  The electronic states of manganese in p-type GaN are investigated using
photoluminescence (PL) and photoluminescence excitation (PLE) spectroscopies. A
series of sharp PL lines at 1.0 eV is observed in codoped GaN and attributed to
the intra d-shell transition 4T2(F)-4T1(F) of Mn4+ ions. PLE spectrum of the
Mn4+ [4T2(F)-4T1(F)] luminescence reveals intra center excitation processes via
the excited states of Mn4+ ions. PLE peaks observed at 1.79 and 2.33 eV are
attributed to the intra-d-shell 4T1(P)-4T1(F) and 4A2(F)-4T1(F) transitions of
Mn4+, respectively. In addition to the intra shell excitation processes, a
broad PLE band involving charge-transfer transition of the Mn4+/3+ deep level
is observed, which is well described by the Lucovsky model. As determined from
the onset of this PLE band, the position of the Mn4+/3+ deep level is 1.11 eV
above the valence band maximum, which is consistent with prior theory using ab
initio calculations. Our work indicates 4+ is the predominant oxidation state
of Mn ions in p-type GaN:Mn when the Fermi energy is lower than 1.11 eV above
the valence band maximum.


  Direct sampling from a Slater determinant is combined with an autoregressive
deep neural network as a Jastrow factor into a fully autoregressive
Slater-Jastrow ansatz for variational quantum Monte Carlo, which allows for
uncorrelated sampling. The elimination of the autocorrelation time leads to a
stochastic algorithm with provable cubic scaling (with a potentially large
prefactor), i.e. the number of operations for producing an uncorrelated sample
and for calculating the local energy scales like $\mathcal{O}(N_s^3)$ with the
number of orbitals $N_s$. The implementation is benchmarked on the
two-dimensional $t-V$ model of spinless fermions on the square lattice.


  This paper presents a new global patent map that represents all technological
categories, and a method to locate patent data of individual organizations and
technological fields on the global map. This overlay map technique may support
competitive intelligence and policy decision-making. The global patent map is
based on similarities in citing-to-cited relationships between categories of
theInternational Patent Classification (IPC) of European Patent Office (EPO)
patents from 2000 to 2006. This patent dataset, extracted from the PATSTAT
database, includes 760,000 patent records in 466 IPC-based categories. We
compare the global patent maps derived from this categorization to related
efforts of other global patent maps. The paper overlays nanotechnology-related
patenting activities of two companies and two different nanotechnology
subfields on the global patent map. The exercise shows the potential of patent
overlay maps to visualize technological areas and potentially support
decision-making. Furthermore, this study shows that IPC categories that are
similar to one another based on citing-to-cited patterns (and thus are close in
the global patent map) are not necessarily in the same hierarchical IPC branch,
thus revealing new relationships between technologies that are classified as
pertaining to different (and sometimes distant) subject areas in the IPC
scheme.


  Even though considerable attention has been given to the polarity of words
(positive and negative) and the creation of large polarity lexicons, research
in emotion analysis has had to rely on limited and small emotion lexicons. In
this paper we show how the combined strength and wisdom of the crowds can be
used to generate a large, high-quality, word-emotion and word-polarity
association lexicon quickly and inexpensively. We enumerate the challenges in
emotion annotation in a crowdsourcing scenario and propose solutions to address
them. Most notably, in addition to questions about emotions associated with
terms, we show how the inclusion of a word choice question can discourage
malicious data entry, help identify instances where the annotator may not be
familiar with the target term (allowing us to reject such annotations), and
help obtain annotations at sense level (rather than at word level). We
conducted experiments on how to formulate the emotion-annotation questions, and
show that asking if a term is associated with an emotion leads to markedly
higher inter-annotator agreement than that obtained by asking if a term evokes
an emotion.


  Scattering-based single-particle tracking (S-SPT) has opened new avenues for
highly sensitive label-free detection and characterization of nanoscopic
objects, making it particularly attractive for various analytical applications.
However, a long-standing issue hindering its widespread applicability is its
high technical demands on optical systems. The most promising solution entails
implementing on-chip light-scattering enhancement, but the existing
field-enhancement technology fails as their highly localized field is
insufficient to cover the three-dimensional trajectory of particles within the
interrogation time. Here, we present a straightforward and robust on-chip
microlens-based strategy for light-scattering enhancement, providing an
enhancement range ten times greater than that of near-field optical techniques.
These properties are attributed to the increased long-range optical fields and
complex composite interactions between two closely spaced structures. Thanks to
this strategy, we demonstrate that high-performance S-SPT can be achieved, for
the first time, under a conventional bright-field microscope with illumination
powers over 1,000 times lower than typically required. This significantly
reduces the technical demands of S-SPT, representing a significant step forward
in facilitating its practical application in biophotonics, biosensors,
diagnostics, and other fields.


  The main aim of this paper is to bridge two directions of research
generalizing asymptotic density zero sets. This enables to transfer results
concerning one direction to the other one.
  Consider a function $g\colon\omega\to [0,\infty)$ such that
$\lim_{n\to\infty}g(n)=\infty$ and $\frac{n}{g(n)}$ does not converge to $0$.
Then the family $\mathcal{Z}_g=\{A\subseteq\omega:\
\lim_{n\to\infty}\frac{\text{card}(A\cap n)}{g(n)}=0\}$ is an ideal called
simple density ideal (or ideal associated to upper density of weight $g$). We
compare this class of ideals with Erd\H{o}s-Ulam ideals. In particular, we show
that there are $\sqsubseteq$-antichains of size $\mathfrak{c}$ among
Erd\H{o}s-Ulam ideals which are and are not simple density ideals.
  We characterize simple density ideals which are Erd\H{o}s-Ulam as those
containing the classical ideal of sets of asymptotic density zero. We also
characterize Erd\H{o}s-Ulam ideals which are simple density ideals. In the
latter case we need to introduce two new notions. One of them, called
increasing-invariance of an ideal $\mathcal{I}$, asserts that given
$B\in\mathcal{I}$ and $C\subseteq\omega$ with $\text{card}(C\cap
n)\leq\text{card}(B\cap n)$ for all $n$, we have $C\in\mathcal{I}$.
  Finally, we pose some open problems.


  Object detection is a fundamental visual recognition problem in computer
vision and has been widely studied in the past decades. Visual object detection
aims to find objects of certain target classes with precise localization in a
given image and assign each object instance a corresponding class label. Due to
the tremendous successes of deep learning based image classification, object
detection techniques using deep learning have been actively studied in recent
years. In this paper, we give a comprehensive survey of recent advances in
visual object detection with deep learning. By reviewing a large body of recent
related work in literature, we systematically analyze the existing object
detection frameworks and organize the survey into three major parts: (i)
detection components, (ii) learning strategies, and (iii) applications &
benchmarks. In the survey, we cover a variety of factors affecting the
detection performance in detail, such as detector architectures, feature
learning, proposal generation, sampling strategies, etc. Finally, we discuss
several future directions to facilitate and spur future research for visual
object detection with deep learning. Keywords: Object Detection, Deep Learning,
Deep Convolutional Neural Networks


  This paper addresses the difficulty of characterizing the time-varying nature
of fading channels. The current time-invariant models often fall short of
capturing and tracking these dynamic characteristics. To overcome this
limitation, we explore using of stochastic differential equations (SDEs) and
Markovian projection to model signal envelope variations, considering scenarios
involving Rayleigh, Rice, and Hoyt distributions. Furthermore, it is of
practical interest to study the performance of channels modeled by SDEs. In
this work, we investigate the fade duration metric, representing the time
during which the signal remains below a specified threshold within a fixed time
interval. We estimate the complementary cumulative distribution function (CCDF)
of the fade duration using Monte Carlo simulations, and analyze the influence
of system parameters on its behavior. Finally, we leverage importance sampling,
a known variance-reduction technique, to estimate the tail of the CCDF
efficiently.


  We introduce a common generalization of essentially all known methods for
explicit computation of Selmer groups, which are used to bound the ranks of
abelian varieties over global fields. We also simplify and extend the proofs
relating what is computed to the cohomologically-defined Selmer groups. Selmer
group computations have been practical for many Jacobians of curves over Q of
genus up to 2 since the 1990s, but our approach is the first to be practical
for general curves of genus 3. We show that our approach succeeds on some
genus-3 examples defined by polynomials with small coefficients.


  In this paper, the tunnelling of a particle through a potential barrier is
investigated in the presence of a time-dependent perturbation. The latter is
attributed to the process of the energy measurement of the scattered particle.
The time-dependent Schrodinger equation of the model is exactly solved. The
calculation of the probability density inside the barrier proves that the
tunnelling dynamics is determined not only by the transmitted and reflected
waves but also by their interference. Furthermore, the interference term is
time-dependent and contribute to the scattering process duration. The
tunnelling time is calculated as the time to stop the flow of probability
density inside the barrier. This is the minimum duration of the measurement
process before detecting the particle beyond the barrier. Based on this, a new
method of estimating the tunnelling time by energy experimental measuring is
proposed.


  We perform global fits to the parameters of the Constrained Minimal
Supersymmetric Standard Model (CMSSM) and to a variant with non-universal Higgs
masses (NUHM1). In addition to constraints from low-energy precision
observables and the cosmological dark matter density, we take into account the
LHC exclusions from searches in jets plus missing transverse energy signatures
with about 5/fb of integrated luminosity at sqrt(s)=7TeV. We also include the
most recent upper bound on the branching ratio Bs->mumu from LHCb. The best fit
of the CMSSM prefers a light Higgs boson just above the experimentally excluded
mass. We find that the description of the low-energy observables, (g-2)(mu) in
particular, and the non-observation of SUSY at the LHC become more and more
incompatible within the CMSSM. A potential SM-like Higgs boson with mass around
126 GeV can barely be accommodated. Values for BF(Bs->mumu) just around the
Standard Model prediction are naturally expected in the best fit region.


  We determine the morphological mix of field galaxies down to $m_{I}\simeq
24.25$ mag ($m_{B}\sim 26.0$ mag) from a single ultradeep HST WFPC2 image in
both the $V_{606}$ and $I_{814}$ filters. In total, we find 227 objects with
$m_{I}\le 24.5$ mag and classify these into three types: ellipticals (16%),
early-type spirals (37%) and late-type spirals/Irregulars (47%). The
differential number counts for each type are compared to simple models in a
standard flat cosmology. We find that both the elliptical and early-type spiral
number counts are well described by {\it little or no}-evolution models, but
only when normalized at $b_{J} = 18.0$ mag. Given the uncertainties in the
luminosity function (LF) normalization, both populations are consistent with a
mild evolutionary scenario based on a normal/low rate of star-formation. This
constrains the end of the last {\it major} star-formation epoch in the giant
galaxy populations to $z\geq 0.8$.
  Conversely, the density of the observed late-type/Irregular population is
found to be a factor of 10 in excess of the conventional no-evolution model.
This large population might be explained by either a modified {\it local}
dwarf-rich LF, and/or strong evolution acting on the {\it local} LF. For the
dwarf-rich case, a {\it steep} faint-end Schechter-slope ($\alpha\simeq -1.8$)
is required plus a five-fold increase in the dwarf normalization. For a purely
evolving model based on a {\it flat} Loveday {\it et al.} (1992) LF
($\alpha\simeq -1.0$), a ubiquitous starburst of $\Delta I\sim$2.0 mag is
needed at z$\simeq 0.5$ for the {\it entire} late-type population. We argue for
a combination of these possibilities, and show that for a steep Marzke {\it et
al.} (1994) LF ($\alpha\simeq -1.5$), a starburst of $\sim$ 1.3 mag is required


  A method for a time-dependent search for flaring astrophysical sources which
can be potentially detected by large neutrino experiments is presented. The
method uses a time-clustering algorithm combined with an unbinned likelihood
procedure. By including in the likelihood function a signal term which
describes the contribution of many small clusters of signal-like events, this
method provides an effective way for looking for weak neutrino flares over
different time-scales. The method is sensitive to an overall excess of events
distributed over several flares which are not individually detectable. For
standard cases (one flare) the discovery potential of the method is about 15%
worse than a standard time-dependent point source analysis with unknown
duration of the flare. However, for flares sufficiently shorter than the total
observation period, the method is more sensitive than a time-integrated
analysis.


  Motivated by the analysis of high-dimensional neuroimaging signals located
over the cortical surface, we introduce a novel Principal Component Analysis
technique that can handle functional data located over a two-dimensional
manifold. For this purpose a regularization approach is adopted, introducing a
smoothing penalty coherent with the geodesic distance over the manifold. The
model introduced can be applied to any manifold topology, can naturally handle
missing data and functional samples evaluated in different grids of points. We
approach the discretization task by means of finite element analysis and
propose an efficient iterative algorithm for its resolution. We compare the
performances of the proposed algorithm with other approaches classically
adopted in literature. We finally apply the proposed method to resting state
functional magnetic resonance imaging data from the Human Connectome Project,
where the method shows substantial differential variations between brain
regions that were not apparent with other approaches.


  In this work it is shown for some spatially homogeneous but anisotropic
models how the inhomogeneities in the distribution of matter on the surface of
the last scattering produce anisotropies in large angular scales (larger than
$\vartheta \gtrsim 2^\circ$) which do not differ from the ones produced in
Friedmann-Lema\^itre-Robertson-Walker (FLRW) geometries. That is, for these
anisotropic models, the imprint left on the cosmic microwave background
radiation (CMBR) by the primordial density fluctuations, in the form of a
fractional variation of the temperature of this radiation, is governed by the
same expression as the one given for FLRW models. More precisely, under
adiabatic initial conditions, the classical Sachs-Wolfe effect is recovered,
provided the anisotropy of the overall expansion is small. This conclusion is
in agreement with previous work on the same anisotropic models where we found
that they may go through an `isotropization' process up to the point that the
observations are unable to distinguish them from the standard FLRW model, if
the Hubble parameters along the orthogonal directions are assumed to be
approximately equal at the present epoch. Here we assumed upper bounds on the
present values of anisotropic parameters imposed by COBE observations.


  We measure Au and Ag atomic-size contacts in magnetic fields, from zero field
to 20 T. We find a magnetic field induced torque which leads to atomic binding
at shorter distances than at zero field. Furthermore, the conductance drops
below $G_0$ at high magnetic fields by about 15\% in Au. We calculate the
conduction through nanosized Au contacts containing residual $O_2$ molecules
attached to the contact region and find a spin polarized current when $O_2$ is
located at the atomic contact. We discuss the role of spin-orbit coupling in
the magnetic properties of $O_2$ attached to Au.


  Generalized BRS transformations such as introduced in Part I (hep-th/9906245)
are applied to a model of quantum gravity. This development is technically
complex; but at the least should illustrate how much less rigid and more
general of application are the new BRS transformations.


  We re-address the classification criterion for extremely red galaxies (ERGs)
of Pozzetti and Mannucci (2000 -- PM00), which aims to separate, in the Ic-K
(or Rc-K) vs. J-K colour--colour diagram, passively evolving, old (> 1 Gyr)
stellar populations in a dust-free environment, associated with ellipticals
(Es), from dusty starburst galaxies (DSGs), both at 1 < z < 2. We explore a
category of objects not considered previously, i.e., galaxies forming in this
redshift range on short (0.1 Gyr) timescales and observed also in their early,
dusty post-starburst phase. We also investigate the impact of structure of the
dusty medium and dust amount on the observed optical/near-IR colours of high-z
DSGs/DPSGs, through multiple-scattering radiative transfer calculations for a
dust/stars configuration and an extinction function calibrated with nearby
dusty starbursts. As a main result, we find that dusty post-starburst galaxies
(DPSGs), with ages between 0.2 and 1 Gyr, at 1.3 < z < 2 mix with Es at 1 < z <
2 for a large range in dust amount. This ``intrusion'' is a source of concern
for the present two-colour classification of ERGs. On the other hand, we
confirm, in agreement with PM00, that DSGs are well separated from Es, both at
1 < z < 2, in the Ic-K vs. J-K colour--colour diagram, whatever the structure
(two-phase clumpy or homogeneous) of their dusty medium and their dust amount
are. This result holds under the new hypothesis of high-z Es being as dusty as
nearby ones. Thus the interpretation of the optical/near-IR colours of high-z
Es may suffer from a multiple degeneracy among age, metallicity, dust and
redshift. We also find that DPSGs at z around 1 mix with DSGs at 1 < z < 2, as
a function of dust amount and structure of the dusty medium. All these results
help explaining the complexity of the ERG classification... (Abridged)


  In mid-2012, a GMIR observed by Voyager 2 crossed through the heliosheath and
collided with the heliopause, generating a pressure pulse that propagated into
the very local interstellar medium. The effects of the transmitted wave were
seen by Voyager 1 just 93 days after its own heliopause crossing. The passage
of the transient was accompanied by long-lasting decreases in galactic cosmic
ray intensities that occurred from ~2012.55 to ~2013.35 and ~2012.91 to
~2013.70 at Voyager 2 and Voyager 1, respectively. Omnidirectional (>20 MeV)
proton-dominated measurements from each spacecraft's Cosmic Ray Subsystem
reveal a remarkable similarity between these causally-related events, with a
correlation coefficient of 91.2% and a time-lag of 130 days. Knowing the
locations of the two spacecraft, we use the observed time-delay to calculate
the GMIR's average speed through the heliosheath (inside the heliopause) as a
function of temperature in the very local interstellar medium. This, combined
with particle, field, and plasma observations enables us to infer previously
unmeasured properties of the heliosheath, including a range of sound speeds and
total effective pressures. For a nominal temperature of ~20,000 K just outside
the heliopause, we find a sound speed of 314 (+/-) 32 km/s and total effective
pressure of 267 (+/-) 55 fPa inside the heliopause. We compare these results
with the Interstellar Boundary Explorer's data-driven models of heliosheath
pressures derived from energetic neutral atom fluxes (the globally distributed
flux) and present them as additional evidence that the heliosheath's dynamics
are driven by suprathermal energetic processes.


  A variety of "pseudo-Voigt" functions, i.e. a linear combination of the
Lorentz and Gauss function (occasionally augmented with a correction term),
have been proposed as a closed-form approximation for the convolution of the
Lorentz and Gauss function known as the Voigt function. First, a compact review
of several approximations using a consistent notation is presented. The
comparison with accurate reference values indicates relative errors as large as
some percent.


  Let $\mathcal{O}_K$ be a discrete valuation ring with fraction field $K$ of
characteristic $0$ and algebraically closed residue field $k$ of characteristic
$p > 0$. Let $A/K$ be an abelian variety of dimension $g$ with a $K$-rational
point of order $p$. In this article, we are interested in the reduction
properties that $A/K$ can have. After discussing the general case, we
specialize to $g=1$, and we study the possible Kodaira types that can occur.


  We have performed local STM studies on potassium-doped C60 (KxC60) monolayers
over a wide regime of the phase diagram. As K content increases from x = 3 to
5, KxC60 monolayers undergo metal-insulator-metal reentrant phase transitions
and exhibit a variety of novel orientational orderings. The most striking new
structure has a pinwheel-like 7-molecule unit cell in insulating K4+dC60. We
propose that the driving mechanism for the orientational ordering in KxC60 is
the lowering of electron kinetic energy through maximization of the overlap of
neighboring molecular orbitals over the entire doping range x = 3 to 5. In the
insulating and metallic phases this gives rise to orbital versions of the
superexchange and double-exchange interactions respectively.


  Measurements of the total amount of stars locked up in galaxies as a function
of host halo mass contain key clues about the efficiency of processes that
regulate star formation. We derive the total stellar mass fraction f_star as a
function of halo mass M500c from z=0.2 to z=1 using two complementary methods.
First, we derive f_star using a statistical Halo Occupation Distribution model
jointly constrained by data from lensing, clustering, and the stellar mass
function. This method enables us to probe f_star over a much wider halo mass
range than with group or cluster catalogs. Second, we derive f_star at group
scales using a COSMOS X-ray group catalog and we show that the two methods
agree to within 30%. We quantify the systematic uncertainty on f_star using
abundance matching methods and we show that the statistical uncertainty on
f_star (~10%) is dwarfed by systematic uncertainties associated with stellar
mass measurements (~45% excluding IMF uncertainties). Assuming a Chabrier IMF,
we find 0.012<f_star<0.025 at M500c=10^13 Msun and 0.0057<f_star<0.015 at
M500c=10^14 Msun. These values are significantly lower than previously
published estimates. We investigate the cause of this difference and find that
previous work has overestimated f_star due to a combination of inaccurate
stellar mass estimators and/or because they have assumed that all galaxies in
groups are early type galaxies with a constant mass-to-light ratio. Contrary to
previous claims, our results suggest that the mean value of f_star is always
significantly lower than f_gas for halos above 10^13 Msun. Combining our
results with recently published gas mas fractions, we find a shortfall in
f_star+f_gas at R500c compared to the cosmic mean. This shortfall varies with
halo mass and becomes larger towards lower halos masses.


  For a class $F$ of complex-valued functions on a set $D$, we denote by
$g_n(F)$ its sampling numbers, i.e., the minimal worst-case error on $F$,
measured in $L_2$, that can be achieved with a recovery algorithm based on $n$
function evaluations. We prove that there is a universal constant
$c\in\mathbb{N}$ such that, if $F$ is the unit ball of a separable reproducing
kernel Hilbert space, then \[ g_{cn}(F)^2 \,\le\, \frac{1}{n}\sum_{k\geq n}
d_k(F)^2, \] where $d_k(F)$ are the Kolmogorov widths (or approximation
numbers) of $F$ in $L_2$. We also obtain similar upper bounds for more general
classes $F$, including all compact subsets of the space of continuous functions
on a bounded domain $D\subset \mathbb{R}^d$, and show that these bounds are
sharp by providing examples where the converse inequality holds up to a
constant. The results rely on the solution to the Kadison-Singer problem, which
we extend to the subsampling of a sum of infinite rank-one matrices.


  In this work, we define the notions of Wronskian and simplified Wronskian for
Stieltjes derivatives and study some of their properties in a similar manner to
the context of time scales or the usual derivative. Later, we use these tools
to investigate second order linear differential equations with Stieltjes
derivatives to find linearly independent solutions, as well as to derive the
variation of parameters method for problems with $g$-continuous coefficients.
This theory is later illustrated with some examples such as the study of the
one-dimensional linear Helmholtz equation with piecewise-constant coefficients.


  We consider the Springer fiber over a nilpotent endomorphism. Fix a Jordan
basis and consider the standard torus relative to this. We deal with the
problem to describe the flags fixed by the torus which belong to a given
component of the Springer fiber. We solve the problem in the hook, two-row and
two-column cases. We provide two main characterizations which are common to the
three cases, and which involve dominance relations between Young diagrams and
combinatorial algorithms. Then, for these three cases, we deduce topological
properties of the components and their intersections.


  Dilatons are pseudo-Nambu-Goldstone bosons arising from the breaking of
conformal invariance. In this letter we point out that in general a dilaton
mass has a power-law dependence on a small parameter related to the explicit
breaking of conformal invariance whereas the ratio between the ultraviolet and
infrared scales in the theory are exponentially related to the same parameter.
We show that this scaling results in a separation between the dilaton mass and
the infrared scale that can not be arbitrary large. Therefore a small dilaton
mass necessarily is associated to a secluded conformal sector. We argue that
the fact that the dilaton field must have a small displacement from the minimum
of its effective potential generated near the infrared scale precludes a
cosmologically interesting amount of dilatonic dark matter to be produced by a
misalignment mechanism in the early Universe.


  In this paper, we investigate properties of classes of functions related to
certain elliptic operators. Firstly, we prove that a main result of Dyakonov
(Acta Math. 178(1997), 143--167) on analytic functions can be extended to this
more general setting. Secondly, we study the radial growth on these functions
and the obtained results are generalizations of the corresponding results of
Makarov (Proc. London Math. Soc. 51(1985), 369--384) and Korenblum (Bull. Amer.
Math. Soc. 12(1985), 99--102). Finally, we discuss the Dirichlet type energy
integrals on such classes of functions and their applications.


  We measure the critical scattering length for the appearance of the first
three-body bound state, or Efimov three-body parameter, at seven different
Feshbach resonances in ultracold 39K atoms. We study both intermediate and
narrow resonances, where the three-body spectrum is expected to be determined
by the non-universal coupling of two scattering channels. We observe instead
approximately the same universal relation of the three-body parameter with the
two-body van der Waals radius already found for broader resonances, which can
be modeled with a single channel. This unexpected observation suggests the
presence of a new regime for three-body scattering at narrow resonances.


  We discuss the quantization and holographic aspects of a class of conical
spaces in 2+1 dimensional pure AdS gravity. These appear as topological
solitons in the Chern-Simons formulation of the theory and are closely related
to the recently studied conical solutions in higher spin gravity. We discuss
the classical fluctuations around these solutions, which form exceptional
coadjoint orbits of the asymptotic Virasoro group. We argue that the
quantization of these solutions leads to nonunitary representations of the
Virasoro algebra, on account of their having boundary graviton fluctuations
which lower the energy. We propose a framework to quantize them in a
semiclassical expansion in the inverse central charge, which we use to compute
their one-loop corrected energies. Interestingly, the resulting Virasoro
representations contain a null vector, thus providing an appearance of Kac's
degenerate representations, which are nonunitary at large central charge, in
the context of gravity. We match the computed quantum corrections in the bulk
with the properties of a class of primaries in Kac's classification.


  We defend a new theory of statistical evidence, which we call Robust
Bayesianism (RB). We prove that, under widely accepted assumptions, RB entails
the law of likelihood [Royall, 1997], the likelihood principle [Berger and
Wolpert, 1988], and a variety of other widely-accepted "statistical
principles", e.g., the sufficiency principle [Birnbaum, 1962, 1972] and
stopping-rule principle [Berger and Wolpert, 1988]. The main technical
contribution of this paper is to extend some of those results to a qualitative
framework in which experimenters are justified only in making comparative,
non-numerical judgments of the form "A given B is more likely than C given D."


  Recent progress in multilinear harmonic analysis naturally raises questions
about the local behaviour of the best constant (or bound) in the general
Brascamp--Lieb inequality as a function of the underlying linear
transformations. In this paper we prove that this constant is continuous, but
is not in general differentiable.


  Large Language Models (LLMs) have been applied to Math Word Problems (MWPs)
with transformative impacts, revolutionizing how these complex problems are
approached and solved in various domains including educational settings.
However, the evaluation of these models often prioritizes final accuracy,
overlooking the crucial aspect of reasoning capabilities. This work addresses
this gap by focusing on the ability of LLMs to detect and correct reasoning
mistakes. We introduce a novel dataset MWP-MISTAKE, incorporating MWPs with
both correct and incorrect reasoning steps generated through rule-based methods
and smaller language models. Our comprehensive benchmarking reveals significant
insights into the strengths and weaknesses of state-of-the-art models, such as
GPT-4o, GPT-4, GPT-3.5Turbo, and others. We highlight GPT-$o's superior
performance in mistake detection and rectification and the persistent
challenges faced by smaller models. Additionally, we identify issues related to
data contamination and memorization, impacting the reliability of LLMs in
real-world applications. Our findings emphasize the importance of rigorous
evaluation of reasoning processes and propose future directions to enhance the
generalization and robustness of LLMs in mathematical problem-solving.


  Altermagnetism (AM), a newly discovered magnetic state, ingeniously
integrates the properties of ferromagnetism and antiferromagnetism,
representing a significant breakthrough in the field of magnetic materials.
Despite experimental verification of some typical AM materials, such as MnTe
and MnTe$_2$, the pursuit of AM materials that feature larger spin splitting
and higher transition temperature is still essential. Here, our research
focuses on CrSb, which possesses N{\'e}el temperature of up to 700K and giant
spin splitting near the Fermi level ($E_F$). Utilizing high-resolution
angle-resolved photoemission spectroscopy and density functional theory
calculations, we meticulously map the three-dimensional electronic structure of
CrSb. Our photoemission spectroscopic results on both (0001) and
(10$\overline{1}$0) cleavages of CrSb collaboratively reveal unprecedented
details on AM-induced band splitting, and subsequently pin down its unique bulk
$g$-wave symmetry through quantitative analysis of the angular and
photon-energy dependence of spin splitting. Moreover, the observed spin
splitting reaches the magnitude of 0.93~eV near $E_F$, the most substantial
among all confirmed AM materials. This study not only validates the nature of
CrSb as a prototype $g$-wave like AM material but also underscores its pivotal
role in pioneering applications in spintronics.


  We calculate the isotope independent Li$^+$-Li potential energy curves for
the electronic ground and first excited states. Scattering phase shifts and
total scattering cross section for the $^7$Li$^+$-$^7$Li collision are
calculated with emphasis on the ultra-low energy domain down to the $s$-wave
regime. The effect of physically motivated alterations on the calculated
potential energy curves is used to determine the bound of accuracy of the
low-energy scattering parameters for the ion-atom system. It is found that the
scattering length for the A$^2\Sigma_u^+$ state, $a_u$ = 1325 a$_0$, is
positive and has well-constrained bounds. For the X$^2\Sigma_g^+$ state, the
scattering length, $a_g$ = 20465 a$_0$ has a large magnitude as it is sensitive
to the restrained change of the potential, due to the presence of a vibrational
state in the vicinity of the dissociation limit.


  We study the class of compact spaces that appear as structure spaces of
separable Banach lattices. In other words, we analyze what $C(K)$ spaces appear
as principal ideals of separable Banach lattices. Among other things, it is
shown that every such compactum $K$ admits a strictly positive regular Borel
measure of countable type that is analytic, and in the nonmetrizable case these
compacta are saturated with copies of $\beta\mathbb N$. Some natural questions
about this class are left open.


  We report measurements of the branching fractions and CP asymmetries for B^+-
-> eta h^+- (h = K or pi) and the observation of the decay B^0 -> eta K^0 from
the final data sample of 772x10^6 BBbar pairs collected with the Belle detector
at the KEKB asymmetric-energy e^+e^- collider. The measured branching fractions
are Br(B^+- -> eta K^+-) = (2.12 +- 0.23 +- 0.11)x10^-6}, Br(B^+- -> eta pi^+-)
= (4.07 +- 0.26 +- 0.21)x10^{-6} and Br(B^0 -> eta K^0) = (1.27^{+0.33}_{-0.29}
+- 0.08)x10^-6, where the last decay is observed for the first time with a
significance of 5.4 standard deviations (\sigma). We also find evidence for CP
violation in the charged B modes, A_{CP}(B^+- -> eta K^+-) = -0.38 +- 0.11 +-
0.01 and A_{CP}(B^+- -> eta pi^+- = -0.19 +- 0.06 +- 0.01 with significances of
3.8 sigma and 3.0 sigma, respectively. For all measurements, the first and
second uncertainties are statistical and systematic, respectively.


  In this paper, using the combined Lorentz-diffeomorphism symmetry, we find a
general formula for quasi-local conserved charge of the covariant gravity
theories in first order formalism of gravity. We simplify the general formula
for Lovelock theory of gravity. Afterwards, we apply the obtained formula on
BHT gravity to obtain energy and angular momentum of the rotating OTT black
hole solution in the context of this theory.


  While it is not generally reflected in the `nice' datasets used for
benchmarking machine learning algorithms, the real-world is full of processes
that would be best described as many-to-many. That is, a single input can
potentially yield many different outputs (whether due to noise, imperfect
measurement, or intrinsic stochasticity in the process) and many different
inputs can yield the same output (that is, the map is not injective). For
example, imagine a sentiment analysis task where, due to linguistic ambiguity,
a single statement can have a range of different sentiment interpretations
while at the same time many distinct statements can represent the same
sentiment. When modeling such a multivalued function $f: X \rightarrow Y$, it
is frequently useful to be able to model the distribution on $f(x)$ for
specific input $x$ as well as the distribution on fiber $f^{-1}(y)$ for
specific output $y$. Such an analysis helps the user (i) better understand the
variance intrinsic to the process they are studying and (ii) understand the
range of specific input $x$ that can be used to achieve output $y$. Following
existing work which used a fiber bundle framework to better model many-to-one
processes, we describe how morphisms of fiber bundles provide a template for
building models which naturally capture the structure of many-to-many
processes.


  We study the light scalar mesons in the QCD sum rule. We find that there are
five independent scalar tetraquark currents in the local form, and we perform
QCD sum rule analysis using both these currents and their combinations.
Compared with the sum rules by conventional \bar{q} q currents, our result
supports a tetraquark structure for low-lying scalar mesons.


  We present the observation of the angular distribution of a characteristic
x-ray emission through a periodic multilayer. The emission coming from the
substrate on which the multilayer is deposited is used for this purpose. It is
generated upon proton irradiation through the multilayer and detected with an
energy sensitive CCD camera. The observed distribution in the low detection
angle range presents a clear dip at a position characteristic of the emitting
element. Thus, such a device can be envisaged as a spectrometer without
mechanical displacement and using various ionizing sources (electrons, x-rays,
ions), their incident direction being irrelevant.


  The theory of quadratic forms and class numbers has connections to many
classical problems in number theory. Recently, class numbers have appeared in
the study of black holes in string theory. We describe this connection and
raise questions in the hope of inspiring new collaborations between number
theorists and physicists.


  A lateral shear interferometer based digital holographic microscopy has been
realized to study the morphology dynamics of Human red blood cells
quantitatively. Here, a lateral shear interferometer is embedded with a
conventional microscope with a CMOS sensor to form a lateral-shearing digital
holographic microscope. It enables recording of image plane holograms of
objects that can be numerically reconstructed to estimate its3-D prole. This
yields the depth information of the sample in addition to its bright field
image. The problem of the duplicate image is addressed by filtering object
information from one of the beams, without losing the contrast in the fringes.
The contrast in the fringes is maintained by increased reflectivity of the back
surface of the shear plate. This improves the resolution in the proposed
system.


  We show that the Gottfried and the Bjorken integrals have the same
nonperturbative evolution, which is related to the gluon polarization in the
proton.


  As a common non-trivial generalization of the concept of a proper generalized
Bassian group, we introduce the notion of a semi-generalized Bassian group and
initiate its comprehensive investigation. Precisely, we give a satisfactory
characterization of these groups by showing in the cases of p-torsion groups,
torsion-free groups and splitting mixed groups their complete description.
Moreover, we classify the groups with the clearly related property that every
subgroup is essential in a direct summand of the whole group.


  Using archival near-infrared observations from the Keck and Lick
Observatories and the Hubble Space Telescope, we document the evolution of
Neptune's cloud activity from 1994 to 2022. We calculate the fraction of
Neptune's disk that contained clouds, as well as the average brightness of both
cloud features and cloud-free background over the planet's disk. We observe
cloud activity and brightness maxima during 2002 and 2015, and minima during
2007 and 2020, the latter of which is particularly deep. Neptune's lack of
cloud activity in 2020 is characterized by a near-total loss of clouds at
mid-latitudes and continued activity at the South Pole. We find that the
periodic variations in Neptune's disk-averaged brightness in the near-infrared
H (1.6 $\mu$m), K (2.1 $\mu$m), FWCH4P15 (893 nm), F953N (955 nm), FWCH4P15
(965 nm), and F845M (845 nm) bands are dominated by discrete cloud activity,
rather than changes in the background haze. The clear positive correlation we
find between cloud activity and Solar Lyman-Alpha (121.56 nm) irradiance lends
support to the theory that the periodicity in Neptune's cloud activity results
from photochemical cloud/haze production triggered by Solar ultraviolet
emissions.


  Long document summarization systems are critical for domains with lengthy and
jargonladen text, yet they present significant challenges to researchers and
developers with limited computing resources. Existing solutions mainly focus on
efficient attentions or divide-and-conquer strategies. The former reduces
theoretical time complexity, but is still memory-heavy. The latter methods
sacrifice global context, leading to uninformative and incoherent summaries.
This work aims to leverage the memory-efficient nature of divide-and-conquer
methods while preserving global context. Concretely, our framework AWESOME uses
two novel mechanisms: (1) External memory mechanisms track previously encoded
document segments and their corresponding summaries, to enhance global document
understanding and summary coherence. (2) Global salient content is further
identified beforehand to augment each document segment to support its
summarization. Extensive experiments on diverse genres of text, including
government reports, transcripts, scientific papers, and novels, show that
AWESOME produces summaries with improved informativeness, faithfulness, and
coherence than competitive baselines on longer documents, while having a
smaller GPU memory footprint.


  The paper introduces and solves a structural controllability problem for
continuum ensembles of linear time-invariant systems. All the individual linear
systems of an ensemble are sparse, governed by the same sparsity pattern.
Controllability of an ensemble system is, by convention, the capability of
using a common control input to simultaneously steer every individual systems
in it. A sparsity pattern is structurally controllable if it admits a
controllable linear ensemble system. A main contribution of the paper is to
provide a graphical condition that is necessary and sufficient for a sparsity
pattern to be structurally controllable. Like other structural problems, the
property of being structural controllable is monotone. We provide a complete
characterization of minimal sparsity patterns as well.


  We consider an application of Grothendieck's dessins d'enfants to the theory
of the sixth Painlev\'e and Gauss hypergeometric functions: two classical
special functions of the isomonodromy type. It is shown that, higher order
transformations and the Schwarz table for the Gauss hypergeometric function are
closely related with some particular Belyi functions. Moreover, we introduce a
notion of deformation of the dessins d'enfants and show that one dimensional
deformations are a useful tool for construction of algebraic the sixth
Painlev\'e functions.


  Rigidity plays an important role on the relaxation properties of glass
forming melts, yet it is usually determined from the average co-ordination
number through the chemical composition. A discussion is presented on how
viscoelasticity can be used as an alternative way to determine glass rigidity
and to give clues about the relaxation processes. In particular, it is shown
that the transverse current dynamical structure factor of dense glass and
crystal forming fluids contain rich information about rigidity that can be
related with the presence of a dynamical-gap for transversal vibrational modes.
As a result, the number of floppy modes can be related with the size of the
dynamical gap and with the liquid relaxation time. From this, a dynamical
average effective coordination number can be defined. As an example, numerical
simulations for hard-disks in a dense fluid phase are provided. Finally, a
discussion is presented on the need to improve glass viscoelasticity models to
describe consistently non-exponential stress and strain relaxation.


  For any graph $G$, assume that $J(G)$ is the cover ideal of $G$. Let
$J(G)^{(k)}$ denote the $k$th symbolic power of $J(G)$. We characterize all
graphs $G$ with the property that $J(G)^{(k)}$ has a linear resolution for some
(equivalently, for all) integer $k\geq 2$. Moreover, it is shown that for any
graph $G$, the sequence $\big({\rm reg}(J(G)^{(k)})\big)_{k=1}^{\infty}$ is
nondecreasing. Furthermore, we compute the largest degree of minimal generators
of $J(G)^{(k)}$ when $G$ is either an unmixed of a claw-free graph.


  With increasing expressive power, deep neural networks have significantly
improved the state-of-the-art on image classification datasets, such as
ImageNet. In this paper, we investigate to what extent the increasing
performance of deep neural networks is impacted by background features? In
particular, we focus on background invariance, i.e., accuracy unaffected by
switching background features and background influence, i.e., predictive power
of background features itself when foreground is masked. We perform experiments
with 32 different neural networks ranging from small-size networks to
large-scale networks trained with up to one Billion images. Our investigations
reveal that increasing expressive power of DNNs leads to higher influence of
background features, while simultaneously, increases their ability to make the
correct prediction when background features are removed or replaced with a
randomly selected texture-based background.


  Peripheral collisions give access to a set of events where hot
quasi-projectile (QP) sources are produced exploring a large range of
excitation energy. In this range evaporation and multifragmentation are both
observed for a similar charge/size of the sources. In this work, this
experimental fact will be described in terms of coexistence of two classes of
events in the first order phase transition formalism. For this, a detailed
study of the experimental correlation between the size/charge of the biggest
cluster/fragment (Z1) and the excitation energy (E*) is made. Making the
parallel with the same correlation derived from the canonical ensemble
description, a first value of the latent heat and boundaries of spinodal and
coexistence zone are extracted.


  We study the localized magnetic states of impurity in biased bilayer and
trilayer graphene. It is found that the magnetic boundary for bilayer and
trilayer graphene presents the mixing features of Dirac and conventional
fermion. For zero gate bias, as the impurity energy approaches the Dirac point,
the impurity magnetization region diminishes for bilayer and trilayer graphene.
When a gate bias is applied, the dependence of impurity magnetic states on the
impurity energy exhibits a different behavior for bilayer and trilayer graphene
due to the opening of a gap between the valence and the conduction band in the
bilayer graphene with the gate bias applied. The magnetic moment and the
corresponding magnetic transition of the impurity in bilayer graphene are also
investigated.


  We study a dynamic traffic assignment model, where agents base their
instantaneous routing decisions on real-time delay predictions. We formulate a
mathematically concise model and derive properties of the predictors that
ensure a dynamic prediction equilibrium exists. We demonstrate the versatility
of our framework by showing that it subsumes the well-known full information
and instantaneous information models, in addition to admitting further
realistic predictors as special cases. We complement our theoretical analysis
by an experimental study, in which we systematically compare the induced
average travel times of different predictors, including a machine-learning
model trained on data gained from previously computed equilibrium flows, both
on a synthetic and a real road network.


  Nowadays, classical count-based word embeddings using positive pointwise
mutual information (PPMI) weighted co-occurrence matrices have been widely
superseded by machine-learning-based methods like word2vec and GloVe. But these
methods are usually applied using very large amounts of text data. In many
cases, however, there is not much text data available, for example for specific
domains or low-resource languages. This paper revisits PPMI by adding Dirichlet
smoothing to correct its bias towards rare words. We evaluate on standard word
similarity data sets and compare to word2vec and the recent state of the art
for low-resource settings: Positive and Unlabeled (PU) Learning for word
embeddings. The proposed method outperforms PU-Learning for low-resource
settings and obtains competitive results for Maltese and Luxembourgish.


  In this article, we address the problem of how temperature of a quantum
system is observed. By proposing a thought experiment, we argue that
temperature must be conceived as an operator and its measurement must
necessarily accompany a collapse in the wavefunction. We model a temperature
measurement device and determine the expectation value and quantum uncertainty
of its readout. Lastly, we explore the consequences of this point of view and
propose an experiment to verify if temperature is indeed a quantum observable.


  Using a sample of 25.9 million psi(2S) decays acquired with the CLEO-c
detector at the CESR e^+e^- collider, we report branching fractions for the
decays chi_cJ -> p p-bar pi^0, p p-bar eta, and p p-bar omega, with J=0,1,2.
Our results for B(chi_cJ-> p p-bar pi^0) and B(chi_cJ-> p p-bar eta) are
consistent with, but more precise than, previous measurements. Furthermore, we
include the first measurement of B(chi_cJ-> p p-bar omega).


  The Adam-Gibbs (AG) relation connects the dynamics of a glass-forming liquid
to its the thermodynamics via. the configurational entropy, and is of
fundamental importance in descriptions of glassy behaviour. The breakdown of
the Stokes-Einstein (SEB) relation between the diffusion coefficient and the
viscosity (or structural relaxation times) in glass formers raises the question
as to which dynamical quantity the AG relation describes. By performing
molecular dynamics simulations, we show that the AG relation is valid over the
widest temperature range for the diffusion coefficient and not for the
viscosity or relaxation times. Studying relaxation times defined at a given
wavelength, we find that SEB and the deviation from the AG relation occur below
a temperature at which the correlation length of dynamical heterogeneity equals
the wavelength probed.


  High-efficiency antiviral surfaces can be effective means to fight against
viral diseases such as the recent Covid-19 pandemic. Copper and copper oxides,
as well as their nanoparticles (Cu NPs) and coatings, are among the effective
antiviral materials having internal and external biocidal effects on viruses.
In this work, stable Cu NP colloids were produced via femtosecond laser
ablation of the metal target in water containing sodium citrate. Raman
spectroscopy and X-ray diffraction studies confirmed that the 32 nm mean size
nanoparticles are mixtures of mainly metallic copper and copper (I) oxide Cu2O.
Polyvinyl butyral was utilized as the binding agent for the spray-coated Cu
NPs. The virucidal efficacy of such coatings containing different Cu content
ranging from 2.9 at.% to 11.2 at.%. was confirmed against animal-origin
coronavirus containing RNA, the agent of avian infectious bronchitis (IBV), and
herpesvirus containing DNA, the agent of bovine herpesvirus (BoHV-1) infection.
It was demonstrated that after a short time of exposure, the Cu NPs-based
coatings do not have a toxic effect on the cell cultures while demonstrating a
negative effect on the biological activity of both model viruses that was
confirmed by quantification of the viruses via the determination of tissue
culture infectious dose (TCID50) virus titre and their viral nucleic acids via
determination of threshold cycle (Ct) employing real-time polymerase chain
reaction analysis. The assays showed that the decrease in TCID50 virus titre
and increase in Ct values correlated with Cu content in Cu NPs-based coatings
for both investigated viruses. Contact with coatings decreased IBV and BoHV-1
numbers from 99.42% to 100.00% and from 98.65% to 99.96% respectively. These
findings suggest that Cu NPs show inhibitory effects leading to the
inactivation of viruses and their nuclei regardless of the presence of a viral
envelope.


  This paper serves as an introduction and overview of the potentially useful
models and methodologies from artificial intelligence (AI) into the field of
transportation engineering for autonomous vehicle (AV) control in the era of
mixed autonomy. We will discuss state-of-the-art applications of AI-guided
methods, identify opportunities and obstacles, raise open questions, and help
suggest the building blocks and areas where AI could play a role in mixed
autonomy. We divide the stage of autonomous vehicle (AV) deployment into four
phases: the pure HVs, the HV-dominated, the AVdominated, and the pure AVs. This
paper is primarily focused on the latter three phases. It is the
first-of-its-kind survey paper to comprehensively review literature in both
transportation engineering and AI for mixed traffic modeling. Models used for
each phase are summarized, encompassing game theory, deep (reinforcement)
learning, and imitation learning. While reviewing the methodologies, we
primarily focus on the following research questions: (1) What scalable driving
policies are to control a large number of AVs in mixed traffic comprised of
human drivers and uncontrollable AVs? (2) How do we estimate human driver
behaviors? (3) How should the driving behavior of uncontrollable AVs be modeled
in the environment? (4) How are the interactions between human drivers and
autonomous vehicles characterized? Hopefully this paper will not only inspire
our transportation community to rethink the conventional models that are
developed in the data-shortage era, but also reach out to other disciplines, in
particular robotics and machine learning, to join forces towards creating a
safe and efficient mixed traffic ecosystem.


  Hierarchical clustering is a fundamental task often used to discover
meaningful structures in data, such as phylogenetic trees, taxonomies of
concepts, subtypes of cancer, and cascades of particle decays in particle
physics. Typically approximate algorithms are used for inference due to the
combinatorial number of possible hierarchical clusterings. In contrast to
existing methods, we present novel dynamic-programming algorithms for
\emph{exact} inference in hierarchical clustering based on a novel trellis data
structure, and we prove that we can exactly compute the partition function,
maximum likelihood hierarchy, and marginal probabilities of sub-hierarchies and
clusters. Our algorithms scale in time and space proportional to the powerset
of $N$ elements which is super-exponentially more efficient than explicitly
considering each of the (2N-3)!! possible hierarchies. Also, for larger
datasets where our exact algorithms become infeasible, we introduce an
approximate algorithm based on a sparse trellis that compares well to other
benchmarks. Exact methods are relevant to data analyses in particle physics and
for finding correlations among gene expression in cancer genomics, and we give
examples in both areas, where our algorithms outperform greedy and beam search
baselines. In addition, we consider Dasgupta's cost with synthetic data.


  When a quantum field theory possesses topological excitations in a phase with
spontaneously broken symmetry, these are created by operators which are
non-local with respect to the order parameter. Due to non-locality, such
disorder operators have non-trivial correlation functions even in free massive
theories. In two dimensions, these correlators can be expressed exactly in
terms of solutions of non-linear differential equations. The correlation
functions of the one-parameter family of non-local operators in the free
charged bosonic and fermionic models are the inverse of each other. We point
out a simple derivation of this correspondence within the form factor approach


  We find new polynomial upper bounds for the size of nodal sets of
eigenfunctions when the Riemannian manifold has a Gevrey or quasianalytic
regularity.


  We present two approaches for studying the uniformity of a tunnel barrier.
The first approach is based on measuring single-electron and two-electron
tunneling in a hybrid single-electron transistor. Our measurements indicate
that the effective area of a conduction channel is about one order of magnitude
larger than predicted by theoretical calculations. With the second method,
transmission electron microscopy, we demonstrate that variations in the barrier
thickness are a plausible explanation for the larger effective area and an
enhancement of higher order tunneling processes.


  We use angle resolved photoemission spectroscopy (ARPES) to study the
momentum dependence of the superconducting gap in NdFeAsO1-xFx single crystals.
We find that the Gamma hole pocket is fully gapped below the superconducting
transition temperature. The value of the superconducting gap is 15 +- 1.5 meV
and its anisotropy around the hole pocket is smaller than 20% of this value.
This is consistent with an isotropic or anisotropic s-wave symmetry of the
order parameter or exotic d-wave symmetry with nodes located off the Fermi
surface sheets. This is a significant departure from the situation in the
cuprates, pointing to possibility that the superconductivity in the iron
arsenic based system arises from a different mechanism.


  The aim of the project is to search for lithium in absorption at 6707.8
Angstroms to constrain the nature and the mass of the brightest low-metallicity
L-type dwarfs (refered to as L subdwarfs) identified in large-scale surveys.
  We obtained low- to intermediate-resolution (R~2500-9000) optical (~560-770
nm) spectra of two mid-L subdwarfs, SDSSJ125637.13-022452.4 (SDSS1256; sdL3.5)
and 2MASSJ162620.14+392519.5 (2MASS1626; sdL4) with spectrographs on the
European Southern Observatory Very Large Telescope and the Gran Telescopio de
Canarias.
  We report the presence of a feature at the nominal position of the lithium
absorption doublet at 6707.8 Angstroms in the spectrum of SDSS1256, with an
equivalent width of 66+/-27 Angstroms at 2.4 sigma, which we identify as
arising from a CaH molecular transition based on atmosphere models. We do not
see any feature at the position of the lithium feature in the spectrum of
2MASS1626. The existence of overlapping molecular absorption sets a confusion
detection limit of [Li/H]=-3 for equivalently-typed L subdwarfs. We provided
improved radial velocity measurements of -126+/-10 km/s and -239+/-12 km/s for
SDSS1256 and 2MASS1626, respectively, as well as revised Galactic orbits. We
implemented adjusting factors for the CaH molecule in combination with the
NextGen atmosphere models to fit the optical spectrum of SDSS1256 in the
6200-7300 Angstroms range. We also estimate the expected Li abundance from
interstellar accretion ([Li/H]=-5), place limits on circumstellar accretion
(10^9 g/yr), and discuss the prospects of Li searches in cooler L and T
subdwarfs.


  We study prediction in the functional linear model with functional outputs :
$Y=SX+\epsilon $ where the covariates $X$ and $Y$ belong to some functional
space and $S$ is a linear operator. We provide the asymptotic mean square
prediction error with exact constants for our estimator which is based on
functional PCA of the input and has a classical form. As a consequence we
derive the optimal choice of the dimension $k_{n}$ of the projection space. The
rates we obtain are optimal in minimax sense and generalize those found when
the output is real. Our main results hold with no prior assumptions on the rate
of decay of the eigenvalues of the input. This allows to consider a wide class
of parameters and inputs $X(\cdot) $ that may be either very irregular or very
smooth. We also prove a central limit theorem for the predictor which improves
results by Cardot, Mas and Sarda (2007) in the simpler model with scalar
outputs. We show that, due to the underlying inverse problem, the bare estimate
cannot converge in distribution for the norm of the function space


  Finding functions, particularly permutations, with good differential
properties has received a lot of attention due to their possible applications.
For instance, in combinatorial design theory, a correspondence of perfect
$c$-nonlinear functions and difference sets in some quasigroups was recently
shown [1]. Additionally, in a recent manuscript by Pal and Stanica [20], a very
interesting connection between the $c$-differential uniformity and boomerang
uniformity when $c=-1$ was pointed out, showing that that they are the same for
an odd APN permutations. This makes the construction of functions with low
$c$-differential uniformity an intriguing problem. We investigate the
$c$-differential uniformity of some classes of permutation polynomials. As a
result, we add four more classes of permutation polynomials to the family of
functions that only contains a few (non-trivial) perfect $c$-nonlinear
functions over finite fields of even characteristic. Moreover, we include a
class of permutation polynomials with low $c$-differential uniformity over the
field of characteristic~$3$. As a byproduct, our proofs shows the permutation
property of these classes. To solve the involved equations over finite fields,
we use various techniques, in particular, we find explicitly many Walsh
transform coefficients and Weil sums that may be of an independent interest.


  Model information can be used to predict future trajectories, so it has huge
potential to avoid dangerous region when implementing reinforcement learning
(RL) on real-world tasks, like autonomous driving. However, existing studies
mostly use model-free constrained RL, which causes inevitable constraint
violations. This paper proposes a model-based feasibility enhancement technique
of constrained RL, which enhances the feasibility of policy using generalized
control barrier function (GCBF) defined on the distance to constraint boundary.
By using the model information, the policy can be optimized safely without
violating actual safety constraints, and the sample efficiency is increased.
The major difficulty of infeasibility in solving the constrained policy
gradient is handled by an adaptive coefficient mechanism. We evaluate the
proposed method in both simulations and real vehicle experiments in a complex
autonomous driving collision avoidance task. The proposed method achieves up to
four times fewer constraint violations and converges 3.36 times faster than
baseline constrained RL approaches.


  Given a rooted tree $T$ with leaves $v_1,v_2,\ldots,v_n$, we define the
ancestral matrix $C(T)$ of $T$ to be the $n \times n$ matrix for which the
entry in the $i$-th row, $j$-th column is the level (distance from the root) of
the first common ancestor of $v_i$ and $v_j$. We study properties of this
matrix, in particular regarding its spectrum: we obtain several upper and lower
bounds for the eigenvalues in terms of other tree parameters. We also find a
combinatorial interpretation for the coefficients of the characteristic
polynomial of $C(T)$, and show that for $d$-ary trees, a specific value of the
characteristic polynomial is independent of the precise shape of the tree.


  We investigate the quantum dynamics of two interacting bosonic atoms confined
in a one-dimensional anharmonic trap. The tunneling rate, an experimentally
measurable parameter of the system, was calculated as a function of the
effective coupling interatomic constant $g$ from the ground (n=N=0) and first
excited atomic states in the trap with respect to relative (n=2,N=0) and
center-of-mass (n=0,N=2) atomic motion. This allows to investigate the initial
population and pair correlation, as well as the effective coupling constant
$g$, of the system by comparing the calculated tunneling rate with the
experimental one. We have observed that the only possible tunneling scenario is
a sequential particle tunneling in the cases we considered. We have also
analyzed a rearrangement $(0,2)\rightleftarrows(2,0)$ of the spectrum in the
limit $g\rightarrow \pm 0$ of noninteracting atoms.


  It had been widely claimed that quantum mechanics can protect private
information during public decision in for example the so-called two-party
secure computation. If this were the case, quantum smart-cards could prevent
fake teller machines from learning the PIN (Personal Identification Number)
from the customers' input. Although such optimism has been challenged by the
recent surprising discovery of the insecurity of the so-called quantum bit
commitment, the security of quantum two-party computation itself remains
unaddressed. Here I answer this question directly by showing that all
``one-sided'' two-party computations (which allow only one of the two parties
to learn the result) are necessarily insecure. As corollaries to my results,
quantum one-way oblivious password identification and the so-called quantum
one-out-of-two oblivious transfer are impossible. I also construct a class of
functions that cannot be computed securely in any ``two-sided'' two-party
computation. Nevertheless, quantum cryptography remains useful in key
distribution and can still provide partial security in ``quantum money''
proposed by Wiesner.


  We address combinatorial problems that can be formulated as minimization of a
partially separable function of discrete variables (energy minimization in
graphical models, weighted constraint satisfaction, pseudo-Boolean
optimization, 0-1 polynomial programming). For polyhedral relaxations of such
problems it is generally not true that variables integer in the relaxed
solution will retain the same values in the optimal discrete solution. Those
which do are called persistent. Such persistent variables define a part of a
globally optimal solution. Once identified, they can be excluded from the
problem, reducing its size.
  To any polyhedral relaxation we associate a sufficient condition proving
persistency of a subset of variables. We set up a specially constructed linear
program which determines the set of persistent variables maximal with respect
to the relaxation. The condition improves as the relaxation is tightened and
possesses all its invariances. The proposed framework explains a variety of
existing methods originating from different areas of research and based on
different principles. A theoretical comparison is established that relates
these methods to the standard linear relaxation and proves that the proposed
technique identifies same or larger set of persistent variables.


  We study risk-free bidding strategies in combinatorial auctions with
incomplete information. Specifically, what is the maximum profit that a
complement-free (subadditive) bidder can guarantee in a multi-item
combinatorial auction? Suppose there are $n$ bidders and $B_i$ is the value
that bidder $i$ has for the entire set of items. We study the above problem
from the perspective of the first bidder, Bidder~1. In this setting, the worst
case profit guarantees arise in a duopsony, that is when $n=2$, so this problem
then corresponds to playing an auction against a budgeted adversary with budget
$B_2$. We present worst-case guarantees for two simple and widely-studied
combinatorial auctions, namely, the sequential and simultaneous auctions, for
both the first-price and second-price case. In the general case of distinct
items, our main results are for the class of {\em fractionally subadditive}
(XOS) bidders, where we show that for both first-price and second-price
sequential auctions Bidder~$1$ has a strategy that guarantees a profit of at
least $(\sqrt{B_1}-\sqrt{B_2})^2$ when $B_2 \leq B_1$, and this bound is tight.
More profitable guarantees can be obtained for simultaneous auctions, where in
the first-price case, Bidder~$1$ has a strategy that guarantees a profit of at
least $\frac{(B_1-B_2)^2}{2B_1}$, and in the second-price case, a bound of
$B_1-B_2$ is achievable. We also consider the special case of sequential
auctions with identical items, for which we provide tight guarantees for
bidders with subadditive valuations.


  We propose an antenna designed to generate monochromatic electromagnetic
knots and other "unusual electromagnetic disturbances" in the microwave domain.
Our antenna is a spherical array of radiating dipolar elements configured to
approximate the desired electromagnetic field near its centre. We show
numerically that a specific embodiment of the antenna with a radius of 61.2 cm
and only 20 element pairs driven at a frequency of 2.45 GHz can yield linked
and torus-knotted electric and magnetic field lines approximating those of an
"electromagnetic tangle": a monochromatic electromagnetic knot closely related
to the well-known Ra\~nada-Hopf type electromagnetic knots but simpler in its
construction. The antenna could be used to locally excite plasmas.


  We apply Euclidean time methods to phenomenological Dyson-Schwinger models of
hadrons. By performing a Fourier transform of the momentum space correlation
function to Euclidean time and by taking the large Euclidean time limit, we
project onto the lightest on-mass-shell hadron for given quantum numbers. The
procedure, which actually resembles lattice gauge theory methods, allows the
extraction of moments of structure functions, moments of light-cone wave
functions and form factors without `ad hoc' extrapolations to the on-mass-shell
points. We demonstrate the practicality of the procedure with the example of
the pion form factor.


  The dissociation number ${\rm diss}(G)$ of a graph $G$ is the maximum order
of a set of vertices of $G$ inducing a subgraph that is of maximum degree at
most $1$. Computing the dissociation number of a given graph is algorithmically
hard even when restricted to subcubic bipartite graphs. For a graph $G$ with
$n$ vertices, $m$ edges, $k$ components, and $c_1$ induced cycles of length $1$
modulo $3$, we show ${\rm diss}(G)\geq n-\frac{1}{3}\Big(m+k+c_1\Big)$.
Furthermore, we characterize the extremal graphs in which every two cycles are
vertex-disjoint.


  We present STARRED, a Point Spread Function (PSF) reconstruction, two-channel
deconvolution, and light curve extraction method designed for high-precision
photometric measurements in imaging time series. An improved resolution of the
data is targeted rather than an infinite one, thereby minimizing deconvolution
artifacts. In addition, STARRED performs a joint deconvolution of all available
data, accounting for epoch-to-epoch variations of the PSF and decomposing the
resulting deconvolved image into a point source and an extended source channel.
The output is a deep sharp frame combining all data, and the photometry of all
point sources in the field of view as a function of time. Of note, STARRED also
provides exquisite PSF models for each data frame. We showcase three
applications of STARRED in the context of the imminent LSST survey and of JWST
imaging: i) the extraction of supernovae light curves and the scene
representation of their host galaxy, ii) the extraction of lensed quasar light
curves for time-delay cosmography, and iii) the measurement of the spectral
energy distribution of globular clusters in the "Sparkler", a galaxy at
redshift z=1.378 strongly lensed by the galaxy cluster SMACS J0723.3-7327.
STARRED is implemented in JAX, leveraging automatic differentiation and GPU
acceleration. This enables rapid processing of large time-domain datasets,
positioning the method as a powerful tool for extracting light curves from the
multitude of lensed or unlensed variable and transient objects in the
Rubin-LSST data, even when blended with intervening objects.


  Highly transparent superconducting contacts to a topological insulator (TI)
remain a persistent challenge on the route to engineer topological
superconductivity. Recently, the higher-order TI WTe$_2$ was shown to turn
superconducting when placed on palladium (Pd) bottom contacts, demonstrating a
promising material system in pursuing this goal. Here, we report the diffusion
of Pd into WTe$_2$ and the formation of superconducting PdTe$_x$ as the origin
of observed superconductivity. We find an atomically sharp interface in
vertical direction to the van der Waals layers between the diffusion crystal
and its host crystal, forming state-of-the-art superconducting contacts to a
TI. The diffusion is discovered to be non-uniform along the width of the
WTe$_2$ crystal, with a greater extend along the edges compared to the bulk.
The potential of this contacting method is highlighted in transport
measurements on Josephson junctions by employing external superconducting
leads.


  We explore optimization methods for planning the placement, sizing and
operations of Flexible Alternating Current Transmission System (FACTS) devices
installed into the grid to relieve congestion created by load growth or
fluctuations of intermittent renewable generation. We limit our selection of
FACTS devices to those that can be represented by modification of the
inductance of the transmission lines. Our master optimization problem minimizes
the $l_1$ norm of the FACTS-associated inductance correction subject to
constraints enforcing that no line of the system exceeds its thermal limit. We
develop off-line heuristics that reduce this non-convex optimization to a
succession of Linear Programs (LP) where at each step the constraints are
linearized analytically around the current operating point. The algorithm is
accelerated further with a version of the cutting plane method greatly reducing
the number of active constraints during the optimization, while checking
feasibility of the non-active constraints post-factum. This hybrid algorithm
solves a typical single-contingency problem over the MathPower Polish Grid
model (3299 lines and 2746 nodes) in 40 seconds per iteration on a standard
laptop---a speed up that allows the sizing and placement of a family of FACTS
devices to correct a large set of anticipated contingencies. From testing of
multiple examples, we observe that our algorithm finds feasible solutions that
are always sparse, i.e., FACTS devices are placed on only a few lines. The
optimal FACTS are not always placed on the originally congested lines, however
typically the correction(s) is made at line(s) positioned in a relative
proximity of the overload line(s).


  Positron emission tomography (PET) suffers from severe resolution limitations
which limit its quantitative accuracy. In this paper, we present a
super-resolution (SR) imaging technique for PET based on convolutional neural
networks (CNNs). To facilitate the resolution recovery process, we incorporate
high-resolution (HR) anatomical information based on magnetic resonance (MR)
imaging. We introduce the spatial location information of the input image
patches as additional CNN inputs to accommodate the spatially-variant nature of
the blur kernels in PET. We compared the performance of shallow (3-layer) and
very deep (20-layer) CNNs with various combinations of the following inputs:
low-resolution (LR) PET, radial locations, axial locations, and HR MR. To
validate the CNN architectures, we performed both realistic simulation studies
using the BrainWeb digital phantom and clinical neuroimaging data analysis. For
both simulation and clinical studies, the LR PET images were based on the
Siemens HR+ scanner. Two different scenarios were examined in simulation: one
where the target HR image is the ground-truth phantom image and another where
the target HR image is based on the Siemens HRRT scanner --- a high-resolution
dedicated brain PET scanner. The latter scenario was also examined using
clinical neuroimaging datasets. A number of factors affected relative
performance of the different CNN designs examined, including network depth,
target image quality, and the resemblance between the target and anatomical
images. In general, however, all CNNs outperformed classical penalized
deconvolution techniques by large margins both qualitatively (e.g., edge and
contrast recovery) and quantitatively (as indicated by two metrics: peak
signal-to-noise-ratio and structural similarity index).


  The turbulent flow over monochromatic waves of moderate steepness is studied
by means of wall resolved LES, and cover a range of wave ages and Reynolds
numbers. We compute the Fourier modes of the flow and analyse the momentum
balance for the mean and fundamental mode. At low wave ages, the form drag
displays a large sensitivity to changes in Reynolds number, and the interaction
between turbulent and wave-induced stresses increases with Reynolds number. At
higher wave ages, a quasi-laminar regime is entered, where the wave-induced
stress is primarily balanced by viscous stresses. To exploit the increasing
importance of the wave kinematics observed in the intermediate to high wave age
regime, a novel split system approach is introduced, where a laminar response
to the wave forces a turbulent RANS type of shear flow . To account for the
effects of turbulence, we force the system using Reynolds stresses from the
corresponding LES. We give an analytic functional dependence for the form drag
associated with the laminar solution. For intermediate to high wave ages, the
form drag of the shear flow exhibits relatively simple behaviour, and we derive
approximate functional dependencies for the quasi-laminar regime. The high
sensitivity of the form drag to variation in Reynolds number at low wave ages
is more challenging to evaluate using this approach. This is primarily due to
the increased importance of nonlinearity in the shear flow, which are
inherently coupled with higher harmonics in the turbulent stresses.
Nevertheless, the split system approach can be utilized to quantify the
importance of different harmonics in the turbulent stresses by explicitly
choosing which modes to include in the split system forcing. We demonstrate
that the fundamental mode of the Reynolds stresses becomes increasingly
important for accurate prediction of the form drag as the Reynolds number
increases.


  We analyse a robust sample of 30 near-infrared-faint (K>25.3, 5 sigma)
submillimetre galaxies selected across a 0.96 deg^2 field, to investigate their
properties and the cause of their lack of detectable optical/near-infrared
emission. Our analysis exploits precise identifications based on ALMA 870um
continuum imaging, combined with the very deep near-infrared imaging from the
UKIDSS-UDS survey. We estimate that K>25.3 submillimetre galaxies represent
15+/-2 per cent of the total population brighter than S870=3.6mJy, with an
expected surface density of ~450/deg^2 above S870>1mJy. As such they pose a
source of contamination in surveys for both high-redshift "quiescent" galaxies
and very-high-redshift Lyman-break galaxies. We show that these K-faint
submillimetre galaxies are simply the tail of the broader submillimetre
population, with comparable dust and stellar masses to K<25.3 mag submillimetre
galaxies, but lying at significantly higher redshifts (z=3.44+/-0.06 versus
z=2.36+/-0.11) and having higher dust attenuation (Av=5.2+/-0.3 versus
Av=2.9+/-0.1). We investigate the origin of the strong dust attenuation and
find indications that these K-faint galaxies have smaller dust continuum sizes
than the K<25.3 galaxies, as measured by ALMA, which suggests their high
attenuation is related to their compact sizes. We find a correlation of dust
attenuation with star-formation rate surface density (Sigma_SFR), with the
K-faint submillimetre galaxies representing the higher-Sigma_SFR and highest-Av
galaxies. The concentrated, intense star-formation activity in these systems is
likely to be associated with the formation of spheroids in compact galaxies at
high redshifts, but as a result of their high obscuration these are completely
missed in UV, optical and even near-infrared surveys.


  The identification of distinct charge transport features, deriving from
nontrivial bulk band and surface states, has been a challenging subject in the
field of topological systems. In topological Dirac and Weyl semimetals,
nontrivial conical bands with Fermi-arc surface states give rise to negative
longitudinal magnetoresistance due to chiral anomaly effect and unusual
thickness dependent quantum oscillation from Weyl-orbit effect, which were
demonstrated recently in experiments. In this work, we report the experimental
observations of large nonlinear and nonreciprocal transport effects for both
longitudinal and transverse channels in an untwinned Weyl metal of SrRuO$_3$
thin film grown on a SrTiO$_{3}$ substrate. From rigorous measurements with
bias current applied along various directions with respect to the crystalline
principal axes, the magnitude of nonlinear Hall signals from the transverse
channel exhibits a simple sin$\alpha$ dependence at low temperatures, where
$\alpha$ is the angle between bias current direction and orthorhombic
[001]$_{\rm o}$, reaching a maximum when current is along orthorhombic
[1-10]$_{\rm o}$. On the contrary, the magnitude of nonlinear and nonreciprocal
signals in the longitudinal channel attains a maximum for bias current along
[001]$_{\rm o}$, and it vanishes for bias current along [1-10]$_{\rm o}$. The
observed $\alpha$-dependent nonlinear and nonreciprocal signals in longitudinal
and transverse channels reveal a magnetic Weyl phase with an effective Berry
curvature dipole along [1-10]$_{\rm o}$ from surface states, accompanied by 1D
chiral edge modes along [001]$_{\rm o}$.


  Mediation analysis is an important statistical tool in many research fields.
Its aim is to investigate the mechanism along the causal pathway between an
exposure and an outcome. The joint significance test is widely utilized as a
prominent statistical approach for examining mediation effects in practical
applications. Nevertheless, the limitation of this mediation testing method
stems from its conservative Type I error, which reduces its statistical power
and imposes certain constraints on its popularity and utility. The proposed
solution to address this gap is the adjusted joint significance test for one
mediator, a novel data-adaptive test for mediation effect that exhibits
significant advancements compared to traditional joint significance test. The
proposed method is designed to be user-friendly, eliminating the need for
complicated procedures. We have derived explicit expressions for size and
power, ensuring the theoretical validity of our approach. Furthermore, we
extend the proposed adjusted joint significance tests for small-scale mediation
hypotheses with family-wise error rate (FWER) control. Additionally, a novel
adjusted Sobel-type approach is proposed for the estimation of confidence
intervals for the mediation effects, demonstrating significant advancements
over conventional Sobel's confidence intervals in terms of achieving desirable
coverage probabilities. Our mediation testing and confidence intervals
procedure is evaluated through comprehensive simulations, and compared with
numerous existing approaches. Finally, we illustrate the usefulness of our
method by analysing three real-world datasets with continuous, binary and
time-to-event outcomes, respectively.


  We show the absence of the ABJ anomaly for the Horava-Lifshitz-like QED with
any even $z$. Besides of this, we study the graph contributing to the ABJ
anomaly at non-zero temperature and extend the Fujikawa's methodology of
studying the integral measure for our model.


  Little Higgs models with T-parity have a new source of lepton flavour
violation. In this paper we consider the anomalous magnetic moment of the muon
\gmtwo and the lepton flavour violating decays \mutoeg and \tautomug in Little
Higgs model with T-parity \cite{Goyal:2006vq}. Our results shows that present
experimental constraints of \mutoeg is much more useful to constrain the new
sources of flavour violation which are present in T-parity models.


  Understanding surface mechanics of soft solids, such as soft polymeric gels,
is crucial in many engineering processes, such as dynamic wetting and adhesive
failure. In these situations, a combination of capillary and elastic forces
drives the motion, which is balanced by dissipative mechanisms to determine the
rate. While shear rheology (i.e. viscoelasticity) has long been assumed to
dominate the dissipation, recent works have suggested that compressibility
effects (i.e. poroelasticity) could play roles in swollen networks. We use fast
interferometric imaging to quantify the relaxation of surface deformations due
to a displaced contact line. By systematically measuring the profiles at
different time and length scales, we experimentally observe a crossover from
viscoelastic to poroelastic surface relaxations.


  In this paper we study the problem of fully dynamic maximal matching with
lookahead. In a fully dynamic $n$-vertex graph setting, we have to handle
updates (insertions and removals of edges), and answer queries regarding the
current graph, preferably with a better time bound than that when running the
trivial deterministic algorithm with worst-case time of $O(m)$ (where $m$ is
the all-time maximum number of the edges) and recompute the matching from
scratch each time a query arrives. We show that a maximal matching can be
maintained in an (undirected) general graph with a deterministic amortized
update cost of $O(\log m)$, provided that a lookahead of length $m$ is
available, i.e. we can ``take a peek'' at the next $m$ update operations in
advance.


  The second law of photochemistry states that in most cases, no more than one
molecule is activated for an excited-state reaction for each photon absorbed by
a collection of molecules. In this work, we demonstrate that it is possible to
trigger a many-molecule reaction using only one photon by strongly coupling the
molecular ensemble to a confined light mode. The collective nature of the
resulting hybrid states of the system (the so-called polaritons) leads to the
formation of a polaritonic "supermolecule" involving the degrees of freedom of
all molecules, opening a reaction path on which all involved molecules undergo
a chemical transformation. We theoretically investigate the system conditions
for this effect to take place and be enhanced.


  Background: Measurements of forward exclusive meson production at different
squared four-momenta of the exchanged virtual photon, $Q^2$, and at different
four-momentum transfer, t, can be used to probe QCD's transition from
meson-nucleon degrees of freedom at long distances to quark-gluon degrees of
freedom at short scales. Ratios of separated response functions in $\pi^-$ and
$\pi^+$ electroproduction are particularly informative. The ratio for
transverse photons may allow this transition to be more easily observed, while
the ratio for longitudinal photons provides a crucial verification of the
assumed pole dominance, needed for reliable extraction of the pion form factor
from electroproduction data. Method: Data were acquired with 2.6-5.2 GeV
electron beams and the HMS+SOS spectrometers in Jefferson Lab Hall C, at
central $Q^2$ values of 0.6, 1.0, 1.6 GeV$^2$ at W=1.95 GeV, and $Q^2$=2.45
GeV$^2$ at W=2.22 GeV. There was significant coverage in $\phi$ and $\epsilon$,
which allowed separation of $\sigma_{L,T,LT,TT}$. Results: $\sigma_L$ shows a
clear signature of the pion pole, with a sharp rise at small -t. In contrast,
$\sigma_T$ is much flatter versus t. The longitudinal/transverse ratios evolve
with $Q^2$ and t, and at the highest $Q^2$=2.45 GeV$^2$ show a slight
enhancement for $\pi^-$ production compared to $\pi^+$. The $\pi^-/\pi^+$ ratio
for transverse photons exhibits only a small $Q^2$-dependence, following a
nearly universal curve with t, with a steep transition to a value of about
0.25, consistent with s-channel quark knockout. The $\sigma_{TT}/\sigma_T$
ratio also drops rapidly with $Q^2$, qualitatively consistent with s-channel
helicity conservation. The $\pi^-/\pi^+$ ratio for longitudinal photons
indicates a small isoscalar contamination at W=1.95 GeV, consistent with what
was observed in our earlier determination of the pion form factor at these
kinematics.


  We analyze the photo-production of $\eta_{c,b}$ off a proton in the threshold
region, in terms of C-odd gluonic correlations in the off-forward proton matrix
element. Near threshold, the skewness is large leading to a production
amplitude that is dominated by four C-odd twist-3 gluon GPDs. We use the QCD
instanton vacuum to estimate these C-odd contributions in the proton. The
results are used to estimate the differential cross sections for coherent
photo-production of $\eta_{c,b}$ in the threshold region, at current electron
facilities.


  We prove that the automorphism groups of simple polarized abelian varieties
of odd prime dimension over finite fields are cyclic, and give a complete list
of finite groups that can be realized as such automorphism groups.


  In this paper we present the two-level homogenization of the flow in a
deformable double-porous structure described at two characteristic scales. The
higher level porosity associated with the mesoscopic structure is constituted
by channels in a matrix made of a microporous material consisting of elastic
skeleton and pores saturated by a viscous fluid. The macroscopic model is
derived by the homogenization of the flow in the heterogeneous structure
characterized by two small parameters involved in the two-level asymptotic
analysis, whereby a scaling ansatz is adopted to respect the pore size
differences. The first level upscaling of the fluid-structure interaction
problem yields a Biot continuum describing the mesoscopic matrix coupled with
the Stokes flow in the channels. The second step of the homogenization leads to
a macroscopic model involving three equations for displacements, the mesoscopic
flow velocity and the micropore pressure. Due to interactions between the two
porosities, the macroscopic flow is governed by a Darcy-Brinkman model
comprising two equations which are coupled with the overall equilibrium
equation respecting the hierarchical structure of the two-phase medium.
Expressions of the effective macroscopic parameters of the homogenized
double-porosity continuum are derived, depending on the characteristic
responses of the mesoscopic structure. Some symmetry and reciprocity
relationships are shown and issues of boundary conditions are discussed. The
model has been implemented in the finite element code SfePy which is
well-suited for computational homogenization. A numerical example of solving a
nonstationary problem using mixed finite element method is included.


  Accurate sensor calibration is a prerequisite for multi-sensor perception and
localization systems for autonomous vehicles. The intrinsic parameter
calibration of the sensor is to obtain the mapping relationship inside the
sensor, and the extrinsic parameter calibration is to transform two or more
sensors into a unified spatial coordinate system. Most sensors need to be
calibrated after installation to ensure the accuracy of sensor measurements. To
this end, we present OpenCalib, a calibration toolbox that contains a rich set
of various sensor calibration methods. OpenCalib covers manual calibration
tools, automatic calibration tools, factory calibration tools, and online
calibration tools for different application scenarios. At the same time, to
evaluate the calibration accuracy and subsequently improve the accuracy of the
calibration algorithm, we released a corresponding benchmark dataset. This
paper introduces various features and calibration methods of this toolbox. To
our knowledge, this is the first open-sourced calibration codebase containing
the full set of autonomous-driving-related calibration approaches in this area.
We wish that the toolbox could be helpful to autonomous driving researchers. We
have open-sourced our code on GitHub to benefit the community. Code is
available at https://github.com/PJLab-ADG/SensorsCalibration.


  We introduce the logics GLP(\Lambda), a generalization of Japaridze's
polymodal provability logic GLP(\omega) where \Lambda is any linearly ordered
set representing a hierarchy of provability operators of increasing strength.
  We shall provide a reduction of these logics to GLP(\omega) yielding among
other things a finitary proof of the normal form theorem for the variable-free
fragment of GLP(\Lambda) and the decidability of GLP(\Lambda) for recursive
orderings \Lambda. Further, we give a restricted axiomatization of the
variable-free fragment of GLP(\Lambda).


  Effective utilization of Multiple-Instruction-Multiple-Data (MIMD) parallel
computers requires the application of good load balancing techniques. In this
paper we show that heuristics derived from observation of complex natural
systems, such as the mammalian immune system, can lead to effective load
balancing strategies. In particular, the immune system processes of regulation,
suppression, tolerance, and memory are seen to be powerful load balancing
mechanisms.
  We provide a detailed example of our approach applied to parallelization of
an image processing task, that of extracting the circuit design from the images
of the layers of a CMOS integrated circuit. The results of this experiment show
that good speedup characteristics can be obtained when using immune system
derived load balancing strategies.


  Granular systems confined in vertically vibrated shallow horizontal boxes
(quasi two-dimensional geometry) present a liquid to solid phase transition
when the frequency of the periodic forcing is increased. An effective model,
where grains move and collide in two-dimensions is presented, which reproduces
the aforementioned phase transition. The key element is that besides the
two-dimensional degrees of freedom, each grain has an additional variable
$\epsilon$ that accounts for the kinetic energy stored in the vertical motion
in the real quasi two-dimensional motion. This energy grows monotonically
during free flight, mimicking the energy gain by collisions with the vibrating
walls and, at collisions, this energy is instantaneously transferred to the
horizontal degrees of freedom. As a result, the average values of $\epsilon$
and the kinetic temperature are decreasing functions of the local density,
giving rise to an effective pressure that can present van der Waals loops. A
kinetic theory approach predicts the conditions that must satisfy the energy
grow function to obtain the phase separation, which are verified with molecular
dynamics simulations. Notably, the effective equation of state and the critical
points computed considering the velocity--time-of-flight correlations differ
only slightly from those obtained by simple kinetic theory calculations that
neglect those correlations.


  Using early data from the Infrared Array Camera (IRAC) on the Spitzer Space
Telescope, taken for the Great Observatories Origins Deep Survey (GOODS), we
identify and study objects that are well-detected at 3.6um, but are very faint
(and in some cases, invisible) in the Hubble Ultra Deep Field (HUDF) ACS and
NICMOS images and in very deep VLT Ks-band imaging. We select a sample of 17
objects with f_nu(3.6um)/f_nu(z_{850})>20. The analysis of their spectral
energy-distributions (SEDs) from 0.4 to 8.0um shows that the majority of these
objects cannot be satisfactorily explained without a well-evolved stellar
population. We find that most of them can be well fitted by a simple
two-component model, where the primary component represents a massive, old
population that dominates the strong IR emission, while the secondary component
represents a low amplitude, on-going star-formation process that accounts for
the weak optical fluxes. Their estimated photometric redshifts (z_p) range from
1.6 to 2.9, with the median at z_p=2.4. For the simple star formation histories
considered here, their corresponding stellar masses range from 0.1 to 1.6e11
M_sun for a Chabrier Initial Mass Function (IMF). Their median rest-frame
Ks-band absolute magnitude is -22.9 mag in AB system, or 1.5xL*(K) for
present--day elliptical galaxies. In the scenario of pure luminosity evolution,
such objects may be direct progenitors for at least 14 to 51% of the local
population of early--type galaxies. Due to the small cosmic volume of the HUDF,
however, this simple estimate could be affected by other effects such as cosmic
variance and the strong clustering of massive galaxies. A full analysis of the
entire GOODS area is now underway to assess such effects.