  Compilation and summary of time-dependent measurements of the CKM angle
$\gamma/\phi_3$ with events collected at the Babar detector at the SLAC PEP-II
asymmetric B factory.


  In this paper, we generalize Huber's criterion to multichannel sparse
recovery problem of complex-valued measurements where the objective is to find
good recovery of jointly sparse unknown signal vectors from the given multiple
measurement vectors which are different linear combinations of the same known
elementary vectors. This requires careful characterization of robust
complex-valued loss functions as well as Huber's criterion function for the
multivariate sparse regression problem. We devise a greedy algorithm based on
simultaneous normalized iterative hard thresholding (SNIHT) algorithm. Unlike
the conventional SNIHT method, our algorithm, referred to as HUB-SNIHT, is
robust under heavy-tailed non-Gaussian noise conditions, yet has a negligible
performance loss compared to SNIHT under Gaussian noise. Usefulness of the
method is illustrated in source localization application with sensor arrays.


  We study equilibrium transport properties of massless Dirac fermions at
finite temperature and chemical potential in spacetime accompanied by torsion,
which in four dimensions couples with Dirac fermions as an axial gauge field.
In particular, we compute the current density at the linear order in the
torsion as well as in an external magnetic field with the Pauli-Villars
regularization, finding that an equilibrium current akin to the chiral magnetic
current is locally induced. Such torsion can be realized in condensed matter
systems along a screw dislocation line, around which localized and extended
current distributions are predicted so as to be relevant to Dirac and Weyl
semimetals. Furthermore, we compute the current density at the linear order in
the torsion as well as in a Weyl node separation, which turns out to vanish in
spite of being allowed from the symmetry perspective. Contrasts of our findings
with torsion-induced currents from previous work are also discussed.


  In this paper, we present that genotype-phenotype mapping can be
theoretically interpreted using the concept of quotient space in mathematics.
Quotient space can be considered as mathematically-defined phenotype space in
the evolutionary computation theory. The quotient geometric crossover has the
effect of reducing the search space actually searched by geometric crossover,
and it introduces problem knowledge in the search by using a distance better
tailored to the specific solution interpretation. Quotient geometric crossovers
are directly applied to the genotype space but they have the effect of the
crossovers performed on phenotype space. We give many example applications of
the quotient geometric crossover.


  Class incremental learning (CIL) is a challenging setting of continual
learning, which learns a series of tasks sequentially. Each task consists of a
set of unique classes. The key feature of CIL is that no task identifier (or
task-id) is provided at test time. Predicting the task-id for each test sample
is a challenging problem. An emerging theory-guided approach (called TIL+OOD)
is to train a task-specific model for each task in a shared network for all
tasks based on a task-incremental learning (TIL) method to deal with
catastrophic forgetting. The model for each task is an out-of-distribution
(OOD) detector rather than a conventional classifier. The OOD detector can
perform both within-task (in-distribution (IND)) class prediction and OOD
detection. The OOD detection capability is the key to task-id prediction during
inference. However, this paper argues that using a traditional OOD detector for
task-id prediction is sub-optimal because additional information (e.g., the
replay data and the learned tasks) available in CIL can be exploited to design
a better and principled method for task-id prediction. We call the new method
TPL (Task-id Prediction based on Likelihood Ratio). TPL markedly outperforms
strong CIL baselines and has negligible catastrophic forgetting. The code of
TPL is publicly available at https://github.com/linhaowei1/TPL.


  The tunnel ionization of an electron bounded by two delta potentials under
the influence of a constant electric field is considered. The equations for the
electron current density for two different initial states are obtained. The
dependence of the emission current on the orientation of the potential with
respect to the field direction and the distance between them is studied.
Appropriate conditions for observation essential interference effects are
defined.


  A stack of thin Nb foils was irradiated with the 100 MeV proton beam at Los
Alamos National Laboratory's Isotope Production Facility, to investigate the
$^{93}$Nb(p,4n)$^{90}$Mo nuclear reaction as a monitor for intermediate energy
proton experiments and to benchmark state-of-the-art reaction model codes. A
set of 38 measured cross sections for $^{\text{nat}}$Nb(p,x) and
$^{\text{nat}}$Cu(p,x) reactions between 40-90 MeV, as well as 5 independent
measurements of isomer branching ratios, are reported. These are useful in
medical and basic science radionuclide productions at intermediate energies.
The $^{\text{nat}}$Cu(p,x)$^{56}$Co, $^{\text{nat}}$Cu(p,x)$^{62}$Zn, and
$^{\text{nat}}$Cu(p,x)$^{65}$Zn reactions were used to determine proton
fluence, and all activities were quantified using HPGe spectrometry. Variance
minimization techniques were employed to reduce systematic uncertainties in
proton energy and fluence, improving the reliability of these measurements. The
measured cross sections are shown to be in excellent agreement with literature
values, and have been measured with improved precision compared with previous
measurements. This work also reports the first measurement of the
$^{\text{nat}}$Nb(p,x)$^{82\text{m}}$Rb reaction, and of the independent cross
sections for $^{\text{nat}}$Cu(p,x)$^{52\text{g}}$Mn and
$^{\text{nat}}$Nb(p,x)$^{85\text{g}}$Y in the 40-90 MeV region. The effects of
$^{\text{nat}}$Si(p,x)$^{22,24}$Na contamination, arising from silicone
adhesive in the Kapton tape used to encapsulate the aluminum monitor foils, is
also discussed as a cautionary note to future stacked-target cross section
measurements. \emph{A priori} predictions of the reaction modeling codes CoH,
EMPIRE, and TALYS are compared with experimentally measured values and used to
explore the differences between codes for the $^{\text{nat}}$Nb(p,x) and
$^{\text{nat}}$Cu(p,x) reactions.


  We present a detailed study of the interplay between chiral symmetry and
spectral properties of the Dirac operator in lattice gauge theories. We
consider, in the framework of the Schwinger model, the fixed point action and a
fermion action recently proposed by Neuberger. Both actions show the remnant of
chiral symmetry on the lattice as formulated in the Ginsparg-Wilson relation.
We check this issue for practical implementations, also evaluating the fermion
condensate in a finite volume by a subtraction procedure. Moreover, we
investigate the distribution of the eigenvalues of a properly defined
anti-hermitian lattice Dirac operator, studying the statistical properties at
the low lying edge of the spectrum. The comparison with the predictions of
chiral Random Matrix Theory enables us to obtain an estimate of the infinite
volume fermion condensate.


  For a system in contact with several reservoirs $r$ at different
inverse-temperatures $\beta_r$, we describe how the Markov jump dynamics with
the generalized detailed balance condition can be analyzed via a statistical
physics approach of dynamical trajectories $[{\cal C}(t)]_{0 \leq t \leq T} $
over a long time interval $T \to + \infty$. The relevant intensive variables
are the time-empirical density $\rho(\cal C)$, that measures the fractions of
time spent in the various configurations ${\cal C}$, and the time-empirical
jump densities $k_r ({\cal C', \cal C}) $, that measure the frequencies of
jumps from configuration ${\cal C} $ to configuration ${\cal C '} $ when it is
the reservoir $r$ that furnishes or absorbs the corresponding energy difference
($E({\cal C '})- E({\cal C })$).


  When a liquid film lies on a non-wettable substrate, the configuration is
unstable and the film then retracts from a solid substrate to form droplets.
This phenomenon, known as dewetting, commonly leads to undesirable
morphological changes. Nevertheless, recent works have demonstrated the
possibility to harness dewetting by employing templated substrates with a
degree of precision on par with advanced lithographic processes for
high-performance nanophotonic applications. Since resonant behavior is highly
sensitive to geometrical changes, predicting quantitatively dewetting dynamics
is of high interest. In this work, we develop a continuum model that predicts
the evolution of a thin film on a patterned substrate, from the initial reflow
to the nucleation and growth of holes. We provide an operative framework based
on macroscopic measurements to model the intermolecular interactions at the
origin of the dewetting process, involving length scales that span from
sub-nanometer to micron range. A comparison of experimental and simulated
results shows that the model can accurately predict the final distributions,
thereby offering novel predictive tools to tailor the optical response of
dewetted nanostructures.


  We investigate the temperature dependence of the lower critical field Hc1(T)
of a high-quality FeSe single crystal under static magnetic fields H parallel
to the c axis. The temperature dependence of the first vortex penetration field
has been experimentally obtained by two independent methods and the
corresponding Hc1(T) was deduced by taking into account demagnetization
factors. A pronounced change in the Hc1(T) curvature is observed, which is
attributed to anisotopic s-wave or multiband superconductivity. The London
penetration depth {\lambda}ab(T) calculated from the lower critical field does
not follow an exponential behavior at low temperatures, as it would be expected
for a fully gapped clean s-wave superconductor. Using either a two-band model
with s-wave-like gaps of magnitudes ?delta 1 = 0.41 meV and delta ?2 = 3.33 meV
or a single anisotropic s-wave order parameter, the temperature dependence of
the lower critical field Hc1(T) can be well described. These observations
clearly show that the superconducting energy gap in FeSe is nodeless.


  The recent gravity field measurements of Jupiter (Juno) and Saturn (Cassini)
confirm the existence of deep zonal flows reaching to a depth of 5\% and 15\%
of the respective radius. Relating the zonal wind induced density perturbations
to the gravity moments has become a major tool to characterise the interior
dynamics of gas giants. Previous studies differ with respect to the assumptions
made on how the wind velocity relates to density anomalies, on the functional
form of its decay with depth, and on the continuity of antisymmetric winds
across the equatorial plane. Most of the suggested vertical structures exhibit
a rather smooth radial decay of the zonal wind, which seems at odds with the
observed secular variation of the magnetic field and the prevailing geostrophy
of the zonal winds. Moreover, the results relied on an artificial equatorial
regularisation or ignored the equatorial discontinuity altogether. We favour an
alternative structure, where the equatorially antisymmetric zonal wind in an
equatorial latitude belt between $\pm 21^\circ$ remains so shallow that it does
not contribute to the gravity signal. The winds at higher latitudes suffice to
convincingly explain the measured gravity moments. Our results indicate that
the winds are geostrophic, i.e. constant along cylinders, in the outer $3000\,$
km and decay rapidly below. The preferred wind structure is 50\% deeper than
previously thought, agrees with the measured gravity moment, is compliant with
the magnetic constraints and the requirement of an adiabatic atmosphere and
unbiased by the treatment of the equatorial discontinuity.


  We introduce a new hybrid qubit consisting of a Majorana qubit interacting
with a transmon longitudinally coupled to a resonator. To do so, we equip the
longitudinal transmon qubit with topological quasiparticles, supported by an
array of heterostructure nanowires, and derive charge- and phase-based
interactions between the Majorana qubit and the resonator and transmon degrees
of freedom. Inspecting the charge coupling, we demonstrate that the Majorana
self-charging can be eliminated by a judicious choice of charge offset, thereby
maintaining the Majorana degeneracy regardless of the quasiparticles spatial
arrangement and parity configuration. We perform analytic and numerical
calculations to derive the effective qubit-qubit interaction elements and
discuss their potential utility for state readout and quantum error correction.
Further, we find that select interactions depend strongly on the overall
superconducting parity, which may provide a direct mechanism to characterize
deleterious quasiparticle poisoning processes.


  Negative mass makes perfect physical sense as long as the dominant energy
condition is satisfied by the corresponding energy-momentum tensor. Heretofore,
only {\it configurations} of negative mass had been found
\cite{Belletete:2013nqa,Mbarek:2014ppa}, the analysis did not address stability
or dynamics. In this paper, we analyze both of these criteria. We demonstrate
the existence of {\it stable}, static, negative mass bubbles in an
asymptotically de Sitter space-time. The bubbles are solutions of the Einstein
equations and correspond to an interior region of space-time containing a
specific mass distribution, separated by a thin wall from the exact, negative
mass Schwarzschild-de Sitter space-time in the exterior. We apply the Israel
junction conditions at the wall. For the case of an interior corresponding
simply to de Sitter space-time with a different cosmological constant from the
outside space-time, separated by a thin wall with energy density that is
independent of the radius, we find static but unstable solutions which satisfy
the dominant energy condition everywhere. The bubbles can collapse through
spherically symmetric configurations to the exact, singular, negative mass
Schwarzschild-de Sitter solution. Interestingly, this provides a
counter-example of the cosmic censorship hypothesis. Alternatively, the
junction conditions can be used to give rise to an interior mass distribution
that depends on the potential for the radius of the wall. We show that for no
choice of the potential, for positive energy density on the wall that is
independent of the radius, can we get a solution that is non-singular at the
origin. However, if we allow the energy density on the wall to depend on the
radius of the bubble, we can find {\it stable}, static, non-singular solutions
of negative mass which everywhere satisfy the dominant energy condition.


  We conducted optical polarimetry and near-infrared spectroscopy of JAXA's
Hayabusa2# mission target, (98943) 2001 CC21, in early 2023. Our new
observations indicated that this asteroid has a polarimetric inversion angle of
~21 deg, absorption bands around 0.9 and 1.9 um, and a geometric albedo of
0.285 +- 0.083. All these features are consistent with those of S-type but
inconsistent with L-type. Based on this evidence, we conclude that JAXA's
Hayabusa2# spacecraft will explore an S-type asteroid with albedo and size
(0.42-0.56 km when we assume the absolute magnitude of 18.6) similar to (25143)
Itokawa.


  Magnetic skyrmionium is a skyrmion-like spin texture with nanoscale size and
high mobility. It is a topologically trivial but dynamically stable structure,
which can be used as a non-volatile information carrier for next-generation
spintronic storage and computing devices. Here, we study the dynamics of a
skyrmionium driven by the spin torque in a ferrimagnetic nanotrack. It is found
that the direction of motion is jointly determined by the internal
configuration of a skyrmionium and the spin polarization vector. Besides, the
deformation of a skyrmionium induced by the intrinsic skyrmion Hall effect
depends on both the magnitude of the driving force and the net angular
momentum. The ferrimagnetic skyrmionium is most robust at the angular momentum
compensation point, whose dynamics is quite similar to the skyrmionium in
antiferromagnet. The skyrmion Hall effect is perfectly prohibited, where it is
possible to observe the position of the skyrmionium by measuring the
magnetization. Furthermore, the current-induced dynamics of a ferrimagnetic
skyrmionium is compared with that of a ferromagnetic and antiferromagnetic
skyrmionium. We also make a comparison between the motion of a ferrimagnetic
skyrmionium and a skyrmion. Our results will open a new field of ferrimagnetic
skyrmioniums for future development of ferrimagnetic spintronics devices.


  Mathematical models of quantum computers such as a multidimensional quantum
Turing machine and quantum circuits are described and its relations with
lattice spin models are discussed. One of the main open problems one has to
solve if one wants to build a quantum computer is the decoherence due to the
coupling with the environment. We propose a possible solution of this problem
by using a control of parameters of the system. This proposal is based on the
analysis of the spin-boson Hamiltonian performed in the stochastic limit
approximation.


  A real singlet scalar, connected to the Standard Model sector through a
portal with the Higgs boson, is one of the simplest and most popular models for
dark matter (DM). However, the experimental advances in direct and indirect DM
searches, together with the latest results from the LHC, have ruled out vast
areas of the parameter space of this scenario, and are expected to probe it
completely within the next years, ruling it out if no signal is found.
Motivated by the simplicity of this model, in this article we address a
minimal, renormalizable extension that could evade detection, consisting of the
addition of an extra real singlet scalar field in the dark sector. We analyze
the physical constraints on the model and show that the new annihilation and/or
coannihilation channels involving the extra singlet allow to reproduce the
correct DM relic abundance while avoiding the bounds from direct and indirect
searches for any DM mass above 50 GeV. We also show that, in some interesting
regions of the parameter space, the extra particle can be integrated-out,
leaving a "clever" effective theory (just involving the DM particle and the
Higgs), that essentially reproduces the results.


  We prove formulas for the number of Jordan blocks of the maximal size for
local monodromies of one-parameter degenerations of complex algebraic varieties
where the bound of the size comes from the monodromy theorem. In case the
general fibers are smooth and compact, the proof calculates some part of the
weight spectral sequence of the limit mixed Hodge structure of Steenbrink. In
the singular case, we can prove a similar formula for the monodromy on the
cohomology with compact supports, but not on the usual cohomology. We also show
that the number can really depend on the position of singular points in the
embedded resolution even in the isolated singularity case, and hence there are
no simple combinatorial formulas using the embedded resolution in general.


  Floating electrode electrowetting is caused by dc voltage applied to a liquid
droplet on the Cytop surface, without electrical connection to the substrate.
The effect is caused by the charge separation in the floating electrode. A
highly-resistive thermally-grown SiO2 layer underneath the Cytop enables the
droplet to hold charges without leakage, which is the key contribution.
Electrowetting with an SiO2 layer shows a memory effect, where the wetting
angle stays the same after the auxiliary electrode is removed from the droplet
in both conventional and floating electrode electrowetting. Floating electrode
electrowetting provides an alternative configuration for developing advanced
electrowetting-based devices.


  We examine the entanglement properties of a system that represents two driven
microwave cavities each optomechanically coupled to two separate driven optical
cavities which are connected by a single-mode optical fiber. The results
suggest that it may be possible to achieve near-maximal entanglement of the
microwave cavities, thus allowing a teleportation scheme to enable interactions
for hybrid quantum computing of superconducting qubits with optical
interconnects.


  This study describes computer simulations of carbonization and graphite
formation, including the effects of hydrogen, nitrogen, oxygen, and sulfur. We
introduce a novel technique to simulate carbonization, "Simulation of Thermal
Emission of Atoms and Molecules (STEAM)," designed to elucidate the removal of
volatiles and density variations in carbonization residue. The investigation
extensively analyzes the functional groups that endure through high-temperature
carbonization and examines the graphitization processes in carbon-rich
materials containing non-carbon "impurity elements". The physical, vibrational,
and electronic attributes of impure amorphous graphite are analyzed, and the
impact of nitrogen on electronic conduction is investigated, revealing its
substitutional integration into the sp$^2$ layered network.


  A search in Scopus within "Article title, Abstract, Keywords" unveils 2,444
documents focused on the biomechanics of Abdominal Aortic Aneurysm (AAA),
mostly on AAA wall stress. Only 24 documents investigated AAA kinematics, an
important topic that could potentially offer insights into the biomechanics of
AAA. In this paper, we present an image-based approach for patient-specific, in
vivo, and non-invasive AAA kinematic analysis using patient's time-resolved 3D
computed tomography angiography (4D CTA) images. Our approach relies on
regularized deformable image registration for estimating wall displacement,
estimation of the local wall strain as the ratio of its normal displacement to
its local radius of curvature, and local surface fitting with non-deterministic
outlier detection for estimating the wall radius of curvature. We verified our
approach against synthetic ground truth image data created by warping a 3D CTA
image of AAA using a realistic displacement field obtained from a finite
element biomechanical model. We applied our approach to assess AAA wall
displacements and strains in ten patients. Our kinematic analysis results
indicated that the 99th percentile of circumferential wall strain, among all
patients, ranged from 3.16% to 7.31%, with an average of 5.36% and a standard
deviation of 1.28%.


  In this article, a novel approach for mobile radio communications is proposed
and analysed, which is promising for future 6G cooperative distributed MIMO
systems. The fundamental idea is a new mechanism namely start stop bit method,
which transmits bit sequences as the start/stop bits of a synchronized counter
instead of transmitting the full encoded bit sequence itself. In that way,
theoretically, we can transmit infinitely long data messages with only one bit
for starting and one bit for stopping the counter. The value of the counter, as
identified by the stop bit, is then used to reconstruct and remap the one and
unique transmitted bit sequence. The start stop bit method is characterized by
a high signal sparsity as only two bits are transmitted, independently of the
bit sequence length for the message. Among the benefits of the start stop bit
method are energy efficient data transmission, and effective distributed MIMO
systems, which exploit the sparse inter cooperation area interference as well
as the low processing complexity for the sparse precoder calculation. Moreover,
for the next mobile wireless generation, we propose an advanced scheme of the
start stop bit method which enhances its resource usage. We call the resulting
method a sparse dMIMO system.


  A covariant functor from the category of the complex tori to the category of
the Effros-Shen algebras is constructed. The functor maps isomorphic complex
tori to the stably isomorphic Effros-Shen algebras. Our construction is based
on the Teichmueller theory of the Riemann surfaces.


  Based on a chain of BBGKI equations with a modified boundary condition that
takes into account multiparticle correlations, kinetic equations in the
approximate "pairs" collisions and in the polarization approximation, taking
into account the interaction through the third particle, obtained. The
specifics of the model representation of the pair potential of particle
interaction through short-range and long-range parts were taken into account.
In the case of the short-range potential in the form of the potential of solid
spheres, the contribution of Enskog's revised theory to the complete
integration of the collision of the kinetic equation is obtained. The collision
integrals include paired quasi-equilibrium distribution functions that depend
on the nonequilibrium mean values of the particle number density and the
inverse temperature. The method of collective variables Yukhnovskii is applied
for the calculation of pair quasi-equilibrium distribution function with an
allocation of short-range and long-range parts in the potential of the
interaction of particles. In this case, the system with short-range interaction
is considered as a frame of reference.


  The features of superfluid-Mott insulator phase transition in the array of
dissipative nonlinear cavities are analyzed. We show analytically that the
coupling to the bath can be reduced to renormalizing the eigenmodes of
atom-cavity system. This gives rise to a localizing effect and drives the
system into mixed states. For the superfluid state, a dynamical instability
will lead to a sweeping to a localized state of photons. For the Mott state, a
dissipation-induced fluctuation will suppress the restoring of long-range phase
coherence driven by interaction.


  Given a stream of Bernoulli random variables, consider the problem of
estimating the mean of the random variable within a specified relative error
with a specified probability of failure. Until now, the Gamma Bernoulli
Approximation Scheme (GBAS) was the method that accomplished this goal using
the smallest number of average samples. In this work, a new method is
introduced that is faster when the mean is bounded away from zero. The process
uses a two-stage process together with some simple inequalities to get rigorous
bounds on the error probability.


  The aim of this note is to give two new conceptual proofs of
Ionescu-Weitzenb\"ock's inequality. The first one, which is a vector proof,
provides us a geometric interpretation of the difference between the two sides
of this inequality and of two known corollary inequalities in differential
geometry. Through a less classical approach, our second proof makes use of the
properties of the set of triangles with a fixed "size", seen as a half-disk.


  A vast amount of valuable data is produced and is becoming available for
analysis as a result of advancements in smart cyber-physical systems. The data
comes from various sources, such as healthcare, smart homes, smart vehicles,
and often includes private, potentially sensitive information that needs
appropriate sanitization before being released for analysis. The incremental
and fast nature of data generation in these systems necessitates scalable
privacy-preserving mechanisms with high privacy and utility. However, privacy
preservation often comes at the expense of data utility. We propose a new data
perturbation algorithm, SEAL (Secure and Efficient data perturbation Algorithm
utilizing Local differential privacy), based on Chebyshev interpolation and
Laplacian noise, which provides a good balance between privacy and utility with
high efficiency and scalability. Empirical comparisons with existing
privacy-preserving algorithms show that SEAL excels in execution speed,
scalability, accuracy, and attack resistance. SEAL provides flexibility in
choosing the best possible privacy parameters, such as the amount of added
noise, which can be tailored to the domain and dataset.


  In 2009, Chmutov introduced the partial-duality for a ribbon graph $G$.
Recently, Gross, Mansour and Tucker enumerated all possible partial-duals of
$G$ by genus and introduced the partial-dual genus polynomial of a ribbon graph
$G.$ This paper mainly enumerates partial-duals for planar ribbon graphs.
First, we obtain a formula for the maximum partial-dual genus for any planar
ribbon graph and give a negative answer to the interpolating conjecture of
Gross, Mansour and Tucker. Then we show that there is a recurrence relation
between the partial-dual genus polynomials of planar ribbon graphs $G-e$ and
$G$. Furthermore, two related results are also given. These recurrence
relations give new approaches to calculate the partial-genus dual polynomials
for some planar ribbon graphs. In addition, we prove the asymptotic normality
for some partial-dual genus distributions.


  Selective ultrafilters are characterized by many equivalent properties, in
particular the Ramsey property that every finite colouring of unordered pairs
of integers has a homogeneous set in U, and the equivalent property that every
function is nondecreasing on some set in U. Natural weakenings of these
properties led to the inequivalent notions of weakly Ramsey and of
quasi-selective ultrafilter, introduced and studied in [1] and [4],
respectively. U is weakly Ramsey if for every finite colouring of unordered
pairs of integers there is a set in U whose pairs share only two colours, while
U is f-quasi-selective if every function g < f is nondecreasing on some set in
U. (So the quasi-selective ultrafilters of [4] are here id-quasi selective.) In
this paper we consider the relations between various natural cuts of the
ultrapowers of N modulo weakly Ramsey and f-quasi-selective ultrafilters. In
particular we characterize those weakly Ramsey ultrafilters that are isomorphic
to a quasi-selective ultrafilter.


  The concept of a storage ring with toroidal magnetic field was presented in
the two previous EPAC conferences. Here we report the first results of
experiments performed with beam transport in toroidal magnetic fields and
details of the injection system. The beam transport experiments were carried
out with 30 degree toroidal segments with an axial magnetic field of 0.6T. The
multi turn injection system relies on a transverse injection coil together with
an electric kicker system.


  The electromagnetic form factor of the pion is obtained using a particular
realization of QCD in the large $N_c$ limit, which sums up the infinite number
of zero-width resonances to yield an Euler's Beta function of the Veneziano
type. This form factor agrees with space-like data much better than single
rho-meson dominance. A simple unitarization ansatz is illustrated, and the
resulting vector spectral function in the time-like region is shown to be in
reasonable agreement with the ALEPH data from threshold up to about 1.3
${GeV}^2$.


  It is argued that Trauzettel et al. [Phys. Rev. B 75, 035305 (2007)] made
some mistakes in their calculations regarding the photon-assisted transport in
graphene that lead to uncoupled sidebands and emergence of step-like features
in dG/dV (G is differential conductance and V is the bias voltage). We discuss
the relevant corrections and explain in detail how the correct results are
expected to be quite different than the incorrect ones.


  Multiphase magnetic systems are common in nature and are increasingly being
recognized in technical applications. One characterization method which has
shown great promise for determining separate and collective effects of
multiphase magnetic systems is first order reversal curves (FORCs). Several
examples are given of FORC patterns which provide distinguishing evidence of
multiple phases. In parallel, a visualization method for understanding
multiphase magnetic interaction is given, which allocates Preisach magnetic
elements as an input 'Preisach hysteron distribution pattern' (PHDP) to enable
simulation of different 'wasp-waisted' magnetic behaviors. These simulated
systems allow reproduction of different major hysteresis loop, FORC pattern,
and switching field distributions of real systems and parameterized theoretical
systems. The experimental FORC measurements and FORC diagrams of four
commercially obtained magnetic materials, particularly those sold as
nanopowders, shows that these materials are often not phase pure. They exhibit
complex hysteresis behaviors that are not predictable based on relative phase
fraction obtained by characterization methods such as diffraction. These
multiphase materials, consisting of various fractions of BaFe12O19,
epsilon-Fe2O3, and gamma-Fe2O3, are discussed.


  We study scatterings of bosonic massive closed string states at arbitrary
mass levels from D-brane. We discover that all the scattering amplitudes can be
expressed in terms of the generalized hypergeometric function with special
arguments, which terminates to a finite sum and, as a result, the whole
scattering amplitudes consistently reduce to the usual beta function. For the
simple case of D-particle, we explicitly calculate high-energy limits of a
series of the above scattering amplitudes for arbitrary mass levels, and derive
infinite linear relations among them for each fixed mass level. The ratios of
these high-energy scattering amplitudes are found to be consistent with the
decoupling of high-energy zero-norm states of our previous works.


  We argue that the recently introduced "statefinder parameters" (Sahni et al.,
JETP Lett. 77, 201 (2003)), that include the third derivative of the cosmic
scale factor, are useful tools to characterize interacting quitessence models.
We specify the statefinder parameters for two classes of models that solve, or
at least alleviate, the coincidence problem.


  The paper introduces the DIverse MultiPLEx Generalized Dot Product Graph
(DIMPLE-GDPG) network model where all layers of the network have the same
collection of nodes and follow the Generalized Dot Product Graph (GDPG) model.
In addition, all layers can be partitioned into groups such that the layers in
the same group are embedded in the same ambient subspace but otherwise all
matrices of connection probabilities can be different. In a common particular
case, where layers of the network follow the Stochastic Block Model (SBM), this
setting implies that the groups of layers have common community structures but
all matrices of block connection probabilities can be different. We refer to
this version as the DIMPLE model. While the DIMPLE-GDPG model generalizes the
COmmon Subspace Independent Edge (COSIE) random graph model developed in
\cite{JMLR:v22:19-558}, the DIMPLE model includes a wide variety of
SBM-equipped multilayer network models as its particular cases. In the paper,
we introduce novel algorithms for the recovery of similar groups of layers, for
the estimation of the ambient subspaces in the groups of layers in the
DIMPLE-GDPG setting, and for the within-layer clustering in the case of the
DIMPLE model. We study the accuracy of those algorithms, both theoretically and
via computer simulations. The advantages of the new models are demonstrated
using real data examples.


  To effectively forage in natural environments, organisms must adapt to
changes in the quality and yield of food sources across multiple timescales.
Individuals foraging in groups act based on both their private observations and
the opinions of their neighbors. How do these information sources interact in
changing environments? We address this problem in the context of honeybee
swarms, showing inhibitory social interactions help maintain adaptivity and
consensus needed for effective foraging. Individual and social interactions of
a mathematical swarm model shape the nutrition yield of a group foraging from
feeders with temporally switching food quality. Social interactions improve
foraging from a single feeder if temporal switching is fast or feeder quality
is low. When the swarm chooses from multiple feeders, the most effective form
of social interaction is direct switching, whereby bees flip the opinion of
nestmates foraging at lower yielding feeders. Model linearization shows that
effective social interactions increase the fraction of the swarm at the correct
feeder (consensus) and the rate at which bees reach that feeder (adaptivity).
Our mathematical framework allows us to compare a suite of social inhibition
mechanisms, suggesting experimental protocols for revealing effective swarm
foraging strategies in dynamic environments.


  The academic social network site ResearchGate (RG) has its own indicator, RG
Score, for its members. The high profile nature of the site means that the RG
score may be used for recruitment, promotion and other tasks for which
researchers are evaluated. In response, this study investigates whether it is
reasonable to employ the RG Score as evidence of scholarly reputation. For
this, three different author samples were investigated. An outlier sample
includes 104 authors with high values. A Nobel sample comprises 73 Nobel
winners from Medicine & Physiology, Chemistry, Physics and Economics (from 1975
to 2015). A longitudinal sample includes weekly data on 4 authors with
different RG Scores. The results suggest that high RG Scores are built
primarily from activity related to asking and answering questions in the site.
In particular, it seems impossible to get a high RG Score solely through
publications. Within RG it is possible to distinguish between (passive)
academics that interact little in the site and active platform users, who can
get high RG Scores through engaging with others inside the site (questions,
answers, social networks with influential researchers). Thus, RG Scores should
not be mistaken for academic reputation indicators.


  The explosion outcome and diagnostics of core-collapse supernovae depend
sensitively on the nature of the stellar progenitor, but most studies to date
have focused exclusively on one-dimensional, spherically-symmetric massive star
progenitors. We present some of the first core-collapse supernovae simulations
of three-dimensional massive star supernovae progenitors, a 12.5- and a
15-M$_{\odot}$ model, evolved in three-dimensions from collapse to bounce
through explosion with the radiation-hydrodynamic code F{\sc{ornax}}. We
compare the results using those starting from three-dimensional progenitors to
three-dimensional simulations of spherically-symmetric, one-dimensional
progenitors of the same mass. We find that the models evolved in three
dimensions during the final stages of massive star evolution are more prone to
explosion. The turbulence arising in these multi-dimensional initial models
serve as seed turbulence that promotes shock revival. Detection of
gravitational waves and neutrinos signals could reveal signatures of pre-bounce
turbulence.


  In most lattice field theories, correlators are plagued by a signal-to-noise
problem of exponential difficulty in the time separation. We propose a method
for improving the signal-to-noise ratio, in which control variates are
systematically constructed from lattice Schwinger-Dyson relations. The method
is demonstrated on various two-dimensional lattices in scalar field theory, and
a strategy for scaling to larger systems is explored.


  We report the first efficient trapping of rare-earth Yb atoms with a
high-power violet laser diode (LD). An injection-locked violet LD with a 25 mW
frequency-stabilized output was used for the magneto-optical trapping (MOT) of
fermionic as well as bosonic Yb isotopes. A typical number of $4\times 10^6$
atoms for $^{174}$Yb with a trap density of $\sim 1\times10^8/$cm$^3$ was
obtained. A 10 mW violet external-cavity LD (ECLD) was used for the
one-dimensional (1D) slowing of an effusive Yb atomic beam without a Zeeman
slower resulting in a 35-fold increase in the number of trapped atoms. The
overall characteristics of our compact violet MOT, e.g., the loss time of 1 s,
the loading time of 400 ms, and the cloud temperature of 0.7 mK, are comparable
to those in previously reported violet Yb MOTs, yet with a greatly reduced cost
and complexity of the experiment.


  We report on high-accuracy measurements of quantized current, sourced by a
tunable-barrier single-electron pump at frequencies $f$ up to $1$ GHz. The
measurements were performed with a new picoammeter instrument, traceable to the
Josephson and quantum Hall effects. Current quantization according to $I=ef$
with $e$ the elementary charge was confirmed at $f=545$ MHz with a total
relative uncertainty of 0.2 ppm, improving the state of the art by about a
factor of 5. For the first time, the accuracy of a possible future quantum
current standard based on single-electron transport was experimentally
validated to be better than the best realization of the ampere within the
present SI.


  The advancements in microwave power transfer (MPT) over past decades have
enabled wireless power transfer over long distances. The latest breakthroughs
in wireless communication, namely massive MIMO, small cells and millimeter-wave
communication, make wireless networks suitable platforms for implementing MPT.
This can lead to the elimination of the "last wires" connecting mobile devices
to the grid for recharging, thereby tackling a long-standing ICT grand
challenge. Furthermore, the seamless integration between MPT and wireless
communication opens a new area called wirelessly powered communications (WPC)
where many new research directions arise e.g., simultaneous
information-and-power transfer, WPC network architectures, and techniques for
safe and efficient WPC. This article provides an introduction to WPC by
describing the key features of WPC, shedding light on a set of frequently asked
questions, and identifying the key design issues and discussing possible
solutions.


  Charged defects in 2D materials have emerging applications in quantum
technologies such as quantum emitters and quantum computation. Advancement of
these technologies requires rational design of ideal defect centers, demanding
reliable computation methods for quantitatively accurate prediction of defect
properties. We present an accurate, parameter-free and efficient procedure to
evaluate quasiparticle defect states and thermodynamic charge transition levels
of defects in 2D materials. Importantly, we solve critical issues that stem
from the strongly anisotropic screening in 2D materials, that have so far
precluded accurate prediction of charge transition levels in these materials.
Using this procedure, we investigate various defects in monolayer hexagonal
boron nitride (h-BN) for their charge transition levels, stable spin states and
optical excitations. We identify $C_BN_V$ (nitrogen vacancy adjacent to carbon
substitution of boron) to be the most promising defect candidate for scalable
quantum bit and emitter applications.


  This is an update of, and a supplement to, a 1986 survey paper by the author
on basic properties of strong mixing conditions.


  We present the discovery of three new $\beta$ Cep pulsators, three new
pulsators with frequency groupings, and frequency patterns in a B3Ib star, all
of which show pulsations with frequencies as high as about 17 d$^{-1}$, with K2
space mission photometry. Based on a Fourier analysis and iterative
pre-whitening we present a classification and evaluate the potential for
asteroseismic modelling. We include the lists of pulsation frequencies for
three new $\beta$ Cep pulsators, CD-28 12286, CD-27 10876, LS 3978, and
additional pulsation mode frequencies for the known $\beta$ Cep pulsator HD
164741. In addition we characterise the regular frequency spacing found in the
new pulsator HD 169173, and discuss its origin. We place the newly discovered
variables in a colour-magnitude diagram using parallaxes from Gaia-DR2,
showcasing their approximate location in the massive star domain. The
identified frequency lists of these multiperiodic pulsators are a good starting
point for future forward seismic modelling, after identification of at least
one pulsation frequency from high-resolution time series spectroscopy and/or
multi-colour photometry.


  An integral curve is a closed piecewise linear curve comprised of unit
intervals. A dome is a polyhedral surface whose faces are equilateral triangles
and whose boundary is an integral curve. Glazyrin and Pak showed that not every
integral curve can be domed by analyzing the case of unit rhombi, and
conjectured that every integral curve is cobordant to a unit rhombus. We show
that this is false for oriented domes, but that every integral curve is
cobordant to the union of finitely many unit rhombi.


  We show how the condition of isochronicity can be studied for two dimensional
systems in the renormalization group (RG) context. We find a necessary
condition for the isochronicity of the Cherkas and another class of cubic
systems. Our conditions are satisfied by all the cases studied recently by
Bardet et al \cite{bard} and Ghose Choudhury and Guha


  In SU(3)_L x U(1)_N gauge models for electroweak interactions, we discuss how
to implement a radiative mechanism of generating Majorana neutrino masses by
considering the property that the Higgs scalar, which has a coupling to a
charged lepton (\ell)-neutrino (\nu) pair, is naturally included. The mechanism
is shown to work in models with a heavy charged lepton, \omega^+, in a lepton
triplet (\nu, \ell, \omega^+) and with a heavy neutral lepton, N, in (\nu,
\ell, N). A minimal model with \ell and \ell^c in (\nu, \ell, \ell^c) together
with a sextet Higgs scalar suffers from a fine-tuning problem to suppress
tree-level neutrino masses.


  In this paper we report on a systematic search for a neutral boson in the
mass range between 5 and 15 MeV/c$^{2}$ in the decay of highly excited nuclei.
Its signature is found a deviation in the angular correlation of the $e^+e^-$
pairs from conventional internal pair conversion (IPC) resulting from of its
two-body decay kinematics. With an $e^{+}e^{-}$ pair-spectrometer, a number of
transitions has been investigated in the
  ${\alpha}$--nuclei $^{8}$Be, $^{12}$C and $^{16}$O, following light ion
induced reactions at low bombarding energies, first at IKF in Frankfurt and
during the last years at ATOMKI in Debrecen. Startlingly, in all isoscalar
transitions excess $e^{+}e^{-}$ pairs are found at large angles with branching
ratios with respect to the total yield ranging from 10$^{-2}$ to 10$^{-6}$. If
these deviations are all related to the two-body decay of an $X$-boson, this
observation implies plural $X$-bosons. An analysis of all angular spectra with
a boson search program, yields a pandemonium of more than ten candidate bosons.


  Due to the high performance and safety requirements of self-driving
applications, the complexity of modern autonomous driving systems (ADS) has
been growing, instigating the need for more sophisticated hardware which could
add to the energy footprint of the ADS platform. Addressing this, edge
computing is poised to encompass self-driving applications, enabling the
compute-intensive autonomy-related tasks to be offloaded for processing at
compute-capable edge servers. Nonetheless, the intricate hardware architecture
of ADS platforms, in addition to the stringent robustness demands, set forth
complications for task offloading which are unique to autonomous driving.
Hence, we present $ROMANUS$, a methodology for robust and efficient task
offloading for modular ADS platforms with multi-sensor processing pipelines.
Our methodology entails two phases: (i) the introduction of efficient
offloading points along the execution path of the involved deep learning
models, and (ii) the implementation of a runtime solution based on Deep
Reinforcement Learning to adapt the operating mode according to variations in
the perceived road scene complexity, network connectivity, and server load.
Experiments on the object detection use case demonstrated that our approach is
14.99% more energy-efficient than pure local execution while achieving a 77.06%
reduction in risky behavior from a robust-agnostic offloading baseline.


  For a local maximal function defined on a certain family of cubes lying
``well inside'' of $\Omega$, a proper open subset of $\mathbb R ^n$, we
characterize the couple of weights $(u,v)$ for which it is bounded from
$L^p(v)$ on $L^q(u)$.


  We present an approximate model of Wheeler-Feynman electrodynamics for which
uniqueness of solutions is proved. It is simple enough to be instructive but
close enough to Wheeler-Feynman electrodynamics such that we can discuss its
natural type of initial data, constants of motion and stable orbits with regard
to Wheeler-Feynman electrodynamics.


  MOND, invented by Milgrom, is a phenomenological scheme whose basic premise
is that the visible matter distribution in a galaxy or cluster of galaxies
alone determines its dynamics. MOND fits many observations surprisingly well.
Could it be that there is no dark matter in these systems and we witness rather
a violation of Newton's universal gravity law ? If so, Einstein's general
relativity would also be violated. For long conceptual problems have prevented
construction of a consistent relativistic substitute which does not obviously
run afoul of the facts. Here I sketch TeVeS, a tensor-vector-scalar field
theory which seems to fit the bill: it has no obvious conceptual problems and
has a MOND and Newtonian limits under the proper circumstances. It also passes
the elementary solar system tests of gravity theory.


  Applying the known physics of plasmas to the evolution of galaxies and
quasars in the Early Universe, a unique "Strong" Magnetic Field Modsl (SMF) was
created that explains the origin of a very large-scale primordial magnetic
field in each Supercluster and the observed large-scale structure of galaxies.
This physical model, involving both gravitation and cosmical magnetism,
explains the existence of significant magnetic fields in galaxies. An intense
highly relativistic gravitationally bound current loop (Storage Ring) is formed
by gravitational collapse explaining the nature of the AGN/Quasar Central
Engine, galactic structure and radio, optical and X-ray jets.


  Vision transformer has achieved impressive performance for many vision tasks.
However, it may suffer from high redundancy in capturing local features for
shallow layers. Local self-attention or early-stage convolutions are thus
utilized, which sacrifice the capacity to capture long-range dependency. A
challenge then arises: can we access efficient and effective global context
modeling at the early stages of a neural network? To address this issue, we
draw inspiration from the design of superpixels, which reduces the number of
image primitives in subsequent processing, and introduce super tokens into
vision transformer. Super tokens attempt to provide a semantically meaningful
tessellation of visual content, thus reducing the token number in
self-attention as well as preserving global modeling. Specifically, we propose
a simple yet strong super token attention (STA) mechanism with three steps: the
first samples super tokens from visual tokens via sparse association learning,
the second performs self-attention on super tokens, and the last maps them back
to the original token space. STA decomposes vanilla global attention into
multiplications of a sparse association map and a low-dimensional attention,
leading to high efficiency in capturing global dependencies. Based on STA, we
develop a hierarchical vision transformer. Extensive experiments demonstrate
its strong performance on various vision tasks. In particular, without any
extra training data or label, it achieves 86.4% top-1 accuracy on ImageNet-1K
with less than 100M parameters. It also achieves 53.9 box AP and 46.8 mask AP
on the COCO detection task, and 51.9 mIOU on the ADE20K semantic segmentation
task. Code is released at https://github.com/hhb072/STViT.


  Image change detection (ICD) to detect changed objects in front of a vehicle
with respect to a place-specific background model using an on-board monocular
vision system is a fundamental problem in intelligent vehicle (IV). From the
perspective of recent large-scale IV applications, it can be impractical in
terms of space/time efficiency to train place-specific background models for
every possible place. To address these issues, we introduce a new autoencoder
(AE) based efficient ICD framework that combines the advantages of AE-based
anomaly detection (AD) and AE-based image compression (IC). We propose a method
that uses AE reconstruction errors as a single unified measure for training a
minimal set of place-specific AEs and maintains detection accuracy. We
introduce an efficient incremental recursive AE (rAE) training framework that
recursively summarizes a large collection of background images into the AE set.
The results of experiments on challenging cross-season ICD tasks validate the
efficacy of the proposed approach.


  In this paper, we present the concept of subdifferential for fuzzy n-cell
number valued functions. Then we state some theorems related to
subdifferentiability based on the new definition. Finally, we present some
applications emphasized on optimization problems, including the Lagrangian dual
problem and minimizing the composite problem.


  The ontic breakthrough in quantum foundations, consisting of three theo-
rems, that of Pusey, Barrett, and Rudolph (PBR), the Colbeck-Renner one, and
Hardy's one, is shortly presented, together with various reactions. Some of the
ideas involved are explained and/or commented upon. Thus, the wave- function is
proved real in three independent ways. Each of the theorems rests on more or
less plausible assumptions, but they require more in-depth anal- yses.


  In this paper we give a generalization of the main results in \cite{ab,ab1}
about $b$-ary expansions of algebraic numbers. As a byproduct we get a large
class of new transcendence criteria. One of our corollaries implies that
$b$-ary expansions of linearly independent irrational algebraic numbers are
quite independent. Motivated by this result, we propose a generalized Borel
conjecture.


  The fluid physics of the heat and mass transfer from an object in its wake
has much importance for natural phenomena as well as for many engineering
applications. Here, we report numerical results on the population density of
the spatial distribution of fluid velocity, pressure, scalar concentration and
scalar fluxes of a wake flow past a sphere in the steady wake regime (Reynolds
number 25 to 285). We find the population density to be well described by a
Lorentzian distribution. We observe this apparently universal form both in the
symmetric wake regime and in the more complex three dimensional wake structure
of the steady oblique regime with Reynolds number larger than 225. The
population density distribution identifies the increase in dimensionless
kinetic energy and scalar fluxes with the increase in Reynolds number, whereas
the dimensionless scalar population density shows negligible variation with the
Reynolds number.


  We propose a geometric explanation of the standard model of Glashow, Weinberg
and Salam for the known elementary particles. Our model is a generic Quantum
Field Theory in dimension four, obtained by developing along a Lorentz
sub-manifold the lagrangian of Einstein and Dirac in dimension twelve. The main
mechanism which gives birth to the standard model is a certain gauge fixing of
triality, which permits to identify the multiplicity of fermions, as seen from
the four dimensional world, with the eight unseen dimensions of the generating
universe. In this way we get the known tables of particles, explaining the
series of fermions and the gauge bosons. We suggest that the Higgs field
dynamics could appear through a bosonization of the right handed neutrino and
correspond to a displacement in the unseen dimensions. We also propose
hypotheses for dark matter, and perhaps dark energy. Then we suggest
predictions to go beyond the standard model.


  Traditional sociotechnical systems (STS) theory has been widely used, but
there are many new characteristics in the STS environment as we enter the
intelligence era, resulting in the limitations of traditional STS. Based on the
"user-centered design" philosophy, this paper proposes a new framework of
intelligent sociotechnical systems (iSTS) and outlines the new characteristics
of iSTS as well as its implications for the development of intelligent systems.
Future research of iSTS requires interdisciplinary collaboration, including
human factors engineering, this paper finally proposes suggestions from two
aspects of human factors engineering methodology and approaches.


  This paper investigates resource allocation for simultaneous wireless
information and power transfer (SWIPT) downlink systems based on a non-linear
energy harvesting model. The resource allocation algorithm design is formulated
as a non-convex optimization problem for the maximization of the total
harvested power. The proposed problem formulation not only takes into account
imperfect channel state information (CSI) but also guarantees the
quality-of-service (QoS) of information transfer. A novel iterative algorithm
is proposed to obtain the globally optimal solution of the considered
non-convex optimization problem. In each iteration, a rank-constrained
semidefinite program (SDP) is solved optimally by SDP relaxation. Simulation
results demonstrate the significant gains in harvested power and the robustness
against CSI imperfection for the proposed optimal resource allocation, compared
to a baseline scheme designed for perfect CSI and the conventional linear
energy harvesting model.


  Pedestrian trajectory prediction is a critical yet challenging task,
especially for crowded scenes. We suggest that introducing an attention
mechanism to infer the importance of different neighbors is critical for
accurate trajectory prediction in scenes with varying crowd size. In this work,
we propose a novel method, AVGCN, for trajectory prediction utilizing graph
convolutional networks (GCN) based on human attention (A denotes attention, V
denotes visual field constraints). First, we train an attention network that
estimates the importance of neighboring pedestrians, using gaze data collected
as subjects perform a bird's eye view crowd navigation task. Then, we
incorporate the learned attention weights modulated by constraints on the
pedestrian's visual field into a trajectory prediction network that uses a GCN
to aggregate information from neighbors efficiently. AVGCN also considers the
stochastic nature of pedestrian trajectories by taking advantage of variational
trajectory prediction. Our approach achieves state-of-the-art performance on
several trajectory prediction benchmarks, and the lowest average prediction
error over all considered benchmarks.


  Stochastic Variance Reduced Gradient (SVRG), introduced by Johnson & Zhang
(2013), is a theoretically compelling optimization method. However, as Defazio
& Bottou (2019) highlights, its effectiveness in deep learning is yet to be
proven. In this work, we demonstrate the potential of SVRG in optimizing
real-world neural networks. Our analysis finds that, for deeper networks, the
strength of the variance reduction term in SVRG should be smaller and decrease
as training progresses. Inspired by this, we introduce a multiplicative
coefficient $\alpha$ to control the strength and adjust it through a linear
decay schedule. We name our method $\alpha$-SVRG. Our results show
$\alpha$-SVRG better optimizes neural networks, consistently reducing training
loss compared to both baseline and the standard SVRG across various
architectures and image classification datasets. We hope our findings encourage
further exploration into variance reduction techniques in deep learning. Code
is available at https://github.com/davidyyd/alpha-SVRG.


  Sparse Bayesian learning (SBL) has emerged as a fast and competitive method
to perform sparse processing. The SBL algorithm, which is developed using a
Bayesian framework, approximately solves a non-convex optimization problem
using fixed point updates. It provides comparable performance and is
significantly faster than convex optimization techniques used in sparse
processing. We propose a signal model which accounts for dictionary mismatch
and the presence of errors in the weight vector at low signal-to-noise ratios.
A fixed point update equation is derived which incorporates the statistics of
mismatch and weight errors. We also process observations from multiple
dictionaries. Noise variances are estimated using stochastic maximum
likelihood. The derived update equations are studied quantitatively using
beamforming simulations applied to direction-of-arrival (DoA). Performance of
SBL using single- and multi-frequency observations, and in the presence of
aliasing, is evaluated. SwellEx-96 experimental data demonstrates qualitatively
the advantages of SBL.


  We investigate dynamics near Turing patterns in reaction-diffusion systems
posed on the real line. Linear analysis predicts diffusive decay of small
perturbations. We construct a "normal form" coordinate system near such Turing
patterns which exhibits an approximate discrete conservation law. The key
ingredients to the normal form is a conjugation of the reaction-diffusion
system on the real line to a lattice dynamical system. At each lattice site, we
decompose perturbations into neutral phase shifts and normal decaying
components. As an application of our normal form construction, we prove
nonlinear stability of Turing patterns with respect to perturbations that are
small in $L^1\cap L^\infty$, with sharp rates.


  In this letter, we exploit generalised unitarity in order to calculate the
cut-constructible part of one-loop amplitudes in non-supersymmetric Yang-Mills
theory. In particular, we rederive the n-gluon MHV amplitudes for both the
adjacent and non-adjacent gluon helicity configurations from 3- and 4-particle
cuts alone.


  Quantum Fisher information matrices (QFIMs) are fundamental to estimation
theory: they encode the ultimate limit for the sensitivity with which a set of
parameters can be estimated using a given probe. Since the limit invokes the
inverse of a QFIM, an immediate question is what to do with singular QFIMs.
Moreover, the QFIM may be discontinuous, forcing one away from the paradigm of
regular statistical models. These questions of nonregular quantum statistical
models are present in both single- and multiparameter estimation.
Geometrically, singular QFIMs occur when the curvature of the metric vanishes
in one or more directions in the space of probability distributions, while
QFIMs have discontinuities when the density matrix has parameter-dependent
rank. We present a nuanced discussion of how to deal with each of these
scenarios, stressing the physical implications of singular QFIMs and the
ensuing ramifications for quantum metrology.


  The paper "Calorimetric Dark Matter Detection with Galactic Center Gas
Clouds" (Bhoonah et al. 2018) aims to derive limits on dark matter interactions
by demanding that heat transfer due to DM interactions is less than that by
astrophysical cooling, using clouds in the hot, high-velocity nuclear outflow
wind of the Milky Way ($T_{wind} \sim 10^{6-7}$ K, $V_{wind} \sim$ 330 km/s).
We argue that clouds in such an extreme environment cannot be assumed to be
stable over the long timescales associated with their radiative cooling rates.
Furthermore, Bhoonah et al. (2018) uses incorrect parameters for their clouds.


  SI-traceable measurements of optical frequencies using International Atomic
Time (TAI) do not require a local primary frequency reference, but suffer from
an uncertainty in tracing to the SI second. For the measurement of the
$^{87}$Sr lattice clock transition, we have reduced this uncertainty to low
$10^{-16}$ level by averaging three sets of ten-day intermittent measurements,
in which we operated the lattice clock for $10^4$ s on each day. Moreover, a
combined oscillator of two hydrogen masers was employed as a local flywheel
oscillator (LFO) in order to mitigate the impact of sporadic excursion of LFO
frequency. The resultant absolute frequency with fractional uncertainty of
$4.3\times10^{-16}$ agrees with other measurements based on local
state-of-the-art cesium fountains.


  An emerging solution for explaining Transformer-based models is to use
vector-based analysis on how the representations are formed. However, providing
a faithful vector-based explanation for a multi-layer model could be
challenging in three aspects: (1) Incorporating all components into the
analysis, (2) Aggregating the layer dynamics to determine the information flow
and mixture throughout the entire model, and (3) Identifying the connection
between the vector-based analysis and the model's predictions. In this paper,
we present DecompX to tackle these challenges. DecompX is based on the
construction of decomposed token representations and their successive
propagation throughout the model without mixing them in between layers.
Additionally, our proposal provides multiple advantages over existing solutions
for its inclusion of all encoder components (especially nonlinear feed-forward
networks) and the classification head. The former allows acquiring precise
vectors while the latter transforms the decomposition into meaningful
prediction-based values, eliminating the need for norm- or summation-based
vector aggregation. According to the standard faithfulness evaluations, DecompX
consistently outperforms existing gradient-based and vector-based approaches on
various datasets. Our code is available at
https://github.com/mohsenfayyaz/DecompX.


  We prove an analogue of Gutzmer's formula for Hermite expansions. As a
consequence we obtain a new proof of a characterisation of the image of $
L^2(\R^n) $ under the Hermite semigroup. We also obtain some new orthogonality
relations for complexified Hermite functions.


  Recent studies have investigated siamese network architectures for learning
invariant speech representations using same-different side information at the
word level. Here we investigate systematically an often ignored component of
siamese networks: the sampling procedure (how pairs of same vs. different
tokens are selected). We show that sampling strategies taking into account
Zipf's Law, the distribution of speakers and the proportions of same and
different pairs of words significantly impact the performance of the network.
In particular, we show that word frequency compression improves learning across
a large range of variations in number of training pairs. This effect does not
apply to the same extent to the fully unsupervised setting, where the pairs of
same-different words are obtained by spoken term discovery. We apply these
results to pairs of words discovered using an unsupervised algorithm and show
an improvement on state-of-the-art in unsupervised representation learning
using siamese networks.


  COVID-19 vaccines have proven to be effective against SARS-CoV-2 infection.
However, the dynamics of vaccine-induced immunological memory development and
neutralizing antibodies generation are not fully understood, limiting vaccine
development and vaccination regimen determination. Herein, we constructed a
mathematical model to characterize the vaccine-induced immune response based on
fitting the viral infection and vaccination datasets. With the example of
CoronaVac, we revealed the association between vaccine-induced immunological
memory development and neutralizing antibody levels. The establishment of the
intact immunological memory requires more than 6 months after the first and
second doses, after that a booster shot can induce high levels neutralizing
antibodies. By introducing the maximum viral load and recovery time after viral
infection, we quantitatively studied the protective effect of vaccines against
viral infection. Accordingly, we optimized the vaccination regimen, including
dose and vaccination timing, and predicted the effect of the fourth dose. Last,
by combining the viral transmission model, we showed the suppression of virus
transmission by vaccination, which may be instructive for the development of
public health policies.


  We study the sample complexity of model-based reinforcement learning
(henceforth RL) in general contextual decision processes that require strategic
exploration to find a near-optimal policy. We design new algorithms for RL with
a generic model class and analyze their statistical properties. Our algorithms
have sample complexity governed by a new structural parameter called the
witness rank, which we show to be small in several settings of interest,
including factored MDPs. We also show that the witness rank is never larger
than the recently proposed Bellman rank parameter governing the sample
complexity of the model-free algorithm OLIVE (Jiang et al., 2017), the only
other provably sample-efficient algorithm for global exploration at this level
of generality. Focusing on the special case of factored MDPs, we prove an
exponential lower bound for a general class of model-free approaches, including
OLIVE, which, when combined with our algorithmic results, demonstrates
exponential separation between model-based and model-free RL in some
rich-observation settings.


  We present two ways in which the model $L({\mathbb R})$ is canonical assuming
the existence of large cardinals. We show that the theory of this model, with
{\em ordinal} parameters, cannot be changed by small forcing; we show further
that a set of ordinals in $V$ cannot be added to $L({\mathbb R})$ by small
forcing. The large cardinal needed corresponds to the consistency strength of
$AD^{L({\mathbb R})}$; roughly $\omega$ Woodin cardinals.


  The imbalanced distribution of long-tailed data presents a considerable
challenge for deep learning models, as it causes them to prioritize the
accurate classification of head classes but largely disregard tail classes. The
biased decision boundary caused by inadequate semantic information in tail
classes is one of the key factors contributing to their low recognition
accuracy. To rectify this issue, we propose to augment tail classes by grafting
the diverse semantic information from head classes, referred to as head-to-tail
fusion (H2T). We replace a portion of feature maps from tail classes with those
belonging to head classes. These fused features substantially enhance the
diversity of tail classes. Both theoretical analysis and practical
experimentation demonstrate that H2T can contribute to a more optimized
solution for the decision boundary. We seamlessly integrate H2T in the
classifier adjustment stage, making it a plug-and-play module. Its simplicity
and ease of implementation allow for smooth integration with existing
long-tailed recognition methods, facilitating a further performance boost.
Extensive experiments on various long-tailed benchmarks demonstrate the
effectiveness of the proposed H2T. The source code is available at
https://github.com/Keke921/H2T.


  Radio continuum emission from the supernova remnant G296.5+10.0 was observed
using the Australia Telescope Compact Array. Using a 104 MHz bandwidth split
into 13 x 8 MHz spectral channels, it was possible to produce a pixel-by-pixel
image of Rotation Measure (RM) across the entire remnant. A lack of correlation
between RM and X-ray surface brightness reveals that the RMs originate from
outside the remnant. Using this information, we will characterise the smooth
component of the magnetic field within the supernova remnant and attempt to
probe the magneto-ionic structure and turbulent scale sizes in the ISM and
galactic halo along the line-of-sight.


  An effective field theory is derived for the ferromagnetic transition of
diffusive electrons at T=0. The static disorder which leads to diffusive
electron dynamics induces an effective long-range interaction between the spins
of the form 1/r^(2d-2). This leads to unusual scaling behavior at the quantum
critical point, which is determined exactly. The crossover from this quantum
fixed point to the classical Heisenberg fixed point should be observable in
ferromagnetic materials with low Curie temperatures.


  After a brief review on the status of few--nucleon studies based on
conventional nuclear forces, we sketch the concepts of the effective field
theory approach constrained by chiral symmetry and its application to nuclear
forces. Then first results for few--nucleon observables are discussed.


  Most Ultraluminous X-ray sources (ULXs) are thought to be powered by
super-Eddington accretion onto stellar-mass compact objects. Accretors in this
extreme regime are naturally expected to ionise copious amounts of plasma in
their vicinity and launch powerful radiation-driven outflows from their discs.
High spectral resolution X-ray observations (with RGS gratings onboard
XMM-Newton) of a few ULXs with the best datasets indeed found complex line
spectra and confirmed such extreme (0.1-0.3c) winds. However, a search for
plasma signatures in a large ULX sample with a rigorous technique has never
been performed, thereby preventing us from understanding their statistical
properties such as the rate of occurrence, to constrain the outflow geometry
and its duty cycle. We developed a fast method for automated line detection in
X-ray spectra and applied it to the full RGS ULX archive, rigorously
quantifying the statistical significance of any candidate lines. Collecting the
135 most significant features detected in 89 observations of 19 objects, we
created the first catalogue of spectral lines detected in soft X-ray ULX
spectra. We found that the detected emission lines are concentrated around
known rest-frame elemental transitions and thus originate from low-velocity
material. The absorption lines instead avoid these transitions, suggesting they
were imprinted by blueshifted outflows. Such winds therefore appear common
among the ULX population. Additionally, we found that spectrally hard ULXs show
fewer line detections than soft ULXs, indicating some difference in their
accretion geometry and orientation, possibly causing over-ionisation of plasma
by the harder spectral energy distributions of harder ULXs.


  This paper addresses the problem of computing the achievable rates for two
(and three) users sharing a same frequency band without coordination and thus
interfering with each other. It is thus primarily related to the field of
cognitive radio studies as we look for the achievable increase in the spectrum
use efficiency. It is also strongly related to the long standing problem of the
capacity region of a Gaussian interference channel (GIC) because of the
assumption of no user coordination (and the underlying assumption that all
signals and interferences are Gaussian). We give a geometrical description of
the SINR region for the two-user and three-user channels. This geometric
approach provides a closed-form expression of the capacity region of the
two-user interference channel and an insightful of known optimal power
allocation scheme.


  In this paper we have derived Young's, Wenzel's and Cassie-Baxter's equations
using conceptual model rather than showing rigorous derivation to help the
new-comers in this field. We then pointed out that if the substrate is
initially hydorphilic then one can modify the surface morphology and make the
substrate to become hydrophobic or superhydrophobic. But, if the substrate is
initially hydrophobic then one can only make it superhydrophobic but not
hydrophilic by modifying the surface morphology using the formalisms mentioned
in this paper


  We study the sensitivities of the directed flow in Au+Au collisions on the
equation of state (EoS), employing the transport theoretical model JAM. The EoS
is modified by introducing a new collision term in order to control the
pressure of a system by appropriately selecting an azimuthal angle in two-body
collisions according to a given EoS. It is shown that this approach is an
efficient method to modify the EoS in a transport model. The beam energy
dependence of the directed flow of protons is examined with two different EoS,
a first-order phase transition and crossover. It is found that our approach
yields quite similar results as hydrodynamical predictions on the beam energy
dependence of the directed flow; Transport theory predicts a minimum in the
excitation function of the slope of proton directed flow and does indeed yield
negative directed flow, if the EoS with a first-order phase transition is
employed. Our result strongly suggests that the highest sensitivity for the
critical point can be seen in the beam energy range of $4.7\leq\srtNN\leq11.5$
GeV.


  We compute the force and torque between well-separated, slowly-moving Giant
Magnons with arbitrary orientations on S^5. We propose an effective Hamiltonian
for Giant Magnons in this regime.


  We give a complete combinatorial answer to Kostant's problem for simple
highest weight modules indexed by fully commutative permutations. We also
propose a reformulation of Kostant's problem in the context of fiab
bicategories and classify annihilators of simple objects in the principal
birepresentations of such bicategories generalising the Barbasch--Vogan theorem
for Lie algebras.


  In order to develop fast inversion algorithms we have used overlap solvers in
two dimensions. Lattice QED theory with U(1) group symmetry in two dimensional
space-times dimensions has always been a testing ground for algorithms. By the
other side, motivated by our previews work that the two-grid algorithm converge
faster than the standard iterative methods for overlap inversion but not for
all quark masses, we thought to test this idea in less dimensions such as U(1)
gauge theory. Our main objective of this paper it is to implement and develop
the idea of a two level algorithm in a new algorithm coded in QCDLAB. This
implementation is presented in the preconditioned GMRESR algorithm, as our new
contribution in QCDLAB package. The preconditioned part of our algorithm,
different from the one of [18], is the approximation of the overlap operator
with the truncated overlap operator with finite N3 dimension. We have tested it
for 100 statistically independent configurations on 32 x 32 lattice background
U(1) field at coupling constant \b{eta}=1 and for different bare quark masses
mq = [0.5, 0.45, 0.4, 0.35, 0.3, 0.25, 0.2, 0.15, 0.1]. We have compared the
convergence history of the preconditioned GMRESR residual norm with another
overlap inverter of QCDLAB as an optimal one, such as SHUMR. We have shown that
our algorithm converges faster than SHUMR for different quark masses. Also, we
have demonstrated that it saves more time for light quarks compared to SHUMR
algorithm. Our algorithm is approximately independent from the quark mass. This
is a key result in simulations with chiral fermions in lattice theories. By the
other side, if we compare the results of [18] for quark mass 0.1 in SU(3),
results that our chosen preconditioned saves a factor of 2 but in U(1). Our
next step is to test this algorithm in SU(3) and to adopt it in parallel.


  Attempts to reproduce theoretically the relatively small width,
$\Gamma_{d^{\ast}}=80\pm 10$ MeV, of the $I(J^P)=0(3^+)$ $d^{\ast}$(2380)
dibaryon resonance established by the WASA-at-COSY Collaboration are discussed.
The validity of associating the $d^{\ast}$(2380) in quark-based models
primarily with a tightly bound $\Delta\Delta$ configuration is questioned. The
$d^{\ast}$(2380) width and decay branching ratios into $NN\pi\pi$, $NN\pi$ and
$NN$ final states are studied within the Gal-Garcilazo hadronic model in which
the $d^{\ast}$(2380) is a $\pi N\Delta$ resonance embedded in the $NN\pi\pi$
continuum some 80 MeV below the $\Delta\Delta$ threshold. In particular,
predictions are made for the branching ratios of the unobserved yet
$d^{\ast}(2380)\to NN\pi$ decays which are suppressed in a
purely-$\Delta\Delta$ dibaryon model. Comments are also made on a possible
connection of the ABC effect observed in the $pn\to d^{\ast}\to d\pi^0\pi^0$
resonance reaction to the $d^{\ast}$(2380) dibaryon.


  In this work, we systematically study the two-proton($2p$) radioactivity
half-lives using the two-potential approach while the nuclear potential is
obtained by using Skyrme-Hartree-Fock approach with the Skyrme effective
interaction of {SLy8}. For true $2p$ radioactivity($Q_{2p}$ $>$ 0 and $Q_p$ $<
$0, where the $Q_p$ and $Q_{2p}$ are the released energy of the one-proton and
two-proton radioactivity), the standard deviation between the experimental
half-lives and our theoretical calculations is {0.701}. In addition, we extend
this model to predict the half-lives of 15 possible $2p$ radioactivity
candidates with $Q_{2p}$ $>$ 0 taken from the evaluated atomic mass table
AME2016. The calculated results indicate that a clear linear relationship
between the logarithmic $2p$ radioactivity half-lives $\rm{log}_{10}T_{1/2}$
and coulomb parameters [ ($Z_{d}^{0.8}$+$l^{0.25}$)$Q_{2p}^{-1/2}$] considered
the effect of orbital angular momentum proposed by Liu $et$ $al$ [Chin. Phys. C
\textbf{45}, 024108 (2021)] is also existed. For comparison, the generalized
liquid drop model(GLDM), the effective liquid drop model(ELDM) and Gamow-like
model are also used. Our predicted results are consistent with the ones
obtained by the other models.


  For a Schwarzchild black hole of mass $M$, we consider a test particle
falling from rest at infinity and becoming trapped, at late time, on the
unstable circular orbit of radius $r=4GM/c^2$. When the particle is endowed
with a small mass, $\mu\ll M$, it experiences an effective gravitational
self-force, whose conservative piece shifts the critical value of the angular
momentum and the frequency of the asymptotic circular orbit away from their
geodesic values. By directly integrating the self-force along the orbit
(ignoring radiative dissipation), we numerically calculate these shifts to
$O(\mu/M)$. Our numerical values are found to be in agreement with estimates
first made within the Effective One Body formalism, and with predictions of the
first law of black-hole-binary mechanics (as applied to the asymptotic circular
orbit). Our calculation is based on a time-domain integration of the
Lorenz-gauge perturbation equations, and it is a first such calculation for an
unbound orbit. We tackle several technical difficulties specific to unbound
orbits, illustrating how these may be handled in more general cases of unbound
motion. Our method paves the way to calculations of the self-force along
hyperbolic-type scattering orbits. Such orbits can probe the two-body potential
down to the "light ring", and could thus supply strong-field calibration data
for eccentricity-dependent terms in the Effective One Body model of merging
binaries.


  In hep-th/9903210 (curvature)$^2$ terms of the effective D-brane action were
derived to lowest order in the string coupling. Their results are correct up to
ambiguous terms which involve the second fundamental form of the D-brane. We
compute five point string amplitudes on the disk. We compare the subleading
order in $\alpha'$ of the string amplitudes with the proposed lagrangian of
hep-th/9903210 supplemented by the ambiguous terms. The comparison determines
the complete form of the gravitational terms in the effective D-brane action to
order ${\calO}(\alpha^{' 2})$. Our results are valid for arbitrary ambient
geometries and world-volume embeddings.


  We present analytical and numerical simulation results for squeezing,
entanglement, and quantum discord in a dissipatively coupled coherent Ising
machine (CIM). Both analytical solutions and numerical simulation results,
which are obtained with positive-P, truncated-Wigner and truncated-Husimi
representations for the density operator, predict the presence of entanglement
and quantum discord, below and above the threshold of CIM. The entanglement
criteria and quantum discord are evaluated as a function of the dissipative
coupling strength relative to the background loss. For coupled two DOPOs, while
entanglement disappears as the background loss exceeds the Ising coupling
strength, the quantum discord remains finite even with a large linear loss. For
one-dimensional lattice of DOPOs, while entanglement disappears for DOPO pair
with large distance, quantum discord remains finite.


  As white-dwarf (WD) stars cool, they go through one or more stages of
$g$(gravity)-mode pulsational instability, becoming multiperiodic variable
stars. Stars passing through these instability domains allow astronomers to
study their interiors through asteroseismological techniques, as if they could
"look" at their interiors by analyzing the spectra of pulsation periods. WD
asteroseismology has experienced extraordinary advances in recent years thanks
to photometric observations of unprecedented quality delivered by space
missions such as Kepler and TESS. These advances in the monitoring of variable
WDs have been accompanied by the development of new stellar models and
techniques for modeling their pulsations. In this article, we review the most
outstanding findings -- up to early 2022 -- about these fascinating pulsating
stars made possible with the high-sensitivity and continuous observations of
the ongoing TESS mission, bearing in mind that there will possibly be many more
new results in the immediate future derived from this unique space telescope.


  Short term load forecasting has an essential medium for the reliable,
economical and efficient operation of the power system. Most of the existing
forecasting approaches utilize fixed statistical models with large historical
data for training the models. However, due to the recent integration of large
distributed generation, the nature of load demand has become dynamic. Thus
because of the dynamic nature of the power load demand, the performance of
these models may deteriorate over time. To accommodate the dynamic nature of
the load demands, we propose a sliding window regression based dynamic model to
predict the load demands of the multiarea power system. The proposed algorithm
is tested on five zones of New York ISO. Results from our proposed algorithm
are compared with four existing techniques to validate the performance
superiority of the proposed algorithm.


  The number of increased social media users has led to a lot of people
misusing these platforms to spread offensive content and use hate speech.
Manual tracking the vast amount of posts is impractical so it is necessary to
devise automated methods to identify them quickly. Large language models are
trained on a lot of data and they also make use of contextual embeddings. We
fine-tune the large language models to help in our task. The data is also quite
unbalanced; so we used a modified cross-entropy loss to tackle the issue. We
observed that using a model which is fine-tuned in hindi corpora performs
better. Our team (HNLP) achieved the macro F1-scores of 0.808, 0.639 in English
Subtask A and English Subtask B respectively. For Hindi Subtask A, Hindi
Subtask B our team achieved macro F1-scores of 0.737, 0.443 respectively in
HASOC 2021.


  It was earlier reported [PRL 78 199, (1997)] that long-lived excited states
of positronium can be formed in crossed electric and magnetic fields at
laboratory field strengths. Unlike the lower-lying states that are localized in
the magnetically distorted Coulomb well, these long-lived states which can
possess a lifetime up to many years are localized in an outer potential well
that is formed for certain values of the pseudomomentum and magnetic field. The
present work extends the original analysis and studies the dependence of the
spectrum as a function of field strength and pseudomomentum over a wide range
of parameters. We predict that in the limit of large pseudomomentum, the ground
state of positronium atom in a magnetic field will become delocalized; for
strong fields, the binding energy of this state is quite large, resulting in a
ground state that is both stable against direct annihilation and against
ionization by low frequency background radiation.


  In this paper, we study the transcendental entire solutions for the nonlinear
differential-difference equations of the forms: $f^{2}(z)+\widetilde{\omega}
f(z)f'(z)+q(z)e^{Q(z)}f(z+c)=u(z)e^{v(z)}$, and $f^{n}(z)+\omega
f^{n-1}(z)f'(z)+q(z)e^{Q(z)}f(z+c)=p_{1}e^{\lambda_{1} z}+p_{2}e^{\lambda_{2}
z}, \quad n\geq 3,$ where $\omega$ is a constant, $\widetilde{\omega}, c,
\lambda_{1}, \lambda_{2}, p_{1}, p_{2}$ are non-zero constants, $q, Q, u, v$
are polynomials such that $Q,v$ are not constants and $q,u\not\equiv0$. Our
results are improvements and complements of some previous results.


  While the existence of scheduler side-channels has been demonstrated recently
for fixed-priority real-time systems (RTS), there have been no similar
explorations for dynamic-priority systems. The dynamic nature of such
scheduling algorithms, e.g., EDF, poses a significant challenge in this regard.
In this paper we demonstrate that side-channels exist in dynamic priority
real-time systems. Using this side-channel, our proposed DyPS algorithm is able
to effectively infer, with high precision, critical task information from the
vantage point of an unprivileged (user space) task. Apart from demonstrating
the effectiveness of DyPS, we also explore the various factors that impact such
attack algorithms using a large number of synthetic task sets. We also compare
against the state-of-the-art and demonstrate that our proposed DyPS algorithms
outperform the ScheduLeak algorithms in attacking the EDF RTS.


  This paper proposes novel set-theoretic approaches for state estimation in
bounded-error discrete-time nonlinear systems, subject to nonlinear
observations/constraints. By transforming the polytopic sets that are
characterized as zonotope bundles (ZB) and/or constrained zonotopes (CZ), from
the state space to the space of the generators of ZB/CZ, we leverage a recent
result on the remainder-form mixed-monotone decomposition functions to compute
the propagated set, i.e., a ZB/CZ that is guaranteed to enclose the set of the
state trajectories of the considered system. Further, by applying the
remainder-form decomposition functions to the nonlinear observation function,
we derive the updated set, i.e., an enclosing ZB/CZ of the intersection of the
propagated set and the set of states that are compatible/consistent with the
observations/constraints. Finally, we show that the mean value extension result
in [1] for computing propagated sets can also be extended to compute the
updated set when the observation function is nonlinear.


  We obtain solutions to conservation laws under any random initial conditions
that are described by Gaussian stochastic processes (in some cases
discretized). We analyze the generalization of Burgers' equation for a smooth
flux function $H\left( p\right) =\left\vert p\right\vert ^{j}$ for $j\geq2$
under random initial data. We then consider a piecewise linear, non-smooth and
non-convex flux function paired with general discretized Gaussian stochastic
process initial data. By partitioning the real line into a finite number of
points, we obtain an exact expression for the solution of this problem. From
this we can also find exact and approximate formulae for the density of shocks
in the solution profile at a given time $t$ and spatial coordinate $x$. We
discuss the simplification of these results in specific cases, including
Brownian motion and Brownian bridge, for which the inverse covariance matrix
and corresponding eigenvalue spectrum have some special properties. We
calculate the transition probabilities between various cases and examine the
variance of the solution $w\left(x,t\right)$ in both $x$ and $t$. We also
describe how results may be obtained for a non-discretized version of a
Gaussian stochastic process by taking the continuum limit as the partition
becomes more fine.


  We propose to enhance the RNN decoder in a neural machine translator (NMT)
with external memory, as a natural but powerful extension to the state in the
decoding RNN. This memory-enhanced RNN decoder is called \textsc{MemDec}. At
each time during decoding, \textsc{MemDec} will read from this memory and write
to this memory once, both with content-based addressing. Unlike the unbounded
memory in previous work\cite{RNNsearch} to store the representation of source
sentence, the memory in \textsc{MemDec} is a matrix with pre-determined size
designed to better capture the information important for the decoding process
at each time step. Our empirical study on Chinese-English translation shows
that it can improve by $4.8$ BLEU upon Groundhog and $5.3$ BLEU upon on Moses,
yielding the best performance achieved with the same training set.


  Let $X$ and $Y$ be Banach spaces and let $\Omega$ be a compact Hausdorff
space. Denote by $\mathcal{C}_{p}(\Omega,X)$ the space of $p$-continous
$X$-valued functions, $1\leq p\leq \infty$. For operators
$S\in\mathcal{L}(\mathcal{C}(\Omega),\mathcal{L}(X,Y))$ and
$U\in\mathcal{L}(\mathcal{C}_{p}(\Omega,X),Y)$, we establish integral
representation theorems with respect to a vector measure $m:\Sigma\rightarrow
\mathcal{L}(X,Y^{**})$, where $\Sigma$ denotes the $\sigma$-algebra of Borel
subsets of $\Omega$. The first theorem extends the classical
Bartle-Dunford-Schwartz representation theorem. It is used to prove the second
theorem, which extends the classical Dinculeanu-Singer representation theorem,
also providing to it an alternative simpler proof. For the latter (and the
main) result, we build the needed integration theory, relying on a new concept
of the $q$-semivariation, $1\leq q\leq \infty$, of a vector measure
$m:\Sigma\rightarrow \mathcal{L}(X,Y^{**})$.


  The computation of detection probabilities and arrival time distributions
within Bohmian mechanics in general needs the explicit knowledge of a relevant
sample of trajectories. Here it is shown how for one-dimensional systems and
rigid inertial detectors these quantities can be computed without calculating
any trajectories. An expression in terms of the wave function and its spatial
derivative, both restricted to the boundary of the detector's spacetime volume,
is derived for the general case, where the probability current at the
detector's boundary may vary its sign.


  As machine learning techniques are applied to a widening range of
applications, high throughput machine learning (ML) inference servers have
become critical for online service applications. Such ML inference servers pose
two challenges: first, they must provide a bounded latency for each request to
support consistent service-level objective (SLO), and second, they can serve
multiple heterogeneous ML models in a system as certain tasks involve
invocation of multiple models and consolidating multiple models can improve
system utilization. To address the two requirements of ML inference servers,
this paper proposes a new ML inference scheduling framework for multi-model ML
inference servers. The paper first shows that with SLO constraints, current
GPUs are not fully utilized for ML inference tasks. To maximize the resource
efficiency of inference servers, a key mechanism proposed in this paper is to
exploit hardware support for spatial partitioning of GPU resources. With the
partitioning mechanism, a new abstraction layer of GPU resources is created
with configurable GPU resources. The scheduler assigns requests to virtual
GPUs, called gpu-lets, with the most effective amount of resources. The paper
also investigates a remedy for potential interference effects when two ML tasks
are running concurrently in a GPU. Our prototype implementation proves that
spatial partitioning enhances throughput by 102.6% on average while satisfying
SLOs.


  In a number of recent experiments, it has been shown that femtosecond laser
pulses can control magnetization on picosecond timescales, which is at least an
order of magnitude faster compared to conventional magnetization dynamics.
Among these demonstrations, one material system (GdFeCo ferromagnetic films) is
particularly interesting, as deterministic toggle-switching of the magnetic
order has been achieved without the need of any symmetry breaking magnetic
field. This phenomenon is often referred to as all optical switching (AOS).
However, so far, GdFeCo remains the only material system where such
deterministic switching has been observed. When extended to ferromagnetic
systems, which are of greater interest in many technological applications, only
a partial effect can be achieved, which in turn requires repeated laser pulses
for full switching. However, such repeated pulsing is not only energy hungry,
it also negates the speed advantage of AOS. Motivated by this problem, we have
developed a general method for single-shot, picosecond timescale, complete all
optical switching of ferromagnetic materials. We demonstrate that in
exchange-coupled layers of Co/Pt and GdFeCo, single shot, switching of the
ferromagnetic Co/Pt layer is achieved within 7 picoseconds after irradiation by
a femtosecond laser pulse. We believe that this approach will greatly expand
the range of materials and applications for ultrafast magnetic switching.


  IceCube is a cubic-kilometer Cherenkov detector in the deep ice at the
geographic South Pole. The dominant event yield in the deep ice detector
consists of penetrating atmospheric muons with energies above approximately 300
GeV, produced in cosmic ray air showers. In addition, the surface array,
IceTop, measures the electromagnetic component and GeV muons of air showers.
Hence, IceCube and IceTop yield unique opportunities to study cosmic rays with
unprecedented statistics in great detail. We will present recent results of
comic ray measurements from IceCube and IceTop. In this overview, we will
highlight measurements of the energy spectrum of cosmic rays from 250 TeV up to
the EeV range and their mass composition above 3 PeV. We will also report
recent results from measurements of the muon content in air showers and discuss
their consistency with predictions from current hadronic interaction models.


  The objective of the present paper is to study 4-dimensional weakly Ricci
symmetric spacetimes $(WRS)_4$ with non-zero constant Ricci scalar. We prove
that such a $(WRS)_4$ satisfying $F(R)$-gravity field equations represents a
perfect fluid with vanishing vorticity. Some energy conditions are studied
under the current setting to constrain the functional form of $F(R)$. We
examine a couple of popular toy models in $F(R)$-gravity, $F(R)=e^{\alpha R}$
where $\alpha$ is constant and $F(R)=R-\beta \tanh(R)$, $\beta$ is a constant.
We also find that the equation of state parameter (EoS) in both models supports
the universe's accelerating behavior, i.e., $\omega=-1$. According to the
recently suggested observations of accelerated expansion, both cases define
that the null, weak, and dominant energy conditions justify their requirements
while the strong energy conditions violate them.