  Open-set Recognition (OSR) aims to identify test samples whose classes are
not seen during the training process. Recently, Unified Open-set Recognition
(UOSR) has been proposed to reject not only unknown samples but also known but
wrongly classified samples, which tends to be more practical in real-world
applications. The UOSR draws little attention since it is proposed, but we find
sometimes it is even more practical than OSR in the real world applications, as
evaluation results of known but wrongly classified samples are also wrong like
unknown samples. In this paper, we deeply analyze the UOSR task under different
training and evaluation settings to shed light on this promising research
direction. For this purpose, we first evaluate the UOSR performance of several
OSR methods and show a significant finding that the UOSR performance
consistently surpasses the OSR performance by a large margin for the same
method. We show that the reason lies in the known but wrongly classified
samples, as their uncertainty distribution is extremely close to unknown
samples rather than known and correctly classified samples. Second, we analyze
how the two training settings of OSR (i.e., pre-training and outlier exposure)
influence the UOSR. We find although they are both beneficial for
distinguishing known and correctly classified samples from unknown samples,
pre-training is also helpful for identifying known but wrongly classified
samples while outlier exposure is not. In addition to different training
settings, we also formulate a new evaluation setting for UOSR which is called
few-shot UOSR, where only one or five samples per unknown class are available
during evaluation to help identify unknown samples. We propose FS-KNNS for the
few-shot UOSR to achieve state-of-the-art performance under all settings.


  In this note we address some issues of recent interest, related to the
asymptotic symmetry algebra of higher spin black holes in
$sl(3,\mathbb{R})\times sl(3,\mathbb{R})$ Chern Simons (CS) formulation. We
compute the fixed time Dirac bracket algebra that acts on two different phase
spaces. Both of these spaces contain black holes as zero modes. The result for
one of these phase spaces is explicitly shown to be isomorphic to
$W^{(2)}_3\times W^{(2)}_3$ in first order perturbations.


  This work presents a microscale approach for simulating the dielectrophoresis
(DEP) assembly of polarizable particles under an external electric field. The
model is shown to capture interesting dynamical and topological features, such
as the formation of chains of particles and their incipient aggregation into
hierarchical structures. A quantitative characterization in terms of the number
and size of these structures is also discussed. This computational model could
represent a viable numerical tool to study the mechanical properties of
particle-based hierarchical materials and suggest new strategies for enhancing
their design and manufacture.


  We study the variation of the broad-band spectral energy distribution (SED)
of the BL Lac object Mrk 501 as a function of source activity, from quiescent
to flaring. Through chi-square-minimization we model eight simultaneous SED
datasets with a one-zone Synchrotron-Self-Compton (SSC) model, and examine how
model parameters vary with source activity. The emerging variability pattern of
Mrk 501 is complex, with the Compton component arising from gamma-electron
scatterings that sometimes are (mostly) Thomson and sometimes (mostly) extreme
Klein-Nishina. This can be seen from the variation of the Compton to
synchrotron peak distance according to source state. The underlying electron
spectra are faint/soft in quiescent states and bright/hard in flaring states. A
comparison with Mrk 421 suggests that the typical values of the SSC parameters
are different in the two sources: however, in both jets the energy density is
particle dominated in all states.


  We report a study of NiBi$_3$ single crystals by means of
electrical-resistivity-, magnetization-, and muon-spin rotation and relaxation
($\mu$SR) measurements. As a single crystal, NiBi$_3$ adopts a needle-like
shape and exhibits bulk superconductivity with $T_c \approx 4.1$ K. By applying
magnetic fields parallel and perpendicular to the $b$-axis of NiBi$_3$, we
establish that its lower- and upper critical fields, as well as the magnetic
penetration depths show slightly different values, suggesting a weakly
anisotropic superconductivity. In both cases, the zero-temperature upper
critical fields are much smaller than the Pauli-limit value, indicating that
the superconducting state is constrained by the orbital pair breaking. The
temperature evolution of the superfluid density, obtained from transverse-field
$\mu$SR, reveals a fully-gapped superconductivity in NiBi$_3$, with a shared
superconducting gap $\Delta_0$ = 2.1 $k_\mathrm{B}$$T_c$ and magnetic
penetration depths $\lambda_0$ = 223 and 210 nm for $H \parallel b$- and $H
\perp b$, respectively. The lack of spontaneous fields below $T_c$ indicates
that time-reversal symmetry is preserved in NiBi$_3$. The absence of a fast
muon-spin relaxation and/or precession in the zero-field $\mu$SR spectra
definitely rules out any type of magnetic ordering in NiBi$_3$ single crystals.
Overall, our investigation suggests that NiBi$_3$ behaves as a conventional
$s$-type superconductor.


  In this article, we show that a Finsler--Laplacian introduced previously can
detect changes in the Finsler metric that the marked length spectrum cannot. We
also construct examples of non-reversible Finsler metrics in negative curvature
such that $4\lambda_1 > h^2$, where $\lambda_1$ is the bottom of the
$L^2$-spectrum and $h$ the topological entropy of the flow.


  We present a new method for multi-agent planning involving human drivers and
autonomous vehicles (AVs) in unsignaled intersections, roundabouts, and during
merging. In multi-agent planning, the main challenge is to predict the actions
of other agents, especially human drivers, as their intentions are hidden from
other agents. Our algorithm uses game theory to develop a new auction, called
GamePlan, that directly determines the optimal action for each agent based on
their driving style (which is observable via commonly available sensors).
GamePlan assigns a higher priority to more aggressive or impatient drivers and
a lower priority to more conservative or patient drivers; we theoretically
prove that such an approach is game-theoretically optimal prevents collisions
and deadlocks. We compare our approach with prior state-of-the-art auction
techniques including economic auctions, time-based auctions (first-in
first-out), and random bidding and show that each of these methods result in
collisions among agents when taking into account driver behavior. We compare
with methods based on DRL, deep learning, and game theory and present our
benefits over these approaches. Finally, we show that our approach can be
implemented in the real-world with human drivers.


  The focus of this paper is on the quantification of sampling variation in
frequentist probabilistic forecasts. We propose a method of constructing
confidence sets that respects the functional nature of the forecast
distribution, and use animated graphics to visualize the impact of parameter
uncertainty on the location, dispersion and shape of the distribution. The
confidence sets are derived via the inversion of a Wald test and are
asymptotically uniformly most accurate and, hence, optimal in this sense. A
wide range of linear and non-linear time series models - encompassing long
memory, state space and mixture specifications - is used to demonstrate the
procedure, based on artificially generated data. An empirical example in which
distributional forecasts of both financial returns and its stochastic
volatility are produced is then used to illustrate the practical importance of
accommodating sampling variation in the manner proposed.


  Lindstr\"om's Theorem characterizes first order logic as the maximal logic
satisfying the Compactness Theorem and the Downward L\"owenheim-Skolem Theorem.
If we do not assume that logics are closed under negation, there is an obvious
extension of first order logic with the two model theoretic properties
mentioned, namely existential second order logic. We show that existential
second order logic has a whole family of proper extensions satisfying the
Compactness Theorem and the Downward L\"owenheim-Skolem Theorem. Furthermore,
we show that in the context of negationless logics, positive logics, as we call
them, there is no strongest extension of first order logic with the Compactness
Theorem and the Downward L\"owenheim-Skolem Theorem.


  This work introduces the one-class slab SVM (OCSSVM), a one-class classifier
that aims at improving the performance of the one-class SVM. The proposed
strategy reduces the false positive rate and increases the accuracy of
detecting instances from novel classes. To this end, it uses two parallel
hyperplanes to learn the normal region of the decision scores of the target
class. OCSSVM extends one-class SVM since it can scale and learn non-linear
decision functions via kernel methods. The experiments on two publicly
available datasets show that OCSSVM can consistently outperform the one-class
SVM and perform comparable to or better than other state-of-the-art one-class
classifiers.


  Jets have been used to verify the theory of quantum chromodynamics (QCD),
measure the structure of the proton and to search for the physics beyond the
Standard Model. In this article, we review the current status of jet physics at
the Tevatron, a sqrt(s) = 1.96 TeV p-pbar collider at the Fermi National
Accelerator Laboratory. We report on recent measurements of the inclusive jet
production cross section and the results of searches for physics beyond the
Standard Model using jets. Dijet production measurements are also reported.


  The isothermal nucleation kinetics in Al-Sm metallic glasses with low Sm
concentrations (xSm) was studied using molecular dynamics simulations in order
to calculate time-temperature-transformation curves. The average delay time of
Al nanocrystal nucleation was found to increase exponentially with xSm, whereas
the estimated critical cooling rate necessary to avoid crystallization
decreases exponentially with xSm. Sm solutes were found to suppress Al
nucleation by increasing the attachment barrier and therefore by reducing the
attachment frequency. The analysis shows that the attachment of Al to the
evolving nucleus has the same characteristics as Al diffusion within the
amorphous matrix and they both take place heterogeneously via collective
movement of a group of Al atoms.


  In this paper we study zero-sum two-player stochastic differential games with
the help of theory of Backward Stochastic Differential Equations (BSDEs). At
the one hand we generalize the results of the pioneer work of Fleming and
Souganidis by considering cost functionals defined by controlled BSDEs and by
allowing the admissible control processes to depend on events occurring before
the beginning of the game (which implies that the cost functionals become
random variables), on the other hand the application of BSDE methods, in
particular that of the notion of stochastic "backward semigroups" introduced by
Peng allows to prove a dynamic programming principle for the upper and the
lower value functions of the game in a straight-forward way, without passing by
additional approximations. The upper and the lower value functions are proved
to be the unique viscosity solutions of the upper and the lower
Hamilton-Jacobi-Bellman-Isaacs equations, respectively. For this Peng's BSDE
method is translated from the framework of stochastic control theory into that
of stochastic differential games.


  We investigate how the splitting of the leading sunspot and associated flux
emergence and cancellation in active region NOAA 11515 caused an eruptive M5.6
flare on 2012 July 2. Our study employs multi-wavelength observations from HMI,
AIA and ChroTel. Emerging flux formed a neutral line ahead of the leading
sunspot and new satellite spots. The sunspot splitting caused a long-lasting
flow toward this neutral line, where a filament formed. Further flux emergence,
partly of mixed-polarity, as well as episodes of flux cancellation occurred
repeatedly at the neutral line. Following a nearby C-class precursor flare with
signs of interaction with the filament, the filament erupted nearly
simultaneously with the onset of the M5.6 flare and evolved into a coronal mass
ejection. The sunspot stretched without forming a light bridge, splitting
unusually fast (within about a day, complete approximately 6 hours after the
eruption) in two nearly equal parts. The front part separated strongly from the
active region to approach the neighbouring active region where all its coronal
magnetic connections were rooted. It also rotated rapidly (by 4.9 degree/hr)
and caused significant shear flows at its edge. The eruption resulted from a
complex sequence of processes in the (sub-)photosphere and corona. The
persistent flows toward the neutral line likely caused the formation of a flux
rope which held the filament. These flows and their associated flux
cancellation, the emerging flux, and the precursor flare all contributed to the
destabilization of the flux rope. We interpret the sunspot splitting as the
separation of two flux bundles differently rooted in the convection zone and
only temporarily joined in the spot. This explains the rotation as continued
rise of the separating flux and implies that at least this part of the sunspot
was still connected to its roots deep in the convection zone.


  Parabolic bifurcations in one complex dimension demonstrate a wide variety of
interesting dynamical phenomena. In this paper we consider parabolic
bifurcations of families of diffeomorphisms in two complex dimensions.
Specifically we consider a two variable family of diffeomorphisms $F_\epsilon:
M\to M$ given locally by $$F_\epsilon(x,y) = (x + x^2 + \epsilon^2+ ...,
b_\epsilon y+...)$$ where $|b_\epsilon|<1$, and the `$...$' terms involve $x$,
$y$ and $\epsilon$.


  Autopilot is a system designed to guide a vehicle without aid. Due to
increase in flight hours and complexity of modern day flight it has become
imperative to equip the aircrafts with autopilot. Thus reliability and
consistency of an Autopilot system becomes a crucial role in a flight. But the
increased complexity and demand for better accuracy has made the process of
evaluating the autopilot for consistency a difficult process .A vast amount of
imprecise data has been involved. Rough sets can be a potent tool for such kind
of Applications containing vague data. This paper proposes an approach towards
Consistency factor determination using Rough Set Theory. The seventeen basic
factors, that are crucial in determining the consistency of an Autopilot
system, are grouped into five Payloads based on their functionality.
Consistency Factor is evaluated through these payloads, using Rough Set Theory.
Consistency Factor determines the consistency and reliability of an autopilot
system and the conditions under which manual override becomes imperative. Using
Rough set Theory the most and the least influential factors towards Autopilot
system are also determined.


  In this paper, we present a novel model-agnostic machine learning technique
to extract a reduced thermochemical model for reacting hypersonic flows
simulation. A first simulation gathers all relevant thermodynamic states and
the corresponding gas properties via a given model. The states are embedded in
a low-dimensional space and clustered to identify regions with different levels
of thermochemical (non)-equilibrium. Then, a surrogate surface from the reduced
cluster-space to the output space is generated using radial-basis-function
networks. The method is validated and benchmarked on a simulation of a
hypersonic flat-plate boundary layer with finite-rate chemistry. The gas
properties of the reactive air mixture are initially modeled using the
open-source Mutation++ library. Substituting Mutation++ with the light-weight,
machine-learned alternative improves the performance of the solver by 50% while
maintaining overall accuracy.


  In this paper we use the results from the first part to compute the vanishing
topology for matrix singularities based on certain spaces of matrices. We place
the variety of singular matrices in a geometric configuration of free divisors
which are the "exceptional orbit varieties" for repesentations of solvable
groups. Because there are towers of representations for towers of solvable
groups, the free divisors actually form a tower of free divisors $E_n$, and we
give an inductive procedure for computing the vanishing topology of the matrix
singularities. The inductive procedure we use is an extension of that
introduced by L\^{e}-Greuel for computing the Milnor number of an ICIS. Instead
of linear subspaces, we use free divisors arising from the geometric
configuration and which correspond to subgroups of the solvable groups.
  Here the vanishing topology involves a singular version of the Milnor fiber;
however, it still has the good connectivity properties and is homotopy
equivalent to a bouquet of spheres, whose number is called the singular Milnor
number. We give formulas for this singular Milnor number in terms of singular
Milnor numbers of various free divisors on smooth subspaces, which can be
computed as lengths of determinantal modules. In addition to being applied to
symmetric, general and skew-symmetric matrix singularities, the results are
also applied to Cohen--Macaulay singularities defined as 2 x 3 matrix
singularities. We compute the Milnor number of isolated Cohen--Macaulay surface
singularities of this type in $\mathbb{C}^4$ and the difference of Betti
numbers of Milnor fibers for isolated Cohen--Macaulay 3--fold singularities of
this type in $\mathbb{C}^5$.


  We consider a class of one--dimensional non--convex non--coercive problems in
the Calculus of Variations. We prove an existence result for this class of
problems using a Liapunov type theorem on the range of non--atomic measures.


  The paper introduces the notion of the size of countable sets that preserves
the Part-Whole Principle and generalizes the notion of the cardinality of
finite sets. The sizes of natural numbers, integers, rational numbers, and all
their subsets, unions, and Cartesian products are algorithmically enumerable up
to one element as sequences of natural numbers. The method is similar to that
of Theory of Numerosities of Benci and Di Nasso 2019) but in comparison, it is
motivated by Bolzano's concept of infinite series from his Paradoxes of the
Infinite, it is constructive because it does not use ultrafilters, and set
sizes are uniquely determined. The results mostly agree with those of Theory of
Numerosities, but some differ, such as the size of rational numbers. However,
set sizes are just partially and not linearly ordered. \emph{Quid pro quo.}


  Mitchell's theorem on the approachability ideal states that it is consistent
relative to a greatly Mahlo cardinal that there is no stationary subset of
$\omega_2 \cap \mathrm{cof}(\omega_1)$ in the approachability ideal
$I[\omega_2]$. In this paper we give a new proof of Mitchell's theorem,
deriving it from an abstract framework of side condition methods.


  We prove that the Jacobi identity for the generalized Poisson bracket is
satisfied in the generalization of Heisenberg picture quantum mechanics
recently proposed by one of us (SLA). The identity holds for any combination of
fermionic and bosonic fields, and requires no assumptions about their mutual
commutativity.


  Nepal has a topographically diverse terrain with variations from plain
flatland to high hills and mountains within a small region. Due to the lack of
abundant ground-based measurement sites, it is difficult to estimate
evapotranspiration (ET) covering most of the areas of Nepal from lower to
higher elevations. In this study, we proposed to use a remote sensing-based
METRIC (Mapping Evapotranspiration at high Resolution with Internalized
Calibration) model for estimating ET in Nepal. Landsat 8 imagery, which
provides a fine spatial resolution (30 m), was used for the estimation. The
results obtained from the METRIC model were compared with ground-based
measurements from an independent Eddy-Covariance (EC) station. Besides ET, the
estimated surface temperatures (Ts) from the remote sensing model were also
compared with ground-based measurements for model validation. The results
obtained from the remote sensing model were close to the ground-based
measurements which establish the accuracy of the model. Root mean square error
(RMSE) for hourly and daily ET was obtained as 0.06 mm/hr and 1.24 mm/day while
mean bias error (MBE) for hourly and daily ET was observed as 0.03 mm/hr and
0.29 mm/day, respectively. Further, we analyzed the variations of ET with
elevation for six different months and found that ET was inversely related to
elevation, in general, over the regions of Nepal. This was established as an
effect of Ts and vegetation distribution over different elevations. To the best
of our knowledge, our study is a first that has investigated ET estimation over
a topographically diverse region of Nepal with fine spatial resolution afforded
by Landsat 8. Such large-scale ET estimation in Nepal has several applications.
This can be leveraged for agricultural planning and forecasting in a country
where most of the population still relies on agriculture for their daily
livelihood.


  Cross-lingual topic models have been prevalent for cross-lingual text
analysis by revealing aligned latent topics. However, most existing methods
suffer from producing repetitive topics that hinder further analysis and
performance decline caused by low-coverage dictionaries. In this paper, we
propose the Cross-lingual Topic Modeling with Mutual Information (InfoCTM).
Instead of the direct alignment in previous work, we propose a topic alignment
with mutual information method. This works as a regularization to properly
align topics and prevent degenerate topic representations of words, which
mitigates the repetitive topic issue. To address the low-coverage dictionary
issue, we further propose a cross-lingual vocabulary linking method that finds
more linked cross-lingual words for topic alignment beyond the translations of
a given dictionary. Extensive experiments on English, Chinese, and Japanese
datasets demonstrate that our method outperforms state-of-the-art baselines,
producing more coherent, diverse, and well-aligned topics and showing better
transferability for cross-lingual classification tasks.


  This paper considers the leader-follower tracking control problem for linear
interconnected systems with undirected topology and linear dynamic coupling.
Interactions between the systems are treated as linear dynamic uncertainty and
are described in terms of integral quadratic constraints (IQCs). A
consensus-type tracking control protocol is proposed for each system based on
its state relative its neighbors. In addition a selected set of subsystems uses
for control their relative states with respect to the leader. Two methods are
proposed for the design of this control protocol. One method uses a coordinate
transformation to recast the protocol design problem as a decentralized robust
control problem for an auxiliary interconnected large scale system. Another
method is direct, it does not employ coordinate transformation; it also allows
for more general linear uncertain interactions. Using these methods, sufficient
conditions are obtained which guarantee that the system tracks the leader.
These conditions guarantee a suboptimal bound on the system consensus and
tracking performance. The proposed methods are compared using a simulation
example, and their effectiveness is discussed. Also, algorithms are proposed
for computing suboptimal controllers.


  Ultrasound computed tomography techniques have the potential to provide
clinicians with 3D, quantitative and high-resolution information of both soft
and hard tissues such as the breast or the adult human brain. Their practical
application requires accurate modelling of the acquisition setup: the spatial
location, orientation, and impulse response of each ultrasound transducer.
However, existing calibration methods fail to accurately characterise these
transducers unless their size can be considered negligible when compared to the
dominant wavelength, which reduces signal-to-noise ratios below usable levels
in the presence of high-contrast tissues such as the skull. In this paper, we
introduce a methodology that can simultaneously estimate the location,
orientation, and impulse response of the ultrasound transducers in a single
calibration. We do this by extending spatial response identification, an
algorithm that we have recently proposed to estimate transducer impulse
responses. Our proposed methodology replaces the transducers in the acquisition
device with a surrogate model whose effective response matches the experimental
data by fitting a numerical model of wave propagation. This results in a
flexible and robust calibration procedure that can accurately predict the
behaviour of the ultrasound acquisition device without ever having to know
where the real transducers are or their individual impulse response.
Experimental results using a ring acquisition system show that spatial response
identification produces calibrations of significantly higher quality than
standard methodologies across all transducers, both in transmission and in
reception. Experimental full-waveform inversion reconstructions of a
tissue-mimicking phantom demonstrate that spatial response identification
generates more accurate reconstructions than those produced with standard
calibration techniques.


  In the mixed-mode asteroseismology of subgiants and red giants, the coupling
between the p- and g-mode cavities must be understood well in order to derive
localised estimates of interior rotation from measurements of mode multiplet
rotational splittings. There exist now two different descriptions of this
coupling: one based on an asymptotic quantisation condition, and the other
arising from coupling matrices associated with "acoustic molecular orbitals".
We examine the analytic properties of both, and derive closed-form expressions
for various quantities -- such as the period-stretching function $\tau$ --
which previously had to be solved for numerically. Using these, we reconcile
both formulations for the first time, deriving relations by which quantities in
each formulation may be translated to and interpreted within the other. This
yields an information criterion for whether a given configuration of mixed
modes meaningfully constrains the parameters of the asymptotic construction,
which is likely not satisfied by the majority of first-ascent red giant stars
in our observational sample. Since this construction has been already used to
make rotational measurements of such red giants, we examine -- through a
hare-and-hounds exercise -- whether, and how, such limitations affect existing
measurements. While averaged estimates of core rotation seem fairly robust,
template-matching using the asymptotic construction has difficulty reliably
assigning rotational splittings to individual multiplets, or estimating mixing
fractions $\zeta$ of the most p-dominated mixed modes, where such estimates are
most needed. We finally discuss implications for extending the two-zone model
of radial differential rotation, e.g. via rotational inversions, with these
methods.


  Accurate and reliable prediction of traffic measurements plays a crucial role
in the development of modern intelligent transportation systems. Due to more
complex road geometries and the presence of signal control, arterial traffic
prediction is a level above freeway traffic prediction. Many existing studies
on arterial traffic prediction only consider temporal measurements of flow and
occupancy from loop sensors and neglect the rich spatial relationships between
upstream and downstream detectors. As a result, they often suffer large
prediction errors, especially for long horizons. We fill this gap by enhancing
a deep learning approach, Diffusion Convolutional Recurrent Neural Network,
with spatial information generated from signal timing plans at targeted
intersections. Traffic at signalized intersections is modeled as a diffusion
process with a transition matrix constructed from the phase splits of the
signal phase timing plan. We apply this novel method to predict traffic flow
from loop sensor measurements and signal timing plans at an arterial
intersection in Arcadia, CA. We demonstrate that our proposed method yields
superior forecasts; for a prediction horizon of 30 minutes, we cut the MAPE
down to 16% for morning peaks, 10% for off peaks, and even 8% for afternoon
peaks. In addition, we exemplify the robustness of our model through a number
of experiments with various settings in detector coverage, detector type, and
data quality.


  We prove a novel pair of Littlewood identities for Schur functions, recently
conjectured by Lee, Rains and Warnaar in the Macdonald case, in which the sum
is over partitions with empty 2-core. As a byproduct we obtain a new Littlewood
identity in the spirit of Littlewood's original formulae.


  Delta-oriented programming (DOP) is a flexible transformational approach to
implement software product lines. In delta-oriented product lines, variants are
generated by applying operations contained in delta modules to a (possibly
empty) base program. These operations can add, remove or modify named elements
in a program (e.g., classes, methods and fields in a Java program). This paper
presents algorithms for refactoring a delta-oriented product line into
monotonic form, i.e., either to contain add and modify operations only
(monotonic increasing) or to contain remove and modify operations only
(monotonic decreasing). Because of their simpler structure, monotonic
delta-oriented product lines are easier to analyze. The algorithms are
formalized by means of a core calculus for DOP of product lines of Java
programs and their correctness and complexity are given.


  The strip map is a natural map from the arc complex of a bordered hyperbolic
surface $S$ to the vector space of infinitesimal deformations of $S$. We prove
that the image of the strip map is a convex hypersurface when $S$ is a surface
of small complexity: the punctured torus or thrice punctured sphere.


  The known near-Earth object (NEO) population consists of over 32,000 objects,
with a yearly discovery rate of over 3000 NEOs per year. An essential component
of the next generation of NEO surveys is an understanding of the population of
known objects, including an accounting of the discovery rate per year as a
function of size. Using a near-Earth asteroid (NEA) reference model developed
for NASA's NEO Surveyor (NEOS) mission and a model of the major current and
historical ground-based surveys, an estimate of the current NEA survey
completeness as a function of size and absolute magnitude has been determined
(termed the Known Object Model; KOM). This allows for understanding of the
intersection of the known catalog of NEAs and the objects expected to be
observed by NEOS. The current NEA population is found to be $\sim38\%$ complete
for objects larger than 140m, consistent with estimates by Harris & Chodas
(2021). NEOS is expected to catalog more than two thirds of the NEAs larger
than 140m, resulting in $\sim76\%$ of NEAs cataloged at the end of its 5 year
nominal survey (Mainzer et al, 2023}, making significant progress towards the
US Congressional mandate. The KOM estimates that $\sim77\%$ of the currently
cataloged objects will be detected by NEOS, with those not detected
contributing $\sim9\%$ to the final completeness at the end its 5 year mission.
This model allows for placing the NEO Surveyor mission in the context of
current surveys to more completely assess the progress toward the goal of
cataloging the population of hazardous asteroids.


  We investigate the notions of weak annihilator and nilpotent associated prime
defined by Ouyang and Birkenmeier \cite{OuyangBirkenmeier2012} in the setting
of noncommutative rings having PBW bases. We extend several results formulated
in the literature concerning annihilators and associated primes of commutative
rings and skew polynomial rings to a more general setting of algebras not
considered before. We exemplify our results with families of algebras appearing
in the theory of enveloping algebras, differential operators on noncommutative
spaces, noncommutative algebraic geometry, and theoretical physics. Finally, we
present some ideas for future research.


  Andreev reflection (AR) and Yanson point-contact spectroscopy (PCS) have been
applied simul-taneously to study the superconducting (SC) gap and the
electron-phonon interaction (EPI) in a Zn single crystal. The correlation
between SC gap value and EPI spectrum allowed us to establish the anisotropy of
the SC gap. Evidence for multiband superconductivity in Zn is present with two
gaps related as 1:1.3. We also found that the AR features are more robust
against the point-contact quality than the EPI ones, possibly, due to the large
coherence length in Zn compared to the typical PC size. Even for the PCs close
to the ballistic regime with intense EPI spectra, the transmission coefficient
evaluated from the AR spectra is near the one predicted theoretically for the
diffusive regime of a current flow in the PC. Understanding those phenomena
would provide a more reliable basis to apply both types of spectroscopies to
study more complex SCs.


  Photon-magnon coupling, where electromagnetic waves interact with spin waves,
and negative refraction, which bends the direction of electromagnetic waves
unnaturally, constitute critical foundations and advancements in the realms of
optics, spintronics, and quantum information technology. Here, we explore a
magnetic-field-controlled, on-off switchable, nonreciprocal negative refraction
within a non-Hermitian photon-magnon hybrid system. By integrating an yttrium
iron garnet film with an inverted split-ring resonator, we discover pronounced
negative refraction driven by the system's non-Hermitian properties. This
phenomenon exhibits unique nonreciprocal behavior dependent on the signal's
propagation direction. Our analytical model sheds light on the crucial
interplay between coherent and dissipative coupling, significantly altering
permittivity and permeability's imaginary components, crucial for negative
refraction's emergence. This work pioneers new avenues for employing negative
refraction in photon-magnon hybrid systems, signaling substantial advancements
in quantum hybrid systems.


  We evaluate the coordinate space dependence of the matrix elements of the
commutator of the electromagnetic and gluon currents in the vicinity of the
light-cone but at large distances within the parton model, DGLAP, the
resummation approaches to the small x behaviour of DIS processes, and for the
Unitarity Bound. We find that an increase of the commutator with relative
distance $py$ as $\propto (py)f(py,y^2=t^2-r^2)$ is the generic property of QCD
at small but fixed space-time interval $y^2=t^2-r^2$ in perturbative and
nonperturbative QCD regimes. We explain that the factor $py$ follows within the
dipole model (QCD factorization theorem) from the properties of Lorents
transformation. The increase of $f(r)$ disappeares at central impact parameters
if cross section of DIS may achieve the Unitarity Limit. We argue that such
long range forces are hardly consistent with thermodynamic equilibrium while a
Unitarity Limit may signal equilibration. Possible implications of this new
long range interaction are briefly discussed.


  The hyperon dynamics in heavy-ion collisions near threshold energy has been
investigated within the quantum molecular dynamics transport model. The isospin
and momentum dependent hyperon-nucleon potential and the threshold energy
correction on the hyperon elementary cross section are included in the model.
It is found that the high-density symmetry energy is dependent on the isospin
ratios $\Sigma^{-}/\Sigma^{+}$ and $\Xi^{-}/\Xi^{0}$, in particular in the
domain of high kinetic energies. The isospin diffusion in heavy-ion collisions
influences the neutron/proton ratio in the high-density region. The
$\Sigma^{-}/\Sigma^{+}$ ratio depends on the stiffness of symmetry energy, in
particular at the beam energy below the threshold value (E$_{th}$=1.58 GeV),
i.e., the kinetic energy spectra of the single ratios, excitation functions and
energy spectra of the double ratios in the isotopic reactions of $^{108}$Sn +
$^{112}$Sn, $^{112}$Sn + $^{112}$Sn, $^{124}$Sn + $^{124}$Sn and $^{132}$Sn +
$^{124}$Sn. The double strangeness ratio $\Xi^{-}/\Xi^{0}$ weakly depends on
the symmetry energy because of the hyperon-hyperon collision mainly
contributing the $\Xi$ production below the threshold energy (E$_{th}$ = 3.72
GeV).


  We study possible charge instabilities in doped Mott insulators by employing
the two-dimensional t-J model with a positive value of the next
nearest-neighbor hopping integral t' on a square lattice, which is applicable
to electron-doped cuprates. Although the d-wave charge density wave (flux
phase) and d-wave Pomeranchuk instability (nematic order) are dominant
instabilities for a negative t' that corresponds to hole-doped cuprates, we
find that those instabilities are strongly suppressed and become relevant only
rather close to half filling. Instead, various types of bond orders with
modulation vectors close to (pi,pi) are dominant in a moderate doping region.
Phase separation is also enhanced, but it can be suppressed substantially by
the nearest-neighbor Coulomb repulsion without affecting the aforementioned
charge instabilities.


  Qualitative and spectral properties of the form-sums
  S_{\pm}(V):=D_{\pm}^{2m}\dotplus V(x),\quad m\in \mathbb{N}, in the Hilbert
space $L_{2}(0,1)$ are studied. Here the periodic $(D_{+})$ and the
semiperiodic $(D_{-})$ differential operators are $D_{\pm}: u\mapsto -i u'$,
and $V(x)$ is a 1-periodic complex-valued distribution in the Sobolev spaces
$H_{per}^{-m\alpha}$, $\alpha\in [0,1]$.


  Recent biological experiments have shown that certain types of cells are able
to move in structured and confined environment even without the activation of
focal adhesion. Focusing on this particular phenomenon and based on previous
works, we derive a novel two-dimensional mechanical model, which relies on the
following physical ingredients: the asymmetrical renewal of the actin cortex
supporting the membrane, resulting in a backward flow of material; the
mechanical description of the nucleus membrane and the inner nuclear material;
the microtubule network guiding nucleus location; the contact interactions
between the cell and the external environment. The resulting fourth order
system of partial differential equations is then solved numerically to conduct
a study of the qualitative effects of the model parameters, mainly those
governing the mechanical properties of the nucleus and the geometry of the
confining structure. Coherently with biological observations, we find that
cells characterized by a stiff nucleus are unable to migrate in channels that
can be crossed by cells with a softer nucleus. Regarding the geometry, cell
velocity and ability to migrate are influenced by the width of the channel and
the wavelength of the external structure. Even though still preliminary, these
results can be potentially useful in determining the physical limit of cell
migration in confined environment and in designing scaffold for tissue
engineering.


  We investigate the effect of on-site Coulomb repulsion $U$ on the band gap of
the electrically gated bilayer graphene by employing coherent potential
approximation in the paramagnetic state, based on an ionic two-layer Hubbard
model. We find that, while either the on-site Coulomb repulsion $U$ or the
external perpendicular electric field $E$ alone will favor a gapped state in
the bilayer graphene, competition between them will surprisingly lead to a
suppression of the gap amplitude. Our results can be applied to understand the
discrepancies of gap size reported from optical and transport measurements, as
well as the puzzling features observed in angular resolved photoemission
spectroscopic study.


  In this paper, we address the problem of privacy-preserving hyperparameter
(HP) tuning for cross-silo federated learning (FL). We first perform a
comprehensive measurement study that benchmarks various HP strategies suitable
for FL. Our benchmarks show that the optimal parameters of the FL server, e.g.,
the learning rate, can be accurately and efficiently tuned based on the HPs
found by each client on its local data. We demonstrate that HP averaging is
suitable for iid settings, while density-based clustering can uncover the
optimal set of parameters in non-iid ones. Then, to prevent information leakage
from the exchange of the clients' local HPs, we design and implement PrivTuna,
a novel framework for privacy-preserving HP tuning using multiparty homomorphic
encryption. We use PrivTuna to implement privacy-preserving federated averaging
and density-based clustering, and we experimentally evaluate its performance
demonstrating its computation/communication efficiency and its precision in
tuning hyperparameters.


  A study of the applicability of the variational treatments based on using of
the modified Lang-Firsov unitary transformation (MLF method) in the
investigation of the vibron self-trapped states in biological macromolecular
chains are presented. We compare the values of the ground state energy
predicted by MLF methods with the values of the ground state energy predicted
by the standard small-polaron theory, for various values of the basic energy
parameters of the system. We obtain regions in system parameter space where MLF
approach gives better description of the vibron states.


  Recent developments in engineering and algorithms have made real-world
applications in quantum computing possible in the near future. Existing quantum
programming languages and compilers use a quantum assembly language composed of
1- and 2-qubit (quantum bit) gates. Quantum compiler frameworks translate this
quantum assembly to electric signals (called control pulses) that implement the
specified computation on specific physical devices. However, there is a
mismatch between the operations defined by the 1- and 2-qubit logical ISA and
their underlying physical implementation, so the current practice of directly
translating logical instructions into control pulses results in inefficient,
high-latency programs. To address this inefficiency, we propose a universal
quantum compilation methodology that aggregates multiple logical operations
into larger units that manipulate up to 10 qubits at a time. Our methodology
then optimizes these aggregates by (1) finding commutative intermediate
operations that result in more efficient schedules and (2) creating custom
control pulses optimized for the aggregate (instead of individual 1- and
2-qubit operations). Compared to the standard gate-based compilation, the
proposed approach realizes a deeper vertical integration of high-level quantum
software and low-level, physical quantum hardware. We evaluate our approach on
important near-term quantum applications on simulations of superconducting
quantum architectures. Our proposed approach provides a mean speedup of
$5\times$, with a maximum of $10\times$. Because latency directly affects the
feasibility of quantum computation, our results not only improve performance
but also have the potential to enable quantum computation sooner than otherwise
possible.


  Determining the Galactic distribution and numbers of massive stars, such as
Wolf-Rayet stars (WRs), is hampered by intervening Galactic or local
circumstellar dust obscuration. In order to probe such regions of the Galaxy we
can use infrared observations, which provide a means for finding such hidden
populations through the dust. The availability of both 2MASS and
Spitzer/GLIMPSE large-scale survey data provides infrared colours from 1.25 to
8$\mu$m for a large fraction of the inner Galactic plane. In 2005 we initiated
a pilot study of the combined set of infrared colours for two GLIMPSE fields
and showed that WRs typically occupy a sparsely populated region of the colour
space. We followed up 42 of our WR candidates spectroscopically in the
near-infrared, and with limited additional observations of some of these
candidates in the optical. Six new WRs, four late-type WN and two late-type WC
stars, were discovered as a result. Of the remaining $\sim$86% of the sample,
five appear to be O-type stars. 21 stars are likely of type Be, and 10 stars
appear to be of late-type, or possibly young stellar objects, which have
"contaminated" the infrared color space. The survey is generally unbiased
towards clusters or field stars, and the new WRs found are in both the field
and in and around the RCW 49 region (including cluster Westerlund 2). In this
work, and in our other recent work, we show that the infrared broad-band
colours to be the most efficient means of identifying (particularly,
dust-obscured) candidate massive stars, notably WRs.


  Resonant Beam Charging (RBC) is a wireless charging technology which supports
multi-watt power transfer over meter-level distance. The features of safety,
mobility and simultaneous charging capability enable RBC to charge multiple
mobile devices safely at the same time. To detect the devices that need to be
charged, a Mask R-CNN based dection model is proposed in previous work.
However, considering the constraints of the RBC system, it's not easy to apply
Mask R-CNN in lightweight hardware-embedded devices because of its heavy model
and huge computation. Thus, we propose a machine learning detection approach
which provides a lighter and faster model based on traditional Mask R-CNN. The
proposed approach makes the object detection much easier to be transplanted on
mobile devices and reduce the burden of hardware computation. By adjusting the
structure of the backbone and the head part of Mask R-CNN, we reduce the
average detection time from $1.02\mbox{s}$ per image to $0.6132\mbox{s}$, and
reduce the model size from $245\mbox{MB}$ to $47.1\mbox{MB}$. The improved
model is much more suitable for the application in the RBC system.


  We consider the nonlinear boundary value problem consisting of the equation
\tag{1} -u" = f(u) + h, \quad \text{a.e. on $(-1,1)$,} where $h \in L^1(-1,1)$,
together with the multi-point, Dirichlet-type boundary conditions \tag{2} u(\pm
1) = \sum^{m^\pm}_{i=1}\alpha^\pm_i u(\eta^\pm_i) where $m^\pm \ge 1$ are
integers, $\alpha^\pm = (\alpha_1^\pm, ...,\alpha_m^\pm) \in [0,1)^{m^\pm}$,
$\eta^\pm \in (-1,1)^{m^\pm}$, and we suppose that $$
  \sum_{i=1}^{m^\pm} \alpha_i^\pm < 1 . $$ We also suppose that $f : \mathbb{R}
\to \mathbb{R}$ is continuous, and $$ 0 < f_{\pm\infty}:=\lim_{s \to \pm\infty}
\frac{f(s)}{s} < \infty. $$ We allow $f_{\infty} \ne f_{-\infty}$ --- such a
nonlinearity $f$ is {\em jumping}.
  Related to (1) is the equation \tag{3} -u" = \lambda(a u^+ - b u^-), \quad
\text{on $(-1,1)$,} where $\lambda,\,a,\,b > 0$, and $u^{\pm}(x) =\max\{\pm
u(x),0\}$ for $x \in [-1,1]$. The problem (2)-(3) is `positively-homogeneous'
and jumping. Regarding $a,\,b$ as fixed, values of $\lambda = \lambda(a,b)$ for
which (2)-(3) has a non-trivial solution $u$ will be called {\em
half-eigenvalues}, while the corresponding solutions $u$ will be called {\em
half-eigenfunctions}.
  We show that a sequence of half-eigenvalues exists, the corresponding
half-eigenfunctions having specified nodal properties, and we obtain certain
spectral and degree theoretic properties of the set of half-eigenvalues. These
properties lead to solvability and non-solvability results for the problem
(1)-(2). The set of half-eigenvalues is closely related to the `Fucik spectrum'
of the problem, which we briefly describe. Equivalent solvability and
non-solvability results for (1)-(2) are obtained from either the
half-eigenvalue or the Fucik spectrum approach.


  Let $s_q(n)$ denote the sum of the digits in the $q$-ary expansion of an
integer $n$. In 1978, Stolarsky showed that $$ \liminf_{n\to\infty}
\frac{s_2(n^2)}{s_2(n)} = 0. $$ He conjectured that, as for $n^2$, this limit
infimum should be 0 for higher powers of $n$. We prove and generalize this
conjecture showing that for any polynomial $p(x)=a_h x^h+a_{h-1} x^{h-1} + ...
+ a_0 \in \Z[x]$ with $h\geq 2$ and $a_h>0$ and any base $q$, \[
\liminf_{n\to\infty} \frac{s_q(p(n))}{s_q(n)}=0.\] For any $\epsilon > 0$ we
give a bound on the minimal $n$ such that the ratio $s_q(p(n))/s_q(n) <
\epsilon$. Further, we give lower bounds for the number of $n < N$ such that
$s_q(p(n))/s_q(n) < \epsilon$.


  In minimal supersymmetric SU(5) models, the proton can decay through
dimension 5 operators. Since this decay depends directly on the supersymmetric
soft masses, it will be constrained by other observables which depend on the
soft masses, such as the Higgs mass and the dark matter relic density. In this
work, we will examine the upper limit on the proton lifetime in minimal
supersymmetric SU(5) with constrained minimal supersymmetric (CMSSM) boundary
conditions set at the grand unification scale. We perform a random scan over
the variables of the (CMSSM), with of order $10^{6}$ points, and find that the
proton lifetime is within reach of JUNO and Hyper-Kamiokande's experiment.


  The use of precise time-of-flight (ToF) detectors for measurements of
diffractive and electromagnetic processes in proton-proton collisions is
discussed. The performance of background rejection exploiting the ToF
measurements of the forward protons is derived. The influence of additional
timing measurements delivered by the central detectors is presented and the
possible gain is studied.


  Part 1 of the study intends to show that the universal trend of amino acid
gain and loss discovered by Jordan et al. (2005) can be accounted for by the
spontaneity of DNA typical damages. These damages lead to replacements of
guanine and cytosine by thymine. Part 2 proposes a hypothesis of the evolution
of the genetic code, the leading mechanism of which is the nucleotide
spontaneous damage. The hypothesis accounts for the universal trend of amino
acid gain and loss, stability of the genetic code towards point mutations, the
presence of code dialects, and the symmetry of the genetic code table.


  We consider the problem of reconstructing the symmetric difference between
similar sets from their representations (sketches) of size linear in the number
of differences. Exact solutions to this problem are based on error-correcting
coding techniques and suffer from a large decoding time. Existing probabilistic
solutions based on Invertible Bloom Lookup Tables (IBLTs) are time-efficient
but offer insufficient success guarantees for many applications. Here we
propose a tunable trade-off between the two approaches combining the efficiency
of IBLTs with exponentially decreasing failure probability. The proof relies on
a refined analysis of IBLTs proposed in (Baek Tejs Houen et al. SOSA 2023)
which has an independent interest. We also propose a modification of our
algorithm that enables telling apart the elements of each set in the symmetric
difference.


  Tabletop exercises are a crucial component of many company's strategy to test
and evaluate its preparedness for security incidents in a realistic way.
Traditionally led by external firms specializing in cybersecurity, these
exercises can be costly, time-consuming, and may not always align precisely
with the client's specific needs. Large Language Models (LLMs) like ChatGPT
offer a compelling alternative. They enable faster iteration, provide rich and
adaptable simulations, and offer infinite patience in handling feedback and
recommendations. This approach can enhances the efficiency and relevance of
security preparedness exercises.


  We present an alternative explanation for the nature of turbulence in
molecular clouds. Often associated with classical models of turbulence, we
instead interpret the observed gas dynamics as random motions, induced when
clumpy gas is subject to a shock. From simulations of shocks, we show that a
supersonic velocity dispersion occurs in the shocked gas provided the initial
distribution of gas is sufficiently non-uniform. We investigate the velocity
size-scale relation $\sigma \propto r^{\alpha}$ for simulations of clumpy and
fractal gas, and show that clumpy shocks can produce realistic velocity
size-scale relations with mean $\alpha \thicksim 0.5$. For a fractal
distribution, with a fractal dimension of 2.2 similar to what is observed in
the ISM, we find $\sigma \propto r^{0.4}$. The form of the velocity size-scale
relation can be understood as due to mass loading, i.e. the post-shock velocity
of the gas is determined by the amount of mass encountered as the gas enters
the shock. We support this hypothesis with analytical calculations of the
velocity dispersion relation for different initial distributions.
  A prediction of this model is that the line-of sight velocity dispersion
should depend on the angle at which the shocked gas is viewed.


  We developed new modified embedded-atom method (MEAM) interatomic potentials
for the Mg-Al alloy system using a first-principles method based on density
functional theory (DFT). The materials parameters, such as the cohesive energy,
equilibrium atomic volume, and bulk modulus, were used to determine the MEAM
parameters. Face-centered cubic, hexagonal close packed, and cubic rock salt
structures were used as the reference structures for Al, Mg, and MgAl,
respectively. The applicability of the new MEAM potentials to atomistic
simulations for investigating Mg-Al alloys was demonstrated by performing
simulations on Mg and Al atoms in a variety of geometries. The new MEAM
potentials were used to calculate the adsorption energies of Al and Mg atoms on
Al (111) and Mg (0001) surfaces. The formation energies and geometries of
various point defects, such as vacancies, interstitial defects and
substitutional defects, were also calculated. We found that the new MEAM
potentials give a better overall agreement with DFT calculations and
experiments when compared against the previously published MEAM potentials.


  We have implemented field models and performed a detailed numerical dosimetry
inside our extremely-low-frequency electromagnetic bioreactor which has been
successfully used in $\textit{in vitro}$ Biotechnology and Tissue Engineering
researches. The numerical dosimetry permitted to map the magnetic induction
field (maximum module equal to about 3.3 mT) and to discuss its biological
effects in terms of induced electric currents and induced mechanical forces
(compression and traction). So, in the frame of the
tensegrity-mechanotransduction theory of Ingber, the study of these
electromagnetically induced mechanical forces could be, in our opinion, a
powerful tool to understand some effects of the electromagnetic stimulation
whose mechanisms remain still elusive.


  In this paper, we report an optimized union-find (UF) algorithm that can
label the connected components on a 2D image efficiently by employing the GPU
architecture. The proposed method contains three phases: UF-based local merge,
boundary analysis, and link. The coarse labeling in local merge reduces the
number atomic operations, while the boundary analysis only manages the pixels
on the boundary of each block. Evaluation results showed that the proposed
algorithm speed up the average running time by more than 1.3X.


  Rapid advances in technology gradually realize immersive mixed-reality (MR)
telepresence between distant spaces. This paper presents a novel visual
guidance system for avatar-mediated telepresence, directing users to optimal
placements that facilitate the clear transfer of gaze and pointing contexts
through remote avatars in dissimilar spaces, where the spatial relationship
between the remote avatar and the interaction targets may differ from that of
the local user. Representing the spatial relationship between the user/avatar
and interaction targets with angle-based interaction features, we assign
recommendation scores of sampled local placements as their maximum feature
similarity with remote placements. These scores are visualized as color-coded
2D sectors to inform the users of better placements for interaction with
selected targets. In addition, virtual objects of the remote space are
overlapped with the local space for the user to better understand the
recommendations. We examine whether the proposed score measure agrees with the
actual user perception of the partner's interaction context and find a score
threshold for recommendation through user experiments in virtual reality (VR).
A subsequent user study in VR investigates the effectiveness and perceptual
overload of different combinations of visualizations. Finally, we conduct a
user study in an MR telepresence scenario to evaluate the effectiveness of our
method in real-world applications.


  We propose a novel phrase break prediction method that combines implicit
features extracted from a pre-trained large language model, a.k.a BERT, and
explicit features extracted from BiLSTM with linguistic features. In
conventional BiLSTM based methods, word representations and/or sentence
representations are used as independent components. The proposed method takes
account of both representations to extract the latent semantics, which cannot
be captured by previous methods. The objective evaluation results show that the
proposed method obtains an absolute improvement of 3.2 points for the F1 score
compared with BiLSTM-based conventional methods using linguistic features.
Moreover, the perceptual listening test results verify that a TTS system that
applied our proposed method achieved a mean opinion score of 4.39 in prosody
naturalness, which is highly competitive with the score of 4.37 for synthesized
speech with ground-truth phrase breaks.


  This is the second part in a four-paper sequence, which establishes the
Threshold Conjecture and the Soliton Bubbling vs.~Scattering Dichotomy for the
hyperbolic Yang--Mills equation in the $(4+1)$-dimensional space-time. This
paper provides the key gauge-dependent analysis of the hyperbolic Yang--Mills
equation.
  We consider topologically trivial solutions in the caloric gauge, which was
defined in the first paper arXiv:1709.08599 using the Yang--Mills heat flow. In
this gauge, we establish a strong form of local well-posedness, where the time
of existence is bounded from below by the energy concentration scale. Moreover,
we show that regularity and dispersive behavior of the solution persists as
long as energy dispersion is small. We also observe that fixed-time regularity
(but not dispersive) properties in the caloric gauge may be transferred to the
temporal gauge without any loss, proving as a consequence small data global
well-posedness in the temporal gauge.
  The results in this paper are used in the subsequent papers arXiv:1709.08604,
arXiv:1709.08606 to prove the sharp Threshold Theorem in caloric gauge in the
trivial topological class, and the dichotomy theorem in arbitrary topological
classes.


  We define a natural class of star products: those which are given by a series
of bidifferential operators which at order $k$ in the deformation parameter
have at most $k$ derivatives in each argument. We show that any such star
product on a symplectic manifold defines a unique symplectic connection. We
parametrise such star products, study their invariance and give necessary and
sufficient conditions for them to yield a quantum moment map. We show that
Kravchenko's sufficient condition for a moment map for a Fedosov star product
is also necessary.


  This article deals with the observation problem in traffic flow theory. The
model used is the semilinear viscous Burgers equation. Instead of using the
traditional fixed sensors to estimate the state of the traffic at given points,
the measurements here are obtained from Probe Vehicles (PVs). We propose then a
moving dynamic boundary observer whose boundaries are defined by the
trajectories of the PVs. The main result of this article is the exponential
convergence of the observation error, and, in some cases, its finite-time
convergence. Finally, numerical simulations show that it is possible to observe
the traffic in the congested, free-flow, and mixed regimes provided that the
number of PVs is large enough.


  We examine the use of linear and non-linear dimensionality reduction
algorithms for extracting low-rank feature representations for speech emotion
recognition. Two feature sets are used, one based on low-level descriptors and
their aggregations (IS10) and one modeling recurrence dynamics of speech (RQA),
as well as their fusion. We report speech emotion recognition (SER) results for
learned representations on two databases using different classification
methods. Classification with low-dimensional representations yields performance
improvement in a variety of settings. This indicates that dimensionality
reduction is an effective way to combat the curse of dimensionality for SER.
Visualization of features in two dimensions provides insight into
discriminatory abilities of reduced feature sets.


  A set is called r-independent, if every two vertices of it are in distance
greater then r. In the r-independent set problem with parameter k, we ask
whether in a given graph G there exists an r-independent set of size k. In this
work we present an algorithm for this problem, which applied to a graph from
any fixed nowhere dense class, works in time bounded by f(k, r)*G, for some
function f. We also present alternative algorithm, with running time bounded by
g(k, r)*G, working on slightly more general classes of graphs.


  In this paper, we prove a Serrin-type result for an elliptic system of
equations, overdetermined with both Dirichlet and a generalized Neumann
conditions. With this tool, we characterize the critical shapes under volume
constraint of some domain functionals.


  We study how to incorporate CP violation in the Froggatt--Nielsen (FN)
mechanism. To this end, we introduce non-renormalizable interactions with a
flavor democratic structure to the fermion mass generation sector. It is found
that at least two iso-singlet scalar fields with imposed a discrete symmetry
are necessary to generate CP violation due to the appearance of the relative
phase between their vacuum expectation values.
  In the simplest model, ratios of quark masses and the
Cabibbo-Kobayashi-Maskawa (CKM) matrix including the CP violating phase are
determined by the CKM element |V_{us}| and the ratio of two vacuum expectation
values R=|R|e^{i*alpha} (a magnitude and a phase). It is demonstrated how the
angles phi_i (i=1--3) of the unitarity triangle and the CKM off-diagonal
elements |V_{ub}| and |V_{cb}| are predicted as a function of |V_{us}|, |R| and
\alpha. Although the predicted value of the CP violating phase does not agree
with the experimental data within the simplest model, the basic idea of our
scenario would be promising to construct a more realistic model of flavor and
CP violation.


  Bifractional transformations which lead to quantities that interpolate
between other known quantities, are considered. They do not form a group, and
groupoids are used to described their mathematical structure. Bifractional
coherent states and bifractional Wigner functions are also defined. The
properties of the bifractional coherent states are studied. The bifractional
Wigner functions are used in generalizations of the Moyal star formalism. A
generalized Berezin formalism in this context, is also studied.


  Empirical risk minimization (ERM) is a fundamental learning rule for
statistical learning problems where the data is generated according to some
unknown distribution $\mathsf{P}$ and returns a hypothesis $f$ chosen from a
fixed class $\mathcal{F}$ with small loss $\ell$. In the parametric setting,
depending upon $(\ell, \mathcal{F},\mathsf{P})$ ERM can have slow
$(1/\sqrt{n})$ or fast $(1/n)$ rates of convergence of the excess risk as a
function of the sample size $n$. There exist several results that give
sufficient conditions for fast rates in terms of joint properties of $\ell$,
$\mathcal{F}$, and $\mathsf{P}$, such as the margin condition and the Bernstein
condition. In the non-statistical prediction with expert advice setting, there
is an analogous slow and fast rate phenomenon, and it is entirely characterized
in terms of the mixability of the loss $\ell$ (there being no role there for
$\mathcal{F}$ or $\mathsf{P}$). The notion of stochastic mixability builds a
bridge between these two models of learning, reducing to classical mixability
in a special case. The present paper presents a direct proof of fast rates for
ERM in terms of stochastic mixability of $(\ell,\mathcal{F}, \mathsf{P})$, and
in so doing provides new insight into the fast-rates phenomenon. The proof
exploits an old result of Kemperman on the solution to the general moment
problem. We also show a partial converse that suggests a characterization of
fast rates for ERM in terms of stochastic mixability is possible.


  We investigate a two-dimensional network simulator that model the dynamics of
two-phase immiscible bulk flow where film flow can be neglected. We present a
method for simulating the detailed dynamical process where the two phases are
allowed to break up into bubbles, and bubbles are allowed to merge together.
The notions of drainage and imbibition are not adequate to describe this
process since there is no clear front between the fluids. In fact, the
simulator is constructed so that one can study the behaviour of the system far
from inlets and outlets, where the two fluids have been mixed together so much
that all initial fronts have broken up. The simulator gives the fractional flow
as a function of the saturation of each of the fluids. For the case of two
fluids with equal viscosity, we classify flow regimes that are parametrized by
the capillary number.


  Motivated by a question of Bumagin and Wise, we construct a continuum of
finitely generated, residually finite groups whose outer automorphism groups
are pairwise non-isomorphic finitely generated, non-recursively-presentable
groups. These are the first examples of such residually finite groups.


  The purpose of this paper is to establish a non-integrated defect relation
for meromorphic mappings from a complete K\"{a}hler manifold into a projective
variety intersecting an arbitrary family of hypersurfaces with explicit
truncation level. In our result, both the total defect and the truncation level
are estimated independently of the number of involving hypersurfaces. Our
result generalizes and improves the previous results in this topic.


  Kalman filtering is a classic state estimation technique used in application
areas such as signal processing and autonomous control of vehicles. It is now
being used to solve problems in computer systems such as controlling the
voltage and frequency of processors.
  Although there are many presentations of Kalman filtering in the literature,
they usually deal with particular systems like autonomous robots or linear
systems with Gaussian noise, which makes it difficult to understand the general
principles behind Kalman filtering. In this paper, we first present the
abstract ideas behind Kalman filtering at a level accessible to anyone with a
basic knowledge of probability theory and calculus, and then show how these
concepts can be applied to the particular problem of state estimation in linear
systems. This separation of concepts from applications should make it easier to
understand Kalman filtering and to apply it to other problems in computer
systems.


  Carbon monoxide (CO) is widely used as a tracer of molecular hydrogen (H2) in
metal-rich galaxies, but is known to become ineffective in low metallicity
dwarf galaxies. Atomic carbon has been suggested as a superior tracer of H2 in
these metal-poor systems, but its suitability remains unproven. To help us to
assess how well atomic carbon traces H2 at low metallicity, we have performed a
series of numerical simulations of turbulent molecular clouds that cover a wide
range of different metallicities. Our simulations demonstrate that in
star-forming clouds, the conversion factor between [CI] emission and H2 mass,
$X_{\rm CI}$, scales approximately as $X_{\rm CI} \propto Z^{-1}$. We recover a
similar scaling for the CO-to-H2 conversion factor, $X_{\rm CO}$, but find that
at this point in the evolution of the clouds, $X_{\rm CO}$ is consistently
smaller than $X_{\rm CI}$, by a factor of a few or more. We have also examined
how $X_{\rm CI}$ and $X_{\rm CO}$ evolve with time. We find that $X_{\rm CI}$
does not vary strongly with time, demonstrating that atomic carbon remains a
good tracer of H2 in metal-poor systems even at times significantly before the
onset of star formation. On the other hand, $X_{\rm CO}$ varies very strongly
with time in metal-poor clouds, showing that CO does not trace H2 well in
starless clouds at low metallicity.


  Peaks in the probabilities of loops or bubbles, helical segments, and
unzipping ends in melting DNA are found in this article using a peak finding
method that maps the hierarchical structure of certain energy landscapes. The
peaks indicate the alternative conformations that coexist in equilibrium and
the range of their fluctuations. This yields a representation of the
conformational ensemble at a given temperature, which is illustrated in a
single diagram called a stitch profile. This article describes the methodology
and discusses stitch profiles vs. the ordinary probability profiles using the
phage lambda genome as an example.


  A wide variety of vacua, and their cosmological realization, may provide an
explanation for the apparently anthropic choices of some parameters of particle
physics and cosmology. If the probability on various parameters is weighted by
volume, a flat potential for slow-roll inflation is also naturally understood,
since the flatter the potential the larger the volume of the sub-universe.
However, such inflationary landscapes have a serious problem, predicting an
environment that makes it exponentially hard for observers to exist and giving
an exponentially small probability for a moderate universe like ours. A general
solution to this problem is proposed, and is illustrated in the context of
inflaton decay and leptogenesis, leading to an upper bound on the reheating
temperature in our sub-universe. In a particular scenario of chaotic inflation
and non-thermal leptogenesis, predictions can be made for the size of CP
violating phases, the rate of neutrinoless double beta decay and, in the case
of theories with gauge-mediated weak scale supersymmetry, for the fundamental
scale of supersymmetry breaking.


  We extend the language of the classical syllogisms with the sentence-forms
"At most 1 p is a q" and "More than 1 p is a q". We show that the resulting
logic does not admit a finite set of syllogism-like rules whose associated
derivation relation is sound and complete, even when reductio ad absurdum is
allowed.


  We study the $S>1/2$ antiferromagnetic Heisenberg model on the 1/5-depleted
square lattice as a function of the ratio of the intra-plaquette coupling to
the inter-plaquette coupling. Using stochastic series expansion quantum Monte
Carlo simulations, we numerically identify three quantum phases, including the
dimer phase, N\'eel phase and plaquette valence bond solid phase. We also
obtain the accurate quantum critical points that belong to the O(3)
universality class using the large-scale finite-size scaling. Most importantly,
we study the dynamic spin structure factors of different phases, which can be
measured by inelastic neutron scattering experiments. The low-energy
excitations can be explained as triplons in the dimer phase and plaquette
valence bond solid phase. While in the N\'eel phase, the more prominent magnon
mode can be found as the spin magnitude increases. Furthermore, we find a
broader continuum at smaller $S$, which may be the dynamical signature of
nearly deconfined spinon excitations.


  The purpose of the present paper is to investigate cohomologies of Reynolds
Lie-Yamaguti algebras of any weight and provide some applications. First, we
introduce the notion of Reynolds Lie-Yamaguti algebras and give some new
examples. Moreover, cohomologies of Reynolds operators and Reynolds
Lie-Yamaguti algebras with coefficients in a suitable representation are
established. Finally, formal deformations and abelian extensions of Reynolds
Lie-Yamaguti algebras are characterized in terms of lower degree cohomology
groups.


  The pre-trained language model is trained on large-scale unlabeled text and
can achieve state-of-the-art results in many different downstream tasks.
However, the current pre-trained language model is mainly concentrated in the
Chinese and English fields. For low resource language such as Tibetan, there is
lack of a monolingual pre-trained model. To promote the development of Tibetan
natural language processing tasks, this paper collects the large-scale training
data from Tibetan websites and constructs a vocabulary that can cover 99.95$\%$
of the words in the corpus by using Sentencepiece. Then, we train the Tibetan
monolingual pre-trained language model named TiBERT on the data and vocabulary.
Finally, we apply TiBERT to the downstream tasks of text classification and
question generation, and compare it with classic models and multilingual
pre-trained models, the experimental results show that TiBERT can achieve the
best performance. Our model is published in http://tibert.cmli-nlp.com/


  In a 3-wave mixing process occurring in some nonlinear optical medium when
}$a_{1}^{\dagger}${\small mode interacts with both }$a_{2}^{\dagger}% ${\small
mode and }$a_{3}^{\dagger}${\small mode, we theoretically study the squeezing
effect generated by the operator }$S_{3}\equiv \exp[\mu(a_{1}%
a_{2}-a_{1}^{\dagger}a_{2}^{\dagger})+\nu(a_{1}a_{3}-a_{1}^{\dagger}%
a_{3}^{\dagger})]${\small . The new 3-mode squeezed vacuum state in Fock space
is derived, and the uncertainty relation for it is demonstrated, It turns out
that }$S_{3}${\small may exhibit enhanced squeezing. By virtue of the technique
of integration within an ordered product (IWOP) of operators, we also derive
}$S_{3}${\small 's normally ordered expansion. The Wigner function of new
3-mode squeezed vacuum state is calculated by using the Weyl ordering
invariance under similar transformations.


  We obtain a necessary and sufficient condition for the linear independence of
solutions of differential equations for hyperlogarithms. The key fact is that
the multiplier (i.e. the factor $M$ in the differential equation $dS=MS$) has
only singularities of first order (Fuchsian-type equations) and this implies
that they freely span a space which contains no primitive. We give direct
applications where we extend the property of linear independence to the largest
known ring of coefficients.


  In this paper, we revisit the proof of the large deviations principle of
Wiener chaoses partially given by Borel, and then by Ledoux in its full form.
We show that some heavy-tail phenomena observed in large deviations can be
explained by the same mechanism as for the Wiener chaoses, meaning that the
deviations are created, in a sense, by translations. More precisely, we prove a
general large deviations principle for a certain class of functionals $f_n :
\mathbb{R}^n \to \mathcal{X}$, where $\mathcal{X}$ is some metric space, under
the $n$-fold probability measure $\nu_{\alpha}^n$, where $\nu_{\alpha}
=Y_{\alpha}^{-1}e^{-|x|^{\alpha}}dx$, $\alpha \in (0,2]$, for which the large
deviations are due to translations. We retrieve, as an application, the large
deviations principles known for the Wigner matrices without Gaussian tails, of
the empirical spectral measure by Bordenave and Caputo, the largest eigenvalue
and traces of polynomials by the author. We also apply our large deviations
result to the last-passage time, which yields a large deviations principle when
the weights have the density $Z_{\alpha}^{-1} e^{-x^{\alpha}}$ with respect to
Lebesgue measure on $\mathbb{R}_+$, with $\alpha \in (0,1)$.


  Quantum nucleation processes in the presence of local moderate
inhomogeneities are studied theoretically at high biases. The quantum
nucleation rate Gamma is calculated for one-dimensional systems in a form Gamma
= A e^(-B/hbar) by using the `bounce' method. The bias-dependence of the
exponent B is shown to be changed by inhomogeneities. This change is explained
by the reduction of the effective spatial dimension of the system. By studying
the system-size dependence of the prefactor A, the condition for the appearance
of inhomogeneity effects is evaluated. Nucleation rates in thermal activation
regimes are also calculated, and compared with quantum tunneling regimes. For
higher-dimensional systems, it is shown that the local approximation of
inhomogeneity does not hold, and that spatial profiles of inhomogeneity become
important.


  In empirical software engineering, benchmarks can be used for comparing
different methods, techniques and tools. However, the recent ACM SIGSOFT
Empirical Standards for Software Engineering Research do not include an
explicit checklist for benchmarking. In this paper, we discuss benchmarks for
software performance and scalability evaluation as example research areas in
software engineering, relate benchmarks to some other empirical research
methods, and discuss the requirements on benchmarks that may constitute the
basis for a checklist of a benchmarking standard for empirical software
engineering research.


  We consider the tension-induced non-linearities of mechanical resonators, and
derive the Hamiltonian of the flexural modes up to the fourth order in the
position operators. This tension can be controlled by a nearby gate voltage. We
focus on systems which allow large deformations $u(x)\gg h$ compared to the
thickness $h$ of the resonator and show that in this case the third-order
coupling can become non-zero due to the induced dc deformation and offers the
possibility to realize equations of motion encountered in optomechanics. The
fourth-order coupling is relevant especially for relatively low voltages. It
can be detected by accessing the Duffing regime, and by measuring frequency
shifts due to mode-mode coupling.


  The Barbero-Immirzi parameter is a one parameter quantization ambiguity
underpinning the loop approach to quantum gravity that bears tantalizing
similarities to the theta parameter of gauge theories such as Yang-Mills and
QCD. Despite the apparent semblance, the Barbero-Immirzi field has resisted a
direct topological interpretation along the same lines as the theta-parameter.
Here we offer such an interpretation. Our approach begins from the perspective
of Einstein-Cartan gravity as the symmetry broken phase of a de Sitter gauge
theory. From this angle, just as in ordinary gauge theories, a theta-term
emerges from the requirement that the vacuum is stable against quantum
mechanical tunneling. The Immirzi parameter is then identified as a combination
of Newton's constant, the cosmological constant, and the theta-parameter.


  We present simple parametric equations in terms of Jacobi elliptic functions
that provide a realistic model of the shape of human normal erythrocytes as
well as of variations in size (anisocytosis) and shape (poikilocytosis)
thereof. We illustrate our results with parameterizations of microcytes,
macrocytes and stomatocytes, and show the applicability of these
parameterizations to the numerical calculation of the induced transmembrane
voltage in microcytes, macrocytes and stomatocytes exposed to an external RF
field of 1800 MHz.


  In this paper we consider an axial torsion to build metric-compatible
connections in conformal gravity, with gauge potentials; the geometric
background is filled with Dirac spinors: scalar fields with suitable potentials
are added eventually. The system of field equations is worked out to have
torsional effects converted into spinorial self-interactions: the massless
spinors display self-interactions of a specific form that gives them the
features they have in the non-conformal theory but with the additional
character of renormalizability, and the mechanisms of generation of mass and
cosmological constants become dynamical. As a final step we will address the
cosmological constant and coincidence problems.


  We investigate the stability of the solutions of the BCS model with the
external pair potential formulated in a work K.V. Grigorishin arXiv:1605.07080.
It has been shown that the cause of superconductivity in this model is the
electron-electron interaction only and the potential cannot impose
superconductivity since the superconducting ordering will be destroyed by phase
fluctuations in a form of quantum turbulence (vortexes, vortex rings, vortex
tangles etc.). The external pair potential renormalizes the order parameter in
initial superconducting matter and the bosonic scenario of transition to normal
state in a clear 3D superconductor occurs unlike BCS theory where the fermionic
scenario takes place.


  We develop two new designs of unitary differential space-time modulation
(DSTM) with low decoding complexity. Their decoder can be separated into a few
parallel decoders, each of which has a decoding search space of less than
sqrt(N) if the DSTM codebook contains N codewords. Both designs are based on
the concept of joint modulation, which means that several information symbols
are jointly modulated, unlike the conventional symbol-by-symbol modulation. The
first design is based on Orthogonal Space-Time Block Code (O-STBC) with joint
constellation constructed from spherical codes. The second design is based on
Quasi-Orthogonal Space-Time Block Code (QO-STBC) with specially designed
pair-wise constellation sets. Both the proposed unitary DSTM schemes have
considerably lower decoding complexity than many prior DSTM schemes, including
those based on Group Codes and Sp(2) which generally have a decoding search
space of N for a codebook size of N codewords, and much better decoding
performance than the existing O-STBC DSTM scheme. Between two designs, the
proposed DSTM based on O-STBC generally has better decoding performance, while
the proposed DSTM based on QO-STBC has lower decoding complexity when 8
transmit antennas.


  We study the effects of electron-electron interactions and hole doping on the
electronic structure of Cu-doped NaFeAs using the density functional theory
plus dynamical mean-field theory (DFT+DMFT) method. In particular, we employ an
effective multi-orbital Hubbard model with a realistic bandstructure of NaFeAs
in which Cu-doping was modeled within a rigid band approximation and compute
the evolution of the spectral properties, orbital-dependent electronic mass
renormalizations, and magnetic properties of NaFeAs upon doping with Cu. In
addition, we perform fully charge self-consistent DFT+DMFT calculations for the
long-range antiferromagnetically ordered Na(Fe,Cu)As with Cu $x=0.5$ with a
real-space ordering of Fe and Cu ions. Our results reveal a crucial importance
of strong electron-electron correlations and local potential difference between
the Cu and Fe ions for understanding the \textbf{k}-resolved spectra of
Na(Fe,Cu)As. Upon Cu-doping, we observe a strong orbital-dependent localization
of the Fe $3d$ states accompanied by a large renormalization of the Fe $xy$ and
$xz$/$yz$ orbitals. Na(Fe,Cu)As exhibits bad metal behavior associated with a
coherence-to-incoherence crossover of the Fe $3d$ electronic states and local
moments formation near a Mott metal-insulator transition (MIT). For heavily
doped NaFeAs with Cu $x \sim 0.5$ we obtain a Mott insulator with a band gap of
$\sim$0.3 eV characterized by divergence of the quasiparticle effective mass of
the Fe $xy$ states. In contrast to this, the quasiparticle weights of the Fe
$xz$/$yz$ and $e_g$ states remain finite at the MIT. The MIT occurs via an
orbital-selective Mott phase to appear at Cu $x\simeq0.375$ with the Fe $xy$
states being Mott localized. We propose the possible importance of Fe/Cu
disorder to explain the magnetic properties of Cu-doped NaFeAs.


  Occluded person re-identification (ReID) is a very challenging task due to
the occlusion disturbance and incomplete target information. Leveraging
external cues such as human pose or parsing to locate and align part features
has been proven to be very effective in occluded person ReID. Meanwhile, recent
Transformer structures have a strong ability of long-range modeling.
Considering the above facts, we propose a Teacher-Student Decoder (TSD)
framework for occluded person ReID, which utilizes the Transformer decoder with
the help of human parsing. More specifically, our proposed TSD consists of a
Parsing-aware Teacher Decoder (PTD) and a Standard Student Decoder (SSD). PTD
employs human parsing cues to restrict Transformer's attention and imparts this
information to SSD through feature distillation. Thereby, SSD can learn from
PTD to aggregate information of body parts automatically. Moreover, a mask
generator is designed to provide discriminative regions for better ReID. In
addition, existing occluded person ReID benchmarks utilize occluded samples as
queries, which will amplify the role of alleviating occlusion interference and
underestimate the impact of the feature absence issue. Contrastively, we
propose a new benchmark with non-occluded queries, serving as a complement to
the existing benchmark. Extensive experiments demonstrate that our proposed
method is superior and the new benchmark is essential. The source codes are
available at https://github.com/hh23333/TSD.


  We consider the sequential decision problem faced by the manager of an
electric vehicle (EV) charging station, who aims to satisfy the charging demand
of the customer while minimizing cost. Since the total time needed to charge
the EV up to capacity is often less than the amount of time that the customer
is away, there are opportunities to exploit electricity spot price variations
within some reservation window. We formulate the problem as a finite horizon
Markov decision process (MDP) and consider a risk-averse objective function by
optimizing under a dynamic risk measure constructed using a convex combination
of expected value and conditional value at risk (CVaR). It has been recognized
that the objective function of a risk-averse MDP lacks a practical
interpretation. Therefore, in both academic and industry practice, the dynamic
risk measure objective is often not of primary interest; instead, the
risk-averse MDP is used as a computational tool for solving problems with
predefined "practical" risk and reward objectives (termed the base model). In
this paper, we study the extent to which the two sides of this framework are
compatible with each other for the EV setting -- roughly speaking, does a "more
risk-averse" MDP provide lower risk in the practical sense as well? In order to
answer such a question, the effect of the degree of dynamic risk-aversion on
the optimal MDP policy is analyzed. Based on these results, we also propose a
principled approximation approach to finding an instance of the risk-averse MDP
whose optimal policy behaves well under the practical objectives of the base
model. Our numerical experiments suggest that EV charging stations can be
operated at a significantly higher level of profitability if dynamic charging
is adopted and a small amount of risk is tolerated.


  The finite satisfiability problem of monadic second order logic is decidable
only on classes of structures of bounded tree-width by the classic result of
Seese (1991). We prove the following problem is decidable:
  Input: (i) A monadic second order logic sentence $\alpha$, and (ii) a
sentence $\beta$ in the two-variable fragment of first order logic extended
with counting quantifiers. The vocabularies of $\alpha$ and $\beta$ may
intersect.
  Output: Is there a finite structure which satisfies $\alpha\land\beta$ such
that the restriction of the structure to the vocabulary of $\alpha$ has bounded
tree-width? (The tree-width of the desired structure is not bounded.)
  As a consequence, we prove the decidability of the satisfiability problem by
a finite structure of bounded tree-width of a logic extending monadic second
order logic with linear cardinality constraints of the form
$|X_{1}|+\cdots+|X_{r}|<|Y_{1}|+\cdots+|Y_{s}|$, where the $X_{i}$ and $Y_{j}$
are monadic second order variables. We prove the decidability of a similar
extension of WS1S.


  Java (de)serialization is prone to causing security-critical vulnerabilities
that attackers can invoke existing methods (gadgets) on the application's
classpath to construct a gadget chain to perform malicious behaviors. Several
techniques have been proposed to statically identify suspicious gadget chains
and dynamically generate injection objects for fuzzing. However, due to their
incomplete support for dynamic program features (e.g., Java runtime
polymorphism) and ineffective injection object generation for fuzzing, the
existing techniques are still far from satisfactory.
  In this paper, we first performed an empirical study to investigate the
characteristics of Java deserialization vulnerabilities based on our manually
collected 86 publicly known gadget chains. The empirical results show that 1)
Java deserialization gadgets are usually exploited by abusing runtime
polymorphism, which enables attackers to reuse serializable overridden methods;
and 2) attackers usually invoke exploitable overridden methods (gadgets) via
dynamic binding to generate injection objects for gadget chain construction.
Based on our empirical findings, we propose a novel gadget chain mining
approach, \emph{GCMiner}, which captures both explicit and implicit method
calls to identify more gadget chains, and adopts an overriding-guided object
generation approach to generate valid injection objects for fuzzing. The
evaluation results show that \emph{GCMiner} significantly outperforms the
state-of-the-art techniques, and discovers 56 unique gadget chains that cannot
be identified by the baseline approaches.


  Quintessential inflation is studied using a string modulus as the inflaton -
quintessence field. The modulus begins its evolution at the steep part of its
scalar potential, which is due to non-perturbative effects (e.g. gaugino
condensation). It is assumed that the modulus crosses an enhanced symmetry
point (ESP) in field space. Particle production at the ESP temporarily traps
the modulus resulting in a brief period of inflation. More inflation follows,
due to the flatness of the potential, since the ESP generates either an
extremum (maximum or minimum) or a flat inflection point in the scalar
potential. Eventually, the potential becomes steep again and inflation is
terminated. After reheating the modulus freezes due to cosmological friction at
a large value, such that its scalar potential is dominated by contributions due
to fluxes in the extra dimensions or other effects. The modulus remains frozen
until the present, when it can become quintessence and account for the dark
energy necessary to explain the observed accelerated expansion.


  Non-parametric models, such as Gaussian Processes (GP), show promising
results in the analysis of complex data. Their applications in neuroscience
data have recently gained traction. In this research, we introduce a novel
neural decoder model built upon GP models. The core idea is that two GPs
generate neural data and their associated labels using a set of low-dimensional
latent variables. Under this modeling assumption, the latent variables
represent the underlying manifold or essential features present in the neural
data. When GPs are trained, the latent variable can be inferred from neural
data to decode the labels with a high accuracy. We demonstrate an application
of this decoder model in a verbal memory experiment dataset and show that the
decoder accuracy in predicting stimulus significantly surpasses the
state-of-the-art decoder models. The preceding performance of this model
highlights the importance of utilizing non-parametric models in the analysis of
neuroscience data.


  We consider multilinear pseudo-differential operators with symbols in the
multilinear H\"ormander class $S_{0,0}$. The aim of this paper is to discuss
the boundedness of these operators in the settings of Besov spaces.


  We determine the Killing spinors for a class of magnetic brane solutions with
Minkowski worldvolume of the theory of AdS Einstein Maxwell theories in d
dimensions. We also obtain curved magnetic brane solutions with Ricci-flat
worldvolumes. If we demand that the curved brane solution admits Killing
spinors, then its worldvolume must admit parallel spinors. Classes of
Ricci-flat worldvolumes admitting parallel spinors are discussed.


  In this paper we give a characterization in terms of ``quasi-geodesics
frames' of visibility and existence of geodesic loops for bounded domains in
$\mathbb C^d$ which are Kobayashi complete hyperbolic and Gromov hyperbolic.


  We describe a tomographic dissection of the Planck CMB lensing data,
cross-correlating this map with galaxies in different ranges of photometric
redshift. We use the nearly all-sky 2MPZ and WISExSCOS catalogues for z<0.35,
extending to z<0.6 using SDSS. We describe checks for consistency between the
different datasets, and perform a test for possible leakage of thermal
Sunyaev--Zel'dovich signal into our cross-correlation measurements. The
amplitude of the cross-correlation allows us to estimate the evolution of
density fluctuations as a function of redshift, thus providing a test of
theories of modified gravity. Assuming the common parametrisation for the
logarithmic growth rate, f_g=Omega_m(z)^gamma, we infer gamma=0.77 +/- 0.18
when Omega_m is fixed using external data. Thus CMB lensing tomography is
currently consistent with Einstein gravity, where gamma=0.55 is expected. We
discuss how such constraints may be expected to improve with future data.


  In this article, we study the circular motion of particles and the well-known
Penrose mechanism around a Kerr-Newman-Kasuya black hole spacetime. The inner
and outer horizons, as well as ergosurfaces of the said black hole, are briefly
examined under the effect of spin and dyonic charge. Moreover, by limiting our
exploration to the equatorial plane, we discuss the characteristics of circular
geodesics and investigate both photons, as well as marginally stable circular
orbits. It is noted that black hole charge diminishing the radii of photon and
marginally stable circular orbits. To investigate the nature of particle
dynamics, we studied the effective potential and Lyapunov exponent. While
inspecting the process of energy extraction, we derived the Wald inequality,
which can help us to locate the energy limits of the Penrose process.
Furthermore, we have found expressions for the negative energy states and the
efficiency of energy extraction. The obtained result illustrates that both
black hole rotation and dyonic charge contributes to the efficiency of energy
extraction.


  In this paper we derive the dynamic equations of a race-car model via
Lie-group methods. Lie-group methods are nowadays quite familiar to
computational dynamicists and roboticists, but their diffusion within the
vehicle dynamics community is still limited. We try to bridge this gap by
showing that this framework merges gracefully with the Articulated Body
Algorithm (ABA) and enables a fresh and systematic formulation of the vehicle
dynamics. A significant contribution is represented by a rigorous
reconciliation of the ABA steps with the salient features of vehicle dynamics,
such as road-tire interactions, aerodynamic forces and load transfers. The
proposed approach lends itself both to the definition of direct simulation
models and to the systematic assembly of vehicle dynamics equations required,
in the form of equality constraints, in numerical optimal control problems. We
put our approach on a test in the latter context which involves the solution of
minimum lap-time problem (MLTP). More specifically, a MLTP for a race car on
the N\"urburgring circuit is systematically set up with our approach. The
equations are then discretized with the direct collocation method and solved
within the CasADi optimization suite. Both the quality of the solution and the
computational efficiency demonstrate the validity of the presented approach.


  Context. Near-Earth asteroid-comet transition object 107P/ (4015)
Wilson-Harrington is a possible target of the joint European Space Agency (ESA)
and Japanese Aerospace Exploration Agency (JAXA) Marco Polo sample return
mission. Physical studies of this object are relevant to this mission, and also
to understanding its asteroidal or cometary nature. Aims. Our aim is to obtain
significant new constraints on the surface thermal properties of this object.
Methods. We present mid-infrared photometry in two filters (16 and 22 microns)
obtained with NASA's Spitzer Space Telescope on February 12, 2007, and results
from the application of the Near Earth Asteroid Thermal Model (NEATM).We
obtained high S/N in two mid-IR bands allowing accurate measurements of its
thermal emission. Results. We obtain a well constrained beaming parameter (eta
= 1.39 +/- 0.26) and obtain a diameter and geometric albedo of D = 3.46 +/-
0.32 km, and pV = 0.059 +/- 0.011. We also obtain similar results when we apply
this best-fitting thermal model to single-band mid-IR photometry reported by
Campins et al. (1995), Kraemer et al. (2005) and Reach et al. (2007).
Conclusions. The albedo of 4015 Wilson-Harrington is low, consistent with those
of comet nuclei and primitive C-, P-, D-type asteorids. We establish a rough
lower limit for the thermal inertia of W-H of 60 Jm^-2s^(-0.5)K^-1 when it is
at r=1AU, which is slightly over the limit of 30 Jm^-2s^(-0.5)K-1 derived by
Groussin et al. (2009) for the thermal inertia of the nucleus of comet
22P/Kopff.


  We show that a two-dimensional system of flocking microswimmers interacting
hydrodynamically can be expressed using a Hamiltonian formalism. The
Hamiltonian depends strictly on the angles between the particles and their
swimming orientation, thereby restricting their available phase-space.
Simulations of co-oriented microswimmers evolve into "escalators" - sharp lines
at a particular tilt along which particles circulate. The conservation of the
Hamiltonian and its symmetry germinate the self-assembly of the observed
steady-state arrangements as confirmed by stability analysis.