  Quantum dots (QD) with electric-field-controlled charge state are promising
for electronics applications, e.g., digital information storage,
single-electron transistors and quantum computing. Inorganic QDs consisting of
semiconductor nanostructures or heterostructures often offer limited control on
size and composition distribution, as well as low potential for scalability
and/or nanoscale miniaturization. Owing to their tunability and self-assembly
capability, using organic molecules as building nano-units can allow for
bottom-up synthesis of two-dimensional (2D) nanoarrays of QDs. However, 2D
molecular self-assembly protocols are often applicable on metals surfaces,
where electronic hybridization and Fermi level pinning can hinder
electric-field control of the QD charge state. Here, we demonstrate the
synthesis of a single-component self-assembled 2D array of molecules [9,
10-dicyanoanthracene (DCA)] that exhibit electric-field-controlled spatially
periodic charging on a noble metal surface, Ag(111). The charge state of DCA
can be altered (between neutral and negative), depending on its adsorption
site, by the local electric field induced by a scanning tunneling microscope
tip. Limited metal-molecule interactions result in an effective tunneling
barrier between DCA and Ag(111) that enables electric-field-induced electron
population of the lowest unoccupied molecular orbital (LUMO) and hence charging
of the molecule. Subtle site-dependent variation of the molecular adsorption
height translates into a significant spatial modulation of the molecular
polarizability, dielectric constant and LUMO energy level alignment, giving
rise to a spatially dependent effective molecule-surface tunneling barrier and
likelihood of charging. This work offers potential for high-density 2D
self-assembled nanoarrays of identical QDs whose charge states can be addressed
individually with an electric field.


  Canids display a wide diversity of social systems, from solitary to pairs to
packs, and hence they have been extensively used as model systems to understand
social dynamics in natural systems. Among canids, the dog can show various
levels of social organization due to the influence of humans on their lives.
Though the dog is known as man's best friend and has been studied extensively
as a pet, studies on the natural history, ecology and behaviour of dogs in a
natural habitat are rare. Here we report results of an extensive
population-level study conducted through one-time censuses in urban India to
understand the ecoethology of free-ranging dogs. We built a model to test if
the observed groups could have been formed through random associations while
foraging. Our modeling results suggest that the dogs, like all efficient
scavengers, tend to forage singly but also form random uncorrelated groups. A
closer inspection of the group compositions however reveals that the foraging
associations are non-random events. The tendency of adults to associate with
the opposite sex in the mating season and of juveniles to stay close to adults
in the non-mating season drives the population towards aggregation, in spite of
the apparently random nature of the group size distribution. Hence we conclude
that to be or not to be social is a matter of choice for the free-ranging dogs,
and not a matter of chance.


  We introduce the novel concept of anti-transfer learning for speech
processing with convolutional neural networks. While transfer learning assumes
that the learning process for a target task will benefit from re-using
representations learned for another task, anti-transfer avoids the learning of
representations that have been learned for an orthogonal task, i.e., one that
is not relevant and potentially misleading for the target task, such as speaker
identity for speech recognition or speech content for emotion recognition. In
anti-transfer learning, we penalize similarity between activations of a network
being trained and another one previously trained on an orthogonal task, which
yields more suitable representations. This leads to better generalization and
provides a degree of control over correlations that are spurious or
undesirable, e.g. to avoid social bias. We have implemented anti-transfer for
convolutional neural networks in different configurations with several
similarity metrics and aggregation functions, which we evaluate and analyze
with several speech and audio tasks and settings, using six datasets. We show
that anti-transfer actually leads to the intended invariance to the orthogonal
task and to more appropriate features for the target task at hand.
Anti-transfer learning consistently improves classification accuracy in all
test cases. While anti-transfer creates computation and memory cost at training
time, there is relatively little computation cost when using pre-trained models
for orthogonal tasks. Anti-transfer is widely applicable and particularly
useful where a specific invariance is desirable or where trained models are
available and labeled data for orthogonal tasks are difficult to obtain.


  Coroutines and events are two common abstractions for writing concurrent
programs. Because coroutines are often more convenient, but events more
portable and efficient, it is natural to want to translate the former into the
latter. CPC is such a source-to-source translator for C programs, based on a
partial conversion into continuation-passing style (CPS conversion) of
functions annotated as cooperative.
  In this article, we study the application of the CPC translator to QEMU, an
open-source machine emulator which also uses annotated coroutine functions for
concurrency. We first propose a new type of annotations to identify functions
which never cooperate, and we introduce CoroCheck, a tool for the static
analysis and inference of cooperation annotations. Then, we improve the CPC
translator, defining CPS conversion as a calling convention for the C language,
with support for indirect calls to CPS-converted function through function
pointers. Finally, we apply CoroCheck and CPC to QEMU (750 000 lines of C
code), fixing hundreds of missing annotations and comparing performance of the
translated code with existing implementations of coroutines in QEMU.
  Our work shows the importance of static annotation checking to prevent actual
concurrency bugs, and demonstrates that CPS conversion is a flexible, portable,
and efficient compilation technique, even for very large programs written in an
imperative language.


  The screened QED corrections of the first orders in \alpha and 1/Z to the g
factor and the hyperfine splitting of lithiumlike ions are evaluated within ab
initio quantum electrodynamical approach. The complete gauge-invariant set of
the two-electron self-energy diagrams in the presence of the magnetic field and
a dominant part of the two-electron vacuum-polarization diagrams are
calculated. The most accurate values of the g factor of Li-like lead and
uranium are presented. The theoretical prediction for the specific difference
of the hyperfine splittings of H- and Li-like bismuth is improved.


  The way the media presents events can significantly affect public perception,
which in turn can alter people's beliefs and views. Media bias describes a
one-sided or polarizing perspective on a topic. This article summarizes the
research on computational methods to detect media bias by systematically
reviewing 3140 research papers published between 2019 and 2022. To structure
our review and support a mutual understanding of bias across research domains,
we introduce the Media Bias Taxonomy, which provides a coherent overview of the
current state of research on media bias from different perspectives. We show
that media bias detection is a highly active research field, in which
transformer-based classification approaches have led to significant
improvements in recent years. These improvements include higher classification
accuracy and the ability to detect more fine-granular types of bias. However,
we have identified a lack of interdisciplinarity in existing projects, and a
need for more awareness of the various types of media bias to support
methodologically thorough performance evaluations of media bias detection
systems. Concluding from our analysis, we see the integration of recent machine
learning advancements with reliable and diverse bias assessment strategies from
other research areas as the most promising area for future research
contributions in the field.


  A Micro-Channel Plate (MCP) is a widely used component for counting particles
in space. Using the background counts of MCPs on Mars Express and Venus Express
orbiters operated over 17 years and 8 years, respectively, we investigate the
galactic cosmic ray (GCR) characteristics in the inner solar system. The MCP
background counts at Mars and Venus on a solar cycle time scale exhibit clear
anti-correlation to the sunspot number. We conclude that the measured MCP
background contain the GCR information. The GCR characteristics measured using
the MCP background at Mars show features that are consistent with the
ground-based measurement in solar cycle 24. The time lag between the sunspot
number and the MCP background at Mars is found ~9 months. The shorter-term
background data recorded along the orbits (with a time scale of several hours)
also show evident depletion of the background counts due to the absorption of
the GCR particles by the planets. Thanks to the visible planetary size change
along an orbit, the GCR contribution to the MCP background can be separated
from the internal contribution due to the \b{eta}-decay. Our statistical
analysis of the GCR absorption signatures at Mars implies that the effective
absorption size of Mars for the GCR particles have a >100 km larger radius than
the solid Martian body.


  We introduce a method based on auxiliary master equation for solving the
problem of an impurity with local electron-electron and electron-phonon
interaction embedded between two conduction leads with a finite bias voltage.
The Anderson-Holstein Hamiltonian is transformed to a corresponding Lindblad
equation with a reduced set of sites providing an optimal approximation of the
hybridization function. The problem is solved in the superfermion
representation using configuration interaction for fermions and bosons. The
phonon basis is shifted and rotated with the intention of permitting a low
phonon basis cutoff even in the strong-coupling regime. We benchmark this
approach with the numerical renormalization group in equilibrium, finding
excellent agreement. We observe, however, that the rotation brings no advantage
beyond the bare shift. This is even more apparent out of equilibrium, where
issues in convergence with respect to the size of the phononic Hilbert space
occur only in the rotated basis. As an application of the method, we explore
the evolution of the phononic peak in the differential conductance spectra with
changing phonon frequency.


  We investigate the possibility of performing quantum tomography on a single
qubit with generalized partial measurements and the technique of measurement
reversal. Using concepts from statistical decision theory, we prove that,
somewhat surprisingly, no information can be obtained using this scheme. It is
shown that, irrespective of the measurement technique used, extraction of
information from single quanta is at odds with other general principles of
quantum physics.


  Cosmic shear data contains a large amount of cosmological information
encapsulated in the non-Gaussian features of the weak lensing mass maps. This
information can be extracted using non-Gaussian statistics. We compare the
constraining power in the $\Omega_{\mathrm{m}} - \sigma_8$ plane of three
map-based non-Gaussian statistics with the angular power spectrum, namely;
peak/minimum counts and Minkowski functionals. We further analyze the impact of
tomography and systematic effects originating from galaxy intrinsic alignments,
multiplicative shear bias and photometric redshift systematics. We forecast the
performance of the statistics for a stage-3-like weak lensing survey and
restrict ourselves to scales $\geq$ 10 arcmin. We find, that in our setup, the
considered non-Gaussian statistics provide tighter constraints than the angular
power spectrum. The peak counts show the greatest potential, increasing the
Figure-of-Merit (FoM) in the $\Omega_{\mathrm{m}} - \sigma_8$ plane by a factor
of about 4. A combined analysis using all non-Gaussian statistics in addition
to the power spectrum increases the FoM by a factor of 5 and reduces the error
on $S_8$ by $\approx$ 25\%. We find that the importance of tomography is
diminished when combining non-Gaussian statistics with the angular power
spectrum. The non-Gaussian statistics indeed profit less from tomography and
the minimum counts and Minkowski functionals add some robustness against galaxy
intrinsic alignment in a non-tomographic setting. We further find that a
combination of the angular power spectrum and the non-Gaussian statistics
allows us to apply conservative scale cuts in the analysis, thus helping to
minimize the impact of baryonic and relativistic effects, while conserving the
cosmological constraining power. We make the code that was used to conduct this
analysis publicly available.


  We present a combined Brillouin light scattering and micromagnetic simulation
investigation of the magnetic-field dependent spin-wave spectra in a hybrid
structure made of permalloy (NiFe) artificial spin-ice (ASI) systems, composed
of stadium-shaped nanoislands, deposited on the top of an unpatterned permalloy
film with a nonmagnetic spacer layer. The thermal spin-wave spectra were
recorded by Brillouin light scattering (BLS) as a function of the magnetic
field applied along the symmetry direction of the ASI sample. Magneto-optic
Kerr effect magnetometry was used to measure the hysteresis loops in the same
orientation as the BLS measurements. The frequency and intensity of several
spin-wave modes detected by BLS were measured as a function of the applied
magnetic field. Micromagnetic simulations enabled us to identify the modes in
terms of their frequency and spatial symmetry and to extract information about
the existence and strength of the dynamic coupling, relevant only to a few
modes of a given hybrid system. Using this approach, we suggest a way to
understand if dynamic coupling between ASI and film modes is present or not,
with interesting implications for the development of future three-dimensional
magnonic applications and devices.


  We reveal that nonlocality can provide a simple physical mechanism for
stabilization of multi-hump optical solitons, and present the first example of
stable rotating dipole solitons and soliton spiraling, known to be unstable in
all types of realistic nonlinear media with local response.


  In this document I recapitulate some results by Hiriart-Urruty and Ye (1995)
concerning the properties of differentiability and the existence of lateral
directional derivatives of the multiple eigenvalues of a complex Hermitian
matrix function of several real variables, where the eigenvalues are supposed
in a decreasing order. Another version of these results was obtained by
Ji-guang Sun (1988).
  This 2020 version has been written following a remark raised by Miloud
Sadkane about the presence or not of the value 1/2 in the formulas that give
the lateral directional derivatives of multiple singular values. Therefore, I
have added Theorem 9. I have also written in more detail the relationship of
the reviewed results with those in the bibliography. Finally, I have also put a
result of mine (Corollary 11 in [1]) (joint with Armentia and Velasco) which
interprets a Lippert's Theorem (2005).


  We propose an algorithm for computing the projection of a symmetric
second-order tensor onto the cone of negative semidefinite symmetric tensors
with respect to the inner product defined by an assigned positive definite
symmetric fourth-order tensor C. The projection problem is written as a
semidefinite programming problem and an algorithm based on a primal-dual
path-following interior point method coupled with a Mehrotra's
predictor-corrector approach is proposed. Implementations based on direct
methods are theoretically and numerically investigated taking into account
tensors C arising in the modelling of masonry-like materials.


  This work presents a direct measurement of the $^{96}$Ru($p,
\gamma$)$^{97}$Rh cross section via a novel technique using a storage ring,
which opens opportunities for reaction measurements on unstable nuclei. A
proof-of-principle experiment was performed at the storage ring ESR at GSI in
Darmstadt, where circulating $^{96}$Ru ions interacted repeatedly with a
hydrogen target. The $^{96}$Ru($p, \gamma$)$^{97}$Rh cross section between 9
and 11 MeV has been determined using two independent normalization methods. As
key ingredients in Hauser-Feshbach calculations, the $\gamma$-ray strength
function as well as the level density model can be pinned down with the
measured ($p, \gamma$) cross section. Furthermore, the proton optical potential
can be optimized after the uncertainties from the $\gamma$-ray strength
function and the level density have been removed. As a result, a constrained
$^{96}$Ru($p, \gamma$)$^{97}$Rh reaction rate over a wide temperature range is
recommended for $p$-process network calculations.


  Capacity is an important quantity in potential theory and in the study of
Markov processes. We give equivalent conditions between the capacity, the mean
exit time, and the Green function for non-reversible diffusions.


  We develop a data driven approach to perform clustering and end-to-end
feature learning simultaneously for streaming data that can adaptively detect
novel clusters in emerging data. Our approach, Adaptive Nonparametric
Variational Autoencoder (AdapVAE), learns the cluster membership through a
Bayesian Nonparametric (BNP) modeling framework with Deep Neural Networks
(DNNs) for feature learning. We develop a joint online variational inference
algorithm to learn feature representations and clustering assignments
simultaneously via iteratively optimizing the Evidence Lower Bound (ELBO). We
resolve the catastrophic forgetting \citep{kirkpatrick2017overcoming}
challenges with streaming data by adopting generative samples from the trained
AdapVAE using previous data, which avoids the need of storing and reusing past
data. We demonstrate the advantages of our model including adaptive novel
cluster detection without discarding useful information learned from past data,
high quality sample generation and comparable clustering performance as
end-to-end batch mode clustering methods on both image and text corpora
benchmark datasets.


  The size dependent exciton dynamics of one-dimensional aggregates of
substituted perylene bisimides are studied by ultrafast transient absorption
spectroscopy and kinetic Monte-Carlo simulations in dependence on the
temperature and the excitation density. For low temperatures the aggregates can
be treated as infinite chains and the dynamics is dominated by diffusion driven
exciton-exciton annihilation. With increasing temperature the aggregates
decompose into small fragments consisting of very few monomers. This scenario
is also supported by the time dependent anisotropy deduced from polarization
dependent experiments.


  Temporal evolutions toward thermal equilibria are numerically investigated in
a Hamiltonian system with many degrees of freedom which has second order phase
transition. Relaxation processes are studied through local order parameter, and
slow relaxations of power type are observed at the critical energy of phase
transition for some initial conditions. Numerical results are compared with
results of a phenomenological theory of statistical mechanics. At the critical
energy, the maximum Lyapunov exponent takes the largest value. Temporal
evolutions and probability distributions of local Lyapunov exponents show that
the system is highly chaotic rather than weakly chaotic at the critical energy.
Consequently theories for perturbed systems may not be applied to the system at
the critical energy in order to explain the slow relaxation of power type.


  Excited states in 17C were investigated through the measurement of
beta?-delayed neutrons and gamma rays emitted in the ? decay of 17B. In the
measurement, three negative-parity states and two inconclusive states, were
identified in 17C above the neutron threshold energy, and seven gamma-lines
were identified in a beta?-delayed multiple neutron emission of the 17B ?
decay. From these transitions, the beta?-decay scheme of 17B was determined. In
the present work, the fibeta-NMR technique is combined with the ?-delayed
particle measurements using a fragmentation-induced spin-polarized 17B beam.
This new scheme allows us to determine the spin parity of beta?-decay feeding
excited states based on the difference in the discrete fibeta-decay asymmetry
parameters, provided the states are connected through the Gamow-Teller
transition. In this work, 1/2-, 3/2-, and (5/2-) are assigned to the observed
states at Ex = 2.71(2), 3.93(2), and 4.05(2) MeV in 17C, respectively.


  Weather station data is a valuable resource for climate prediction, however,
its reliability can be limited in remote locations. To compound the issue,
making local predictions often relies on sensor data that may not be accessible
for a new, previously unmonitored location. In response to these challenges, we
propose a novel zero-shot learning approach designed to forecast various
climate measurements at new and unmonitored locations. Our method surpasses
conventional weather forecasting techniques in predicting microclimate
variables by leveraging knowledge extracted from other geographic locations.


  We show how multiplier ideals can be used to obtain uniform multiplicative
bounds for certain families of ideals on a smooth complex algebraic variety. In
particular we prove a quick but rather surprising result about symbolic powers
of radical ideals on such a variety. Specifically, let I be a radical ideal
sheaf on a smooth variety X defining a reduced subscheme Z of X and suppose
that every irreducible component of Z has codimension at most e in X. Given an
integer m > 0 suppose that f is a function germ that vanishes to order at least
e.m at a general point of each irreducible component of Z . Then in fact f lies
in the m-th power I^m of I.


  Utilities have introduced demand charges to encourage customers to reduce
their demand peaks, since a high peak may cause very high costs for both the
utility and the consumer. We herein study the bill minimization problem for
customers equipped with an energy storage device and a self-owned renewable
energy production. A model-free reinforcement learning algorithm is carefully
designed to reduce both the energy charge and the demand charge of the
consumer. The proposed algorithm does not need forecasting models for the
energy demand and the renewable energy production. The resulting controller can
be used online, and progressively improved with newly gathered data. The
algorithm is validated on real data from an office building of IFPEN Solaize
site. Numerical results show that our algorithm can reduce electricity bills
with both daily and monthly demand charges.


  In this work we explore the geodesic deviations of spinning test particles in
a string inspired Einstein-Kalb Ramond background. Such a background is known
to be equivalent to a spacetime geometry with torsion. We have shown here that
the antisymmetric Kalb-Ramond field has significant effect on the geodesic
deviation of a spinning test particle. A search for an observational evidence
of such an effect in astrophysical experiments may lead to a better
undestanding of the geometry of the background spacetime.


  We construct a bosonization of the quantum superalgebra $U_q(\hat{sl}(N|1))$
for an arbitrary level $k$. We construct the screening that commutes with the
quantum superalgebra for an arbitrary level $k \neq -N+1$. We propose a
bosonization of the vertex operator that gives the intertwiner among the
Wakimoto realization and the typical representation.


  A study of 12 ultracompact HII regions was conducted to probe the physical
conditions and kinematics in the inner envelopes of the molecular clumps
harboring them. The APEX telescope was used to observe the sources in the CO
(4-3) and 13CO (8-7) lines. Line intensities were modeled with the RATRAN
radiative transfer code using power laws for the density and temperature to
describe the physical structure of the clumps. All sources were detected in
both lines. The optically thick CO (4-3) line shows predominantly blue skewed
profiles reminiscent of infall. Line intensities can be reproduced well using
the physical structure of the clumps taken from the literature. The optically
thick line profiles show that CO is a sensitive tracer of ongoing infall in the
outer envelopes of clumps harboring ultracompact HII regions and hot molecular
cores.


  We investigate the physical meaning of quantum superposition states between
reactants and products in electron transfer reactions. We show that such
superpositions are strongly suppressed and to leading orders of perturbation
theory do not pertain in electron transfer reactions. This is because of the
intermediate manifold of states separating the reactants from the products. We
provide an intuitive description of these considerations with Feynman diagrams.
We also discuss the relation of such quantum coherences to understanding the
fundamental quantum dynamics of spin-selective radical-ion-pair reactions.


  Let $\{\Omega_t:-1<t<1\}$ be a family of bounded pseudoconvex domains and
$\varphi_t\in PSH(\Omega_t)$. Let $K_t(z,w)$ denote the Bergman kernel with
weight $\varphi_t$ on $\Omega_t$. We study the continuity and H\"older
continuity of $K_t(z,w)$ in $t$. Several applications to singularity theory of
psh functions are given, including a new proof of the openness theorem.


  During the first half of their main-sequence lifetimes, stars rapidly lose
angular momentum to their magnetized winds, a process known as magnetic
braking. Recent observations suggest a substantial decrease in the magnetic
braking efficiency when stars reach a critical value of the Rossby number, the
stellar rotation period normalized by the convective overturn timescale. Cooler
stars have deeper convection zones with longer overturn times, reaching this
critical Rossby number at slower rotation rates. The nature and timing of the
transition to weakened magnetic braking has previously been constrained by
several solar analogs and two slightly hotter stars. In this Letter, we derive
the first direct constraints from stars cooler than the Sun. We present new
spectropolarimetry of the old G8 dwarf $\tau$ Cet from the Large Binocular
Telescope, and we reanalyze a published Zeeman Doppler image of the younger G8
star 61 UMa, yielding the large-scale magnetic field strengths and
morphologies. We estimate mass-loss rates using archival X-ray observations and
inferences from Ly$\alpha$ measurements, and we adopt other stellar properties
from asteroseismology and spectral energy distribution fitting. The resulting
calculations of the wind braking torque demonstrate that the rate of angular
momentum loss drops by a factor of 300 between the ages of these two stars
(1.4-9 Gyr), well above theoretical expectations. We summarize the available
data to help constrain the value of the critical Rossby number, and we identify
a new signature of the long-period detection edge in recent measurements from
the Kepler mission.


  A broadcast on a nontrivial connected graph G=(V,E) is a function f from V(G)
to {0,1,...,diam(G)} such that f(v) does not exceed the eccentricity of v. The
cost of f is the sum of the function values. A broadcast f is dominating if
each vertex of G is at distance at most f(v) from a vertex v with positive
f(v).
  We use properties of minimal dominating broadcasts to define the concept of
an irredundant broadcast on G. We determine conditions under which an
irredundant broadcast is maximal irredundant. Denoting the minimum costs of
dominating and maximal irredundant broadcasts by gamma_{b}(G) and ir_{b}(G)
respectively, the definitions imply that ir_{b}(G) is bounded above by
gamma_{b}(G) for all graphs. We show that gamma_{b} in turn is bounded above by
(5/4)ir_{b}(G) for all graphs G.
  We also briefly consider the upper broadcast number Gamma_{b}(G) and upper
irredundant broadcast number IR_{b}(G), and illustrate that the ratio IR_{b} to
Gamma_{b} is unbounded for general graphs.


  A Friedmann-Robertson-Walker cosmological model dominated by tachyonic --
faster-than-light -- dark matter can exhibit features similar to those of a
standard dark energy/dark matter or $Lambda$CDM model. It can undergo expansion
which decelerates to a minimum rate, passes through a "cosmic jerk," then
accelerates. But some features of a tachyon-dominated model are sufficiently
distinct from those of the standard model that the two possibilities might be
distinguished observationally. As a demonstration of concept, the
distance-redshift relation of such a model is compared here with some
observations of Type Ia supernovae. Other measures of the third time derivative
of the cosmic scale factor -- the true cosmic jerk -- might be found to test a
tachyonic-dark-matter hypothesis.


  With our previous study, the Super-k algorithm, we have introduced a novel
way of piecewise-linear classification. While working on the Super-k algorithm,
we have found that there is a similar, and simpler way to explain for obtaining
a piecewise-linear classifier based on Voronoi tessellations. Replacing the
multidimensional voxelization and expectation-maximization stages of the
algorithm with a distance-based clustering algorithm, preferably k-means, works
as well as the prior approach. Since we are replacing the voxelization with the
clustering, we have found it meaningful to name the modified algorithm, with
respect to Super-k, as Supervised k Clusters or in short Super-klust. Similar
to the Super-k algorithm, the Super-klust algorithm covers data with a labeled
Voronoi tessellation, and uses resulting tessellation for classification.
According to the experimental results, the Super-klust algorithm has similar
performance characteristics with the Super-k algorithm.


  We show that the unique isoperimetric hypersurfaces in $\mathbb{R}^n$ with
density $r^p$ for $n \ge 3$ and $p>0$ are spheres that pass through the origin.


  We consider the class of counting problems,i.e. functions in $\#$P, which are
self reducible, and have easy decision version, i.e. for every input it is easy
to decide if the value of the function $f(x)$ is zero. For example,
$\#$independent-sets of all sizes, is such a problem, and one of the hardest of
this class, since it is equivalent to $\#$SAT under multiplicative
approximation preserving reductions.
  Using these two powerful properties, self reducibility and easy decision, we
prove that all problems/ functions $f$ in this class can be approximated in
probabilistic polynomial time within an absolute exponential error
$\epsilon\cdot 2^{n'}, \forall\epsilon>0$, which for many of those problems
(when $n'=n+$constant) implies additive approximation to the fraction
$f(x)/2^n$. (Where $n'$ is the amount of non-determinism of some associated
NPTM).
  Moreover we show that for all these problems we can have multiplicative error
to the value $f(x)$, of any desired accuracy (i.e. a RAS), in time of order
$2^{2n'/3}poly(n)$, which is strictly smaller than exhaustive search. We also
show that $f(x)<g(x)$ can be decided deterministically in time $g(x)poly(n),
\forall g$.
  Finally we show that the Circuit Acceptance Probability Problem, which is
related to derandomization and circuit lower bounds, can be solved with high
probability and in polynomial time, for the family of all circuits for which
the problems of counting either satisfying or unsatisfying assignments belong
to TotP (which is the Karp-closure of self reducible problems with easy
decision version).


  Given an environment (e.g., a simulator) for evaluating samples in a
specified design space and a set of weighted evaluation metrics -- one can use
Theta-Resonance, a single-step Markov Decision Process (MDP), to train an
intelligent agent producing progressively more optimal samples. In
Theta-Resonance, a neural network consumes a constant input tensor and produces
a policy as a set of conditional probability density functions (PDFs) for
sampling each design dimension. We specialize existing policy gradient
algorithms in deep reinforcement learning (D-RL) in order to use evaluation
feedback (in terms of cost, penalty or reward) to update our policy network
with robust algorithmic stability and minimal design evaluations. We study
multiple neural architectures (for our policy network) within the context of a
simple SoC design space and propose a method of constructing synthetic space
exploration problems to compare and improve design space exploration (DSE)
algorithms. Although we only present categorical design spaces, we also outline
how to use Theta-Resonance in order to explore continuous and mixed
continuous-discrete design spaces.


  We investigate the impact of unparticle physics on the annihilation of relic
neutrinos with the neutrinos identified as primary source of ultra high energy
(UHE) cosmic ray events, producing a cascade of photons and charged particles.
We compute the contribution of the unparticle exchange to the cross-sections
$\nu \bar\nu\to\gamma \gamma$ and $\nu \bar\nu\to f \bar f$ scattering. We
estimate the neutrino photon decoupling temperature from the reaction rate of
$\nu \bar\nu\to\gamma \gamma$. We find that inclusion of unparticles can in
fact account for the flux of UHE cosmic rays and can also result in the
lowering of neutrino - photon decoupling temperature below the QCD phase
transition for unparticle physics parameters in a certain range. We calculate
the mean free path of these high energy neutrinos annihilating themselves with
the relic neutrinos to produce vector and tensor unparticles.


  We study the Chern-Ricci flow, an evolution equation of Hermitian metrics, on
a family of Oeljeklaus-Toma (OT-) manifolds which are non-K\"{a}hler compact
complex manifolds with negative Kodaira dimension. We prove that, after an
initial conformal change, the flow converges, in the Gromov-Hausdorff sense, to
a torus with a flat Riemannian metric determined by the OT-manifolds
themselves.


  A model is proposed to demonstrate that classical general relativity can
emerge from loop quantum gravity, in a relational description of gravitational
field in terms of coordinates given by matter. Local Dirac observables and
coherent states are defined to explore physical content of the model.
Expectation values of commutators between the observables for the coherent
states recover the four-dimensional diffeomorphism algebra and the large-scale
dynamics of the gravitational field relative to the matter coordinates. Both
results conform with general relativity up to calculable corrections near
singularities.


  Despite of achieving great success in real-world applications, Deep
Reinforcement Learning (DRL) is still suffering from three critical issues,
i.e., data efficiency, lack of the interpretability and transferability. Recent
research shows that embedding symbolic knowledge into DRL is promising in
addressing those challenges. Inspired by this, we introduce a novel deep
reinforcement learning framework with symbolic options. Our framework features
a loop training procedure, which enables guiding the improvement of policy by
planning with planning models (including action models and hierarchical task
network models) and symbolic options learned from interactive trajectories
automatically. The learned symbolic options alleviate the dense requirement of
expert domain knowledge and provide inherent interpretability of policies.
Moreover, the transferability and data efficiency can be further improved by
planning with the symbolic planning models. To validate the effectiveness of
our framework, we conduct experiments on two domains, Montezuma's Revenge and
Office World, respectively. The results demonstrate the comparable performance,
improved data efficiency, interpretability and transferability.


  Future colliders will probe the electroweak theory at energies much larger
than the gauge boson masses. Large double (DL) and single (SL) logarithmic
virtual electroweak Sudakov corrections lead to significant effects for
observable cross sections. Recently, leading and subleading universal
corrections for external fermions and transverse gauge boson lines were
resummed by employing the infrared evolution equation method. The results were
confirmed at the DL level by explicit two loop calculations with the physical
Standard Model (SM) fields. Also for longitudinal degrees of freedom the
approach was utilized for DL-corrections via the Goldstone boson equivalence
theorem. In all cases, the electroweak Sudakov logarithms exponentiate. In this
paper we extend the same approach to both Yukawa enhanced as well as subleading
Sudakov corrections to longitudinal gauge boson and Higgs production. We use
virtual contributions to splitting functions of the appropriate Goldstone
bosons in the high energy regime and find that all universal subleading terms
exponentiate. The approach is verified by employing a non-Abelian version of
Gribov's factorization theorem and by explicit comparison with existing one
loop calculations. As a side result, we obtain also all top-Yukawa enhanced
subleading logarithms for chiral fermion production at high energies to all
orders. In all cases, the size of the subleading contributions at the two loop
level is non-negligible in the context of precision measurements at future
linear colliders.


  Many standard model extensions that address the hierarchy problem contain
Dirac-fermion partners of the top quark, which are typically expected around
the TeV scale. Searches for these vector-like quarks mostly focus on their
decay into electroweak gauge bosons and Higgs plus a standard model quark. In
this article, backed by models of composite Higgs, we propose a set of
simplified scenarios, with effective Lagrangians and benchmarks, that include
more exotic decay channels, which modify the search strategies and affect the
bounds. Analysing several classes of underlying models, we show that exotic
decays are the norm and commonly appear with significant rates. All these
models contain light new scalars that couple to top partners with charge $5/3$,
$2/3$, and $-1/3$.


  Text-only and semi-supervised training based on audio-only data has gained
popularity recently due to the wide availability of unlabeled text and speech
data. In this work, we propose incorporating text-only and semi-supervised
training into an attention-based deliberation model. By incorporating text-only
data in training a bidirectional encoder representation from transformer (BERT)
for the deliberation text encoder, and large-scale text-to-speech and
audio-only utterances using joint acoustic and text decoder (JATD) and
semi-supervised training, we achieved 4%-12% WER reduction for various tasks
compared to the baseline deliberation. Compared to a state-of-the-art language
model (LM) rescoring method, the deliberation model reduces the Google Voice
Search WER by 11% relative. We show that the deliberation model also achieves a
positive human side-by-side evaluation compared to the state-of-the-art LM
rescorer with reasonable endpointer latencies.


  We propose a survey of Michel H\'enon works devoted to studying periodic
solutions of the well-known celestial mechanics problem -- restricted
three-body problem. The description of the main results obtained by H\'enon is
given in comparison with results of russian mathematician Alexander Bruno.
Finaly, a survey of H\'enon's works on Hill problem is given as well, and, more
over, the authors propose some generalization of Hill problem that makes
possible to provide the description of its families of periodic orbits in the
form of common network.


  We prove the explicit characterization of the so-called "best f" for degree
$p$ Artin-Schreier and degree $p$ Kummer extensions of Henselian valuation
rings in residue characteristic $p$. This characterization is mentioned briefly
in [Th16, Th18]. Existence of best $f$ is closely related to the defect of such
extensions and this characterization plays a crucial role in understanding
their intricate structure. We also treat degree $p$ Artin-Schreier defect
extensions of higher rank valuation rings, extending the results in [Th16], and
thus completing the study of degree $p$ extensions that are the building blocks
of the general theory.


  This letter uses the Block Maxima Extreme Value approach to quantify
catastrophic risk in international equity markets. Risk measures are generated
from a set threshold of the distribution of returns that avoids the pitfall of
using absolute returns for markets exhibiting diverging levels of risk. From an
application to leading markets, the letter finds that the Nikkei is more prone
to catastrophic risk than the FTSE and Dow Jones Indexes.


  Accurately detecting student behavior in classroom videos can aid in
analyzing their classroom performance and improving teaching effectiveness.
However, the current accuracy rate in behavior detection is low. To address
this challenge, we propose the Student Classroom Behavior Detection system
based on based on YOLOv7-BRA (YOLOv7 with Bi-level Routing Attention ). We
identified eight different behavior patterns, including standing, sitting,
speaking, listening, walking, raising hands, reading, and writing. We
constructed a dataset, which contained 11,248 labels and 4,001 images, with an
emphasis on the common behavior of raising hands in a classroom setting
(Student Classroom Behavior dataset, SCB-Dataset). To improve detection
accuracy, we added the biformer attention module to the YOLOv7 network.
Finally, we fused the results from YOLOv7 CrowdHuman, SlowFast, and DeepSort
models to obtain student classroom behavior data. We conducted experiments on
the SCB-Dataset, and YOLOv7-BRA achieved an<EMAIL_ADDRESS>of 87.1%, resulting in a
2.2% improvement over previous results. Our SCB-dataset can be downloaded from:
https://github.com/Whiffe/SCB-datase


  We have searched for HI 21cm absorption toward the two brightest radio AGN at
high redshift, J0924--2201 at $z = 5.20$, and J0913+5919 at $z=5.11$, using the
Giant Meter Wave Radio Telescope (GMRT). These data set a 3$\sigma$ upper limit
to absorption of $< 30%$ at 40 km s$^{-1}$ resolution for the 30 mJy source
J0913+5919, and $< 3%$ for the 0.55 Jy source J0924--2201 at 20 km s$^{-1}$
resolution. For J0924--2201, limits to broader lines at the few percent level
are set by residual spectral baseline structure. For J0924--2201 the column
density limit per 20 km s $^{-1}$ channel is: N(HI) $< 2.2\times 10^{18} \rm
T_s$ cm$^{-2}$ over a velocity range of -700 km s$^{-1}$ to $+1180$ km s$^{-1}$
centered on the galaxy redshift determined through CO emission, assuming a
covering factor of one. For J0913+5919 the column density limit per 40 km
s$^{-1}$ channel is: N(HI) $< 2.2\times 10^{19} \rm T_s$ cm$^{-2}$ within $\pm
2400$ km s$^{-1}$ of the optical redshift. These data rule out any cool, high
column density HI clouds within roughly $\pm 1000$ km s$^{-1}$ of the galaxies,
as are often seen in Compact Steep Spectrum radio AGN, or clouds that might
correspond to residual gas left over from cosmic reionization.


  In [B. Binz, A. Vishwanath and V. Aji, Phys. Rev. Lett. 96, 207202 (2006)], a
magnetic structure that breaks time reversal symmetry in the absence of net
magnetization was proposed as an explanation for the high pressure "partially
ordered" state of MnSi. Here we make explicit the anomalous magneto-transport
properties of such a state: a magnetoresistivity which is linear and a Hall
conductance which is quadratic in the applied magnetic field. Field cooling
procedures for obtaining single domain samples are discussed. The anomalous
effects are elaborated in the case of three geometries chosen to produce
experimentally unambiguous signals of this unusual magnetic state; e.g., it is
predicted that a field in z-direction induces an anisotropy in the x-y plane.
Another geometry leads to a Hall voltage parallel to the magnetic field.


  An electron beam may be used to generate bremsstrahlung photons that go on to
create photoneutrons within metals. This serves as a low-energy neutron source
for irradiation experiments [1-3]. In this article, we present simulation
results for optimizing photoneutron yield for a 10-MeV electron beam on
tantalum foil and erbium deuteride (ErD$_3$). The thickness of the metal layers
was varied. A tantalum foil thickness of 1.5 mm resulted in the most photons
reaching the second metal layer. When a second metal layer of ErD$_3$ was
included, the photoneutron yield increased with the thickness of the secondary
layer. When the electron beam was directly incident upon a layer of ErD$_3$,
the photoneutron yield did not differ significantly from the yield when a layer
of tantalum was included. The directional photoneutron yield reached a maximum
level when the thickness of the ErD$_3$ layer was around 12 cm. About 1 neutron
was generated per $10^4$ source electrons. When using a 2-mA beam current, it
is possible to generate up to $10^{ 12}$ neutrons per second, making this
combination a relatively-inexpensive neutron generator.


  In the last decade, a combination of high sensitivity, high spatial
resolution observations and of coordinated multi-wavelength surveys has
revolutionized our view of extra-galactic black hole (BH) astrophysics. We now
know that supermassive black holes reside in the nuclei of almost every galaxy,
grow over cosmological times by accreting matter, interact and merge with each
other, and in the process liberate enormous amounts of energy that influence
dramatically the evolution of the surrounding gas and stars, providing a
powerful self-regulatory mechanism for galaxy formation. The different
energetic phenomena associated to growing black holes and Active Galactic
Nuclei (AGN), their cosmological evolution and the observational techniques
used to unveil them, are the subject of this chapter. In particular, I will
focus my attention on the connection between the theory of high-energy
astrophysical processes giving rise to the observed emission in AGN, the
observable imprints they leave at different wavelengths, and the methods used
to uncover them in a statistically robust way. I will show how such a combined
effort of theorists and observers have led us to unveil most of the SMBH growth
over a large fraction of the age of the Universe, but that nagging
uncertainties remain, preventing us from fully understating the exact role of
black holes in the complex process of galaxy and large-scale structure
formation, assembly and evolution.


  We investigate mild solutions for stochastic evolution equations driven by a
fractional Brownian motion (fBm) with Hurst parameter H in (1/3, 1/2] in
infinite-dimensional Banach spaces. Using elements from rough paths theory we
introduce an appropriate integral with respect to the fBm. This allows us to
solve pathwise our stochastic evolution equation in a suitable function space.


  We have investigated the magnetic properties of highly anisotropic layered
ferromagnetic semiconductor CrI$_3$ in presence of hydrostatic pressure ($P$).
At ambient pressure, magnetization exhibits a clear anomaly below 212 K along
with a thermal hysteresis over a wide temperature range (212-180 K), where a
first-order structural transition is observed. CrI$_3$ undergoes a second-order
ferromagnetic-paramagnetic phase transition with Curie temperature $T_C$=60.4
K. With application of pressure, the transition becomes sharper and $T_C$ is
found to increase from 60.4 to 64.9 K as $P$ increases from 0 to 1.0 GPa. $T_C$
increases with $P$ in a sublinear fashion. The thermal hysteresis in
magnetization and the increase of $T_C$ with pressure suggest that the spin and
lattice degrees of freedom are coupled. The observed increase in $T_C$ has been
explained on the basis of change in inter-layer coupling and Cr-I-Cr bond angle
with pressure.


  A previous short analysis of the seesaw mechanism, based on quark-lepton
symmetry, experimental data and hierarchical neutrino spectrum, is enlarged to
include small but not zero U_{e3}, inverted mass hierarchy, and the qualitative
effect of Majorana phases. The structure of the heavy neutrino mass matrix
obtained in several cases is discussed. We find two leading forms for this
matrix. One is diagonal and stands at the unification scale or above. The other
is off-diagonal and stands at the intermediate scale.


  The newly synthesized strontium doped RNiO$_2$ (R=Nd, La) superconductors
have stimulated extensive interests in understanding their pairing mechanism
and pairing nature. Here we study the pairing mechanism in this family from a
two-orbital model comprising the Ni- $3d_{x^2-y^2}$- and $3d_{xy}$- orbitals,
equipped with extended Hubbard interactions and induced low-energy effective
superexchange interactions. We then study the pairing symmetry in this system
by using large scale variational Monte Carlo approach. Our results yield the
intraorbital $d_{x^2-y^2}$-wave singlet pairing as the leading pairing symmetry
in the nickelates, which is analogous to the cuprates. However, there exist two
important differences between the physical properties of the two families due
to the fact that at the low Sr-doping regime, while the Ni-$3d_{x^2-y^2}$
orbitals remain half-filled and singly-occupied to form a Mott-insulating
background, the Ni-$3d_{xy}$ orbitals accommodate nearly all the extra doped
holes, which move freely on this background. The first difference lies in the
single-particle aspect: while the $3d_{x^2-y^2}$ degree of freedom remains Mott
insulating with spectra weight pinned down at zero at low dopings, the
$3d_{xy}$ one behaves as Fermi liquid with spectra weight near 1. The second
difference lies in the pairing aspect: while the huge
intra-$3d_{x^2-y^2}$-orbital pairing gap is actually a pseudo gap which has
nothing to do with the SC, the small intra-$3d_{xy}$-orbital pairing gap serves
as the true superconducting pairing gap, which is related to the $T_c$ via the
BCS relation. Both differences can be verified by the angle-resolved
photo-emission spectrum.


  The equation of state (EoS) of dark energy plays an important role in the
evolution of the universe and arouses great interests in recent years. With the
progress on observational technique, precise constraint on the EoS of dark
energy becomes possible. In this paper, we reconstruct the EoS of dark energy
and cosmic expansion using Gaussian processes (GP) from the most up-to-date
Pantheon compilation of type Ia supernovae (SNe Ia), which consists of 1048
finely calibrated SNe Ia. The reconstructed EoS of dark energy has large
uncertainty due to its dependence on the second order derivative of the
construction. Adding the direct measurements of Hubble parameters $H(z)$ as an
additional constraint on the first order derivative can partially reduce the
uncertainty, but is still not precise enough to distinguish between evolving
and constant dark energy. Besides, the results heavily rely on the prior of
Hubble constant $H_0$. The $H_0$ value inferred from SNe+$H(z)$ without prior
is $H_0=70.5\pm 0.5~{\textrm{km}~\textrm{s}^{-1}~\textrm{Mpc}^{-1}}$. Moreover,
the matter density $\Omega_M$ has an unnegligible effect on the reconstruction
of dark energy. Therefore, more accurate determinations on $H_0$ and $\Omega_M$
are needed to tightly constrain the EoS of dark energy.


  We study the effects of gravitational lensing on the estimation of
non-Gaussianity from the bispectrum of the cosmic microwave background (CMB)
temperature anisotropies. We find that the effect of lensing on the bispectrum
may qualitatively be described as a smoothing of the acoustic features
analogous to the temperature power spectrum. In contrast to previous results,
for a Planck-like experiment which is cosmic-variance limited to L=2000, we
find that lensing causes no significant degradation of our ability to constrain
the non-Gaussianity amplitude fNL for both local and equilateral
configurations, provided that the biases due to the cross correlation between
the lensing potential and the integrated-Sachs-Wolfe (ISW) contribution to the
CMB temperature are adequately understood. With numerical simulations, we also
verify that low-order Taylor approximations to the lensed bispectrum and
ISW-lensing biases are accurate.


  When students are learning to use math in physics, one of the most important
ideas they need to learn is that equations are not just calculational tools;
they represent relationships between physical variables that change together
(covary). How much a change in one variable or parameter is associated with a
change in another depends on how they appear in the equation: their functional
dependence. Understanding this sort of relationship is rarely taught in
introductory mathematics classes, and students who have not yet learned to
blend conceptual ideas with mathematical symbols may not see the relevance and
power of this idea. We need to explicitly teach functional dependence as part
of our effort to help students to learn to use math productively in science.


  For a compact Riemannian manifold $(M, g_2)$ with constant $Q$-curvature of
dimension $n\geq 6$ satisfying nondegeneracy condition, we show that one can
construct many examples of constant $Q$-curvature manifolds by gluing
construction. We provide a general procedure of gluing together $(M,g_2)$ with
any compact manifold $(N, g_1)$ satisfying a geometric assumption. In
particular, we can prove that there exists a metric with constant $Q$-curvature
on the connected sum $N #M$.


  Given an ample line bundle $L$ over a projective $\mathbb{K}$-variety $X$,
with $\mathbb{K}$ a non-Archimedean field, we study limits of non-Archimedean
metrics on $L$ associated to submultiplicative sequences of norms on the graded
pieces of the section ring $R(X,L)$. We show that in a rather general case, the
corresponding asymptotic Fubini-Study operator yields a one-to-one
correspondence between equivalence classes of bounded graded norms and bounded
plurisubharmonic metrics that are regularizable from below. This generalizes
results of Boucksom-Jonsson where this problem has been studied in the
trivially valued case.


  We show that Voevodsky's univalence axiom for intensional type theory is
valid in categories of simplicial presheaves on elegant Reedy categories. In
addition to diagrams on inverse categories, as considered in previous work of
the author, this includes bisimplicial sets and $\Theta_n$-spaces. This has
potential applications to the study of homotopical models for higher
categories.


  In this paper, we extend the calculation of the atmospheric neutrino
flux~\cite{hkkm2004,hkkms2006,hkkm2011} to the sites in polar and tropical
regions. In our earliest full 3D-calculation~\cite{hkkm2004}, we used
DPMJET-III~\cite{dpm} for the hadronic interaction model above 5~GeV, and
NUCRIN~\cite{nucrin} below 5~GeV. We modified DPMJET-III as in
Ref.~\cite{hkkms2006} to reproduce the experimental muon spectra better, mainly
using the data observed by BESS group~\cite{BESSTeVpHemu}. In a recent
work~\cite{hkkm2011}, we introduced JAM interaction model for the low energy
hadronic interactions. JAM is a nuclear interaction model developed with PHITS
(Particle and Heavy-Ion Transport code System)~\cite{phits}. In
Ref.~\cite{hkkm2011}, we could reproduce the observed muon flux at the low
energies at balloon altitude with DPMJET-III above 32 GeV and JAM below that
better than the combination of DPMJET-III above 5~GeV and NUCRIN below that.
Besides the interaction model, we have also improved the calculation scheme
according to the increase of available computational power, such as the
"virtual detector correction" introduced in Ref.~\cite{hkkms2006} and the
optimization of it in Ref.~\cite{hkkm2011}. The statistics of the Monte Carlo
simulation is also improved at every step of the work.


  We explore the evolution of wave-function statistics on a finite Bethe
lattice (Cayley tree) from the central site ("root") to the boundary
("leaves"). We show that the eigenfunction moments $P_q=N
\left<|\psi|^{2q}(i)\right>$ exhibit a multifractal scaling $P_q\propto
N^{-\tau_q}$ with the volume (number of sites) $N$ at $N\to\infty$. The
multifractality spectrum $\tau_q$ depends on the strength of disorder and on
the parameter $s$ characterizing the position of the observation point $i$ on
the lattice. Specifically, $s= r/R$, where $r$ is the distance from the
observation point to the root, and $R$ is the "radius" of the lattice. We
demonstrate that the exponents $\tau_q$ depend linearly on $s$ and determine
the evolution of the spectrum with increasing disorder, from delocalized to the
localized phase. Analytical results are obtained for the $n$-orbital model with
$n \gg 1$ that can be mapped onto a supersymmetric $\sigma$ model. These
results are supported by numerical simulations (exact diagonalization) of the
conventional ($n=1$) Anderson tight-binding model.


  The most debated status of the wave function of Quantum Mechanics is
discussed in the light of the epistemological vs ontological opposition.


  The impulsive phase of solar flares is a time of rapid energy deposition and
heating in the lower solar atmosphere, leading to changes in the temperature
and density structure of the region. We use an O V density diagnostic formed of
the 192 to 248 line ratio, provided by Hinode EIS, to determine the density of
flare footpoint plasma, at O V formation temperatures of 250,000 K, giving a
constraint on the properties of the heated transition region. Hinode EIS
rasters from 2 small flare events in December 2007 were used. Raster images
were co-aligned to identify and establish the footpoint pixels,
multiple-component Gaussian line fitting of the spectra was carried out to
isolate the diagnostic pair, and the density was calculated for several
footpoint areas. The assumptions of equilibrium ionization and optically thin
radiation for the O V lines were found to be acceptable. Properties of the
electron distribution, for one event, were deduced from earlier RHESSI hard
X-ray observations and used to calculate the plasma heating rate, delivered by
an electron beam adopting collisional thick-target assumptions, for 2 model
atmospheres. Electron number densities of at least log n = 12.3 cm-3 were
measured during the flare impulsive phase, far higher than previously expected.
For one footpoint, the radiative loss rate for this plasma was found to exceed
that which can be delivered by an electron beam implied by the RHESSI data.
However, when assuming a completely ionised target atmosphere the heating rate
exceeded the losses. A chromospheric thickness of 70-700 km was found to be
required to balance a conductive input to the O V-emitting region with
radiative losses. The analysis shows that for heating by collisional electrons,
it is difficult, or impossible to raise the temperature of the chromosphere to
explain the observed densities without assuming a completely ionised
atmosphere.


  Each finite algebra $\mathbf A$ induces a lattice~$\mathbf L_{\mathbf A}$ via
the quasi-order~$\to$ on the finite members of the variety generated
by~$\mathbf A$, where $\mathbf B \to \mathbf C$ if there exists a homomorphism
from $\mathbf B$ to~$\mathbf C$. In this paper, we introduce the question:
`Which lattices arise as the homomorphism lattice $\mathbf L_{\mathbf A}$
induced by a finite algebra $\mathbf A$?' Our main result is that each finite
distributive lattice arises as~$\mathbf L_{\mathbf Q}$, for some quasi-primal
algebra~$\mathbf Q$. We also obtain representations of some other classes of
lattices as homomorphism lattices, including all finite partition lattices, all
finite subspace lattices and all lattices of the form $\mathbf L\oplus \mathbf
1$, where $\mathbf L$ is an interval in the subgroup lattice of a finite group.


  In this paper, by establishing a new characterization of the notion of upper
semi-continuity of multi-valued mappings in generalized Banach spaces, we prove
some Perov type fixed point theorems for multi-valued mappings with closed
graphs. Moreover, we derive some Krasnoselskii's fixe point results for
multi-valued mappings in generalized Banach spaces. Our results are applied to
a large class of nonlinear inclusions systems.


  A snap-stabilizing protocol, starting from any configuration, always behaves
according to its specification. In this paper, we present a snap-stabilizing
protocol to solve the message forwarding problem in a message-switched network.
In this problem, we must manage resources of the system to deliver messages to
any processor of the network. In this purpose, we use information given by a
routing algorithm. By the context of stabilization (in particular, the system
starts in an arbitrary configuration), this information can be corrupted. So,
the existence of a snap-stabilizing protocol for the message forwarding problem
implies that we can ask the system to begin forwarding messages even if routing
information are initially corrupted. In this paper, we propose two
snap-stabilizing algorithms (in the state model) for the following
specification of the problem: - Any message can be generated in a finite time.
- Any emitted message is delivered to its destination once and only once in a
finite time. This implies that our protocol can deliver any emitted message
regardless of the state of routing tables in the initial configuration. These
two algorithms are based on the previous work of [MS78]. Each algorithm needs a
particular method to be transform into a snap-stabilizing one but both of them
do not introduce a significant overcost in memory or in time with respect to
algorithms of [MS78].


  When a magnetic field confines the carriers of a Fermi sea to their lowest
Landau level, electron-electron interactions are expected to play a significant
role in determining the electronic ground state. Graphite is known to host a
sequence of magnetic field-induced states driven by such interactions. Three
decades after their discovery, thermodynamic signatures of these instabilities
are still elusive. Here, we report the first detection of these transitions
with sound velocity. We find that the phase transition occurs in the vicinity
of a magnetic field at which at least one of the Landau levels cross the Fermi
energy. The evolution of elastic constant anomalies with temperature and
magnetic field draws a detailed phase diagram which shows that the ground state
evolves in a sequence of thermodynamic phase transitions.Our analysis indicates
that electron-electron interaction is not the sole driving force of these
transitions and that lattice degrees of freedom play an important role.


  We measure the covariance of the non-linear matter power spectrum from N-body
simulations using two methods. In the first case, the covariance of power is
estimated from the scatter over many random realizations of the density field.
In the second, we use a novel technique to measure the covariance matrix from
each simulation individually by re-weighting the density field with a carefully
chosen set of functions. The two methods agree at linear scales, but
unexpectedly they disagree substantially at increasingly non-linear scales.
Moreover, the covariance of non-linear power measured using the re-weightings
method changes with box size. The numerical results are consistent with an
explanation given in a companion paper, which argues that the cause of the
discrepancy is beat-coupling, in which products of Fourier modes separated by a
small wavevector couple by gravitational growth to the large-scale beat mode
between them. We calculate the information content of the non-linear power
spectrum (about the amplitude of the initial, linear power spectrum) using both
methods and confirm the result of a previous paper, that at translinear scales
the power spectrum contains little information over and above that in the
linear power spectrum, but that there is a marked increase in information at
non-linear scales. We suggest that, in real galaxy surveys, the covariance of
power at non-linear scales is likely to be dominated by beat-coupling to the
largest scales of the survey and that, as a result, only part of the
information potentially available at non-linear scales is actually measurable
from real galaxy surveys.


  Deep feedforward neural networks (DFNNs) are a powerful tool for functional
approximation. We describe flexible versions of generalized linear and
generalized linear mixed models incorporating basis functions formed by a DFNN.
The consideration of neural networks with random effects is not widely used in
the literature, perhaps because of the computational challenges of
incorporating subject specific parameters into already complex models.
Efficient computational methods for high-dimensional Bayesian inference are
developed using Gaussian variational approximation, with a parsimonious but
flexible factor parametrization of the covariance matrix. We implement natural
gradient methods for the optimization, exploiting the factor structure of the
variational covariance matrix in computation of the natural gradient. Our
flexible DFNN models and Bayesian inference approach lead to a regression and
classification method that has a high prediction accuracy, and is able to
quantify the prediction uncertainty in a principled and convenient way. We also
describe how to perform variable selection in our deep learning method. The
proposed methods are illustrated in a wide range of simulated and real-data
examples, and the results compare favourably to a state of the art flexible
regression and classification method in the statistical literature, the
Bayesian additive regression trees (BART) method. User-friendly software
packages in Matlab, R and Python implementing the proposed methods are
available at https://github.com/VBayesLab


  We demonstrate on the basis of ab initio simulations how passivated
semiconductor surfaces can be exploited to study bulklike interaction
properties and wave functions of magnetic impurities on the atomic scale with
conventional and spin-polarized scanning tunneling microscopy. By applying our
approach to the case of $3d$ transition metal impurities close to the
H/Si$(111)$ surface, we show exemplarily that their wave functions in Si are
less extended than for Mn in GaAs, thus obstructing ferromagnetism in Si.
Finally, we discuss possible applications of this method to other dilute
magnetic semiconductors.


  Superinsulators are dual superconductors, dissipationless magnetic monopole
condensates with infinite resistance. The long-distance field theory of such
states of matter is QED with dynamical matter coupled via a compact BF
topological interaction. We will quantize the 2D model in the functional
Schr\"odinger picture and show how strong entanglement of charges leads to a
phase which is a single-color, asymptotically free version of QCD in which the
infinite resistance is caused by the linear confinement of charges. This phase
has been experimentally detected in TiN, NbTiN and InO thin films, including
signatures of asymptotically free behaviour and of the dual, electric Meissner
effect. This makes superinsulators a ``toy realization" of QCD with Cooper
pairs playing the role of quarks.


  The theory of belief functions is widely used for data from multiple sources.
Different evidence combination rules have been proposed in this framework
according to the properties of the sources to combine. However, most of these
combination rules are not efficient when there are a large number of sources.
This is due to either the complexity or the existence of an absorbing element
such as the total conflict mass function for the conjunctive based rules when
applied on unreliable evidence. In this paper, based on the assumption that the
majority of sources are reliable, a combination rule for a large number of
sources is proposed using a simple idea: the more common ideas the sources
share, the more reliable these sources are supposed to be. This rule is
adaptable for aggregating a large number of sources which may not all be
reliable. It will keep the spirit of the conjunctive rule to reinforce the
belief on the focal elements with which the sources are in agreement. The mass
on the emptyset will be kept as an indicator of the conflict. The proposed
rule, called LNS-CR (Conjunctive combinationRule for a Large Number of
Sources), is evaluated on synthetic mass functions. The experimental results
verify that the rule can be effectively used to combine a large number of mass
functions and to elicit the major opinion.


  The minimum energy, and, more generally, the minimum cost, to transmit one
bit of information has been recently derived for bursty communication when
information is available infrequently at random times at the transmitter.
Furthermore, it has been shown that even if the receiver is constrained to
sample only a fraction $\rho\in (0,1]$ of the channel outputs, there is no
capacity penalty. That is, for any strictly positive sampling rate $\rho>0$,
the asynchronous capacity per unit cost is the same as under full sampling,
i.e., when $\rho=1$. Moreover, there is no penalty in terms of decoding delay.
  The above results are asymptotic in nature, considering the limit as the
number $B$ of bits to be transmitted tends to infinity, while the sampling rate
$\rho$ remains fixed. A natural question is then whether the sampling rate
$\rho(B)$ can drop to zero without introducing a capacity (or delay) penalty
compared to full sampling. We answer this question affirmatively. The main
result of this paper is an essentially tight characterization of the minimum
sampling rate. We show that any sampling rate that grows at least as fast as
$\omega(1/B)$ is achievable, while any sampling rate smaller than $o(1/B)$
yields unreliable communication. The key ingredient in our improved
achievability result is a new, multi-phase adaptive sampling scheme for
locating transient changes, which we believe may be of independent interest for
certain change-point detection problems.


  We argue that extensions of the Standard Model (SM) with a warped extra
dimension, which successfully address the hierarchy and flavor problems of
elementary particle physics, can provide an elegant explanation of the 750 GeV
diphoton excess recently reported by ATLAS and CMS. A gauge-singlet bulk scalar
with ${\cal O}(1)$ couplings to fermions is identified as the new resonance
$S$, and the vector-like Kaluza-Klein excitations of the SM quarks and leptons
mediate its loop-induced couplings to photons and gluons. The electroweak gauge
symmetry almost unambiguously dictates the bulk matter content and hence the
hierarchies of the $S\to \gamma\gamma$, $WW$, $ZZ$, $Z\gamma$, $t\bar t$ and
dijet decay rates. We find that the $S\to Z\gamma$ decay mode is strongly
suppressed, such that $\mbox{Br}(S\to
Z\gamma)/\mbox{Br}(S\to\gamma\gamma)<0.1$. The hierarchy problem for the new
scalar boson is solved in analogy with the Higgs boson by localizing it near
the infrared brane. The infinite sums over the Kaluza-Klein towers of fermion
states are finite and can be calculated in closed form with a remarkably simple
result. Reproducing the observed $pp\to S\to\gamma\gamma$ signal requires
Kaluza-Klein masses in the multi-TeV range, consistent with bounds from flavor
physics and electroweak precision observables.
  Useful side products of our analysis, which can be adapted to almost any
model for the diphoton resonance, are the calculation of the gluon-fusion
production cross section $\sigma(pp\to S)$ at NNLO in QCD, an exact expression
for the inclusive $S\to gg$ decay rate at N$^3$LO, a study of the $S\to t\bar t
h$ three-body decay and a phenomenological analysis of portal couplings
connecting $S$ with the Higgs field.


  We elucidate connections between four models in statistical physics and
probability theory: (1) the toric code model of Kitaev, (2) the uniform
eight-vertex model, (3) random walk on a hypercube, and (4) a classical Ising
model with four-body interaction. As a consequence of our analysis (and of the
GKS-inequalities for the Ising model) we obtain correlation inequalities for
the toric code model and the uniform eight-vertex model.


  We present a new code to evaluate thermoelectric and electronic transport
properties of extended systems with a maximally-localized Wannier function
basis set. The semiclassical Boltzmann transport equations for the homogeneous
infinite system are solved in the constant relaxation-time approximation and
band energies and band derivatives are obtained via Wannier interpolations.
Thanks to the exponential localization of the Wannier functions obtained, very
high accuracy in the Brillouin zone integrals can be achieved with very
moderate computational costs. Moreover, the analytical expression for the band
derivatives in the Wannier basis resolves any issues that may occur when
evaluating derivatives near band crossings. The code is tested on binary and
ternary skutterudites CoSb_3 and CoGe_{3/2}S_{3/2}.


  Given an Artin group $A_\Gamma$, a common strategy in the study of $A_\Gamma$
is the reduction to parabolic subgroups whose defining graphs have small
diameter, i.e. showing that $A_\Gamma$ has a specific property if and only if
all "small" parabolic subgroups of $A_\Gamma$ have this property. Since "small"
parabolic subgroups are the puzzle pieces of $A_\Gamma$ one needs to study
their behavior, in particular their intersections. The conjecture we address
here says that the class of parabolic subgroups of $A_\Gamma$ is closed under
intersection. Under the assumption that intersections of parabolic subgroups in
complete Artin groups are parabolic, we show that the intersection of a
complete parabolic subgroup with an arbitrary parabolic subgroup is parabolic.
Further, we connect the intersection behavior of complete parabolic subgroups
of $A_\Gamma$ to fixed point properties and to automatic continuity of
$A_\Gamma$ using Bass-Serre theory and a generalization of the Deligne complex.


  We report on the first observation of Bragg scattering of an ultracold $^6$Li
Fermi gas. We demonstrate a Ramsey-type matter-wave interferometer based on
Bragg diffraction and find robust signatures of persistent matter wave
coherences using an echo pulse sequence. Because of the Pauli principle, the
diffracted fermions oscillate nearly unperturbed in the trapping potential for
long times beyond 2 s. This suggests extremely long coherence times. On these
timescales, only the presence of a $^{87}$Rb cloud seems sufficient to induce
noticeable perturbations.


  Community detection in graphs, data clustering, and local pattern mining are
three mature fields of data mining and machine learning. In recent years,
attributed subgraph mining is emerging as a new powerful data mining task in
the intersection of these areas. Given a graph and a set of attributes for each
vertex, attributed subgraph mining aims to find cohesive subgraphs for which (a
subset of) the attribute values has exceptional values in some sense. While
research on this task can borrow from the three abovementioned fields, the
principled integration of graph and attribute data poses two challenges: the
definition of a pattern language that is intuitive and lends itself to
efficient search strategies, and the formalization of the interestingness of
such patterns. We propose an integrated solution to both of these challenges.
The proposed pattern language improves upon prior work in being both highly
flexible and intuitive. We show how an effective and principled algorithm can
enumerate patterns of this language. The proposed approach for quantifying
interestingness of patterns of this language is rooted in information theory,
and is able to account for prior knowledge on the data. Prior work typically
quantifies interestingness based on the cohesion of the subgraph and for the
exceptionality of its attributes separately, combining these in a parametrized
trade-off. Instead, in our proposal this trade-off is implicitly handled in a
principled, parameter-free manner. Extensive empirical results confirm the
proposed pattern syntax is intuitive, and the interestingness measure aligns
well with actual subjective interestingness.


  We report the first observations of an astronomical object using a
superconducting tunnel junction (STJ) device, a pixel detector with intrinsic
energy resolution in the optical wavelength range. The Crab pulsar was observed
using a 6 times 6 array of Tantalum STJs at the 4.2-m William Herschel
Telescope on La Palma. Each array element provides photon counting capability
recording up to ~ 10^3 photons per pix per s with an arrival time accuracy of
about 5 microsecond, and providing a wavelength resolution of about 100 nm. We
derive a photometrically resolved light curve which, however, shows no
significant colour index variations with pulsar phase.


  The recently identified Circinus Galaxy is the nearest (about 4 Mpc) Seyfert
2 galaxy known and we now demonstrate to be one of the best laboratories for
studying the effects of nuclear activity on the surrounding environment. Here
we present new imaging Fabry-Perot observations of Circinus which confirm the
existence of an ionization cone in this object but also show for the first time
a complex of ionized filaments extending radially from the nucleus out to
distances of 1 kpc. Arcs suggestive of bow shocks are observed at the terminus
of some of these filamentary structures. Most spectacular of all, one of the
structures appears to be a scaled-up version of a Herbig-Haro jet. The velocity
field of the filaments confirms that they represent material expelled from the
nucleus (possibly in the form of `bullets') or entrained in a wide-angle wind
roughly aligned with the polar axis of the galaxy. The motions observed across
the ionization cone are highly supersonic, so high-velocity shocks are likely
to contribute to the ionization of the line emitting gas. However, it is not
clear at present whether shock ionization dominates over photoionization by the
Seyfert 2 nucleus. Extrapolation of the filaments to smaller radii comes to
within 1 arcsec (about 20 pc) of the infrared nucleus, therefore suggesting a
AGN or nuclear starburst origin to these features. The complex of radial
filaments detected in the Circinus galaxy is unique among active galaxies. The
frequency of such events is unknown since only a handful of galaxies have been
observed at the sensitivity level of our present observations. The event in the
Circinus galaxy may represent a relatively common evolutionary phase in the
lives of gas-rich active galaxies during which the dusty cocoon surrounding the
nucleus is expelled by the action of jet or wind phenomena.


  We introduce the (q,2)-Fock space over a given Hilbert space, calculate the
explicit form of a product of the creation and annihilation operators acting on
the vacuum vector, demonstrate that this explicit form involves a specific
subset of the set of all pair partitions, and provide a detailed
characterization of this subset.


  We report magnetic-field-induced first-order phase transitions in the
ferro-quadrupole (FQ) ordered state of PrTi2Al20, in which non-Kramers Pr3+
ions with two 4f electrons have a non-magnetic Gamma3 doublet ground state in
the cubic Td crystalline electric field. For magnetic fields along [111],
27Al-NMR and magnetization experiments reveal Qz \propto 3z2-r2 type FQ order
below 2 K independent of field strength. Magnetic fields along [001] or [110],
however, induce discontinuous switching of order parameters within the two
dimensional space spanned by Qz and Qx \propto x2-y2 at small field values less
than a few tesla. A symmetry-based theoretical analysis shows that the
transitions can be caused by competition between the magnetic Zeeman
interaction and anisotropy in the quadrupole-quadrupole interactions, if the
latter dominates over the former in low fields and vice versa in high fields.
Furthermore, striking violation of proportionality between NMR Knight shift and
magnetic susceptibility is observed in the symmetry-broken FQ phases,
indicating significant influence of FQ order on the hybridization between
conduction and f electrons, which in turn mediates the RKKY-type quadrupole
interaction causing the FQ order. This feedback effect may be a specific
feature of quadrupole orders not commonly observed in magnetic phase
transitions and play a key role for inducing the discontinuous transitions.


  In this paper using the third-order WKB approximation, a numerical method
devised by Schutz, Will and Iyer, we investigate the quasinormal frequencies of
the scalar field in the background of five-dimensional Lovelock black hole. We
find that the ultraviolet correction to Einstein theory in the Lovelock theory
makes the scalar field decay more slowly and makes the scalar field oscillate
more quickly, and the cosmological constant makes the scalar field decay more
slowly and makes the scalar field oscillate more slowly in Lovelock black hole
backgroud. On the other hand we also find that quasinormal frequencies depend
very weakly on the angular quantum number $l$.


  We study the simple random walk dynamics on an annealed version of a
Small-World Network (SWN) consisting of $N$ nodes. This is done by calculating
the mean number of distinct sites visited S(n) and the return probability
$P_{00}(t)$ as a function of the time $t$. $S(t)$ is a key quantity both from
the statistical physics point of view and especially for characterizing the
efficiency of the network connectedness. Our results for this quantity shows
features similar to the SWN with quenched disorder, but with a crossover time
that goes inversely proportianal to the probability $p$ of making a long range
jump instead of being proportional to $p^{-2}$ as in quenched case. We have
also carried out simulations on a modified annealed model where the crossover
time goes as $p^{-2}$ due to specific time dependent transition probabilities
and we present an approximate self-consistent solution to it.


  Federated learning (FL) is an emerging technique used to collaboratively
train a global machine learning model while keeping the data localized on the
user devices. The main obstacle to FL's practical implementation is the
Non-Independent and Identical (Non-IID) data distribution across users, which
slows convergence and degrades performance. To tackle this fundamental issue,
we propose a method (ComFed) that enhances the whole training process on both
the client and server sides. The key idea of ComFed is to simultaneously
utilize client-variance reduction techniques to facilitate server aggregation
and global adaptive update techniques to accelerate learning. Our experiments
on the Cifar-10 classification task show that ComFed can improve
state-of-the-art algorithms dedicated to Non-IID data.


  GJ 436b is a warm-- approximately 800 K--extrasolar planet that periodically
eclipses its low-mass (half the mass of the Sun) host star, and is one of the
few Neptune-mass planets that is amenable to detailed characterization.
Previous observations have indicated that its atmosphere has a methane-to-CO
ratio that is 100,000 times smaller than predicted by models for
hydrogen-dominated atmospheres at these temperatures. A recent study proposed
that this unusual chemistry could be explained if the planet's atmosphere is
significantly enhanced in elements heavier than H and He. In this study we
present complementary observations of GJ 436b's atmosphere obtained during
transit. Our observations indicate that the planet's transmission spectrum is
effectively featureless, ruling out cloud-free, hydrogen-dominated atmosphere
models with an extremely high significance of 48 sigma. The measured spectrum
is consistent with either a high cloud or haze layer located at a pressure of
approximately 1 mbar or with a relatively hydrogen-poor (three percent hydrogen
and helium mass fraction) atmospheric composition.


  In this article, for Banach left and right module actions, we will extend
some propositions from Lau and $\ddot{U}lger$ into general situations and we
establish the relationships between topological centers of module actions. We
also introduce the new concepts as $Lw^*w$-property and $Rw^*w$-property for
Banach $A-bimodule$ $B$ and we investigate the relations between them and
topological center of module actions. We have some applications in dual groups.


  Category-level object pose estimation involves estimating the 6D pose and the
3D metric size of objects from predetermined categories. While recent
approaches take categorical shape prior information as reference to improve
pose estimation accuracy, the single-stage network design and training manner
lead to sub-optimal performance since there are two distinct tasks in the
pipeline. In this paper, the advantage of two-stage pipeline over single-stage
design is discussed. To this end, we propose a two-stage deformation-and
registration pipeline called DR-Pose, which consists of completion-aided
deformation stage and scaled registration stage. The first stage uses a point
cloud completion method to generate unseen parts of target object, guiding
subsequent deformation on the shape prior. In the second stage, a novel
registration network is designed to extract pose-sensitive features and predict
the representation of object partial point cloud in canonical space based on
the deformation results from the first stage. DR-Pose produces superior results
to the state-of-the-art shape prior-based methods on both CAMERA25 and REAL275
benchmarks. Codes are available at https://github.com/Zray26/DR-Pose.git.


  The sensing matrix of a compressive system impacts the stability of the
associated sparse recovery problem. In this paper, we study the sensing matrix
of the modulated wideband converter, a recently proposed system for sub-Nyquist
sampling of analog sparse signals. Attempting to quantify the conditioning of
the converter sensing matrix with existing approaches leads to unreasonable
rate requirements, due to the relatively small size of this matrix. We propose
a new conditioning criterion, named the expected restricted isometry property,
and derive theoretical guarantees for the converter to satisfy this property.
We then show that applying these conditions to popular binary sequences, such
as maximal codes or Gold codes, leads to practical rate requirements.


  We investigate the generation rate of quantum gravity induced entanglement of
masses(QGEM) in setup with multiple quantum massive particles, among of which
only the gravity interaction due to the Newton potential is taken into account.
When the distance between any two adjacent Stern-Gerlach (SG) devices is fixed,
we consider all the possible configurations of the setup with the same number
of particles. In particular, we systemically analyze the case of particle
number n=4 and find that the prism setup with a massive particle at the center
is the most efficient setup for the entanglement generation. This result can be
extended to a system with multiple particles up to seven, where the
entanglement efficiency is also enhanced in comparison with the setup with
fewer particles. This work provides the strategy to construct the QGEM setup
with the best generation rate of entanglement.


  We prove new $L^p(\mathbb{R}^3)$ bounds on Stein's square function for
$p\geq3.25$. As an application, it improves the maximal Bochner-Riesz
conjecture to the same range of $p$.


  Spherical monogenics can be regarded as a basic tool for the study of
harmonic analysis of the Dirac operator in Euclidean space R^m. They play a
similar role as spherical harmonics do in case of harmonic analysis of the
Laplace operator on R^m. Fix the direct sum R^m = R^p x R^q. In this paper we
will study the decomposition of the space M_n(R^m;C_m) of spherical monogenics
of order n under the action of Spin(p) x Spin(q). As a result we obtain a
Spin(p) x Spin(q)-invariant orthonormal basis for M_n(R^m;C_m). In particular,
using the construction with p = 2 inductively, this yields a new orthonormal
basis for the space M_n(R^m;C_m).


  This is a brief survey of the known black hole solutions in the theories of
ghost-free bigravity and massive gravity. Various black holes exist in these
theories, in particular those supporting a massive graviton hair. However, it
seems that solutions which could be astrophysically relevant are the same as in
General Relativity, or very close to them. Therefore, the no-hair conjecture
essentially applies, and so it would be hard to detect the graviton mass by
observing black holes.


  LTEs uplink (UL) efficiency critically depends on how the interference across
different cells is controlled. The unique characteristics of LTEs modulation
and UL resource assignment poses considerable challenges in achieving this goal
because most LTE deployments have 1:1 frequency re-use, and the uplink
interference can vary considerably across successive time slots. In this work,
we propose LeAP, a measurement data driven machine learning paradigm for power
control to manage up-link interference in LTE. The data driven approach has the
inherent advantage that the solution adapts based on network traffic,
propagation and network topology, that is increasingly heterogeneous with
multiple cell-overlays. LeAP system design consists of the following
components: (i) design of user equipment (UE) measurement statistics that are
succinct, yet expressive enough to capture the network dynamics, and (ii)
design of two learning based algorithms that use the reported measurements to
set the power control parameters and optimize the network performance. LeAP is
standards compliant and can be implemented in centralized SON (self organized
networking) server resource (cloud). We perform extensive evaluations using
radio network plans from real LTE network operational in a major metro area in
United States. Our results show that, compared to existing approaches, LeAP
provides a 4.9x gain in the 20th percentile of user data rate, and 3.25x gain
in median data rate.


  The phase diagram of quantum electron bilayers in zero magnetic field is
obtained using density functional theory. For large electron densities the
system is in the liquid phase, while for smaller densities the liquid may
freeze (Wigner crystallization) into four different crystalline phases; the
lattice symmetry and the critical density depend on the the inter-layer
distance. The phase boundaries between different Wigner crystals consist of
both first and second order transitions, depending on the phases involved, and
join the freezing curve at three different triple points.


  Spectrum of the doubly heavy tetraquarks, $bb\bar q\bar q$, is studied in a
constituent quark model. Four-body problem is solved in a variational method
where the real scaling technique is used to identify resonant states above the
fall-apart decay thresholds. In addition to the two bound states that were
reported in the previous study we have found several narrow resonant states
above the $BB^*$ and $B^*B^*$ thresholds. Their structures are studied and are
interpreted by the quark dynamics. A narrow resonance with spin-parity
$J^P=1^+$ is found to be a mixed state of a compact tetraquark and a $B^*B^*$
scattering state. This is driven by a strong color Coulombic attraction between
the $bb$ quarks. Negative-parity excited resonances with $J^P=0^-$, $1^-$ and
$2^-$ form a triplet under the heavy-quark spin symmetry. It turns out that
they share a similar structure to the $\lambda$-mode of a singly heavy baryon
as a result of the strongly attractive correlation for the doubly heavy
diquark.


  In reaction to a previous critique(Opthof & Leydesdorff, 2010), the Center
for Science and Technology Studies (CWTS) in Leiden proposed to change their
old "crown" indicator in citation analysis into a new one. Waltman et al.
(2011)argue that this change does not affect rankings at various aggregated
levels. However, CWTS data is not publicly available for testing and criticism.
In this correspondence, we use previously published data of Van Raan (2006) to
address the pivotal issue of how the results of citation analysis correlate
with the results of peer review. A quality parameter based on peer review was
neither significantly correlated with the two parameters developed by the CWTS
in the past (CPP/JCSm or CPP/FCSm) nor with the more recently proposed h-index
(Hirsch, 2005). Given the high correlations between the old and new "crown"
indicators, one can expect that the lack of correlation with the peer-review
based quality indicator applies equally to the newly developed ones.


  Temporal Reasoning is one important functionality for vision intelligence. In
computer vision research community, temporal reasoning is usually studied in
the form of video classification, for which many state-of-the-art Neural
Network structures and dataset benchmarks are proposed in recent years,
especially 3D CNNs and Kinetics. However, some recent works found that current
video classification benchmarks contain strong biases towards static features,
thus cannot accurately reflect the temporal modeling ability. New video
classification benchmarks aiming to eliminate static biases are proposed, with
experiments on these new benchmarks showing that the current clip-based 3D CNNs
are outperformed by RNN structures and recent video transformers.
  In this paper, we find that 3D CNNs and their efficient depthwise variants,
when video-level sampling strategy is used, are actually able to beat RNNs and
recent vision transformers by significant margins on static-unbiased temporal
reasoning benchmarks. Further, we propose Temporal Fully Connected Block (TFC
Block), an efficient and effective component, which approximates fully
connected layers along temporal dimension to obtain video-level receptive
field, enhancing the spatiotemporal reasoning ability. With TFC blocks inserted
into Video-level 3D CNNs (V3D), our proposed TFCNets establish new
state-of-the-art results on synthetic temporal reasoning benchmark, CATER, and
real world static-unbiased dataset, Diving48, surpassing all previous methods.


  An effective two-dimensional two-band model for infinite-layer nickelates
consists of bands obtained from $d_{x^2-y^2}$ and $s$--like orbitals. We
investigate whether it could be mapped onto a single-band Hubbard model and the
filling of Hubbard bands. We find that both one-band physics and a
Kondo-lattice regime emerge from the same two-orbital model, depending on the
strength of electronic correlations and the filling of the itinerant $s$-band.
Next we investigate one-particle excitations by changing the screening. First,
for weak screening the strong correlations push electrons out of the $s$-band
so that the undoped nickelate is similar to a cuprate. Second, for strong
screening the $s$ and $d_{x^2-y^2}$ bands are both partly filled and weakly
couple. Particularly in this latter regime mapping to a one-band model gives
significant spectral weight transfer between the Hubbard subbands. Finally we
point out that the superconducting phases may have either $d$-wave or $s$-wave
symmetry.


  We introduce a new method for training generative adversarial networks by
applying the Wasserstein-2 metric proximal on the generators. The approach is
based on Wasserstein information geometry. It defines a parametrization
invariant natural gradient by pulling back optimal transport structures from
probability space to parameter space. We obtain easy-to-implement iterative
regularizers for the parameter updates of implicit deep generative models. Our
experiments demonstrate that this method improves the speed and stability of
training in terms of wall-clock time and Fr\'echet Inception Distance.


  Existing datasets available to address crucial problems, such as child
mortality and family planning discontinuation in developing countries, are not
ample for data-driven approaches. This is partly due to disjoint data
collection efforts employed across locations, times, and variations of
modalities. On the other hand, state-of-the-art methods for small data problem
are confined to image modalities. In this work, we proposed a data-level
linkage of disjoint surveys across Sub-Saharan African countries to improve
prediction performance of neonatal death and provide cross-domain
explainability.


  Modern inertial measurements units (IMUs) are small, cheap, energy efficient,
and widely employed in smart devices and mobile robots. Exploiting inertial
data for accurate and reliable pedestrian navigation supports is a key
component for emerging Internet-of-Things applications and services. Recently,
there has been a growing interest in applying deep neural networks (DNNs) to
motion sensing and location estimation. However, the lack of sufficient
labelled data for training and evaluating architecture benchmarks has limited
the adoption of DNNs in IMU-based tasks. In this paper, we present and release
the Oxford Inertial Odometry Dataset (OxIOD), a first-of-its-kind public
dataset for deep learning based inertial navigation research, with fine-grained
ground-truth on all sequences. Furthermore, to enable more efficient inference
at the edge, we propose a novel lightweight framework to learn and reconstruct
pedestrian trajectories from raw IMU data. Extensive experiments show the
effectiveness of our dataset and methods in achieving accurate data-driven
pedestrian inertial navigation on resource-constrained devices.


  Using a left multiplication defined on a right quaternionic Hilbert space, we
shall demonstrate that pure squeezed states can be defined with all the desired
properties on a right quaternionic Hilbert space. Further, we shall also
demonstrate squeezed states can be defined on the same Hilbert space, but the
noncommutativity of quaternions prevent us in getting the desired results.
However, we will show that if once considers the quaternionic slice wise
approach, then the desired properties can be obtained for quaternionic squeezed
states.