  With the development of technological progress, mining on asteroids is
becoming a reality. This paper focuses on how to distribute asteroid mineral
resources in a reasonable way to ensure global equity. To distribute asteroid
resources fairly, 7 primary indicators and 20 secondary indicators are
introduced to build a mathematical model to evaluate global equity and the
weights are given by Analytic Hierarchy Process (AHP). Then Global Equity
Score(GES) Model based on 12 primary indicators and 40 secondary indicators is
built and TOPSIS method is applied to rank all countries. A t-distribution
probability density function is applied to simulate the rate of asteroid
mining. The Backward Algorithm is applied to quantitatively measure the impact
of changing indicators on global equity. Then Pearson correlation coefficient
analysis is conducted for each indicator, and t-test is performed lastly. The
results demonstrate that asteroid mining promotes global equity that poor
countries can be allocated slightly more mineral resources, and a schedule of
the implementation of each measure is given. To gain more insight, sensitivity
analysis is conducted and the results demonstrate that scores vary less than
7%. It can be concluded that our GES model have great potential as its
robustness, accuracy and strengths.


  Mobile health studies often collect multiple within-day self-reported
assessments of participants' behavior and well-being on different scales such
as physical activity (continuous), pain levels (truncated), mood states
(ordinal), and life events (binary). These assessments, when indexed by time of
day, can be treated as functional data of different types - continuous,
truncated, ordinal, and binary. We develop a functional principal component
analysis that deals with all four types of functional data in a unified manner.
It employs a semiparametric Gaussian copula model, assuming a generalized
latent non-paranormal process as the underlying mechanism for these four types
of functional data. We specify latent temporal dependence using a covariance
estimated through Kendall's tau bridging method, incorporating smoothness
during the bridging process. Simulation studies demonstrate the method's
competitive performance under both dense and sparse sampling conditions. We
then apply this approach to data from 497 participants in the National
Institute of Mental Health Family Study of the Mood Disorder Spectrum to
characterize within-day temporal patterns of mood differences among individuals
with major mood disorder subtypes, including Major Depressive Disorder, Type 1,
and Type 2 Bipolar Disorder.


  The three-dimensional parallel spinor flow is the evolution flow defined by a
parallel spinor on a globally hyperbolic Lorentzian four-manifold. We prove
that, despite the fact that Lorentzian metrics admitting parallel spinors are
not necessarily Ricci flat, the parallel spinor flow preserves the vacuum
momentum and Hamiltonian constraints and therefore the Einstein and parallel
spinor flows coincide on common initial data. Using this result, we provide an
initial data characterization of parallel spinors on Ricci flat Lorentzian
four-manifolds, which in turn yields the first initial data characterization of
Ricci-flat pp-waves. Furthermore, we explicitly solve the left-invariant
parallel spinor flow on simply connected Lie groups, obtaining along the way
necessary and sufficient conditions for the flow to be immortal. These are, to
the best of our knowledge, the first non-trivial examples of evolution flows of
parallel spinors. Finally, we use some of these examples to construct families
of $\eta\,$-Einstein cosymplectic structures and to produce solutions to the
left-invariant Ricci flow in three dimensions. This suggests the intriguing
possibility of using first-order hyperbolic spinorial flows to construct
special solutions of curvature flows in Riemannian signature.


  We study the competitive action of magnetic field, Coulomb repulsion and
space curvature on the motion of a charged particle. The three types of
interaction are characterized by three basic lengths: l_{B} the magnetic
length, l_{0} the Bohr radius and R the radius of the sphere. The energy
spectrum of the particle is found by solving a Schr\"odinger equation of the
Heun type, using the technique of continued fractions. It displays a rich set
of functioning regimes where ratios \frac{R}{l_{B}} and \frac{R}{l_{0}} take
definite values.


  Given an increasing graph property $\cal F$, the strong Avoider-Avoider $\cal
F$ game is played on the edge set of a complete graph. Two players, Red and
Blue, take turns in claiming previously unclaimed edges with Red going first,
and the player whose graph possesses $\cal F$ first loses the game. If the
property $\cal F$ is "containing a fixed graph $H$", we refer to the game as
the $H$ game.
  We prove that Blue has a winning strategy in two strong Avoider-Avoider
games, $P_4$ game and ${\cal CC}_{>3}$ game, where ${\cal CC}_{>3}$ is the
property of having at least one connected component on more than three
vertices.
  We also study a variant, the strong CAvoider-CAvoider games, with additional
requirement that the graph of each of the players must stay connected
throughout the game. We prove that Blue has a winning strategy in the strong
CAvoider-CAvoider games $S_3$ and $P_4$, as well as in the $Cycle$ game, where
the players aim at avoiding all cycles.


  The modification of the ac conductivity and the complex permittivity of
conducting polypyrrole was monitored throughout a two years thermal aging at
343K. Reduction of the cross-over frequency is correlated with the degradation
of dc-conductivity, while the ac conductivity region corresponding to the
so-called 'universal' dielectric relaxation remains practically invariant
during the first year of ageing, which implies a collective co-operativity
among multiple degradation processes that yield a practically time-independent
effective disordered environment. A broad dielectric loss peak recorded in
fresh specimens splits into two distinct relaxations for intermediate stages of
the annealing process. The ageing-time evolution of the dc component and the
relaxations are qualitatively analysed and time constants are determined.


  We study the spin-dependent quark distributions at large transverse momentum.
We derive their transverse momentum behaviors in the collinear factorization
approach in this region. We further calculate the angular distribution of the
Drell-Yan lepton pair production with polarized beams and present the results
in terms of the collinear twist-three quark-gluon correlation functions. In the
intermediate transverse momentum region, we find that the two pproaches: the
collinear factorization and the transverse momentum dependent factorization
approaches are consistent in the description of the lepton pair angular
distributions.


  We explore different design choices for injecting noise into generative
adversarial networks (GANs) with the goal of disentangling the latent space.
Instead of traditional approaches, we propose feeding multiple noise codes
through separate fully-connected layers respectively. The aim is restricting
the influence of each noise code to specific parts of the generated image. We
show that disentanglement in the first layer of the generator network leads to
disentanglement in the generated image. Through a grid-based structure, we
achieve several aspects of disentanglement without complicating the network
architecture and without requiring labels. We achieve spatial disentanglement,
scale-space disentanglement, and disentanglement of the foreground object from
the background style allowing fine-grained control over the generated images.
Examples include changing facial expressions in face images, changing beak
length in bird images, and changing car dimensions in car images. This
empirically leads to better disentanglement scores than state-of-the-art
methods on the FFHQ dataset.


  We report on linear and non-linear dielectric property measurements of BaTiO3
- CoFe2O4 (BTO-CFO) ferroelectro-magnetic nano-composites and pure BaTiO3 and
CoFe2O4 samples with Scanning Near Field Microwave Microscopy. The permittivity
scanning image with spatial resolution on the micro-meter scale shows that the
nano-composites have very uniform quality with an effective dielectric constant
\epsilon_r = 140 +/- 6.4 at 3.8 GHz and room temperature. The temperature
dependence of dielectric permittivity shows that the Curie temperature of pure
BTO was shifted by the clamping effect of the MgO substrate, whereas the Curie
temperature shift of the BTO ferroelectric phase in BTO-CFO composites is less
pronounced, and if it exists at all, would be mainly caused by the CFO.
Non-linear dielectric measurements of BTO-CFO show good ferroelectric
properties from BTO.


  The use of the dimensional regularization in the on-mass-shell
renormalization scheme sometimes fails to locally cancel the ultraviolet
divergence for a class of diagrams in the two-loop order. The mechanism is
discussed based on an example with explicit computation.


  We present a series of systematic abundance measurements for a group of hot
DA white dwarfs in the temperature range 20,000-75,000K, based on far-UV
spectroscopy with STIS on HST, IUE and FUSE. Using our latest heavy element
blanketed non-LTE stellar atmosphere calculations we have addressed the heavy
element abundance patterns for the hottest stars for the first time, showing
that they are similar to objects like G191-B2B. The abundances observed in the
cooler (<50,000K) white dwarfs are something of a mystery. Some of the patterns
(e.g. REJ1032) can be explained by self-consistent levitation-diffusion
calculations but there is then a serious difficulty in understanding the
appearance of the apparently pure H atmospheres. We also report the detection
of photospheric HeII in the atmosphere of WD2218+706.


  We investigate transport through a mononuclear transition-metal complex with
strong tunnel coupling to two electrodes. The ground state of this molecule is
a singlet while the first excited state is a triplet. We show that a modulation
of the tunnel-barrier due to a molecular distortion which couples to the
tunneling induces a Kondo-effect, provided the discrete vibrational energy
compensates the singlet/triplet gap. We discuss the single-phonon and
two-phonon assisted co-tunneling and possible experimental realization of the
theory.


  Dimensional reduction of maximal supergravity to two dimensions leads to an
infinite-dimensional (non-local) symmetry group W x E_9 which has a simpler
action when the bosonic fields are dualised to an infinite tower of dual
potentials. We construct a doubled-valued representation of its compact
subgroup K x K(E_9) and we show that off-shell fermions take place in this
infinite-dimensional representation. The equations of motion can be written in
a fully gauge-covariant way as a selfduality condition for the
infinite-dimensional fields. The W x E_9 global symmetry is thus manifest. The
linear system associated to the theory is recovered in a triangular gauge.
Finally we provide supersymmetry transformations for off-shell fields.


  Since the 1940's there has been an interest in the question why social
networks often give rise to two antagonistic factions. Recently a dynamical
model of how and why such a balance might occur was developed. This note
provides an introduction to the notion of social balance and a new (and
simplified) analysis of that model. This new analysis allows us to choose
general initial conditions, as opposed to the symmetric ones previously
considered. We show that for general initial conditions, four factions will
evolve instead of two. We characterize the four factions, and we give an idea
of their relative sizes.


  This note contains some comments on a recent paper by Friedman on
two-component spinors in spacetimes which do not admit a time-orientation, and
is intended to clarify the relation of the work reported in that paper to
previous literature.


  We performed numerical simulations of supersonic isothermal turbulence driven
by mostly compressive large-scale forcing, using both a static grid and
adaptive mesh refinement with an effective resolution N=768^3. After a
transient phase dominated by shocks, turbulence evolves into a steady state
with an RMS Mach number about 2.5, in which cloud-like structures of over-dense
gas are surrounded by highly rarefied gas. The index of the turbulence energy
spectrum function beta = 2.0 in the shock-dominated phase. As the flow
approaches statistical equilibrium, the spectrum flattens, with beta = 1.9. For
the scaling exponent of the root mean square velocity fluctuation, we obtain
gamma = 0.43 from the velocity structure functions of second order. These
results are well within the range of observed scaling properties for the
velocity dispersion in molecular clouds. Calculating structure functions of
order p=1,...,5, we find for all scaling exponents significant deviations from
the Kolmogorov-Burgers model proposed by Boldyrev. Our results are very well
described by a general log-Poisson model with a higher degree of intermittency,
which implies an influence of the forcing on the scaling properties. Contrary
to previous numerical results for isothermal turbulence, we obtain a skewed
probability density function of the mass density fluctuations that is not
consistent with log-normal statistics and entails a substantially higher
fraction of mass in the density peaks than implied by the Padoan-Nordlund
relation between the variance of the density fluctuations and the Mach number.
In conclusion, it seems necessary to account for the production mechanism of
turbulence in the ISM.


  Quantum systems are the ultimate touchstone for the production of random
sequences of numbers. Spatially spread entangled systems allow the generation
of identical random sequences in remote locations. The impossibility of
observing a quantum system, without disturbing it, ensures that the messages
encoded using these sequences cannot be eavesdropped. This is the basis of
Quantum Key Distribution. It is then of crucial importance knowing whether the
sequences generated in the practice by spatially spread entangled states are
truly random, or not. Yet, that knowledge is not immediate. One of the
obstacles is the very definition of randomness. Statistical randomness is
related with the frequency of occurrence of strings of data. On the other hand,
algorithmic randomness is related with the compressibility of the sequence,
what is given by Kolmogorov complexity. We analyze sequences generated by
entangled pairs of photons focusing on an estimation of their complexity.


  IC-planar graphs are those graphs that admit a drawing where no two crossed
edges share an end-vertex and each edge is crossed at most once. They are a
proper subfamily of the 1-planar graphs. Given an embedded IC-planar graph $G$
with $n$ vertices, we present an $O(n)$-time algorithm that computes a
straight-line drawing of $G$ in quadratic area, and an $O(n^3)$-time algorithm
that computes a straight-line drawing of $G$ with right-angle crossings in
exponential area. Both these area requirements are worst-case optimal. We also
show that it is NP-complete to test IC-planarity both in the general case and
in the case in which a rotation system is fixed for the input graph.
Furthermore, we describe a polynomial-time algorithm to test whether a set of
matching edges can be added to a triangulated planar graph such that the
resulting graph is IC-planar.


  Quantum entanglement, a key resource in quantum information processing, is
reduced by interaction between the quantum system concerned and its unavoidable
noisy environment. Therefore it is of particular importance to study the
dynamical properties of entanglement in open quantum systems. In this work, we
mainly focus on two qubits coupled to an adjustable environment, namely a
semi-infinite transmission line. The two qubits' relaxations, through
individual channels or collective channel or both, can be adjusted by the
qubits' transition frequencies. We examine entanglement dynamics in this model
system with initial Werner state, and show that the phenomena of entanglement
sudden death and revival can be observed. Due to the hardness of preparing the
Werner state experimentally, we introduce a new type of entangled state called
pseudo-Werner state, which preserves as much entangling property as the Werner
state, and more importantly, is experiment friendly. Furthermore, we provide
detailed procedures for generating pseudo-Werner state and studying
entanglement dynamics with it, which can be straightforwardly implemented in a
superconducting waveguide quantum electrodynamics system.


  The physical implementation of holonomic quantum computation is challenging
due to the needed complex controllable interactions in multilevel quantum
systems. Here we propose to implement nonadiabatic holonomic quantum
computation with conventional capacitive coupled superconducting transmon
qubits. A universal set of holonomic gates is constructed with the help of the
interaction with an auxiliary qubit rather than relying on delicate control
over an auxiliary level of multilevel quantum systems. Explicitly, these
quantum gates are realized by tunable interactions in an all-resonant way,
which leads to high-fidelity gate operations. In this way, the distinct merit
of our scheme is that we use only the lowest two levels of a transmon to form
the qubit states. In addition, the auxiliary qubits are in their ground states
before and after every gate operation, so that the holonomic gates can be
constructed successively. Therefore, our scheme provides a promising method
towards the practical realization of high-fidelity nonadiabatic holonomic
quantum computation.


  The problem of keyword spotting i.e. identifying keywords in a real-time
audio stream is mainly solved by applying a neural network over successive
sliding windows. Due to the difficulty of the task, baseline models are usually
large, resulting in a high computational cost and energy consumption level. We
propose a new method called SANAS (Stochastic Adaptive Neural Architecture
Search) which is able to adapt the architecture of the neural network
on-the-fly at inference time such that small architectures will be used when
the stream is easy to process (silence, low noise, ...) and bigger networks
will be used when the task becomes more difficult. We show that this adaptive
model can be learned end-to-end by optimizing a trade-off between the
prediction performance and the average computational cost per unit of time.
Experiments on the Speech Commands dataset show that this approach leads to a
high recognition level while being much faster (and/or energy saving) than
classical approaches where the network architecture is static.


  We present the design of a high repetition rate MeV energy ultrafast electron
diffraction instrument based on a DC photoelectron gun and an SRF linac with
multiple independently controlled accelerating and bunching cavities. The
design is based on the existing Cornell photoinjector, which can readily be
applied to the presented findings. Using particle tracking simulations in
conjunction with multiobjective genetic algorithm optimization, we explore the
smallest bunch lengths, emittance, and probe spot sizes achievable. We present
results for both stroboscopic conditions (with single electrons per pulse) and
with $10^5$ electrons/bunch which may be suitable for single-shot diffraction
images. In the stroboscopic case, the flexibility provided by the many-cavity
bunching and acceleration allows for longitudinal phase space linearization
without a higher harmonic field, providing sub-fs bunch lengths at the sample.
Given low emittance photoemission conditions, these small bunch lengths can be
maintained with probe transverse sizes at the single micron scale and below. In
the case of $10^5$ electrons per pulse, we simulate state-of the art 5D
brightness conditions: rms bunch lengths of 10 fs with 3 nm normalized
emittances, while now permitting repetition rates as high as 1.3 GHz. Finally,
to aid in the design of new SRF-based UED machines, we simulate the trade-off
between the number of cavities used and achievable bunch length and emittance.


  Topics generated by topic models are usually represented by lists of $t$
terms or alternatively using short phrases and images. The current
state-of-the-art work on labeling topics using images selects images by
re-ranking a small set of candidates for a given topic. In this paper, we
present a more generic method that can estimate the degree of association
between any arbitrary pair of an unseen topic and image using a deep neural
network. Our method has better runtime performance $O(n)$ compared to $O(n^2)$
for the current state-of-the-art method, and is also significantly more
accurate.


  The multifractal spectra of daily foreign exchange rates for US dollar (USD),
the British Pound (GBP), the Euro (Euro) and the Japanese Yen (Yen) with
respect to the Indian Rupee are analysed for the period 6th January 1999 to
24th July 2018. We observe that the time series of logarithmic returns of all
the four exchange rates exhibit features of multifractality. Next, we research
the source of the observed multifractality. For this, we transform the return
series in two ways: a) We randomly shuffle the original time series of
logarithmic returns and b) We apply the process of phase randomisation on the
unchanged series. Our results indicate in the case of the US dollar the source
of multifractality is mainly the fat tail. For the British Pound and the Euro,
we see the long-range correlations between the observations and the thick tails
of the probability distribution give rise to the observed multifractal
features, while in the case of the Japanese Yen, the origin of the multifractal
nature of the return series is mostly due to the broad tail.


  We show, under a very general set of assumptions, that pairs of identical
particle detectors in spacelike separation, such as atomic probes, can only
harvest entanglement from the vacuum state of a quantum field when they have a
non-zero energy gap. Furthermore, we show that degenerate probes are strongly
challenged to become entangled through their interaction through scalar and
electromagnetic fields even in full light-contact. We relate these results to
previous literature on remote entanglement generation and entanglement
harvesting, giving insight into the energy gap's protective role against local
noise, which prevents the detectors from getting entangled through the
interaction with the field.


  We give a necessary and sufficient criterion when a normal CP-map on a von
Neumann algebra admits a restriction to a maximal commutative subalgebra. We
apply this result to give a far reaching generalization of Rebolledo's
sufficient criterion for the Lindblad generator of a Markov semigroup on B(G).


  We consider the micellization of block copolymers in solution, employing self
consistent field theory with an additional constraint that permits the
examination of intermediate structures. From the information for an isolated
micelle (structure, binding energy, free energy) we describe how the global
thermodynamics of these systems can be obtained, which can be used to build a
realistic phase diagram; the role of translational entropy must be addressed in
this regard.


  The hot massive luminous blue variables (LBVs) represent an important
evolutionary phase of massive stars. Here, we report the discovery of a new LBV
-- LAMOST J0037+4016 in the distant outskirt of the Andromeda galaxy. It is
located in the south-western corner (a possible faint spiral arm) of M31 with
an unexpectedly large projection distance of $\sim$ 22 kpc from the center. The
optical light curve shows a 1.2 mag variation in $V$ band and its outburst and
quiescence phases both last over several years. The observed spectra indicate
an A-type supergiant at epoch close to the outburst phase and a hot B-type
supergiant with weak [Fe II] emission lines at epoch of much dimmer brightness.
The near-infrared color-color diagram further shows it follows the distribution
of Galactic and M31 LBVs rather than B[e] supergiants. All the existing data
strongly show that LAMOST J0037+4016 is an LBV. By spectral energy distribution
fitting, we find it has a luminosity ($4.42 \pm 1.64$)$\times 10^5$ $L_{\odot}$
and an initial mass $\sim 30$ $M_{\odot}$, indicating its nature of less
luminosity class of LBV.


  We revisit the model of a Brownian particle in a heat bath submitted to an
actively controlled force proportional to the velocity that leads to thermal
noise reduction (cold damping). We investigate the influence of the continuous
feedback on the fluctuations of the total entropy production and show that the
explicit expression of the detailed fluctuation theorem involves different
dynamics and observables in the forward and backward processes. As an
illustration, we study the analytically solvable case of a harmonic oscillator
and calculate the characteristic function of the entropy production in a
nonequilibrium steady state. We then determine the corresponding large
deviation function which results from an unusual interplay between 'boundary'
and 'bulk' contributions.


  In this paper, we generalize Bernoulli-Goss polynomials, and give a criterion
on the divisibility of zeta functions of cyclotomic function fields. As an
application of our criterion, for a given polynomial $f(u)$, we prove that
there are infinitely many cyclotomic function fields whose zeta polynomial is
divided by $f(u)$.


  The series of nickel-oxide compounds LaNiO$_3$ (formal Ni$(d^7)$),
La$_2$NiO$_4$ (formal Ni$(d^8)$) and LaNiO$_2$ (formal Ni$(d^9)$) is
investigated by first-principles many-body, using a combination of density
functional theory, self-interaction correction and dynamical mean-field theory.
The characteristics of these different nickelates, in good agreement with
available experimental data, is revealed by employing a compound-independent
choice for the local Coulomb interactions. The dichotomy within the low-energy
dominant Ni-$e_g$ sector of $\{d_{z^2},d_{x^2-y^2}\}$ kind is rising with
growing Ni$(3d)$ filling across the series. An intermediate-coupling scheme for
spin-polarized calculations is introduced, which leads to very weak Ni ordered
moments for the infinite-layer compound LaNiO$_2$ in contrast to the
robust-moment system La$_2$NiO$_4$.


  Spectrum sharing between radars and cellular systems is an emerging area of
research. In this paper, we model channel between a seaborne MIMO radar and
MIMO cellular system. We model a 2D channel to capture the azimuth aspect of
the spectrum sharing scenario. Our channel modeling methodology allows MIMO
radar to place accurate nulls in the azimuth location of base stations (BS),
thus, protecting them from harmful radar interference. We use a projection
based approach, where radar waveform is projected onto null space of channel,
for mitigating radar interference to BSs. This is also known as an approach
based on eigen-nulling which is different from spatial-nulling commonly
employed by radars. We show through simulations that the proposed spatial
channel model allows eigen-nulling which performs superior to traditional
spatial-nulling for interference mitigation. The proposed channel model can be
leveraged to use eigen-nulling that enhances target detection and beampattern
resolution of MIMO radar while mitigating interference to BSs.


  Charged multiplicity distribution in a pseudo-rapidity window is formulated
under the assumption that the charge conservation is satisfied in the full
phase space.
  At first, we analyze measured charged particle multiplicity distributions in
pseudo-rapidity windows in LHC by CMS and ALICE collaborations with the two
probability distributions. One is the convolution of negative binomial and
Poisson distributions, and the other is the Glauber-Lachs formula.
  Each distribution is considered as an analogy of the quantum optics. Next, we
analyze the data with the double GL formulae for $|\eta|<2.4$ at 7 TeV by the
CMS collaboration and for $|\eta|<1.5$ at 8 TeV by the ALICE collaboration to
describe the global structure of measured distributions.


  We propose a novel single-image super-resolution approach based on the
geostatistical method of kriging. Kriging is a zero-bias minimum-variance
estimator that performs spatial interpolation based on a weighted average of
known observations. Rather than solving for the kriging weights via the
traditional method of inverting covariance matrices, we propose a supervised
form in which we learn a deep network to generate said weights. We combine the
kriging weight generation and kriging process into a joint network that can be
learned end-to-end. Our network achieves competitive super-resolution results
as other state-of-the-art methods. In addition, since the super-resolution
process follows a known statistical framework, we are able to estimate bias and
variance, something which is rarely possible for other deep networks.


  We study roughening interfaces with a constant slope that become self
organized critical by a rule that is similar to that of invasion percolation.
The transient and critical dynamical exponents show Galilean invariance. The
activity along the interface exhibits non-trivial power law correlations in
both space and time. The probability distribution of the activity pattern
follows an algebraic relation.


  A fast, hydrodynamic numerical model has been developed on the COMSOL
Multi-physics platform to simulate the evolution and dynamics of charged
particles in gaseous ionization detectors based on the Gaseous Electron
Multipliers (GEM). Effects of using two-dimensional (2D), 2D axisymmetric and
three-dimensional(3D) models of the detectors have been analyzed to choose the
optimum configuration. The chosen model has been used to follow the entire
operating regime of single, double and triple GEM detectors, including
avalanche and streamer mode operations. The accumulation of space charge, its
contribution towards the distortion of the applied electric field and
production of streamers have been investigated in fair detail using the
optimized model.


  The advent of foundation models (FMs) as an emerging suite of AI techniques
has struck a wave of opportunities in computational healthcare. The interactive
nature of these models, guided by pre-training data and human instructions, has
ignited a data-centric AI paradigm that emphasizes better data
characterization, quality, and scale. In healthcare AI, obtaining and
processing high-quality clinical data records has been a longstanding
challenge, ranging from data quantity, annotation, patient privacy, and ethics.
In this survey, we investigate a wide range of data-centric approaches in the
FM era (from model pre-training to inference) towards improving the healthcare
workflow. We discuss key perspectives in AI security, assessment, and alignment
with human values. Finally, we offer a promising outlook of FM-based analytics
to enhance the performance of patient outcome and clinical workflow in the
evolving landscape of healthcare and medicine. We provide an up-to-date list of
healthcare-related foundation models and datasets at
https://github.com/Yunkun-Zhang/Data-Centric-FM-Healthcare .


  Radio-frequency (RF) front-end forms a critical part of any radio system,
defining its cost as well as communication performance. However, these
components frequently exhibit non-ideal behavior, referred to as impairments,
due to the imperfections in the manufacturing/design process. Most of the
designers rely on simplified closed-form models to estimate these impairments.
On the other hand, these models do not holistically or accurately capture the
effects of real-world RF front-end components. Recently, machine learning-based
algorithms have been proposed to estimate these impairments. However, these
algorithms are not capable of estimating multiple RF impairments jointly, which
leads to limited estimation accuracy. In this paper, the joint estimation of
multiple RF impairments by exploiting the relationship between them is
proposed. To do this, a deep multi-task learning-based algorithm is designed.
Extensive simulation results reveal that the performance of the proposed joint
RF impairments estimation algorithm is superior to the conventional individual
estimations in terms of mean-square error. Moreover, the proposed algorithm
removes the need of training multiple models for estimating the different
impairments.


  Maximizing nonlinear light-matter interactions is a primary motive for
compressing laser pulses to achieve ultrashort transform limited pulses. Here
we show how, by appropriately shaping the pulses, resonant multiphoton
transitions can be enhanced significantly beyond the level achieved by
maximizing the pulse's peak intensity. We demonstrate the counterintuitive
nature of this effect with an experiment in a resonant two-photon absorption,
in which, by selectively removing certain spectral bands, the peak intensity of
the pulse is reduced by a factor of 40, yet the absorption rate is doubled.
Furthermore, by suitably designing the spectral phase of the pulse, we increase
the absorption rate by a factor of 7.


  In this paper, we consider the nonlinear Schr\"odinger equation with the
super critical power of nonlinearity in the attractive case. We give a
sufficient condition and a necessary condition to obtain global or blowing up
solutions. These conditions coincide in the critical case, thereby extending
the results of Weinstein. Furthermore, we improve a blow-up condition.


  In this paper, we investigate the differential geometry properties of curves
of constant breadth according to Darboux frame in a given strict Walker
3-manifold. The considered curves are lying on a timelike surface in the Walker
3-manifold.


  Let $G$ be a group with subgroup $H$, and let $(\pi,V)$ be a complex
representation of $G$. The natural action of the normalizer $N$ of $H$ in $G$
on the space $\mathrm{Hom}_H(\pi,\mathbb{C})$ of $H$-invariant linear forms on
$V$, provides a representation $\chi_{\pi}$ of $N$ trivial on $H$, which is a
character when $\mathrm{Hom}_H(\pi,\mathbb{C})$ is one dimensional. If moreover
$G$ is a reductive group over a local field, and $\pi$ is smooth irreducible,
it is an interesting problem to express $\chi_{\pi}$ in terms of the possibly
conjectural Langlands parameter $\phi_\pi$ of $\pi$. In this paper we consider
the following situation: $G=\mathrm{GL}_m(D)$ for $D$ a central division
algebra of dimension $d^2$ over a local field $F$ of characteristic zero, $H$
is the centralizer of a non central element $\delta\in G$ such that $\delta^2$
is in the center of $G$, and $\pi$ has generic Jacquet-Langlands transfer to
$\mathrm{GL}_{md}(F)$. In this setting the space
$\mathrm{Hom}_H(\pi,\mathbb{C})$ is at most one dimensional. When
$\mathrm{Hom}_H(\pi,\mathbb{C})\simeq \mathbb{C}$ and $H\neq N$, we prove that
the value of the $\chi_{\pi}$ on the non trivial class of $\frac{N}{H}$ is
$(-1)^m\epsilon(\phi_\pi)$ where $\epsilon(\phi_\pi)$ is the root number of
$\phi_{\pi}$. Along the way we extend many useful multiplicity one results for
linear and Shalika models to the case of non split $G$. When $F$ is $p$-adic we
also classify standard modules with linear periods and Shalika models, which
are new results even when $D=F$.


  Stylometry, the science of inferring characteristics of the author from the
characteristics of documents written by that author, is a problem with a long
history and belongs to the core task of Text categorization that involves
authorship identification, plagiarism detection, forensic investigation,
computer security, copyright and estate disputes etc. In this work, we present
a strategy for stylometry detection of documents written in Bengali. We adopt a
set of fine-grained attribute features with a set of lexical markers for the
analysis of the text and use three semi-supervised measures for making
decisions. Finally, a majority voting approach has been taken for final
classification. The system is fully automatic and language-independent.
Evaluation results of our attempt for Bengali author's stylometry detection
show reasonably promising accuracy in comparison to the baseline model.


  Metasurfaces have appeared as a versatile platform for miniaturized
functional nonlinear optics due to their design freedom in tailoring
wavefronts. The key factor that limits its application in functional devices is
the low conversion efficiency. Recently, dielectric metasurfaces governed by
either high-quality factor modes (quasi-bound states in the continuum) or Mie
modes, enabling strong light-matter interaction, have become a prolific route
to achieve high nonlinear efficiency. Here, we demonstrate both numerically and
experimentally an effective way of spatial nonlinear phase control by using the
Pancharatnam-Berry phase principle with a high third harmonic conversion
efficiency of $10^{-4}$ $1/W^2$. We find that the magnetic Mie resonance
appears to be the main contributor to the third harmonic response, while the
contribution from the quasi-bound states in the continuum is negligible. This
is confirmed by a phenomenological model based on coupled anharmonic
oscillators. Besides, our metasurface provides experimentally a high
diffraction efficiency (80-90%) in both polarization channels. We show a
functional application of our approach by experimentally reconstructing an
encoded polarization-multiplexed vortex beam array with different topological
charges at the third harmonic frequency with high fidelity. Our approach has
the potential viability for future on-chip nonlinear signal processing and
wavefront control.


  The modulation instability is a focusing mechanism responsible for the
formation of strong wave localizations not only on the water surface, but also
in a variety of nonlinear dispersive media. Such dynamics is initiated from the
injection of side-bands, which translate into an amplitude modulation of the
wave field. The nonlinear stage of unstable wave evolution can be described by
exact solutions of the nonlinear Schr\"odinger equation (NLSE). In that case,
the amplitude modulation of such coherent extreme wave structures is connected
to a particular phase-shift seed in the carrier wave. In this letter, we show
that phase-shifts localization applied to the background, excluding any
amplitude modulation excitation, can indeed trigger extreme events. Such rogue
waves can be for instance generated by considering the parametrization of
fundamental breathers and thus, by seeding only the local phase-shift
information to the regular carrier wave. Our wave tank experiments show an
excellent agreement with the expected NLSE hydrodynamics and confirm that even
though delayed in their evolution, breather-type extreme waves can be generated
from a purely regular wave train. Such novel focusing mechanism awaits
experimental confirmation in other nonlinear media, such optics, plasma, and
Bose-Einstein condensates.


  In this paper, we prove that the nonlocal complex modified Korteweg-de Vries
(mKdV) equation introduced by Ablowitz and Musslimani [Nonlinearity, 29,
915-946 (2016)] is gauge equivalent to a spin-like model. From the gauge
equivalence, one can see that there exists significant difference between the
nonlocal complex mKdV equation and the classical complex mKdV equation. Through
constructing the Darboux transformation(DT) for nonlocal complex mKdV equation,
a variety of exact solutions including dark soliton, W-type soliton, M-type
soliton and periodic solutions are derived.


  This paper introduces Conformal Thresholded Intervals (CTI), a novel
conformal regression method that aims to produce the smallest possible
prediction set with guaranteed coverage. Unlike existing methods that rely on
nested conformal framework and full conditional distribution estimation, CTI
estimates the conditional probability density for a new response to fall into
each interquantile interval using off-the-shelf multi-output quantile
regression. CTI constructs prediction sets by thresholding the estimated
conditional interquantile intervals based on their length, which is inversely
proportional to the estimated probability density. The threshold is determined
using a calibration set to ensure marginal coverage. Experimental results
demonstrate that CTI achieves optimal performance across various datasets.


  In order to detect and characterise cold extended circumstellar dust
originating from collisions of planetesimal bodies in disks, belts, or rings at
Kuiper-Belt distances (30-50 AU or beyond) sensitive submillimetre observations
are essential. Measurements of the flux densities at these wavelengths will
extend existing IR photometry and permit more detailed modelling of the
Rayleigh-Jeans tail of the disks spectral energy distribution (SED),
effectively constraining dust properties and disk extensions. By observing
stars spanning from a few up to several hundred Myr, the evolution of debris
disks during crucial phases of planet formation can be studied. We have
performed 870-micron observations of 22 exo-Kuiper-Belt candidates, as part of
a Large Programme with the LABOCA bolometer at the APEX telescope. Dust masses
(or upper limits) were calculated from integrated 870-micron fluxes, and fits
to the SED of detected sources revealed the fractional dust luminosities
f_dust, dust temperatures T_dust, and power-law exponents beta of the opacity
law. A total of 10 detections with at least 3-sigma significance were made, out
of which five (HD 95086, HD 131835, HD 161868, HD 170773, and HD 207129) have
previously never been detected at submillimetre wavelengths. Three additional
sources are marginally detected with >2.5-sigma significance. The best-fit beta
parameters all lie between 0.1 and 0.8, in agreement with previous results
indicating the presence of grains that are significantly larger than those in
the ISM. From our relatively small sample we estimate f_dust proportional to
t^(-alpha), with alpha~0.8-2.0, and identify an evolution of the characteristic
radial dust distance R_dust that is consistent with the t^(1/3) increase
predicted from models of self-stirred collisions in debris disks.


  In this paper, we present moderately-high resolution (~65 km/s) spectroscopy,
acquired with ESI on Keck II, of 11 ultraluminous infrared galaxies at z < 0.3
from the IRAS 1 Jy sample. The targets were chosen as good candidates to host
galaxy-scale outflows, and most have infrared luminosities dominated by star
formation. We use a chi-squared minimization to fit one- to three-component
profiles to the NaI D interstellar absorption doublet in each object. Assuming
that gas blueshifted by more than 70 km/s relative to the systemic velocity of
the host is outflowing, we detect outflows in 73% of these objects. We adopt a
simple model of a mass-conserving free wind to infer mass outflow rates in the
range (dM/dt)_tot(H) = 13-133 M_sun/yr for galaxies hosting a wind. These
values of (dM/dt)_tot, normalized to the corresponding global star formation
rates inferred from infrared luminosities, are in the range eta = (dM/dt)_tot /
SFR = 0.1-0.7. This is on average a factor of only 10 less than eta from recent
measurements of nearby dwarfs, edge-on spirals, and lower-luminosity infrared
galaxies. Within our sample, we conclude that eta has no dependence on the mass
of the host (parameterized by host galaxy kinematics and absolute R- and
K'-band magnitudes). We also attempt to estimate the average escape fraction
<f_esc> = Sum(dM/dt_esc^i) / Sum(dM/dt_tot^i) and ``ejection efficiency''
<delta> = Sum(dM/dt_esc^i) / Sum(SFR^i) for our sample, which we find to be
\~0.4-0.5 and ~0.1, respectively. The complex absorption-line properties of Mrk
231, an ultraluminous infrared galaxy which is optically classified as a
Seyfert 1, are discussed separately in an appendix.


  Linear arithmetics are extensions of Presburger arithmetic (Pr) by one or
more unary functions, each intended as multiplication by a fixed element
(scalar), and containing the full induction schemes for their respective
languages. In this paper we construct a model M of the 2-linear arithmetic LA_2
(linear arithmetic with two scalars) in which an infinitely long initial
segment of "Peano multiplication" on M is 0-definable. This shows, in
particular, that LA_2 is not model complete in contrast to theories LA_1 and
LA_0=Pr that are known to satisfy quantifier elimination up to disjunctions of
primitive positive formulas. As an application, we show that M, as a discretely
ordered module over the discretely ordered ring generated by the two scalars,
is not NIP, answering negatively a question of Chernikov and Hils.


  We present a new inflation model, known as noncommutative decrumpling
inflation, in which space has noncommutative geometry with time variability of
the number of spatial dimensions. Within the framework of noncommutative
decrumpling inflation, we compute both the spectral index and its running. Our
results show that the effects of both time variability of the number of spatial
dimensions and noncommutative geometry on the spectral index and its running.
Two classes of examples have been studied and comparisons made with the
standard slow-roll formulae. We conclude that the effects of noncommutative
geometry on the spectral index and its running are much smaller than the
effects of time variability of spatial dimensions.


  We study the s-wave quintet Cooper pairing phase ($S_{tot}=2$) in spin-3/2
cold atomic systems and identify various novel features which do not appear in
the spin-1/2 counterpart. A single quantum vortex is shown to be energetically
less stable than a pair of half-quantum vortices (HQV). The HQV exhibits the
global analogue of the non-Abelian Alice string and SO(4) Cheshire charge in
gauge theories. The non-Abelian HQV loop enables topological generation of
quantum entanglement.


  It is known that the center-of-mass energy of the collision of two massive
particles following geodesics around a black hole presents a maximum. The
maximum energy increases when the black hole is endowed with spin, and for a
maximally rotating hole this energy blows up, offering, in principle, a unique
probe of fundamental physics. This work extends the latter studies by
considering that the colliding particles possess intrinsic angular momentum
(spin), described by the Hanson-Regge-Hojman theory of spinning particles. By
analyzing planar trajectories of spinning particles around non-rotating black
holes, a significant increase of the invariant collision energy is found.
Radial turning points, causality constraints, and limitations of the theory are
discussed.


  The interaction of nonlinear Schr\"{o}dinger (NLS) solitons with potential
wells with variable shapes is investigated numerically. For fixed initial
velocities below the threshold for transmission, the outcome pattern as a
function of the width of the potential yields periodically repeating regions of
trapping, transmission and reflection. The observed effects are explained by an
excitation and a following resonant deexcitation of amplitude (shape)
oscillations of the solitons at the boundaries of the well, associated with
radiation modes.


  The cooling of a young bare strange star is studied numerically by solving
the equations of energy conservation and heat transport for both normal and
superconducting strange quark matter inside the star. We show that the thermal
luminosity from the strange star surface, due to both photon emission and e+e-
pair production, may be orders of magnitude higher than the Eddington limit,
for about one day for normal quark matter but possibly for up to a hundred
years for superconducting quark matter, while the maximum of the photon
spectrum is in hard X-rays with a mean energy of ~ 100 keV or even more. This
differs both qualitatively and quantitatively from the photon emission from
young neutron stars and provides a definite observational signature for bare
strange stars. It is shown that the energy gap of superconducting strange quark
matter may be estimated from the light curves if it is in the range from ~ 0.5
MeV to a few MeV.


  Given side information that an Ising tree-structured graphical model is
homogeneous and has no external field, we derive the exact asymptotics of
learning its structure from independently drawn samples. Our results, which
leverage the use of probabilistic tools from the theory of strong large
deviations, refine the large deviation (error exponents) results of Tan,
Anandkumar, Tong, and Willsky [IEEE Trans. on Inform. Th., 57(3):1714--1735,
2011] and strictly improve those of Bresler and Karzand [Ann. Statist., 2020].
In addition, we extend our results to the scenario in which the samples are
observed in random noise. In this case, we show that they strictly improve on
the recent results of Nikolakakis, Kalogerias, and Sarwate [Proc. AISTATS,
1771--1782, 2019]. Our theoretical results demonstrate keen agreement with
experimental results for sample sizes as small as that in the hundreds.


  Harris Corporation has an interest in making HF radios a suitable medium for
wireless information networks using standard Internet protocols. Although HF
radio links have many unique characteristics, HF wireless subnets can be
subject to many of the same traffic flow characteristics and topologies as
existing line-of-sight (LOS) radio networks, giving rise to similar issues
(media access, connectivity, routing) which lend themselves to investigation
through simulation. Accordingly, we have undertaken to develop efficient,
high-fidelity simulations of various aspects of HF radio communications and
networking using the OMNeT++ framework. Essential aspects of these simulations
include HF channel models simulating relevant channel attributes such as Signal
to Noise Ratio, multipath, and Doppler spread; a calibrated physical layer
model reproducing the error statistics (including burst error distributions) of
the MIL-STD-188-110B/C HF modem waveforms, both narrowband (3 kHz) and wideband
(up to 24 kHz) on the simulated HF channels; a model of the NATO STANAG 5066
data link protocol; and integration of these models with the OMNeT++ network
simulation framework and its INET library of Internet protocol models. This
simulation is used to evaluate the impacts of different STANAG 5066
configuration settings on TCP network performance, and to evaluate strategies
for optimizing throughput over HF links using TCP Performance Enhancing Proxy
(PEP) techniques.


  We give algorithms that, given a straight-line program (SLP) with $g$ rules
that generates (only) a text $T [1..n]$, builds within $O(g)$ space the
Lempel-Ziv (LZ) parse of $T$ (of $z$ phrases) in time $O(n\log^2 n)$ or in time
$O(gz\log^2(n/z))$. We also show how to build a locally consistent grammar
(LCG) of optimal size $g_{lc} = O(\delta\log\frac{n}{\delta})$ from the SLP
within $O(g+g_{lc})$ space and in $O(n\log g)$ time, where $\delta$ is the
substring complexity measure of $T$. Finally, we show how to build the LZ parse
of $T$ from such a LCG within $O(g_{lc})$ space and in time $O(z\log^2 n
\log^2(n/z))$. All our results hold with high probability.


  We introduce our project, AGNSTRONG (Active Galactic Nuclei and STaR
fOrmation in Nearby Galaxies). Our research goals encompass investigating the
kinematic properties of ionized and molecular gas outflows, understanding the
impact of AGN feedback, and exploring the coevolution dynamics between AGN
strength activity and star formation activity. We aim to conduct a thorough
analysis to determine whether there is an increase or suppression in SFRs among
targets with and without powerful relativistic jets. Our sample consists of 35
nearby AGNs with and without powerful relativistic jet detections. Utilizing
sub-millimeter (sub-mm) continuum observations at 450 {\mu}m and 850 {\mu}m
from SCUBA-2 at the James Clerk Maxwell Telescope, we determine star-formation
rates (SFRs) for our sources using spectral energy distribution (SED) fitting
models. Additionally, we employ high-quality, spatially resolved spectra from
UV-optical to near-infrared bands obtained with the Double Spectrograph and
Triple Spectrograph mounted on the 200-inch Hale telescope at Palomar
Observatory to study their multiphase gas outflow properties. This paper
presents an overview of our sample selection methodology, research strategy,
and initial results of our project. We find that the SFRs determined without
including the sub-mm data in the SED fitting are overestimated by approximately
0.08 dex compared to those estimated with the inclusion of sub-mm data.
Additionally, we compare the estimated SFRs in our work with those traced by
the 4000{\AA} break, as provided by the MPA-JHU catalog. We find that our
determined SFRs are systematically higher than those traced by the 4000{\AA}
break. Finally, we outline our future research plans.


  A model of stochastic games where multiple controllers jointly control the
evolution of the state of a dynamic system but have access to different
information about the state and action processes is considered. The asymmetry
of information among the controllers makes it difficult to compute or
characterize Nash equilibria. Using common information among the controllers,
the game with asymmetric information is shown to be equivalent to another game
with symmetric information. Further, under certain conditions, a Markov state
is identified for the equivalent symmetric information game and its Markov
perfect equilibria are characterized. This characterization provides a backward
induction algorithm to find Nash equilibria of the original game with
asymmetric information in pure or behavioral strategies. Each step of this
algorithm involves finding Bayesian Nash equilibria of a one-stage Bayesian
game. The class of Nash equilibria of the original game that can be
characterized in this backward manner are named common information based Markov
perfect equilibria.


  In the context of a Hubble tension problem that is growing in its statistical
significance, we reconsider the effectiveness of non-parametric reconstruction
techniques which are independent of prescriptive cosmological models. By taking
cosmic chronometers, Type Ia Supernovae and baryonic acoustic oscillation data,
we compare and contrast two important reconstruction approaches, namely
Gaussian processes (GP) and the \textbf{Lo}cally w\textbf{e}ighted
\textbf{S}catterplot \textbf{S}moothing together with \textbf{Sim}ulation and
\textbf{ex}trapolation method (LOESS-Simex or LS). In the context of these
methods, besides not requiring a cosmological model, they also do not require
physical parameters in their approach to their reconstruction of data (but they
do depend on statistical hyperparameters). We firstly show how both GP and
LOESS-Simex can be used to successively reconstruct various data sets to a high
level of precision. We then directly compare both approaches in a quantitative
manner by considering several factors, such as how well the reconstructions
approximate the data sets themselves to how their respective uncertainties
evolve. In light of the puzzling Hubble tension, it is important to consider
how the uncertain regions evolve over redshift and the methods compare for
estimating cosmological parameters at current times. For cosmic chronometers
and baryonic acoustic oscillation compiled data sets, we find that GP
generically produce smaller variances for the reconstructed data with a minimum
value of $\sigma_{\rm GP-min} = 1.1$, while the situation for LS is totally
different with a minimum of $\sigma_{\rm LS-min} = 50.8$. Moreover, some of
these characteristics can be alleviate at low $z$, where LS presents less
underestimation in comparison to GP.


  In this paper, we introduce Neural-ABC, a novel parametric model based on
neural implicit functions that can represent clothed human bodies with
disentangled latent spaces for identity, clothing, shape, and pose. Traditional
mesh-based representations struggle to represent articulated bodies with
clothes due to the diversity of human body shapes and clothing styles, as well
as the complexity of poses. Our proposed model provides a unified framework for
parametric modeling, which can represent the identity, clothing, shape and pose
of the clothed human body. Our proposed approach utilizes the power of neural
implicit functions as the underlying representation and integrates
well-designed structures to meet the necessary requirements. Specifically, we
represent the underlying body as a signed distance function and clothing as an
unsigned distance function, and they can be uniformly represented as unsigned
distance fields. Different types of clothing do not require predefined
topological structures or classifications, and can follow changes in the
underlying body to fit the body. Additionally, we construct poses using a
controllable articulated structure. The model is trained on both open and newly
constructed datasets, and our decoupling strategy is carefully designed to
ensure optimal performance. Our model excels at disentangling clothing and
identity in different shape and poses while preserving the style of the
clothing. We demonstrate that Neural-ABC fits new observations of different
types of clothing. Compared to other state-of-the-art parametric models,
Neural-ABC demonstrates powerful advantages in the reconstruction of clothed
human bodies, as evidenced by fitting raw scans, depth maps and images. We show
that the attributes of the fitted results can be further edited by adjusting
their identities, clothing, shape and pose codes.


  We consider tit-for-tat dynamics in production markets, where there is a set
of $n$ players connected via a weighted graph. Each player $i$ can produce an
eponymous good using its linear production function, given as input various
amounts of goods in the system. In the tit-for-tat dynamic, each player $i$
shares its good with its neighbors in fractions proportional to how much they
helped player $i$'s production in the last round.
  Our contribution is to characterize the asymptotic behavior of the dynamic as
a function of the graph structure, finding that the fortune of a player grows
in the long term if and only if the player has a good self loop (i.e. the
player works well alone) or works well with at least one other player. We also
consider a generalized damped update, where the players may update their
strategies with different speeds, and obtain a lower bound on their rate of
growth by identifying a function that gives insight into the behavior of the
dynamical system.
  The model can capture circular economies, where players use each other's
products, and organizational partnerships, where fostering long-term growth of
an organization hinges on creating relationships in which reciprocal exchanges
between the agents in the organization are paramount.


  Inference in general Markov random fields (MRFs) is NP-hard, though
identifying the maximum a posteriori (MAP) configuration of pairwise MRFs with
submodular cost functions is efficiently solvable using graph cuts. Marginal
inference, however, even for this restricted class, is in #P. We prove new
formulations of derivatives of the Bethe free energy, provide bounds on the
derivatives and bracket the locations of stationary points, introducing a new
technique called Bethe bound propagation. Several results apply to pairwise
models whether associative or not. Applying these to discretized
pseudo-marginals in the associative case we present a polynomial time
approximation scheme for global optimization provided the maximum degree is
$O(\log n)$, and discuss several extensions.


  We investigate the Mach number dependence of the radiative overstability of
shocks. We find that the stability of radiative shocks increases with
decreasing Mach number, with the result that M=2 shocks require cooling
exponents < -1.2 to be overstable. The frequency of oscillation of the
fundamental mode has a strong Mach number dependence. We find that feedback
between the cooling region and the cold dense layer (CDL) further downstream is
a function of Mach number, with stronger feedback and oscillation of the
boundary between the CDL and the cooling region occuring at lower Mach numbers.
This feedback can be quantified in terms of the reflection coefficient of sound
waves. An interesting finding is that the stability properties of low Mach
number shocks can be dramatically altered if the shocked gas is able to cool to
temperatures less than the pre-shock value, and it is probable that low Mach
number astrophysical shocks will be overstable in a variety of situations. The
results of this work are relevant to astrophysical shocks with low Mach
numbers, such as supernova remnants (SNRs) immersed in a hot interstellar
medium (e.g., within a starburst region), and shocks in molecular clouds, where
time-dependent chemistry can lead to overstability. (Abridged)


  ALAMO is a computational methodology for leaning algebraic functions from
data. Given a data set, the approach begins by building a low-complexity,
linear model composed of explicit non-linear transformations of the independent
variables. Linear combinations of these non-linear transformations allow a
linear model to better approximate complex behavior observed in real processes.
The model is refined, as additional data are obtained in an adaptive fashion
through error maximization sampling using derivative-free optimization. Models
built using ALAMO can enforce constraints on the response variables to
incorporate first-principles knowledge. The ability of ALAMO to generate simple
and accurate models for a number of reaction problems is demonstrated. The
error maximization sampling is compared with Latin hypercube designs to
demonstrate its sampling efficiency. ALAMO's constrained regression methodology
is used to further refine concentration models, resulting in models that
perform better on validation data and satisfy upper and lower bounds placed on
model outputs.


  In this paper we give the Weierstrass equations for Jacobian fibrations on
the K3 surface that is the minimal resolution of the double covering of
projective plane ramified along generic six lines.


  We use x-ray photon correlation spectroscopy to investigate the dynamics of a
high volume fraction emulsion creaming under gravity. The dodecane-in-water
emulsion has interfaces stabilized solely by colloidal particles (silica). The
samples were observed soon after mixing: as the emulsion becomes compact we
discern two regimes of ageing with a cross-over between them. The young
emulsion has faster dynamics associated with creaming in a crowded environment
accompanied by local rearrangements. The dynamics slow down for the older
emulsion although our studies show that motion is associated with large
intermittent events. The relaxation rate, as seen from the intensity
autocorrelation function, depends linearly on the wave vector at all times;
however, the exponent associated with the line shape changes from 1.5 for young
samples to less than 1 as the emulsion ages. The combination of ballisticlike
dynamics, an exponent that drops below 1 and large intermittent fluctuations
has not been reported before.


  We address the measurement of density of states within and beyond the
superconducting gap in tunnel-coupled finite-size nanostructures using a
capacitive method. Third-harmonic generation is used to yield the full
differential conductance spectrum without destruction of the low dimensionality
otherwise induced by intimate ohmic coupling to an electrode. The method is
particularly relevant to attempts to discern the presence of the fragile
Majorana quasiparticle at the end of spin-orbit-coupled nanowires in
appropriate magnetic field conditions by their signature mid-gap density of
states.


  A significant number of intermediate age clusters (1-2 Gyr) in the Magellanic
Clouds appear to have multiple stellar populations within them, derived from
bi-modal or extended main sequence turn offs. If this is interpreted as an age
spread, the multiple populations are separated by a few hundred Myr, which
would call into question the long held notion that clusters are simple stellar
populations. Here we show that stellar rotation in stars with masses between
1.2-1.7 Msun can mimic the effect of a double or multiple population, whereas
in actuality only a single population exists. The two main causes of the spread
near the turn-off are the effects of stellar rotation on the structure of the
star and the inclination angle of the star relative to the observer. Both
effects change the observed effective temperature, hence colour, and flux of
the star. In order to match observations, the required rotation rates are
20-50% of the critical rotation, which are consistent with observed rotation
rates of similar mass stars in the Galaxy. We provide scaling relations which
can be applied to non-rotating isochrones in order to mimic the effects of
rotation. Finally, we note that rotation is unlikely to be the cause of the
multiple stellar populations observed in old globular clusters, as low mass
stars (<1 Msun) are not expected to be rapid rotators.


  \emph{Wolf-Villain (WV) model} is a simple model used to study \emph{ideal}
molecular beam epitaxy (MBE) growth by using computer simulations. In this
model, an adatom diffuses instantaneously within a finite diffusion length to
maximize its coordination number. We study statistical properties of thin films
grown by this model. The morphology of the WV model is found to be kinetically
rough with a downhill particle diffusion current. In real MBE growth, however,
there are additional factors such as the existence of a potential barrier that
is known as the \emph{Ehrlich-Schwoebel (ES) barrier}. The ES barrier is an
additional barrier for an adatom that diffuses over a step edge from the upper
to a lower terrace which is known to induce an uphill particle current. We
found that with the addition of the ES barrier, the WV-ES model morphology is
rough with \emph{mound formation} on the surface when the barrier is strong
enough. To confirm these results, the correlation function is also studied. We
find no oscillation in the correlation function in the WV model. For the WV-ES
model, the correlation function oscillates. These results confirm that a strong
enough ES barrier can cause mound formation on the WV surface in our study.


  The orchestration of complex algorithms demands high levels of automation to
use modern hardware efficiently. Task-based programming with OpenMP 5.0 is a
prominent candidate to accomplish this goal. We study OpenMP 5.0's tasking in
the context of a wave equation solver (ExaHyPE) using three different
architectures and runtimes. We describe several task-scheduling flaws present
in currently available runtimes, demonstrate how they impact performance and
show how to work around them. Finally, we propose extensions to the OpenMP
standard.


  The Child-Langmuir law is investigated numerically using a fully
electromagnetic particle-in-cell code for a closed axially symmetric diode. It
is found that the average current transmitted to the anode increases with the
injected current even after the formation of virtual cathode in both the
non-relativistic and relativistic cases. The increase is found to be a power
law. In other words, the time averaged fraction $f$ of electrons reaching the
anode varies with the input current as, $f\sim J_{\rm IN}^{-\beta}$ where
$\beta < 1$. In contrast, for an infinite parallel plate diode, $f \sim J_{\rm
IN}^{-1}$. The possibility of asymptotic saturation is also discussed.


  We estimate the mass of the central black hole in our Galaxy from stellar
kinematical data published by Ghez et al. (1998) and Genzel et al. (2000). For
this we develop a method, related to Merritt (1993), for non-parametrically
reconstructing the mass profile and the stellar distribution function in the
central region of the Galaxy from discrete kinematic data, including velocity
errors. Models are searched using the Metropolis algorithm. We assume that the
mass distribution is spherical and the stellar velocity distribution is
isotropic, and devise a test of this assumption. From proper motions we obtain
an enclosed mass of $2.0\pm{0.7}\times10^6{\rm M}_{\odot}$ within the inner
$0.0044\rm pc$, from radial velocities we obtain a mass of
$2.2^{+1.6}_{-1.0}\times10^6{\rm M}_{\odot}$ within 0.046pc and from
three-dimensional velocities we obtain $1.8^{+0.4}_{-0.3}\times10^6{\rm
M}_{\odot}$ within 0.046pc.


  We introduce Dataset Grouper, a library to create large-scale
group-structured (e.g., federated) datasets, enabling federated learning
simulation at the scale of foundation models. This library facilitates the
creation of group-structured versions of existing datasets based on
user-specified partitions and directly leads to a variety of useful
heterogeneous datasets that can be plugged into existing software frameworks.
Dataset Grouper offers three key advantages. First, it scales to settings where
even a single group's dataset is too large to fit in memory. Second, it
provides flexibility, both in choosing the base (non-partitioned) dataset and
in defining partitions. Finally, it is framework-agnostic. We empirically
demonstrate that Dataset Grouper enables large-scale federated language
modeling simulations on datasets that are orders of magnitude larger than in
previous work, allowing for federated training of language models with hundreds
of millions, and even billions, of parameters. Our experimental results show
that algorithms like FedAvg operate more as meta-learning methods than as
empirical risk minimization methods at this scale, suggesting their utility in
downstream personalization and task-specific adaptation. Dataset Grouper is
available at https://github.com/google-research/dataset_grouper.


  An exact energy expression for a physical black hole is derived by
considering the escape of a photon from the black hole. The mass of the black
hole within its horizon is found to be twice its mass as observed at infinity.
This result is important in understanding gravitational waves in black hole
collisions.


  We investigate the effects of local population structure in
reaction-diffusion processes representing a contact process (CP) on
metapopulations represented as complex networks. Considering a model in which
the nodes of a large scale network represent local populations defined in terms
of a homogeneous graph, we show by means of extensive numerical simulations
that the critical properties of the reaction-diffusion system are independent
of the local population structure, even when this one is given by a ordered
linear chain. This independence is confirmed by the perfect matching between
numerical critical exponents and the results from a heterogeneous mean field
theory suited, in principle, to describe situations of local homogeneous
mixing. The analysis of several variations of the reaction-diffusion process
allow to conclude the independence from population structure of the critical
properties of CP-like models on metapopulations, and thus of the universality
of the reaction-diffusion description of this kind of models.


  We predict the emergence of a time crystal generated by an incoherently
driven and dissipative nonlinear optical oscillator, where the nonlinearity
also comes from dissipation. We show that a second-order dissipative phase
transition of light occurs in the frame rotating at the cavity frequency, while
a boundary (dissipative) time crystal emerges in the laboratory frame. We
relate these two phenomena by using the Liouvillian superoperator associated
with the Lindblad master equation and its symmetries. These results connect the
emergence of a second-order dissipative phase transition and a dissipative time
crystal in the thermodynamic limit, allowing to interpret them as the same
phenomenon in terms of the Liouvillian spectrum, but just in different frames.


  We study the long-term evolution of two or more stellar black holes (BHs) on
initially separated but unstable circular orbits around a supermassive BH
(SMBH). Such a close-packed orbital configuration can naturally arise from BH
migrations in the AGN disk. Dynamical instability of the orbits leads to
recurring close encounters between two BHs, during which the BH separation
$r_{\rm p}$ becomes less than the Hill radius $R_{\rm H}$. In the rare very
close encounters (with $r_{\rm p}$ several orders of magnitude less than
$R_{\rm H}$), a tight merging BH binary can form with the help of gravitational
wave emission. We use $N$-body simulations to study the time evolution of close
encounters of various degrees of "closeness" and the property of the resulting
binary BH mergers. For a typical "SMBH + 2 BHs" system, the averaged cumulative
number of close encounters (with $r_{\rm p} \lesssim R_{\rm H}$) scales
approximately as $\propto t^{0.5}$. The minimum encounter separation $r_{\rm
p}$ follows a linear cumulative distribution $P(<r_{\rm p}) \propto r_{\rm p}$
for $r_{\rm p} \ll R_{\rm H}$. From these, we obtain a semi-analytical
expression for the averaged rate of binary captures that lead to BH mergers.
Our results suggest that close-packed BHs in AGN disks may take a long time
($\gtrsim 10^7$ orbits around the SMBH) to experience a sufficiently close
encounter and form a bound binary, although this time can be shorter if the
initial BH orbits are highly aligned. The BH binary mergers produced in this
scenario always have high eccentricities when entering the LIGO band, and have
a broad distribution of orbital inclinations relative to the original AGN disk.
We also explore the effects of the gas disk and find that simple gas drags on
the BHs do not necessarily lead to an enhanced BH binary capture rate.


  We deal with a Carleson measure type problem for the tent spaces
$AT_{p}^{q}(\alpha)$ in the unit disc of the complex plane. They consist of the
analytic functions of the tent spaces $T_{p}^{q}(\alpha)$ introduced by
Coifman, Meyer and Stein. Well known spaces like the Bergman spaces arise as a
special case of this family. Let $s,t,p,q\in (0,\infty)$ and $\alpha >0\,.$ We
find necessary and sufficient conditions on a positive Borel measure $\mu$ of
the unit disc in order to exist a positive constant $C $ such that $$
\int_{\mathbb{T}} \left(\int_{\Gamma (\xi)} |f(z)|^{t}\ d\mu(z)\right)^{s/t}\
|d\xi|\leq C \|f\|^s_{T_{p}^{q}(\alpha)} \,,\quad f\in AT_{p}^{q}(\alpha)\,, $$
where $\Gamma (\xi) = \Gamma_M (\xi)=\{ z\in \mathbb{D} : |1-\bar{\xi} z |< M
(1-|z|^2)\},$ $M> 1/2 $ and $\xi$ is a boundary point of the unit disk. This
problem was originally posed by D. Luecking. We apply our results to the study
of the action of the integration operator $T_g$, also known as Pommerenke
operator, between the average integrability spaces $RM(p,q) ,$ for $p,q\in
[1,\infty)$. These spaces have appeared recently in the work of the first
author with M. D. Contreras and L. Rodr\'iguez-Piazza. We also consider the
action from an $RM(p,q)$ to a Hardy space $H^s$, where $ p,q,s \in [1,\infty)$.


  We present theoretical calculations of the Land\'e g-factors of semiconductor
nanostructures using a time-dependent empirical tight-binding method. The
eigenenergies and eigenfunctions of the band edge states are calculated as a
function of an external magnetic field with the electromagnetic field
incorporated into the tight-binding Hamiltonian in a gauge-invariant form. The
spin-orbit interaction and magnetic field are treated non-perturbatively. The
g-factors are extracted from the energy splitting of the eigenstates induced by
the applied magnetic field. Both electron and hole g-factors are investigated
for CdSe nanostructures. The size and aspect ratio dependence of g-factors is
studied. We observe that the electron g-factors are anisotropic and find that
the calculated values agree quantitatively with experimental data. We conclude
that the two distinct g-factor values extracted from time resolved Faraday
rotation experiments should be assigned to the anisotropic in plane
($g_\parallel$) and out of plane ($g_z$) electron g-factors, rather than to
isotropic electron and exciton g-factors. We find that the anisotropy in the
electron g-factor depends on the aspect ratio of the nanocrystal. The g-factor
anisotropy derived from the wurtzite structure and from the non-unity aspect
ratio may cancel each other in some regime. We observe that hole g-factors
oscillate as a function of size, due to size dependent mixing between the heavy
hole-light hole components of the valence band edge states. Extension to the
calculation of exciton g-factors is discussed.


  The strong energy dependence of the s-wave eta-N scattering amplitude at and
below threshold, as evident in coupled-channels K-matrix fits and chiral models
that incorporate the S11 N*(1535) resonance, is included self-consistently in
eta-nuclear bound-state calculations. This approach, applied recently in
calculations of kaonic atoms and Kbar-nuclear bound states, is found to impose
stronger constraints than ever on the onset of eta-nuclear binding, with a
minimum value of Re a_{eta N} approximately 0.9 fm required to accommodate an
eta-4He bound state. Binding energies and widths of eta-nuclear states are
calculated within several underlying eta-N models for nuclei across the
periodic table, including eta-25Mg for which some evidence was proposed in a
recent COSY experiment.


  The study of spacetime, and its role in understanding functional systems has
received little attention in information science. Recent work, on the origin of
universal scaling in cities and biological systems, provides an intriguing
insight into the functional use of space, and its measurable effects. Cities
are large information systems, with many similarities to other technological
infrastructures, so the results shed new light indirectly on the scaling the
expected behaviour of smart pervasive infrastructures and the communities that
make use of them.
  Using promise theory, I derive and extend the scaling laws for cities to
expose what may be extrapolated to technological systems. From the promise
model, I propose an explanation for some anomalous exponents in the original
work, and discuss what changes may be expected due to technological
advancement.


  We introduce a novel gradient descent algorithm extending the well-known
Gradient Sampling methodology to the class of stratifiably smooth objective
functions, which are defined as locally Lipschitz functions that are smooth on
some regular pieces-called the strata-of the ambient Euclidean space. For this
class of functions, our algorithm achieves a sub-linear convergence rate. We
then apply our method to objective functions based on the (extended) persistent
homology map computed over lower-star filters, which is a central tool of
Topological Data Analysis. For this, we propose an efficient exploration of the
corresponding stratification by using the Cayley graph of the permutation
group. Finally, we provide benchmark and novel topological optimization
problems, in order to demonstrate the utility and applicability of our
framework.


  In computational optics, numerical modeling of diffraction between arbitrary
planes offers unparalleled flexibility. However, existing methods suffer from
the trade-off between computational accuracy and efficiency. To resolve this
dilemma, we present a novel approach that rigorously and efficiently models
wave propagation between two arbitrary planes. This is achieved by rearranging
the angular spectrum of the source field, coupled with linear algebraic
computations. Notably, our method achieves comparable computational efficiency
to the control method for both scalar and vectorial diffraction modeling, while
eliminating nearly all numerical errors. Furthermore, we selectively merge the
angular spectrum to further enhance the efficiency at the expense of precision
in a controlled manner. Thereafter, the time consumption is reduced to at most
3% of that before merging.


  We describe the setting and results of the ConvAI2 NeurIPS competition that
aims to further the state-of-the-art in open-domain chatbots. Some key
takeaways from the competition are: (i) pretrained Transformer variants are
currently the best performing models on this task, (ii) but to improve
performance on multi-turn conversations with humans, future systems must go
beyond single word metrics like perplexity to measure the performance across
sequences of utterances (conversations) -- in terms of repetition, consistency
and balance of dialogue acts (e.g. how many questions asked vs. answered).


  We study the mass-to-light ratio of galaxy systems from poor groups to rich
clusters, and present for the first time a large database for useful
comparisons with theoretical predictions. We extend a previous work, where B_j
band luminosities and optical virial masses were analyzed for a sample of 89
clusters. Here we also consider a sample of 52 more clusters, 36 poor clusters,
7 rich groups, and two catalogs, of about 500 groups each, recently identified
in the Nearby Optical Galaxy sample by using two different algorithms. We
obtain the blue luminosity and virial mass for all systems considered. We
devote a large effort to establishing the homogeneity of the resulting values,
as well as to considering comparable physical regions, i.e. those included
within the virial radius. By analyzing a fiducial, combined sample of 294
systems we find that the mass increases faster than the luminosity: the linear
fit gives M\propto L_B^{1.34 \pm 0.03}, with a tendency for a steeper increase
in the low--mass range. In agreement with the previous work, our present
results are superior owing to the much higher statistical significance and the
wider dynamical range covered (about 10^{12}-10^{15} M_solar). We present a
comparison between our results and the theoretical predictions on the relation
between M/L_B and halo mass, obtained by combining cosmological numerical
simulations and semianalytic modeling of galaxy formation.


  We investigate rotational properties of a system of bosons with attractive
interactions confined in a one-dimensional torus. Two kinds of ground states,
uniform-density and bright-soliton states, are obtained analytically as
functions of the strength of interaction and of the rotational frequency of the
torus. The quantization of circulation appears in the uniform-density state,
but disappears upon formation of the soliton. By comparison with the results of
exact diagonalization of the many-body Hamiltonian, we show that the Bogoliubov
theory is valid at absolute zero over a wide range of parameters. At finite
temperature we employ the exact diagonalization method to examine how thermal
fluctuations smear the plateaus of the quantized circulation. Finally, by
rotating the system with an axisymmetry-breaking potential, we clarify the
process in which the quantized circulation becomes thermodynamically
stabilized.


  We obtain new types of exponential decay laws for solutions of density-matrix
master equations in the weak-coupling limit: after comparing with results
already present in the literature and developing the necessary techniques, we
study the crucial aspect of complete positivity under fairly general
conditions. We propose a new type of time average that guarantees complete
positivity and approximates, in markovian fashion, the exact dynamics for a
plethora of physical applications, no matter which are the spectral properties
of the subsystem, or its dimensions. We shall comment on some interesting
examples, like a new Quantum version of the celebrated Fermi's Golden Rule and
some recently proposed entangling projections.


  We prove that every finitely presented group with positive first
$\ell^2$-Betti number that virtually surjects onto $\mathbb Z$ is
acylindrically hyperbolic. In particular, this implies acylindrical
hyperbolicity of finitely presented residually finite groups with positive
first $\ell^2$-Betti number as well as groups of deficiency at least $2$.


  Recent work on perturbative quantum field theory has led to much study of the
Connes-Kreimer Hopf algebra. Its (graded) dual, the Grossman-Larson Hopf
algebra of rooted trees, had already been studied by algebraists. L. Foissy
introduced a noncommutative version of the Connes-Kreimer Hopf algebra, which
turns out to be self-dual. Using some homomorphisms defined by the author and
W. Zhao, we describe a commutative diagram that relates the aforementioned Hopf
algebras to each other and to the Hopf algebras of symmetric functions,
noncommutative symmetric functions, and quasi-symmetric functions.


  We determine all orbits of the prehomogeneous vector space
$(\mathrm{GL}_5\times \mathrm{GL}_4,\wedge^2\mathrm{Aff}^5 \otimes
\mathrm{Aff}^4)$ rationally over an arbitrary perfect field in this paper.


  We propose conformal hyperrectangular prediction regions for multi-target
regression. We propose split conformal prediction algorithms for both point and
quantile regression to form hyperrectangular prediction regions, which allow
for easy marginal interpretation and do not require covariance estimation. In
practice, it is preferable that a prediction region is balanced, that is,
having identical marginal prediction coverage, since prediction accuracy is
generally equally important across components of the response vector. The
proposed algorithms possess two desirable properties, namely, tight asymptotic
overall nominal coverage as well as asymptotic balance, that is, identical
asymptotic marginal coverage, under mild conditions. We then compare our
methods to some existing methods on both simulated and real data sets. Our
simulation results and real data analysis show that our methods outperform
existing methods while achieving the desired nominal coverage and good balance
between dimensions.


  We report on the long term monitoring of X-ray dips from the ultracompact
low-mass X-ray binary (LMXB) XB 1916-053. Roughly one-month interval
observations were carried out with the Rossi X-ray Timing Explorer (RXTE)
during 1996, during which the source varied between dim, hard states and more
luminous, soft states. The dip spectra and dip lightcurves were compared
against both the broadband luminosity and the derived mass accretion rate Mdot.
The dips spectra could be fitted by an absorbed blackbody plus cut-off power
law non-dip spectral model, with additional absorption ranging from 0 to >100 x
10^22 cm^-2. The amount of additional blackbody absorption was found to vary
with the source luminosity. Our results are consistent with an obscuration of
the inner disk region by a partially ionized outer disk. The size of the
corona, derived from the dip ingress times, was found to be ~10^9 cm. The
corona size did not correlate with the coronal temperature, but seemed to
increase when \Mdot also increased. We discuss our findings in the context of
an evaporated accretion disk corona model and an ADAF-type model.


  Learning-to-rank techniques have proven to be extremely useful for
prioritization problems, where we rank items in order of their estimated
probabilities, and dedicate our limited resources to the top-ranked items. This
work exposes a serious problem with the state of learning-to-rank algorithms,
which is that they are based on convex proxies that lead to poor
approximations. We then discuss the possibility of "exact" reranking algorithms
based on mathematical programming. We prove that a relaxed version of the
"exact" problem has the same optimal solution, and provide an empirical
analysis.


  Hierarchical Associative Memory models have recently been proposed as a
versatile extension of continuous Hopfield networks. In order to facilitate
future research on such models, especially at scale, we focus on increasing
their simulation efficiency on digital hardware. In particular, we propose two
strategies to speed up memory retrieval in these models, which corresponds to
their use at inference, but is equally important during training. First, we
show how they can be cast as Deep Equilibrium Models, which allows using faster
and more stable solvers. Second, inspired by earlier work, we show that
alternating optimization of the even and odd layers accelerates memory
retrieval by a factor close to two. Combined, these two techniques allow for a
much faster energy minimization, as shown in our proof-of-concept experimental
results. The code is available at https://github.com/cgoemaere/hamdeq


  We consider a dynamical system, possibly infinite dimensional or
non-autonomous, with fast and slow time scales which is oscillatory with high
frequencies in the fast directions. We first derive and justify the limit
system of the slow variables. Assuming a steady state persists, we construct
the stable, unstable, center-stable, center-unstable, and center manifolds of
the steady state of a size of order O(1) and give their leading order
approximations. Finally, using these tools, we study the persistence of
homoclinic solutions in this type of normally elliptic singular perturbation
problems.


  3D panoptic segmentation is a challenging perception task that requires both
semantic segmentation and instance segmentation. In this task, we notice that
images could provide rich texture, color, and discriminative information, which
can complement LiDAR data for evident performance improvement, but their fusion
remains a challenging problem. To this end, we propose LCPS, the first
LiDAR-Camera Panoptic Segmentation network. In our approach, we conduct
LiDAR-Camera fusion in three stages: 1) an Asynchronous Compensation Pixel
Alignment (ACPA) module that calibrates the coordinate misalignment caused by
asynchronous problems between sensors; 2) a Semantic-Aware Region Alignment
(SARA) module that extends the one-to-one point-pixel mapping to one-to-many
semantic relations; 3) a Point-to-Voxel feature Propagation (PVP) module that
integrates both geometric and semantic fusion information for the entire point
cloud. Our fusion strategy improves about 6.9% PQ performance over the
LiDAR-only baseline on NuScenes dataset. Extensive quantitative and qualitative
experiments further demonstrate the effectiveness of our novel framework. The
code will be released at https://github.com/zhangzw12319/lcps.git.


  We show that every trivial 3-strand braid diagram contains a disk, defined as
a ribbon ending in opposed crossings. Under a convenient algebraic form, the
result extends to every Artin--Tits group of dihedral type, but it fails to
extend to braids with 4 strands and more. The proof uses a partition of the
Cayley graph and a continuity argument.


  Many real-world phenomena are observed at multiple resolutions. Predictive
models designed to predict these phenomena typically consider different
resolutions separately. This approach might be limiting in applications where
predictions are desired at fine resolutions but available training data is
scarce. In this paper, we propose classification algorithms that leverage
supervision from coarser resolutions to help train models on finer resolutions.
The different resolutions are modeled as different views of the data in a
multi-view framework that exploits the complementarity of features across
different views to improve models on both views. Unlike traditional multi-view
learning problems, the key challenge in our case is that there is no one-to-one
correspondence between instances across different views in our case, which
requires explicit modeling of the correspondence of instances across
resolutions. We propose to use the features of instances at different
resolutions to learn the correspondence between instances across resolutions
using an attention mechanism.Experiments on the real-world application of
mapping urban areas using satellite observations and sentiment classification
on text data show the effectiveness of the proposed methods.


  The Higgs mechanism is the favourite cure for the main problem with
electroweak unification, namely how to reconcile a gauge theory with the need
for massive gauge bosons. This problem does not exist in preon models for quark
and lepton substructure with composite $Z^0$ and $W$s, which, consequently,
also avoid all other theoretical complications and paradoxes with the Higgs
mechanism. We present a new, minimal preon model, which explains the family
structure, and predicts several new, heavy quarks, leptons and vector bosons.
Our preons obey a phenomenological supersymmetry, but without so-called squarks
and sleptons, since this SUSY is effective only on the composite scale.


  Artificial Intelligence (AI) Safety Institutes and governments worldwide are
deciding whether they evaluate and audit advanced AI themselves, support a
private auditor ecosystem or do both. Auditing regimes have been established in
a wide range of industry contexts to monitor and evaluate firms compliance with
regulation. Auditing is a necessary governance tool to understand and manage
the risks of a technology. This paper draws from nine such regimes to inform
(i) who should audit which parts of advanced AI; and (ii) how much resources,
competence and access public bodies may need to audit advanced AI effectively.
First, the effective responsibility distribution between public and private
auditors depends heavily on specific industry and audit conditions. On the
basis of the risk profile of advanced AI, the sensitivity of information
involved in the auditing process, and the high costs of verifying safety and
benefit claims of AI Labs, we recommend that public bodies become directly
involved in safety critical, especially gray- and white-box, AI model audits.
Governance and security audits, which are well-established in other industry
contexts, as well as black-box model audits, may be more efficiently provided
by a private market of auditors under public oversight. Secondly, to
effectively fulfill their role in advanced AI audits, public bodies need
extensive access to models and facilities. Public bodies capacity should scale
with the industry's risk level, size and market concentration, potentially
requiring 100s of employees for auditing in large jurisdictions like the EU or
US, like in nuclear safety and life sciences.


  A dielectric medium consisting of roughly polarized molecules is treated as a
3D disordered spin system (spin glass). A microscopic approach for the study of
statistical properties of this system on micrometer space scale and nanosecond
time scale of standing electromagnetic wave is developed. Using ergodic
hypothesis the initial 3D spin problem is reduced to two separate 1D problems
along external field propagation. The first problem describes the disordered
spin chain system while the second one describes a disordered N-particle
quantum system with relaxation in the framework of Langevin-Schroedinger
(L-Sch) type equation. Statistical properties of both systems are investigated
in detail. Basing on these constructions, the coefficient of polarizability,
related to collective orientational effects, is calculated. Clausius-Mossotti
formula for dielectric constant is generalized. For dielectric permittivity
function generalized equation is found taking into account Clausius-Mossotti
generalized formula.


  This paper presents a novel multi-task learning-based method for unsupervised
domain adaptation. Specifically, the source and target domain classifiers are
jointly learned by considering the geometry of target domain and the divergence
between the source and target domains based on the concept of multi-task
learning. Two novel algorithms are proposed upon the method using Regularized
Least Squares and Support Vector Machines respectively. Experiments on both
synthetic and real world cross domain recognition tasks have shown that the
proposed methods outperform several state-of-the-art domain adaptation methods.


  Stance detection concerns the classification of a writer's viewpoint towards
a target. There are different task variants, e.g., stance of a tweet vs. a full
article, or stance with respect to a claim vs. an (implicit) topic. Moreover,
task definitions vary, which includes the label inventory, the data collection,
and the annotation protocol. All these aspects hinder cross-domain studies, as
they require changes to standard domain adaptation approaches. In this paper,
we perform an in-depth analysis of 16 stance detection datasets, and we explore
the possibility for cross-domain learning from them. Moreover, we propose an
end-to-end unsupervised framework for out-of-domain prediction of unseen,
user-defined labels. In particular, we combine domain adaptation techniques
such as mixture of experts and domain-adversarial training with label
embeddings, and we demonstrate sizable performance gains over strong baselines,
both (i) in-domain, i.e., for seen targets, and (ii) out-of-domain, i.e., for
unseen targets. Finally, we perform an exhaustive analysis of the cross-domain
results, and we highlight the important factors influencing the model
performance.


  In this paper, Capacitance-Voltage (C-V) characteristics and direct tunneling
(DT) gate leakage current of antimonide based surface channel MOSFET were
investigated. Self-consistent method was applied by solving coupled
Schr\"odinger-Poisson equation taking wave function penetration and strain
effects into account. Experimental I-V and gate leakage characteristic for
p-channel InxGa1-xSb MOSFETs are available in recent literature. However, a
self- consistent simulation of C-V characterization and direct tunneling gate
leakage current is yet to be done for both n- channel and p-channel InxGa1-xSb
surface channel MOSFETs. We studied the variation of C-V characteristics and
gate leakage current with some important process parameters like oxide
thickness, channel composition, channel thickness and temperature for n-channel
MOSFET in this work. Device performance should improve as compressive strain
increases in channel. Our simulation results validate this phenomenon as
ballistic current increases and gate leakage current decreases with the
increase in compressive strain. We also compared the device performance by
replacing InxGa1-xSb with InxGa1-xAs in channel of the structure. Simulation
results show that performance is much better with this replacement.


  We propose that the knots of the large-scale jets in powerful radio sources
represent moving and separate portions of the jet matter, with the excess
kinetic power. This can explain many morphological properties of quasar jets -
like high knot-to-interknot brightness contrasts, frequency-independent knot
profiles and almost universal extents of the knot regions - independently of
the exact emission mechanisms responsible for producing broad-band jet
emission. We briefly discuss a possible connection between this scenario and
the idea of highly modulated/intermittent activity of the jet engine.