat-space embeddings
which occurs outside the horizon, at and below the Buchdahl-Bondi limit
(R/M=9/4 in the Schwarzschild case). In particular, the horizon can be captured
in the optical geometry embedding diagram. Moreover, by using the compact
Poincare ball representation of the hyperbolic space, the embedding diagram can
cover the whole extent of radius from spatial infinity down to the horizon.
Attention is drawn to advantages of such embeddings in an appropriately curved
space: this approach gives compact embeddings and it distinguishes clearly the
case of an extremal black hole from a non-extremal one in terms of topology of
the embedded horizon.


  As part of a feasibility study, this paper shows the NASA Valkyrie humanoid
robot performing an end-to-end improvised explosive device (IED) response task.
To demonstrate and evaluate robot capabilities, sub-tasks highlight different
locomotion, manipulation, and perception requirements: traversing uneven
terrain, passing through a narrow passageway, opening a car door, retrieving a
suspected IED, and securing the IED in a total containment vessel (TCV). For
each sub-task, a description of the technical approach and the hidden
challenges that were overcome during development are presented. The discussion
of results, which explicitly includes existing limitations, is aimed at
motivating continued research and development to enable practical deployment of
humanoid robots for IED response. For instance, the data shows that operator
pauses contribute to 50\% of the total completion time, which implies that
further work is needed on user interfaces for increasing task completion
efficiency.


  Let $E/F$ be a quadratic extension of fields, and $G$ a connected quasi-split
reductive group over $F$. Let $G^{op}$ be the opposition group obtained by
twisting $G$ by the duality involution considered by Prasad. Assume that the
field $F$ is finite. Let $\pi$ be an irreducible generic representation of
$G(E)$. When $\pi$ is a Shintani base change lift of some representation of
$G^{op}(F)$, we give an explicit nonzero $G(F)$-invariant vector in terms of
the Whittaker vector of $\pi$. This shows particularly that $\pi$ is
$G(F)$-distinguished.
  When the field $F$ is $p$-adic, the paper also proves that the duality
involution takes an irreducible admissible generic representation of $G(F)$ to
its contragredient. As a special case of this result, all generic
representations of $G_2,\ F_4$ or $E_8$ are self-dual.


  We explain the solution of the following two problems: obtaining of Kepler's
laws from Newton's laws (so called two bodies problem) and obtaining the fourth
Newton's law (the formula for gravitation) as a corollary of Kepler's laws.
  This small book is devoted to the scholars, who are interested in physics and
mathematics. We also make a series of digressions, where explain some technique
of the higher mathematics, which are used in the proofs.


  We give a direct proof of a result of Sweedler describing the cofree
cocommutative coalgebra over a vector space, and use our approach to give an
explicit construction of liftings of maps into this universal coalgebra. The
basic ingredients in our approach are local cohomology and residues.


  We show that minimal shifts with zero topological entropy are topologically
conjugate to interval exchange transformations, generally infinite. When these
shifts have linear factor complexity (linear block growth), the conjugate
interval exchanges are proved to satisfy strong finiteness properties.


  The gauge equivalent counterparts of the some (1+1)-, or (2+0)-dimensional
sigma models with potentials are found. The gauge equivalence between the some
soliton equations of spin-phonon systems and the Yajima-Oikawa and Ma equations
are also established.


  Cloud computing provides on-demand access to affordable hardware (multi-core
CPUs, GPUs, disks, and networking equipment) and software (databases,
application servers and data processing frameworks) platforms with features
such as elasticity, pay-per-use, low upfront investment and low time to market.
This has led to the proliferation of business critical applications that
leverage various cloud platforms. Such applications hosted on single or
multiple cloud provider platforms have diverse characteristics requiring
extensive monitoring and benchmarking mechanisms to ensure run-time Quality of
Service (QoS) (e.g., latency and throughput). This paper proposes, develops and
validates CLAMBS:Cross-Layer Multi-Cloud Application Monitoring and
Benchmarking as-a-Service for efficient QoS monitoring and benchmarking of
cloud applications hosted on multi-clouds environments. The major highlight of
CLAMBS is its capability of monitoring and benchmarking individual application
components such as databases and web servers, distributed across cloud layers,
spread among multiple cloud providers. We validate CLAMBS using prototype
implementation and extensive experimentation and show that CLAMBS efficiently
monitors and benchmarks application components on multi-cloud platforms
including Amazon EC2 and Microsoft Azure.


  Let $H$ be a semisimple Hopf algebra acting on an Artin-Schelter regular
algebra $A$, homogeneously, inner-faithfully, preserving the grading on $A$,
and so that $A$ is an $H$-module algebra. When the fixed subring $A^H$ is also
AS regular, thus providing a generalization of the Chevalley-Shephard-Todd
Theorem, we say that $H$ is a reflection Hopf algebra for $A$. We show that
each of the semisimple Hopf algebras $H_{2n^2}$ of Pansera, and
$\mathcal{A}_{4m}$ and $\mathcal{B}_{4m}$ of Masuoka is a reflection Hopf
algebra for an AS regular algebra of dimension 2 or 3.


  The origin of the spin gap in the underdoped cuprate superconductors is still
mysterious. Experimental evidence from neutron scattering and NMR experiments
indicates that the spin gap might be present only in the bilayer compounds. A
naive calculation for a two plane Heisenberg model locates the order-disorder
transition only for very large exchange coupling between the bilayers. We
propose a interplane relaxation experiment which might quantitatively estimate
the strength of the bilayer coupling. We make detailed predictions for the size
and the temperature dependence of the interplane relaxation rate.


  Word embeddings improve the performance of NLP systems by revealing the
hidden structural relationships between words. Despite their success in many
applications, word embeddings have seen very little use in computational social
science NLP tasks, presumably due to their reliance on big data, and to a lack
of interpretability. I propose a probabilistic model-based word embedding
method which can recover interpretable embeddings, without big data. The key
insight is to leverage mixed membership modeling, in which global
representations are shared, but individual entities (i.e. dictionary words) are
free to use these representations to uniquely differing degrees. I show how to
train the model using a combination of state-of-the-art training techniques for
word embeddings and topic models. The experimental results show an improvement
in predictive language modeling of up to 63% in MRR over the skip-gram, and
demonstrate that the representations are beneficial for supervised learning. I
illustrate the interpretability of the models with computational social science
case studies on State of the Union addresses and NIPS articles.


  Low-metallicity very massive stars with an initial mass of $\sim 140$--$260\,
{\rm M_\odot}$ are expected to end their lives as pair-instability supernovae
(PISNe). The abundance pattern resulting from a PISN differs drastically from
regular core-collapse supernova (CCSN) models and is expected to be seen in
very metal-poor (VMP) stars of ${\rm[Fe/H]}\lesssim -2$. Despite the routine
discovery of many VMP stars, the unique abundance pattern expected from PISNe
has not been unambiguously detected. The recently discovered VMP star LAMOST
J1010+2358, however, shows a peculiar abundance pattern that is remarkably well
fit by a PISN, indicating the potential first discovery of a bonafide star born
from gas polluted by a PISN. In this paper, we study the detailed
nucleosynthesis in a large set of models of CCSN of Pop III and Pop II star of
metallicity ${\rm[Fe/H]}=-3$ with masses ranging from $12$--$30\,{\rm
M_\odot}$. We find that the observed abundance pattern in LAMOST J1010+2358 can
be fit at least equally well by CCSN models of $\sim 12$--$14\,{\rm M_\odot}$
that undergo negligible fallback following the explosion. The best-fit CCSN
models provide a fit that is even marginally better than the best-fit PISN
model. We conclude the measured abundance pattern in LAMOST J1010+2358 could
have originated from a CCSN and therefore cannot be unambiguously identified
with a PISN given the set of elements measured in it to date. We identify key
elements that need to be measured in future detections in stars like LAMOST
J1010+2358 that can differentiate between CCSN and PISN origin.


  We present progress on two old conjectures about longest cycles in graphs.
The first conjecture, due to Thomassen from 1978, states that apart from a
finite number of exceptions, all connected vertex-transitive graphs contain a
Hamiltonian cycle. The second conjecture, due to Smith from 1984, states that
for $r\ge 2$ in every $r$-connected graph any two longest cycles intersect in
at least $r$ vertices. In this paper, we prove a new lemma about the
intersection of longest cycles in a graph which can be used to improve the best
known bounds towards both of the aforementioned conjectures: First, we show
that every connected vertex-transitive graph on $n\geq 3$ vertices contains a
cycle of length at least $\Omega(n^{13/21})$, improving on $\Omega(n^{3/5})$
from [De Vos, arXiv:2302:04255, 2023]. Second, we show that in every
$r$-connected graph with $r\geq 2$, any two longest cycles meet in at least
$\Omega(r^{5/8})$ vertices, improving on $\Omega(r^{3/5})$ from [Chen, Faudree
and Gould, J. Combin. Theory, Ser.~ B, 1998]. Our proof combines combinatorial
arguments, computer-search and linear programming.


  Recent determinations of the deuterium abundance, $^2$H/H, in high redshift
Lyman limit hydrogen clouds challenge the usual picture of primordial
nucleosynthesis based on \lq\lq concordance\rq\rq\ of the calculated light
element ($^2$H, $^3$He, $^4$He, $^7$Li) nucleosynthesis yields with the
observationally-inferred abundances of these species. Concordance implies that
all light element yields can be made to agree with the observationally-inferred
abundances (within errors) for single global specifications of the
baryon-to-photon ratio, $\eta$; lepton number; neutron lifetime; and expansion
rate (or equivalently, effective number of light neutrino degrees of freedom
$N_{\nu} $). Though one group studying Lyman limit systems obtains a high value
of $^2$H/H ($\sim 2\times {10}^{-4}$), another group finds consistently low
values ($\sim 2\times {10}^{-5}$). In the former case, concordance for $N_{\nu}
=3$ is readily attained for the current observationally-inferred abundances of
$^4$He and $^7$Li. But if the latter case represents the primordial deuterium
abundance, then concordance for {\it any} $N_{\nu}$ is impossible unless the
primordial value of $^7$Li/H is considerably larger than the abundance of
lithium as measured in old, hot Pop II halo stars. Furthermore, concordance
with $N_{\nu}=3$ is possible for low $^2$H/H only if either (1) the primordial
$^4$He abundance has been significantly underestimated, or (2) new neutrino
sector physics is invoked. We argue that systematic underestimation of both the
$^7$Li and $^4$He primordial abundances is the likely resolution of this
problem, a conclusion which is strengthened by new results on $^4$He.


  A method to prepare monodisperse and highly coercive L10-FePt nanoparticles
which are dispersible in nonpolar organic solvents such as toluene, chloroform,
and hexane was developed. By vigorously stirring the SiO2-coated L10-FePt
nanoparticles synthesized by the SiO2-nanoreactor method (Appl. Phys. Lett.
2005, 87, 032503) in a mixture of an aqueous NaOH solution, chloroform, and
hexadecyltrimethlyammonium bromide, the SiO2 coating was dissolved off and bare
FePt nanoparticles could be extracted to the chloroform phase without degrading
their magnetic properties. These particles showed a tendency to form a close
packed lattice on slow drying of the chloroform-based solution. The present
success may promote the practical application to ultra-high density magnetic
recording and also may open the door to providing these particles with new
physical and/or chemical functions.


  Swift has revealed features in GRB early light curves, such as steep decays
and X-ray flares, whose properties are consistent with an internal origin
though they are far from understood. The steep X-ray decay is often explained
using the curvature effect; however a significant number of GRBs display strong
spectral evolution during this phase, and a new mechanism must be invoked to
explain this. Of particular interest are the longest duration GRBs in which the
early emission can be studied in most detail. Here we present data for GRB
070616, in which the prompt emission shows a complex multipeaked structure,
leading to one of the longest prompt emission durations ever recorded. We take
advantage of extensive coverage of such a long burst by all Swift instruments.
Combining data from Swift and Suzaku we study the evolution of the prompt
emission spectrum, following the temporal variability of the peak energy and
spectral slope.


  We report on some technical aspects of our calculation of alpha_s^4
corrections to R(s) and the semi-leptonic tau decay width [1-3]. We discuss the
inner structure of the result as well as the issue of its correctness. We
demonstrate recently appeared independent evidence positively testing one of
two components of the full result.


  Let $K\left\langle X \right\rangle$ denote the free associative algebra
generated by a set $X = \{x_1, \dots, x_n\}$ over a field $K$ of characteristic
$0$. Let $I_p$, for $p \geq 2$, denote the two-sided ideal in $K\left\langle X
\right\rangle$ generated by all commutators of the form $[u_1, \dots, u_p]$,
where $u_1, \dots, u_p \in K\left\langle X \right\rangle$. We discuss the
$\mathrm{GL}(n, K)$-module structure of the quotient $K\left\langle X
\right\rangle / I_{p+1}$ for all $p \geq 1$ under the standard diagonal action.
We give a bound on the values of partitions $\lambda$ such that the irreducible
$\mathrm{GL}(n, K)$-module $V_{\lambda}$ appears in the decomposition of
$K\left\langle X \right\rangle / I_{p+1}$ as a $\mathrm{GL}(n, K)$-module. As
an application, we take $K = \mathbb{C}$ and we consider the algebra of
invariants $(\mathbb{C}\left\langle X \right\rangle / I_{p+1})^G$ for $G =
\mathrm{SL}(n, \mathbb{C})$, $\mathrm{O}(n, \mathbb{C})$, $\mathrm{SO}(n,
\mathbb{C})$, or $\mathrm{Sp}(2s, \mathbb{C})$ (for $n=2s$). By a theorem of
Domokos and Drensky, $(\mathbb{C}\left\langle X \right\rangle / I_{p+1})^G$ is
finitely generated. We give an upper bound on the degree of generators of
$(\mathbb{C}\left\langle X \right\rangle / I_{p+1})^G$ in a minimal generating
set. In a similar way, we consider also the algebra of invariants
$(\mathbb{C}\left\langle X \right\rangle / I_{p+1})^{G}$, where
$G=\mathrm{UT}(n, \mathbb{C})$, and give an upper bound on the degree of
generators in a minimal generating set. These results provide useful
information about the invariants in $\mathbb{C}\left\langle X \right\rangle^G$
from the point of view of Classical Invariant Theory. In particular, for all
$G$ as above we give a criterion when a $G$-invariant of
$\mathbb{C}\left\langle X \right\rangle$ belongs to $I_p$.


  The ongoing miniaturization of semiconductor lasers has enabled ultra-low
threshold devices and even provided a path to approach thresholdless lasing
with linear input-output characteristics. Such nanoscale lasers have initiated
a discourse on the origin of the physical mechanisms involved and their
boundaries, such as the required photon number, the importance of optimized
light confinement in a resonator and mode-density enhancement. Here, we
investigate high-$\beta$ metal-clad coaxial nanolasers, which facilitate
thresholdless lasing. We experimentally and theoretically investigate both the
conventional lasing characteristics, as well as the photon statistics of the
emitted light. While the former lacks adequate information to determine the
threshold to coherent radiation, the latter reveals a finite threshold pump
power. Our work clearly highlights an important and often misunderstood aspect
of high-$\beta$ lasers, namely that a thresholdless laser does have a finite
threshold pump power and must not be confused with a hypothetical zero
threshold laser.


  Field theoretical scheme of regular Big Bang in 4-dimensional physical
space-time, built in the framework of gauge approach to gravitation, is
discussed. Regular bouncing character of homogeneous isotropic cosmological
models is ensured by gravitational repulsion effect at extreme conditions
without quantum gravitational corrections. The most general properties of
regular inflationary cosmological models are examined. Developing theory is
valid, if energy density of gravitating matter is positive and energy dominance
condition is fulfilled.


  Given the particle content of the standard model without and with a
right-handed neutrino, the requirement that all anomalies cancel singles out a
set of possible global symmetries which can be gauged. I review this topic and
propose a new gauge symmetry B - 3L_tau in the context of the minimal standard
model consisting of the usual three families of quarks and leptons plus just
one nu_R. The many interesting phenomenological consequences of this hypothesis
are briefly discussed.


  Measuring instruments, especially ones that observe continually over time,
have a reality to them that is independent of the states that stimulate their
senses. This is the Principle of Instrument Autonomy. Although the mathematical
concept of an instrument implicitly embodies this principle, the conventional
analysis of continual observation has become overwhelmingly focused on state
evolution rather than on descriptions of instruments themselves. Because of
this, it can be hard to appreciate that an instrument that observes for a
finite amount of time has an evolution of its own, a stochastic evolution that
precedes the Born rule and Schr\"odinger equation of the measured system. In
this article, the two most established of the continually observing
instruments, the Srinivas-Davies photodetector and the Goetsch-Graham-Wiseman
heterodyne detector, are reviewed with an emphasis on the autonomous instrument
evolution they define, made explicit by application of the recently introduced
Kraus-operator distribution function. It is then pointed out how the heterodyne
instrument evolution is a complete alternative to the original idea of energy
quantization, where the usual ideas of \emph{temperature} and \emph{energy} of
a \emph{state} are replaced by the \emph{time} and \emph{positivity} of the
\emph{instrument}.


  We analyze the capacity scaling laws of clustered ad hoc networks in which
nodes are distributed according to a doubly stochastic shot-noise Cox process.
We identify five different operational regimes, and for each regime we devise a
communication strategy that allows to achieve a throughput to within a
poly-logarithmic factor (in the number of nodes) of the maximum theoretical
capacity.


  The application of evolution in the digital realm, with the goal of creating
artificial intelligence and artificial life, has a history as long as that of
the digital computer itself. We illustrate the intertwined history of these
ideas, starting with the early theoretical work of John von Neumann and the
pioneering experimental work of Nils Aall Barricelli. We argue that
evolutionary thinking and artificial life will continue to play an integral
role in the future development of the digital world.


  Visual grounding aims to align visual information of specific regions of
images with corresponding natural language expressions. Current visual
grounding methods leverage pre-trained visual and language backbones
independently to obtain visual features and linguistic features. Although these
two types of features are then fused through elaborately designed networks, the
heterogeneity of the features renders them unsuitable for multi-modal
reasoning. This problem arises from the domain gap between the single-modal
pre-training backbones used in current visual grounding methods, which can
hardly be bridged by the traditional end-to-end training method. To alleviate
this, our work proposes an Empowering Pre-trained Model for Visual Grounding
(EpmVG) framework, which distills a multimodal pre-trained model to guide the
visual grounding task. EpmVG relies on a novel cross-modal distillation
mechanism that can effectively introduce the consistency information of images
and texts from the pre-trained model, reducing the domain gap in the backbone
networks, and thereby improving the performance of the model in the visual
grounding task. Extensive experiments have been conducted on five
conventionally used datasets, and the results demonstrate that our method
achieves better performance than state-of-the-art methods.


  This paper describes a topological approach to generating families of open-
and closed-loop walking gaits for underactuated 2D and 3D biped walkers subject
to configuration inequality constraints, physical holonomic constraints
(e.g.,closed-loop linkages), and virtual holonomic constraints (user-defined
constraints enforced through feedback control). Our method constructs
implicitly-defined manifolds of feasible periodic gaits within a
state-time-control space that parameterizes the biped's hybrid trajectories.
Since equilibrium configurations of the biped often belong to such manifolds,
we use equilibria as "templates" from which to grow the gait families.
Equilibria are reliable seeds for the construction of gait families,
eliminating the need for random, intuited, or bio-inspired initial guesses at
feasible trajectories in an optimization framework. We demonstrate the approach
on several 2D and 3D biped walkers.


  In this paper we study finite element discretizations of a surface
vector-Laplace eigenproblem. We consider two known classes of finite element
methods, namely one based on a vector analogon of the Dziuk-Elliott surface
finite element method and one based on the so-called trace finite element
technique. A key ingredient in both classes of methods is a penalization method
that is used to enforce tangentiality of the vector field in a weak sense. This
penalization and the perturbations that arise from numerical approximation of
the surface lead to essential nonconformities in the discretization of the
variational formulation of the vector-Laplace eigenproblem. We present a
general abstract framework applicable to such nonconforming discretizations of
eigenproblems. Error bounds both for eigenvalue and eigenvector approximations
are derived that depend on certain consistency and approximability parameters.
Sharpness of these bounds is discussed. Results of a numerical experiment
illustrate certain convergence properties of such finite element
discretizations of the surface vector-Laplace eigenproblem.


  It is known that the norm map N_G for a finite group G acting on a ring R is
surjective if and only if for every elementary abelian subgroup E of G the norm
map N_E for E is surjective. Equivalently, there exists an element x_G in R
with N_G(x_G) = 1 if and only for every elementary abelian subgroup E there
exists an element x_E in R such that N_E(x_E) = 1. When the ring R is
noncommutative, it is an open problem to find an explicit formula for x_G in
terms of the elements x_E. In this paper we present a method to solve this
problem for an arbitrary group G and an arbitrary group action on a ring.Using
this method, we obtain a complete solution of the problem for the quaternion
and the dihedral 2-groups,and for a group of order 27. We also show how to
reduce the problem to the class of (almost) extraspecial p-groups.


  The double fractional quantum Hall system of spin 1/2 electrons is
numerically studied to predict that there exists a novel spin-unpolarized
quantum liquid specific to the multi-species system, which exemplifies a link
between the spin state and the inter-layer electron correlation. Even when the
ground state is spin-polarized, the lowest charge-excitation mode involves the
spin when the interlayer tunneling is considered.


  Discrete Morse theory, a cell complex-analog to smooth Morse theory, has been
developed over the past few decades since its original formulation by Robin
Forman in 1998. In particular, discrete gradient vector fields on simplicial
complexes capture important features of discrete Morse functions. We prove that
the characteristic polynomials of the Laplacian matrices of a simplicial
complex are generating functions for discrete gradient vector fields of
discrete Morse functions when the complex is either a graph or a triangulation
of an orientable manifold. Furthermore, we provide a full characterization of
the correspondence between rooted forests in higher dimensions and discrete
gradient vector fields.


  We study the nonparametric estimators of the infinitesimal coefficients of
the second-order jump-diffusion models. Under the mild conditions, we obtain
the weak consistency and the asymptotic normalities of the estimators.


  Deception is a technique to mislead human or computer systems by manipulating
beliefs and information. Successful deception is characterized by the
information-asymmetric, dynamic, and strategic behaviors of the deceiver and
the deceivee. This paper proposes a game-theoretic framework of a deception
game to model the strategic behaviors of the deceiver and deceivee and
construct strategies for both attacks and defenses over a continuous
one-dimensional information space. We use the signaling game model to capture
the information-asymmetric, dynamic, and strategic behaviors of deceptions by
modeling the deceiver as a privately-informed player called sender and the
deceivee as an uninformed player called receiver. We characterize perfect
Bayesian Nash equilibrium (PBNE) solution of the game and study the
deceivability. We highlight the condition of deceivee's knowledge enhancement
through evidences to maintain the equilibrium and analyze the impacts of direct
deception costs and players' conflict of interest on the deceivability.


  We study output reference tracking for unknown continuous-time systems with
arbitrary relative degree. The control objective is to keep the tracking error
within predefined time-varying bounds while measurement data is only available
at discrete sampling times. To achieve the control objective, we propose a
two-component controller. One part is a recently developed sampled-data
zero-order hold controller, which achieves reference tracking within prescribed
error bounds. To further improve the control signal, we explore the system
dynamics via input-output data, and include as the second component a
data-driven MPC scheme based on Willems et al.'s fundamental lemma. This
combination yields significantly improved input signals as illustrated by a
numerical example.


  In recent years, pretrained models revolutionized the paradigm of natural
language understanding (NLU), where we append a randomly initialized
classification head after the pretrained backbone, e.g. BERT, and finetune the
whole model. As the pretrained backbone makes a major contribution to the
improvement, we naturally expect a good pretrained classification head can also
benefit the training. However, the final-layer output of the backbone, i.e. the
input of the classification head, will change greatly during finetuning, making
the usual head-only pretraining (LP-FT) ineffective. In this paper, we find
that parameter-efficient tuning makes a good classification head, with which we
can simply replace the randomly initialized heads for a stable performance
gain. Our experiments demonstrate that the classification head jointly
pretrained with parameter-efficient tuning consistently improves the
performance on 9 tasks in GLUE and SuperGLUE.


  We consider joint detection of co-channel signals---specifically, signals
which do not possess a natural separability due to, for example, the multiple
access technique or the use of multiple antennas. Iterative joint detection and
decoding is a well known approach for utilizing the error correction code to
improve detection performance. However, the joint maximum a posteriori
probability (MAP) detector may be prohibitively complex, especially in a
multipath channel. In this paper, we present an approximation to the joint MAP
detector motivated by a factor graph model of the received signal. The proposed
algorithm is designed to approximate the joint MAP detector as closely as
possible within the computational capability of the receiver.


  Certain static soliton configurations of gauge fields in 4+1 dimensions
correspond to the instanton in 4-Euclidean dimensions ``turned on its side,''
becoming a monopole in 4+1. The periodic instanton solution can be used with
the method of images to construct solutions satisfying D-brane boundary
conditions. The $\theta$-term on the brane becomes a topological current
source, yielding an emission amplitude for monopoles into the bulk. Instantons
have a novel reinterpretation in terms of monopole exchange between branes.


  We consider distributed inference in social networks where a phenomenon of
interest evolves over a given social interaction graph, referred to as the
\emph{social digraph}. For inference, we assume that a network of agents
monitors certain nodes in the social digraph and no agent may be able to
perform inference within its neighborhood; the agents must rely on inter-agent
communication. The key contributions of this paper include: (i) a novel
construction of the distributed estimator and distributed observability from
the first principles; (ii) a graph-theoretic agent classification that
establishes the importance and role of each agent towards inference; (iii)
characterizing the necessary conditions, based on the classification in (ii),
on the agent network to achieve distributed observability. Our results are
based on structured systems theory and are applicable to any parameter choice
of the underlying system matrix as long as the social digraph remains fixed. In
other words, any social phenomena that evolves (linearly) over a
structure-invariant social digraph may be considered--we refer to such systems
as Liner Structure-Invariant (LSI). The aforementioned contributions,
(i)--(iii), thus, only require the knowledge of the social digraph (topology)
and are independent of the social phenomena. We show the applicability of the
results to several real-wold social networks, i.e. social influence among
monks, networks of political blogs and books, and a co-authorship graph.


  Loss functions are widely used to compare several competing forecasts.
However, forecast comparisons are often based on mismeasured proxy variables
for the true target. We introduce the concept of exact robustness to
measurement error for loss functions and fully characterize this class of loss
functions as the Bregman class. For such exactly robust loss functions,
forecast loss differences are on average unaffected by the use of proxy
variables and, thus, inference on conditional predictive ability can be carried
out as usual. Moreover, we show that more precise proxies give predictive
ability tests higher power in discriminating between competing forecasts.
Simulations illustrate the different behavior of exactly robust and non-robust
loss functions. An empirical application to US GDP growth rates demonstrates
that it is easier to discriminate between forecasts issued at different
horizons if a better proxy for GDP growth is used.


  We develop an axiomatic set theory -- the Theory of Hyperfinite Sets THS,
which is based on the idea of existence of proper subclasses of big finite
sets. We demonstrate how theorems of classical continuous mathematics can be
transfered to THS, prove consistency of THS and present some applications.


  Recently there has been a proposal for modified gravitational f(R) actions
which include a direct coupling between the matter action and the Ricci scalar,
R. Of particular interest is the specific case where both the action and the
coupling are linear in R. It is shown that such an action leads to a theory of
gravity which includes higher order derivatives of the matter fields without
introducing more dynamics in the gravity sector and, therefore, cannot be a
viable theory for gravitation.


  Artificial Intelligence (AI)-driven defect inspection is pivotal in
industrial manufacturing. Yet, many methods, tailored to specific pipelines,
grapple with diverse product portfolios and evolving processes. Addressing
this, we present the Incremental Unified Framework (IUF), which can reduce the
feature conflict problem when continuously integrating new objects in the
pipeline, making it advantageous in object-incremental learning scenarios.
Employing a state-of-the-art transformer, we introduce Object-Aware
Self-Attention (OASA) to delineate distinct semantic boundaries. Semantic
Compression Loss (SCL) is integrated to optimize non-primary semantic space,
enhancing network adaptability for novel objects. Additionally, we prioritize
retaining the features of established objects during weight updates.
Demonstrating prowess in both image and pixel-level defect inspection, our
approach achieves state-of-the-art performance, proving indispensable for
dynamic and scalable industrial inspections. Our code will be released at
\url{https://github.com/jqtangust/IUF}.