  We present a new characterization of partially coherent electric and magnetic
wave vector fields.This characterization is based on the 36 auto/cross
correlations of the 3+3 complex Cartesian components of the electric and
magnetic wave fields and is particularly suited for analyzing electromagnetic
wave data on board spacecraft. Data from spacecraft based electromagnetic wave
instruments are usually processed as data arrays. These data arrays however do
not have a physical interpretation in themselves; they are simply a convenient
storage format. In contrast, the characterization proposed here contains
exactly the same information but are in the form of manifestly covariant
space-time tensors. We call this data format the Canonical Electromagnetic
Observables (CEO) since they correspond to unique physical observables. Some of
them are already known, such as energy density, Poynting flux, stress tensor,
etc, while others should be relevant in future space research. As an example we
use this formalism to analyze data from a chorus emission in the mid-latitude
magnetosphere, as recorded by the STAFF-SA instrument on board the Cluster-II
spacecraft.


  We introduce in this work the normalizing field flows (NFF) for learning
random fields from scattered measurements. More precisely, we construct a
bijective transformation (a normalizing flow characterizing by neural networks)
between a Gaussian random field with the Karhunen-Lo\`eve (KL) expansion
structure and the target stochastic field, where the KL expansion coefficients
and the invertible networks are trained by maximizing the sum of the
log-likelihood on scattered measurements. This NFF model can be used to solve
data-driven forward, inverse, and mixed forward/inverse stochastic partial
differential equations in a unified framework. We demonstrate the capability of
the proposed NFF model for learning Non Gaussian processes and different types
of stochastic partial differential equations.


  Several large-scale gravitational wave (GW) interferometers have achieved
long term operation at design sensitivity. Questions arise on how to best
combine all available data from detectors of different sensitivities for
detection, consistency check or veto, localization and waveform extraction. We
show that these problems can be formulated using the singular value
decomposition (SVD) method. We present techniques based on the SVD method for
(1) detection statistic, (2) stable solutions to waveforms, (3) null-stream
construction for an arbitrary number of detectors, and (4) source localization
for GWs of unknown waveforms.


  The evaporation-induced self-assembling of a few-layer graphene results in
macroscopic branched fractal-like conductive patterns with reduced percolation
thresholds.


  We summarize recent work on the structure and dynamics of the Galactic bar
and inner disk. Current work focusses on constructing a quantitative model
which integrates NIR photometry, source count observations, gas kinematics,
stellar dynamical observations, and microlensing. Some avenues for future
research are discussed.


  Using the Rossi X-ray Timing Explorer we have measured lags of the 9 to 33
keV photons relative to the 2 to 9 keV photons in the timing noise between 0.01
and 100 Hz in the accreting neutron stars 4U 0614+091 and 4U 1705-44. We
performed similar measurements on the accreting black hole candidates Cyg X-1
and GX 339-4 as a comparison. During the observations these sources were all in
low (hard) states. We find phase lags of between 0.03 and 0.2 radians in all
these sources, with a variation in frequency much less than expected for a lag
constant in time. We also measure a coherence consistent with unity in all
sources. As already noted for the black hole candidates, these data are
inconsistent with simple Comptonization models invoking a constant time delay.
Comptonization in a non-uniform medium can perhaps explain the lags. However,
the magnitudes of the lags imply that the hot electron gas extends to more than
1000 Schwarzschild radii. This may constitute an energy problem. We argue that
while a large hot cloud is possible for black holes which may hide some of
their accretion energy in advection, such a distribution may not be possible
neutron stars where all the accretion energy is eventually released at the
neutron star surface. This casts doubt on the Comptonization model, though the
energy problem may be resolved for example by a wind from the inner disk.


  We consider the cross-section of electromagnetic production of $e^+ e^-$ pair
in adiabatic scattering of heavy nuclei.


  In this work we report a theoretical study of the lateral resolution granted
by a simple glass microcylinder. In this 2D study, we had in mind the 3D
analogue -- a microsphere whose ability to form a deeply subwavelength and
strongly magnified image of submicron objects has been known since 2011.
Conventionally, the microscope in which such the image is observed is tuned so
that to see the areas behind the microsphere. This corresponds to the location
of the virtual source formed by the microsphere at a distance longer than the
distance of the real source to the miscroscope. Recently, we theoretically
found a new scenario of superresolution, when the virtual source is formed in
the wave beam transmitted through the microsphere. However, in this work we
concentrated on the case when the superresolution is achieved in the
impractical imaging system, in which the microscope objective lens is replaced
by a microlens located at a distance smaller than the Rayleigh range. The
present paper theoretically answers an important question: which scenario of
far-field nanoimaging by a microsphere grants the finest spatial at very large
distances. We found that the novel scenario (corresponding to higher refractive
indices) promises further enhancement of the resolution.


  Following up on earlier work on the regularization of the singular
Schwarzschild solution, we now apply the same procedure to the singular
Friedmann solution. Specifically, we are able to remove the divergences of the
big bang singularity, at the price of introducing a 3-dimensional spacetime
defect with a vanishing determinant of the metric. This particular
regularization also suggests the existence of a "pre-big-bang" phase.


  The goal of this work is to build a classifier that can identify text
complexity within the context of teaching reading to English as a Second
Language (ESL) learners. To present language learners with texts that are
suitable to their level of English, a set of features that can describe the
phonological, morphological, lexical, syntactic, discursive, and psychological
complexity of a given text were identified. Using a corpus of 6171 texts, which
had already been classified into three different levels of difficulty by ESL
experts, different experiments were conducted with five machine learning
algorithms. The results showed that the adopted linguistic features provide a
good overall classification performance (F-Score = 0.97). A scalability
evaluation was conducted to test if such a classifier could be used within real
applications, where it can be, for example, plugged into a search engine or a
web-scraping module. In this evaluation, the texts in the test set are not only
different from those from the training set but also of different types (ESL
texts vs. children reading texts). Although the overall performance of the
classifier decreased significantly (F-Score = 0.65), the confusion matrix shows
that most of the classification errors are between the classes two and three
(the middle-level classes) and that the system has a robust performance in
categorizing texts of class one and four. This behavior can be explained by the
difference in classification criteria between the two corpora. Hence, the
observed results confirm the usability of such a classifier within a real-world
application.


  In this paper we theoretically study exact recovery of sparse vectors from
compressed measurements by minimizing a general nonconvex function that can be
decomposed into the sum of single variable functions belonging to a class of
smooth nonconvex sparsity promoting functions. Null space property (NSP) and
restricted isometry property (RIP) are used as key theoretical tools. The
notion of \emph{scale function} associated to a sparsity promoting function is
introduced to generalize the state-of-the-art analysis technique of the $l_p$
minimization problem. The analysis is used to derive an upper bound on the null
space constant (NSC) associated to this general nonconvex minimization problem,
which is further utilized to derive sufficient conditions for exact recovery as
upper bounds on the restricted isometry constant (RIC), as well as bounds on
optimal sparsity $K$ for which exact recovery occurs. The derived bounds are
explicitly calculated when the sparsity promoting function $f$ under
consideration possesses the property that the associated \emph{elasticity
function}, defined as, $\psi(x)=\frac{xdf(x)/dx}{f(x)}$, is monotonic in
nature. Numerical simulations are carried out to verify the efficacy of the
bounds and interesting conclusions are drawn about the comparative performances
of different sparsity promoting functions for the problem of $1$-sparse signal
recovery.


  Given $H\in [0,1)$ and given a $C^0$ exterior domain $\Omega$ in a
$H-$hypersphere of $\mathbb{H}^3,$ the existence of hyperbolic Killing graphs
of CMC $H$ defined in $\overline{\Omega}$ with boundary $ \partial \Omega $
included in the $H-$hypersphere is obtained.


  We illustrate using a quantum system the principle of a cryptographic switch,
in which a third party (Charlie) can control to a continuously varying degree
the amount of information the receiver (Bob) receives, after the sender (Alice)
has sent her information. Suppose Charlie transmits a Bell state to Alice and
Bob. Alice uses dense coding to transmit two bits to Bob. Only if the 2-bit
information corresponding to choice of Bell state is made available by Charlie
to Bob can the latter recover Alice's information. By varying the information
he gives, Charlie can continuously vary the information recovered by Bob. The
performance of the protocol subjected to the squeezed generalized amplitude
damping channel is considered. We also present a number of practical situations
where a cryptographic switch would be of use.


  Efficient inference in Large Language Models (LLMs) is impeded by the growing
memory demands of key-value (KV) caching, especially for longer sequences.
Traditional KV cache eviction strategies, which prioritize less critical
KV-pairs based on attention scores, often degrade generation quality, leading
to issues such as context loss or hallucinations. To address this, we introduce
Dynamic Discriminative Operations (D2O), a novel method that utilizes two-level
discriminative strategies to optimize KV cache size without fine-tuning, while
preserving essential context. Initially, by observing varying densities of
attention weights between shallow and deep layers, we use this insight to
determine which layers should avoid excessive eviction to minimize information
loss. Subsequently, for the eviction strategy in each layer, D2O innovatively
incorporates a compensation mechanism that maintains a similarity threshold to
re-discriminate the importance of previously discarded tokens, determining
whether they should be recalled and merged with similar tokens. Our approach
not only achieves significant memory savings and enhances inference throughput
by more than 3 times but also maintains high-quality long-text generation.
Extensive experiments across various benchmarks and LLM architectures have
demonstrated that D2O significantly enhances performance with a constrained KV
cache budget.


  In this paper we introduce the new notion of complex isoparametric functions
on Riemannian manifolds. These are then employed to devise a general method for
constructing proper $p$-harmonic functions. We then apply this to construct the
first known explicit proper $p$-harmonic functions on the Lie group semidirect
products $\mathbb{R}^m \ltimes \mathbb{R}^n$ and $\mathbb{R}^m \ltimes
\mathrm{H}^{2n+1}$, where $\mathrm{H}^{2n+1}$ denotes the classical
$(2n+1)$-dimensional Heisenberg group. In particular, we construct such
examples on all the simply connected irreducible four-dimensional Lie groups.


  We discuss a problem of parameter estimation for quantum two-level system,
qubit system, in presence of unknown phase parameter. We analyze trade-off
relations for mean-square errors when estimating relevant parameters with
separable measurements based on known precision bounds; the symmetric
logarithmic derivative Cramer-Rao bound and Hayashi-Gill-Massar (HGM) bound. We
investigate the optimal measurement which attains the HGM bound and discuss its
properties. We show that the HGM bound for relevant parameters can be attained
asymptotically by using some fraction of given $n$ quantum states to estimate
the phase parameter. We also discuss the Holevo bound which can be attained
asymptotically by a collective measurement.


  Photosynthesis, the process by which energy from sunlight drives cellular
metabolism, relies on a unique organization of light-harvesting and reaction
center complexes. Recently, the organization of light-harvesting LH2 complexes
and dimeric reaction center-light harvesting I-PufX (RC-LH1-PufX) core
complexes in membranes of purple non-sulfur bacteria was revealed by atomic
force microscopy (AFM)1. Here, we report that the structure of LH2 and its
organization within the membrane can be largely rationalized by a simple
physical model that relies primarily on exciton transfer optimization. The
process through which the light-harvesting complexes transfer excitation energy
has been recognized to incorporate both coherent and incoherent processes
mediated by the surrounding protein environment. Using the Haken-Strobl model,
we show that the organization of the complexes in the membrane can be almost
entirely explained by simple electrostatic considerations and that quantum
effects act primarily to enforce robustness with respect to spatial disorder
between complexes. The implications of such an arrangement are discussed in the
context of biomimetic photosynthetic analogs capable of transferring energy
efficiently across tens to hundreds of nanometers


  We present a novel method to measure transient photovoltage at nanointerfaces
using ultrafast electron diffraction. In particular, we report our results on
the photoinduced electronic excitations and their ensuing relaxations in a
hydroxyl-terminated silicon surface, a standard substrate for fabricating
molecular electronics interfaces. The transient surface voltage is determined
by observing Coulomb refraction changes induced by the modified space-charge
barrier within a selectively probed volume by femtosecond electron pulses. The
results are in agreement with ultrafast photoemission studies of surface state
charging, suggesting a charge relaxation mechanism closely coupled to the
carrier dynamics near the surface that can be described by a drift-diffusion
model. This study demonstrates a newly implemented ultrafast diffraction method
for investigating interfacial processes, with both charge and structure
resolution.


  We show that quantum coherence can enhance the performance of a continuous
quantum heat engine in the Lindblad description. We investigate the
steady-state solutions of the particle-exchanging quantum heat engine, composed
of degenerate double quantum dots coupled to two heat baths in parallel, where
quantum coherence may be induced due to interference between relaxation
channels. We find that the engine power can be enhanced by the coherence in the
nonlinear response regime, when the symmetry of coupling configurations between
dots and two baths is broken. In the symmetric case, the coherence cannot be
maintained in the steady state, except for the maximum interference degenerate
case, where initial-condition-dependent multiple steady states appear with a
dark state.


  The use of reinforcement learning (RL) in practical applications requires
considering sub-optimal outcomes, which depend on the agent's familiarity with
the uncertain environment. Dynamically adjusting the level of epistemic risk
over the course of learning can tactically achieve reliable optimal policy in
safety-critical environments and tackle the sub-optimality of a static risk
level. In this work, we introduce a novel framework, Distributional RL with
Online Risk Adaption (DRL-ORA), which can quantify the aleatory and epistemic
uncertainties compositely and dynamically select the epistemic risk levels via
solving a total variation minimization problem online. The risk level selection
can be efficiently achieved through grid search using a Follow-The-Leader type
algorithm, and its offline oracle is related to "satisficing measure" (in the
decision analysis community) under a special modification of the loss function.
We show multiple classes of tasks where DRL-ORA outperforms existing methods
that rely on either a fixed risk level or manually predetermined risk level
adaption. Given the simplicity of our modifications, we believe the framework
can be easily incorporated into most RL algorithm variants.


  We reexamine Chew's method for extracting the $\pi NN$ coupling constant from
np differential cross section measurements. Values for this coupling are
extracted below 350 MeV, in the potential model region, and up to 1 GeV. The
analyses to 1~GeV have utilized 55 data sets. We compare these results to those
obtained via $\chi^2$ mapping techniques. We find that these two methods give
consistent results which are in agreement with previous Nijmegen
determinations.


  We report on a non-perturbative study of two dimensional $\cN=(2,2)$ super
QCD. Our lattice formulation retains a single exact supersymmetry at non-zero
lattice spacing, and contains $N_f$ fermions in the fundamental representation
of a $U(N_c)$ gauge group. The lattice action we employ contains an additional
Fayet-Iliopoulos term which is also invariant under the exact lattice
supersymmetry. This work constitutes the first numerical study of this theory
which serves as a toy model for understanding some of the issues that are
expected to arise in four dimensional super QCD. We present evidence that the
exact supersymmetry breaks spontaneously when $N_f<N_c$ in agreement with
theoretical expectations.


  Lenia is a continuous generalization of Conway's Game of Life. Bert Wang-Chak
Chan has discovered and published many seemingly organic dynamics in his Lenia
simulations since 2019. These simulations follow the Euler curve algorithm
starting from function space initial conditions. The Picard-Lindel\"of Theorem
for the existence of integral curves to Lipschitz vector fields on Banach
spaces fails to guarantee solutions, because the vector field associated with
the integro-differential equation defining Lenia is discontinuous. However, we
demonstrate the dynamic Chan is using to generate simulations is actually an
arc field and not the traditional Euler method for the vector field derived
from the integro-differential equation. Using arc field theory we prove the
Euler curves converge to a unique flow which solves the original
integro-differential equation. Extensions are explored and the modeling of
entropy is discussed.
  Keywords: arc fields; discontinuous vector fields; integro-differential
equations; entropy models


  The final analysis of the Extensive Air Shower (EAS) maximum X_max depth
distribution derived from the data of Tunka-25 atmospheric Cherenkov light
array in the energy range 3.10^15 - 3.10^16 eV is presented. The perspectives
of X_max studies with the new Cherenkov light array Tunka-133 of 1 km^2 area,
extending the measurements up to 10^18 eV, are discussed.


  An integrable two-component nonlinear Schr\"odinger equation in $2+1$
dimensions is presented. The singular manifold method is applied in order to
obtain a three-component Lax pair. The Lie point symmetries of this Lax pair
are calculated in terms of nine arbitrary functions and one arbitrary constant
that yield a non-trivial infinite-dimensional Lie algebra. The main non-trivial
similarity reductions associated to these symmetries are identified. The
spectral parameter of the reduced spectral problem appears as a consequence of
one of the symmetries.


  Let $L$ be the infinitesimal generator of an analytic semigroup on $L^2(R^n)$
with Gaussican kernel bounds, and let $L^{-\alpha/2}$ be the fractional
integrals of $L$ for $0<\alpha<n.$ For any locally integrable function $b$, The
commutators associated with $L^{-\alpha/2}$ are defined by
$[b,L^{-\alpha/2}](f)(x)=b(x)L^{-\alpha/2}(f)(x)-L^{-\alpha/2}(bf)(x)$. When
$b\in BMO(\omega)$(weighted $BMO$ space) or $b\in BMO$, the author obtain the
necessary and sufficient conditions for the boundedness of $[b,L^{-\alpha/2}]$
on weighted Morrey spaces respectively.


  We are considering the commuting variety of the Lie algebra
$\mathfrak{pgl}_n$ over an algebraically closed field of characteristic $p >0$,
namely the set of pairs $ \{ (A,B) \in \mathfrak{pgl}_n \times \mathfrak{pgl}_n
\mid [A,B]=0 \} $. We prove that if $n=pr$, then there are precisely two
irreducible components, of dimensions $n^2+r-1$ and $n^2+n-2$. We also prove
that the variety $\{ (x,y) \in GL_n(k) \times GL_n(k) \mid [x,y]=\zeta I \}$ is
irreducible of dimension $n^2 +n/d$, where $\zeta$ is a root of unity of order
$d$ with $d$ dividing $n$.


  With the surge in data-centric AI and its increasing capabilities, AI
applications have become a part of our everyday lives. However,
misunderstandings regarding their capabilities, limitations, and associated
advantages and disadvantages are widespread. Consequently, in the university
setting, there is a crucial need to educate not only computer science majors
but also students from various disciplines about AI. In this experience report,
we present an overview of an introductory course that we offered to students
coming from different majors. Moreover, we discuss the assignments and quizzes
of the course, which provided students with a firsthand experience of AI
processes and insights into their learning patterns. Additionally, we provide a
summary of the course evaluation, as well as students' performance. Finally, we
present insights gained from teaching this course and elaborate on our future
plans.


  We consider a new approach to describe a quantum optical Bose-system with
internal Gell-Mann symmetry by the SU(3)-symmetry polarization map in Hilbert
space. The operational measurement in density (or coherency) matrix elements
for the three mode optical field is discussed for the first time. We have
introduced a set of operators that describes the quantum measurement procedure
and the behavior of fluctuations for the amplitude and phase characteristics of
three level system. The original twelve-port interferometer for parallel
measurements of the Gell-Mann parameters is proposed. The quantum properties of
W-qutrit states under the measurement procedure are examined.


  We report the existence of moir\'e patterns and magic angle physics in all
families of chiral collapsed carbon nanotubes. A detailed study of the
electronic structure of all types of chiral nanotubes, previously collapsed via
molecular dynamics, has been performed. We find that each family possesses a
unique geometry and moir\'e disposition, as well as a characteristic number of
flat bands. Remarkably, all kinds of nanotubes behave the same with respect to
magic angle tuning, showing a monotonic behavior that gives rise to magic
angles in full agreement with those of twisted bilayer graphene. Therefore,
magic angle behavior is universally found in chiral collapsed nanotubes with a
small chiral angle, giving rise to moir\'e patterns. Our approach comprises
first-principles and semi-empirical calculations of the band structure, density
of states and spatial distribution of the localized states signaled by flat
bands.


  Lyotropic cholesteric liquid crystal phases are ubiquitously observed in
biological and synthetic polymer solutions, characterized by a complex
interplay between thermal fluctuations, entropic and enthalpic forces. The
elucidation of the link between microscopic features and macroscopic chiral
structure, and of the relative roles of these competing contributions on phase
organization, remains a topical issue. Here we provide theoretical evidence of
a novel mechanism of chirality amplification in lyotropic liquid crystals,
whereby phase chirality is governed by fluctuation-stabilized helical
deformations in the conformations of their constituent molecules. Our results
compare favorably to recent experimental studies of DNA origami assemblies and
demonstrate the influence of intra-molecular mechanics on chiral
supra-molecular order, with potential implications for a broad class of
experimentally-relevant colloidal systems.


  Point source localisation is generally modelled as a Lasso-type problem on
measures. However, optimisation methods in non-Hilbert spaces, such as the
space of Radon measures, are much less developed than in Hilbert spaces. Most
numerical algorithms for point source localisation are based on the Frank-Wolfe
conditional gradient method, for which ad hoc convergence theory is developed.
We develop extensions of proximal-type methods to spaces of measures. This
includes forward-backward splitting, its inertial version, and primal-dual
proximal splitting. Their convergence proofs follow standard patterns. We
demonstrate their numerical efficacy.


  We derive a universal expression for the gravitational radiation energy
spectrum $dE^{GW}/d\omega$ at sub-leading order emitted from a generic
gravitational hard scattering of multi-particles or multi-bodies. Our result
includes all $\mathcal{O}(\omega)$ corrections to the gravitational radiation
flux from a generic $2\rightarrow N$ collision, in both the cases of massless
and massive particles/bodies. We also show the dependence of the radiation
energy fluxby the quantum spin in case of particle collisions. Then, we
consider the specific case of a gravitational elastic scattering of two massive
bodies, i.e. $m+M\rightarrow m+M$ with $m,M$ the masses of the two bodies
respectively. We demonstrate that in this case all $\mathcal{O}(\omega)$
contributions to the energy flux exactly cancel each others. Nevertheless, we
also show that, for a $2\rightarrow 2$ inelastic scattering, the inclusion of
sub-leading soft gravitons leads to a not zero radiation flux, having a simple
expression in certain asymptotic regimes. Our results can be applied to the
case of Black Holes' collisions with possible testable implications in
gravitational waves physics.


  We investigate the quantum recoil force acting on an excited atom close to
the surface of a nonreciprocal photonic topological insulator (PTI). The main
atomic emission channel is the unidirectional surface-plasmon propagating at
the PTI-vacuum interface, and we show that it enables a spontaneous lateral
recoil force that scales at short distance as $1/d^4$, where $d$ is the
atom-PTI separation. Remarkably, the sign of the recoil force is polarization
and orientation-independent, and it occurs in a translation-invariant
homogeneous system in thermal equilibrium. Surprisingly, the recoil force
persists for very small values of the gyration pseudovector, which, for a
biased plasma, corresponds to very low cyclotron frequencies. The ultra-strong
recoil force is rooted on the quasi-hyperbolic dispersion of the
surface-plasmons. We consider both an initially excited atom and a continuous
pump scenario, the latter giving rise to a continuous lateral force whose
direction can be changed at will by simply varying the orientation of the
biasing magnetic field. Our predictions may be tested in experiments with cold
Rydberg atoms and superconducting qubits.


  We describe a new, direct method for determining the opacity of foreground
galaxies which does not require any a priori assumptions about the spatial
distribution or the reddening law of the obscuring material. The method is to
measure the colors and counts of background galaxies which can be identified
through the foreground system. The method is calibrated, and the effects of
confusion and obscuration are decoupled by adding various versions of a
suitable deep reference frame containing only field galaxies with known
properties into the image of the foreground galaxy, and analyzing these
``synthetic field'' images in the same way as the real images. We test the
method on HST WFPC2 archived images of two galaxies which are quite different:
NGC 4536 is a large Sc spiral, and NGC 3664 is a small Magellanic irregular.
The reference frames are taken from the Hubble Deep Field.
  From the background galaxy counts, NGC 4536 shows an extinction A_I ~ 1 mag
in the northwestern arm region, and lower than 0.5 mag in the corresponding
interarm region (no correction for inclination has been attempted). However,
from the galaxy colors, the same reddening of E(V - I) ~ 0.2 is observed in
both the arm and the interarm regions. In the interarm region, the combination
of extinction and reddening can be explained by a diffuse component with a
Galactic reddening law (R_V ~ 3). In the spiral arm, however, the same diffuse,
low opacity component seems to coexist with regions of much higher opacity.
Since the exposures are shorter the results for NGC 3664 are less clear, but
also appear to be consistent with a two component distribution.


  We discuss how a level-1 trigger, about 8 us after a hadron-hadron collision,
can be derived from the Transition Radiation Detector (TRD) in A Large Ion
Collider Experiment (ALICE) at the LHC. Chamber-wise track segments from fast
on-detector reconstruction are read out with position, angle and electron
likelihood. In the Global Tracking Unit up to 6 tracklets from a particle
traversing the detector layers are matched and used for the reconstruction of
transverse momentum and electron identification. Such tracks form the basis for
versatile and flexible trigger conditions, e.g. single high-pt hadron, single
high-pt electron, di-electron (J/Psi, Upsilon) and at least n close high-pt
tracks (jet).
  The need for low-latency on-line reconstruction poses challenges on the
detector operation. The calibration for gain (pad-by-pad) and drift velocity
must be applied already in the front-end electronics. Due to changes in
pressure and gas composition an on-line monitoring and feedback loop for these
parameters is required. First experiences on the performance were gathered from
triggering in cosmic and pp runs.


  We study a nonlocal wave equation with logarithmic damping which is rather
weak in the low frequency zone as compared with frequently studied strong
damping case. We consider the Cauchy problem for this model in the whole space
and we study the asymptotic profile and optimal estimates of the solutions and
the total energy as time goes to infinity in L^{2}-sense. In that case some
results on hypergeometric functions are useful.


  In orbital-free density functional theory (OFDFT), an equation exists for
$\psi = \sqrt n$, the square root of the ground state electron density $n$. We
show that $\psi$ cannot be expanded as a linear combination of elements of a
complete set of basis functions except in the case of one or two electron
systems. This is unlike the case for the ground state of a system of identical
bosons in which the square root of the ground state bosonic density can have an
expansion as a linear combination of elements of a complete set of basis
functions.


  We study in detail the motions of three planets interacting with each other
under the influence of a central star. It is known that the system with more
than two planets becomes unstable after remaining quasi-stable for long times,
leading to highly eccentric orbital motions or ejections of some of the
planets. In this paper, we are concerned with the underlying physics for this
quasi-stability as well as the subsequent instability and advocate the
so-called "stagnant motion" in the phase space, which has been explored in the
field of dynamical system. We employ the Lyapunov exponent, the power spectra
of orbital elements and the distribution of the durations of quasi-stable
motions to analyze the phase space structure of the three-planet system, the
simplest and hopefully representative one that shows the instability. We find
from the Lyapunov exponent that the system is almost non-chaotic in the initial
quasi-stable state whereas it becomes intermittently chaotic thereafter. The
non-chaotic motions produce the horizontal dense band in the action-angle plot
whereas the voids correspond to the chaotic motions. We obtain power laws for
the power spectra of orbital eccentricities. Power-law distributions are also
found for the durations of quasi-stable states. All these results combined
together, we may reach the following picture: the phase space consists of the
so-called KAM tori surrounded by satellite tori and imbedded in the chaotic
sea. The satellite tori have a self-similar distribution and are responsible
for the scale-free power-law distributions of the duration times. The system is
trapped around one of the KAM torus and the satellites for a long time (the
stagnant motion) and moves to another KAM torus with its own satellites from
time to time, corresponding to the intermittent chaotic behaviors.


  Strong-field ionization, involving tunnel ionization and electron
rescattering, enables femtosecond time-resolved dynamics measurements of
chemical reactions involving radical cations. Here, we compare the formation of
CH3S+ following the strong-field ionization of the isomers CH3SCN and CH3NCS.
The former involves the release of neutral CN, while the latter involves an
intramolecular rearrangement. We find the intramolecular rearrangement takes
place on the single picosecond timescale and exhibits vibrational coherence.
Density functional theory and coupled-cluster calculations on the neutral and
singly ionized species help us determine the driving force responsible for
intramolecular rearrangement in CH3NCS. Our findings illustrate the complexity
that accompanies radical cation chemistry following electron ionization and
demonstrate a useful tool for understanding the cation dynamics after
ionization.


  We explore how the expulsion of gas from star-cluster forming cloud-cores due
to supernova explosions affects the shape of the initial cluster mass function,
that is, the mass function of star clusters when effects of gas expulsion are
over. We demonstrate that if the radii of cluster-forming gas cores are roughly
constant over the core mass range, as supported by observations, then more
massive cores undergo slower gas expulsion. Therefore, for a given star
formation efficiency, more massive cores retain a larger fraction of stars
after gas expulsion. The initial cluster mass function may thus differ from the
core mass function substantially, with the final shape depending on the star
formation efficiency. A mass-independent star formation efficiency of about 20
per cent turns a power-law core mass function into a bell-shaped initial
cluster mass function, while mass-independent efficiencies of order 40 per cent
preserve the shape of the core mass function.


  Whole atmosphere seeing \beta_0 is the most important parameter in site
testing measurements. Estimation of the seeing from a variance of differential
image motion is always biased by a non-zero DIMM exposure, which results in a
wind smoothing. In the paper, the wind effects are studied within short
exposure approximation, i.e. when the wind shifts turbulence during exposure by
distance lesser than device aperture. The method of correction for this effect
on the base of image motion correlation between adjacent frames is proposed. It
is shown that the correlation can be used for estimation of the mean wind speed
V_2 and atmospheric coherence time \tau_0. Total power of longitudinal and
transverse image motion is suggested for elimination of dependence on the wind
direction. Obtained theoretical results were tested on the data obtained on
Mount Shatdjatmaz in 2007--2010 with MASS/DIMM device and good agreement was
found.


  The expected value of partial perfect information (EVPPI) denotes the value
of eliminating uncertainty on a subset of unknown parameters involved in a
decision model. The EVPPI can be regarded as a decision-theoretic sensitivity
index, and has been widely used for identifying relatively important unknown
parameters. It follows from Jensen's inequality, however, that the standard
nested Monte Carlo computation of the EVPPI results in biased estimates. In
this paper we introduce two unbiased Monte Carlo estimators for the EVPPI based
on multilevel Monte Carlo method, introduced by Heinrich (1998) and Giles
(2008), and its extension by Rhee and Glynn (2012, 2015). Our unbiased
estimators are simple and straightforward to implement, and thus are of highly
practical use. Numerical experiments show that even the convergence behaviors
of our unbiased estimators are superior to that of the standard nested Monte
Carlo estimator.


  Consider a homogenous fluid membrane described by the Helfrich-Canham energy,
quadratic in the mean curvature of the membrane surface. The shape equation
that determines equilibrium configurations is fourth order in derivatives and
cubic in the mean curvature. We introduce a Hamiltonian formulation of this
equation which dismantles it into a set of coupled first order equations. This
involves interpreting the Helfrich-Canham energy as an action; equilibrium
surfaces are generated by the evolution of space curves. Two features
complicate the implementation of a Hamiltonian framework: (i) The action
involves second derivatives. This requires treating the velocity as a phase
space variable and the introduction of its conjugate momentum. The canonical
Hamiltonian is constructed on this phase space. (ii) The action possesses a
local symmetry -- reparametrization invariance. The two labels we use to
parametrize points on the surface are themselves physically irrelevant. This
symmetry implies primary constraints, one for each label, that need to be
implemented within the Hamiltonian. The two lagrange multipliers associated
with these constraints are identified as the components of the acceleration
tangential to the surface. The conservation of the primary constraints imply
two secondary constraints, fixing the tangential components of the momentum
conjugate to the position. Hamilton's equations are derived and the appropriate
initial conditions on the phase space variables are identified. Finally, it is
shown how the shape equation can be reconstructed from these equations.


  A collector wishes to collect $m$ complete sets of $N$ distinct coupons. The
draws from the population are considered to be independent and identical
distributed with replacement, and the probability that a type-$j$ coupon is
drawn is noted as $p_{j}$. Let $T_{m}(N)$ the number of trials needed for this
problem. We present the asymptotics for the expectation (five terms plus an
error), the second rising moment (six terms plus an error), and the variance of
$T_{m}(N)$ (leading term), as well as its limit distribution as $N\rightarrow
\infty$, when \begin{equation*} p_{j}=\frac{a_{j}}{\sum_{j=2}^{N+1} a_{j}},
\,\,\,\text{where}\,\,\, a_{j}=\left(\ln j\right)^{-p}, \,\,p>0.
\end{equation*} These "log-Zipf" classes of coupon probabilities are not
covered by the existing literature and the present paper comes to fill this
gap. Therefore, we enlarge the classes for which the collector's problem is
solved (moments, variance, distribution).


  We investigate the random flight process that arises as the Boltzmann-Grad
limit of a random scatterer Lorentz gas with variable scatterer density in a
gravitational field. For power function densities we show how the parameters of
the model determine recurrence or transience of the vertical component of the
trajectory. Finally, our methods show that, with appropriate scaling of space,
time and the density of obstacles, the trajectory of the particle converges to
a diffusion with explicitly given parameters.


  We consider deterministic mean field games where the dynamics of a typical
agent is non-linear with respect to the state variable and affine with respect
to the control variable. Particular instances of the problem considered here
are mean field games with control on the acceleration. We focus our attention
on the approximation of such mean field games by analogous problems in discrete
time and finite state space. For these approximations, we show the existence
and, under an additional monotonicity assumption, uniqueness of solutions. In
our main result, we establish the convergence of equilibria of the discrete
mean field games problems towards equilibria of the continuous one. Finally, we
provide some numerical results for two MFG problems. In the first one, the
dynamics of a typical player is nonlinear with respect to the state and, in the
second one, a typical player controls its acceleration.


  The invariant cross sections for direct photon production in hadron-hadron
collisions are calculated for several initial energies (SPS, ISR, S$p \bar p$S,
RHIC, Tevatron, LHC) including initial parton transverse momenta within the
formalism of unintegrated parton distributions (UPDF). Different approaches
from the literature are compared and discussed. A special emphasis is put on
the Kimber-Martin-Ryskin (KMR) distributions and their extension into the soft
region. Sum rules for UPDFs are formulated and discussed in detail. We find a
violation of naive number sum rules for the KMR UPDFs. An interesting interplay
of perturbative (large $k_t^2$) and nonperturbative (small $k_t^2$) regions of
UPDFs in the production of both soft and hard photons is identified. The
$k_t$-factorization approach with the KMR UPDFs is inconsistent with the
collinear approach at large transverse momenta of photons. Kwieci\'nski UPDFs
provide very good description of all world data, especially at SPS and ISR
energies. Off-shell effects are discussed and quantified. Predictions for the
CERN LHC are given. Very forward/backward regions in rapidity at LHC energy are
discussed and a possibility to test unintegrated gluon distributions (UGDF) is
presented.


  We investigate the suitability of nearly half-metallic ferrimagnetic
quaternary Heusler alloys, CoCrMnZ (Z=Al, Ga, Si, Ge) to assess the feasibility
as electrode materials of MgO-based magnetic tunnel junctions (MTJ). Low
magnetic moments of these alloys originated from the anti-ferromagnetic
coupling between Mn and Cr spins ensure a negligible stray field in spintronics
devices as well as a lower switching current required to flip their spin
direction. We confirmed mechanical stability of these materials from the
evaluated values of elastic constants, and the absence of any imaginary
frequency in their phonon dispersion curves. The influence of swapping
disorders on the electronic structures and their relative stability are also
discussed. A high spin polarization of the conduction electrons are observed in
case of CoCrMnZ/MgO hetrojunctions, independent of terminations at the
interface. Based on our ballistic transport calculations, a large coherent
tunnelling of the majority-spin $s$-like $\Delta_1$ states can be expected
through MgO-barrier. The calculated tunnelling magnetoresistance (TMR) ratios
are in the order of 1000\%. A very high Curie temperatures specifically for
CoCrMnAl and CoCrMnGa, which are comparable to $bcc$ Co, could also yield a
weaker temperature dependece of TMR ratios for CoCrMnAl/MgO/CoCrMnAl (001) and
CoCrMnGa/MgO/CoCrMnGa (001) MTJ.


  We propose an exact algorithm for solving biobjective integer programming
problems, which arise in various applications of operations research. The
algorithm is based on solving Pascoletti-Serafini scalarizations to search
specified regions (boxes) in the objective space and returns the set of
nondominated points. We implement the algorithm with different strategies,
where the choices of the scalarization model parameters and splitting rule
differ. We then derive bounds on the number of scalarization models solved; and
demonstrate the performances of the variants through computational experiments
both as exact algorithms and as solution approaches under time restriction. The
experiments demonstrate that different strategies have advantages in different
aspects: while some are quicker in finding the whole set of nondominated
solutions, others return good-quality solutions in terms of representativeness
when run under time restriction. We also compare the proposed approach with
existing algorithms. The results of our experiments show the satisfactory
behaviour of our algorithm, especially when run under time limit, as it
achieves better coverage of the whole frontier with a smaller number of
solutions compared to the existing algorithms.


  We review a recollement for derived categories of DG categories arising from
Drinfeld quotients. As an application we show that an exact sequence well-known
in K-theory descends to numerical K-groups provided that either the quotient or
the category we take the quotient with has a Serre functor, and if either the
quotient functor preserves compactness or if the K-group of the quotient is
torsion-free.


  Nondegenerate forms N of degree d on a unital nonassociative algebra A over a
ring R which permit composition, i.e., satisfy N(1)=1 and N(xy)=N(x)N(y) for
all x,y in A, are studied. These forms were first classified by Schafer over
fields of characteristic 0 or >d. We investigate cubic and quartic
nondegenerate forms which permit composition over certain rings and curves.
Classes of highly degenerate cubic forms N over fields which permit composition
are constructed.


  We constrain effective field theories by going beyond the familiar positivity
bounds that follow from unitarity, analyticity, and crossing symmetry of the
scattering amplitudes. As interesting examples, we discuss the implications of
the bounds for the Galileon and ghost-free massive gravity. The combination of
our theoretical bounds with the experimental constraints on the graviton mass
implies that the latter is either ruled out or unable to describe gravitational
phenomena, let alone to consistently implement the Vainshtein mechanism, down
to the relevant scales of fifth-force experiments, where general relativity has
been successfully tested. We also show that the Galileon theory must contain
symmetry-breaking terms that are at most one-loop suppressed compared to the
symmetry-preserving ones. We comment as well on other interesting applications
of our bounds.


  Manipulating the polarization of light on the microscale or nanoscale is
essential for integrated photonics and quantum optical devices. Nowadays, the
metasurface allows one to build on-chip devices that efficiently manipulate the
polarization states. However, it remains challenging to generate different
types of polarization states simultaneously, which is required to encode
information for quantum computing and quantum cryptography applications. By
introducing geometrical-scaling-induced (GSI) phase modulations, we demonstrate
that an assembly of circularly polarized (CP) and linearly polarized (LP)
states can be simultaneously generated by a single metasurface made of L-shaped
resonators with different geometrical features. Upon illumination, each
resonator diffracts the CP state with a certain GSI phase. The interaction of
these diffractions leads to the desired output beams, where the polarization
state and the propagation direction can be accurately tuned by selecting the
geometrical shape, size, and spatial sequence of each resonator in the unit
cell. As an example of potential applications, we show that an image can be
encoded with different polarization profiles at different diffraction orders
and decoded with a polarization analyzer. This approach resolves a challenging
problem in integrated optics and is inspiring for on-chip quantum information
processing.


  Causal Dynamical Triangulations (CDT) is a non-perturbative quantisation of
general relativity. Ho\v{r}ava-Lifshitz gravity on the other hand modifies
general relativity to allow for perturbative quan- tisation. Past work has
given rise to the speculation that Ho\v{r}ava-Lifshitz gravity might correspond
to the continuum limit of CDT. In this paper we add another piece to this
puzzle by applying the CDT quantisation prescription directly to
Ho\v{r}ava-Lifshitz gravity in 2 dimensions. We derive the continuum
Hamiltonian and we show that it matches exactly the Hamiltonian one derives
from canonically quantising the Ho\v{r}ava-Lifshitz action. Unlike the standard
CDT case, here the intro- duction of a foliated lattice does not impose further
restriction on the configuration space and, as a result, lattice quantisation
does not leave any imprint on continuum physics as expected.


  The hydrogen binding energy in the Pauli-Fierz model with the spin Zeeman
term is determined up to the order alpha cube, where alpha denotes the
fine-structure constant.


  An exact de Sitter solution of scalar-tensor gravity is found, in which the
non-minimal coupling scalar is rolling along a non-constant potential. Based on
this solution, a dust-filled FRW universe is explored in frame of scalar-tensor
gravity. The effective dark energy induced by the sole non-minimal scalar can
be quintessence-like, phantom-like, and more significantly, can cross the
phantom divide. The rich and varied properties of scalar-tensor gravity even
with only one scalar is shown in this article.


  We have carried out a fluctuation analysis in four bands (R4, R5, R6 and R7
corresponding to 0.44-1.01 keV, 0.56-1.21 keV, 0.73-1.56 keV and to 1.05-2.04
keV respectively) of two very deep ROSAT PSPC observations in directions where
the galactic H{\small I} column is minimal. This has enabled us to study the
average spectrum of the sources contributing to 0.5-2 keV fluxes $\sim 10^{-15}
\rm \ergpcmsqps$. The best fit spectral energy index for the average faint
source spectrum, $\alpha=0.95^{+0.10}_{-0.15}$, is still steeper than the one
measured for the extragalactic XRB at these energies $\alpha\sim 0.4-0.7$, but
flatter than the typical AGN spectral index $\alpha\sim 1-1.5$. This result has
allowed us to constrain the existence of a population of sources harder than
the AGNs contributing to the source counts at these fluxes. We find that a
population of X-ray sources with energy spectral index $\alpha\sim 0.4-0.6$
would contribute $(30\pm 20)$ per cent to the source counts at these fluxes if
the rest of them are AGNs with energy spectral index $\alpha\sim 1.2$.


  We consider rotations on the torus $\mathbb{T}^2$, and we classify them with
respect to the complexity functions. In dimension one, a minimal rotation can
be coded by a sturmian word. A sturmian word has complexity $n+1$ by the
Morse-Hedlund theorem. Here we make a generalization in dimension two.


  A search is performed for a new resonance decaying into a lighter resonance
and a Z boson. Two channels are studied, targeting the decay of the lighter
resonance into either a pair of oppositely charged tau leptons or a b b-bar
pair. The Z boson is identified via its decays to electrons or muons. The
search exploits data collected by the CMS experiment at a centre-of-mass energy
of 8 TeV, corresponding to an integrated luminosity of 19.8 inverse femtobarns.
No significant deviations are observed from the standard model expectation and
limits are set on production cross sections and parameters of two-Higgs-doublet
models.


  The original ideas about noncommuting coordinates are recalled. The
connection between U(1) gauge fields defined on noncommuting coordinates and
fluid mechanics is explained. Non-Abelian fluid mechanics is described.


  We employ the functional renormalization group to study the effects of
phonon-assisted tunneling on the nonequilibrium steady-state transport through
a single level molecular quantum dot coupled to electronic leads. Within the
framework of the spinless Anderson-Holstein model, we focus on small to
intermediate electron-phonon couplings, and we explore the evolution from the
adiabatic to the antiadiabatic limit and also from the low-temperature
non-perturbative regime to the high temperature perturbative one. We identify
the phononic signatures in the bias-voltage dependence of the electrical
current and the differential conductance. Considering a temperature gradient
between the electronic leads, we further investigate the interplay between the
transport of charge and heat. Within the linear response regime, we compare the
temperature dependence of various thermoelectric coefficients to our earlier
results obtained within the numerical renormalization group [Phys.~Rev.~B {\bf
96}, 195156 (2017)]. Beyond the linear response regime, in the context of
thermoelectric generators, we discuss the influence of molecular vibrations on
the output power and the efficiency. We find that the molecular energy
dissipation, which is inevitable in the presence of phonons, is significantly
suppressed in the antiadiabatic limit resulting in the enhancement of the
thermoelectric efficiency.


  We extend the concept of exponential B-spline to complex orders. This
extension contains as special cases the class of exponential splines and also
the class of polynomial B-splines of complex order. We derive a time domain
representation of a complex exponential B-spline depending on a single
parameter and establish a connection to fractional differential operators
defined on Lizorkin spaces. Moreover, we prove that complex exponential splines
give rise to multiresolution analyses of $L^2(\mathbb{R})$ and define wavelet
bases for $L^2(\mathbb{R})$.


  Synchrotron X-ray diffraction experiment shows that the metal-insulator
transition occurring in a ferromagnetic state of a hollandite
K$_2$Cr$_8$O$_{16}$ is accompanied by a structural distortion from the
tetragonal $I4/m$ to monoclinic $P112_{1}/a$ phase with a
$\sqrt{2}\times\sqrt{2}\times 1$ supercell. Detailed electronic structure
calculations demonstrate that the metal-insulator transition is caused by a
Peierls instability in the quasi-one-dimensional column structure made of four
coupled Cr-O chains running in the $c$-direction, leading to the formation of
tetramers of Cr ions below the transition temperature. This furnishes a rare
example of the Peierls transition of fully spin-polarized electron systems.


  Snapshot back-ended reduced basis methods for dynamical systems commonly rely
on the singular value decomposition of a matrix whose columns are high-fidelity
solution vectors. An alternative basis generation framework is developed here.
The advocated maximum entropy snapshot sampling (MESS) identifies the snapshots
that encode essential information regarding the system's evolution, by
exploiting quantities that are suitable for quantifying a notion of dynamical
stability. The maximum entropy snapshot sampling enables a direct reduction of
the number of snapshots. A reduced basis is then obtained with any
orthonormalization process on the resulting reduced sample of snapshots. The
maximum entropy sampling strategy is supported by rigid mathematical
foundations, it is computationally efficient, and it is inherently automated
and easy to implement.


  Graph convolutional networks (GCNs) have recently enabled a popular class of
algorithms for collaborative filtering (CF). Nevertheless, the theoretical
underpinnings of their empirical successes remain elusive. In this paper, we
endeavor to obtain a better understanding of GCN-based CF methods via the lens
of graph signal processing. By identifying the critical role of smoothness, a
key concept in graph signal processing, we develop a unified graph
convolution-based framework for CF. We prove that many existing CF methods are
special cases of this framework, including the neighborhood-based methods,
low-rank matrix factorization, linear auto-encoders, and LightGCN,
corresponding to different low-pass filters. Based on our framework, we then
present a simple and computationally efficient CF baseline, which we shall
refer to as Graph Filter based Collaborative Filtering (GF-CF). Given an
implicit feedback matrix, GF-CF can be obtained in a closed form instead of
expensive training with back-propagation. Experiments will show that GF-CF
achieves competitive or better performance against deep learning-based methods
on three well-known datasets, notably with a $70\%$ performance gain over
LightGCN on the Amazon-book dataset.


  We present a detailed study to show the possibility of approaching the
quantum ground-state of a hybrid optomechanical quantum device formed by a
Bose-Einstein condensate (BEC) confined inside a high-finesse optical cavity
with an oscillatory end mirror. Cooling is achieved using two experimentally
realizable schemes: back-action cooling and cold damping quantum feedback
cooling. In both the schemes, we found that increasing the two body atom-atom
interaction brings the mechanical oscillator to its quantum ground state. It
has been observed that back-action cooling is more effective in the good cavity
limit while the cold damping cooling scheme is more relevant in the bad cavity
limit. It is also shown that in the cold damping scheme, the device is more
efficient in the presence of BEC than in the absence of BEC.


  With recent research advancements, deep learning models are becoming
attractive and powerful choices for speech enhancement in real-time
applications. While state-of-the-art models can achieve outstanding results in
terms of speech quality and background noise reduction, the main challenge is
to obtain compact enough models, which are resource efficient during inference
time. An important but often neglected aspect for data-driven methods is that
results can be only convincing when tested on real-world data and evaluated
with useful metrics. In this work, we investigate reasonably small recurrent
and convolutional-recurrent network architectures for speech enhancement,
trained on a large dataset considering also reverberation. We show interesting
tradeoffs between computational complexity and the achievable speech quality,
measured on real recordings using a highly accurate MOS estimator. It is shown
that the achievable speech quality is a function of network complexity, and
show which models have better tradeoffs.


  Several recent studies have reported different intrinsic correlations between
the AGN mid-IR luminosity ($L_{MIR}$) and the rest-frame 2-10 keV luminosity
($L_{X}$) for luminous quasars. To understand the origin of the difference in
the observed $L_{X}-L_{MIR}$ relations, we study a sample of 3,247
spectroscopically confirmed type 1 AGNs collected from Bo\"{o}tes, XMM-COSMOS,
XMM-XXL-North, and the SDSS quasars in the Swift/XRT footprint spanning over
four orders of magnitude in luminosity. We carefully examine how different
observational constraints impact the observed $L_{X}-L_{MIR}$ relations,
including the inclusion of X-ray non-detected objects, possible X-ray
absorption in type 1 AGNs, X-ray flux limits, and star formation contamination.
We find that the primary factor driving the different $L_{X}-L_{MIR}$ relations
reported in the literature is the X-ray flux limits for different studies. When
taking these effects into account, we find that the X-ray luminosity and mid-IR
luminosity (measured at rest-frame $6\mu m$, or $L_{6\mu m}$) of our sample of
type 1 AGNs follow a bilinear relation in the log-log plane: $\log L_X
=(0.84\pm0.03)\times\log L_{6\mu m}/10^{45}{\rm erg\;s^{-1}} + (44.60\pm0.01)$
for $L_{6\mu m} < 10^{44.79}{\rm erg\;s^{-1}} $, and $\log L_X =
(0.40\pm0.03)\times\log L_{6\mu m}/10^{45}{\rm erg\;s^{-1}} +(44.51\pm0.01)$
for $L_{6\mu m} \geq 10^{44.79}{\rm erg\;s^{-1}} $. This suggests that the
luminous type 1 quasars have a shallower $L_{X}-L_{MIR}$ correlation than the
approximately linear relations found in local Seyfert galaxies. This result is
consistent with previous studies reporting a luminosity-dependent
$L_{X}-L_{MIR}$ relation, and implies that assuming a linear $L_{X}-L_{MIR}$
relation to infer the neutral gas column density for X-ray absorption might
overestimate the column densities in luminous quasars.


  We show that typical extensions of ergodic systems inherit the triviality of
pairwise independent self-joinings. This property (introduced by A. del Junco
and D. Rudolph) is related with Rokhlin's famous multiple mixing problem and
several questions from joining theory.


  Following the regularization method presented by Zydor, we study in this
paper the regularized linear periods of square-integrable automormphic forms on
$\mathrm{GL}_{2n}(\mathbb{A}_F)$, where $F$ is a number field and
$\mathbb{A}_F$ its ring of adeles. We obtain a formula that expresses the
regularized period of a noncuspidal, square-integrable automorphic form in
terms of degenerate Whittaker functions in an inductive manner. As a
consequence we characterize irreducible automorphic representations in the
discrete spectrum of $\mathrm{GL}_{2n}(\mathbb{A})$ that are distinguished by
$\mathrm{GL}_n(\mathbb{A}) \times \mathrm{GL}_n(\mathbb{A})$. We also show the
vanishing of the regularized periods of square-integrable automorphic forms on
$\mathrm{GL}_n(\mathbb{A})$ over $\mathrm{GL}_p(\mathbb{A}) \times
\mathrm{GL}_q(\mathbb{A})$ when $p$ is not equal to $q$.


  The brane inflationary model inspired by a polytropic inflationary idea is
studied. In the slow-roll approximation and high energy limit, for a chaotic
potential, the model is developed, and its characteristics are discussed. We
obtain explicit expressions for the scalar power spectrum, the tensor-scalar
ratio, the scalar spectral index and its running in terms of the polytropic
parameters. We find a new constraint on the energy scale of the inflation and
the brane tension using the WMAP9 data.


  We report an x-ray scattering study of the microscopic structure of the
surface of a liquid alkali metal. The bulk liquid structure factor of the
eutectic K67Na33 alloy is characteristic of an ideal mixture, and so shares the
properties of an elemental liquid alkali metal. Analysis of off-specular
diffuse scattering and specular x-ray reflectivity shows that the surface
roughness of the K-Na alloy follows simple capillary wave behavior with a
surface structure factor indicative of surface induced layering. Comparison of
thelow-angle tail of the K67Na33 surface structure factor with the one measured
for liquid Ga and In previously suggests that layering is less pronounced in
alkali metals. Controlled exposure of the liquid to H2 and O2 gas does not
affect the surface structure, indicating that oxide and hydride are not stable
at the liquid surface under these experimental conditions.


  Under suitable conditions on the range of the Gauss map of a complete
submanifold of Euclidean space with parallel mean curvature, we construct a
strongly subharmonic function and derive a-priori estimates for the harmonic
Gauss map. The required conditions here are more general than in previous work
and they therefore enable us to improve substantially previous results for the
Lawson-Osseman problem concerning the regularity of minimal submanifolds in
higher codimension and to derive Bernstein type results.


  We study the risk of minimum-norm interpolants of data in Reproducing Kernel
Hilbert Spaces. Our upper bounds on the risk are of a multiple-descent shape
for the various scalings of $d = n^{\alpha}$, $\alpha\in(0,1)$, for the input
dimension $d$ and sample size $n$. Empirical evidence supports our finding that
minimum-norm interpolants in RKHS can exhibit this unusual non-monotonicity in
sample size; furthermore, locations of the peaks in our experiments match our
theoretical predictions. Since gradient flow on appropriately initialized wide
neural networks converges to a minimum-norm interpolant with respect to a
certain kernel, our analysis also yields novel estimation and generalization
guarantees for these over-parametrized models.
  At the heart of our analysis is a study of spectral properties of the random
kernel matrix restricted to a filtration of eigen-spaces of the population
covariance operator, and may be of independent interest.


  Unmanned Aerial Systems (UAS) are being increasingly deployed for commercial,
civilian, and military applications. The current UAS state-of-the-art still
depends on a remote human controller with robust wireless links to perform
several of these applications. The lack of autonomy restricts the domains of
application and tasks for which a UAS can be deployed. Enabling autonomy and
intelligence to the UAS will help overcome this hurdle and expand its use
improving safety and efficiency. The exponential increase in computing
resources and the availability of large amount of data in this digital era has
led to the resurgence of machine learning from its last winter. Therefore, in
this chapter, we discuss how some of the advances in machine learning,
specifically deep learning and reinforcement learning can be leveraged to
develop next-generation autonomous UAS. We first begin motivating this chapter
by discussing the application, challenges, and opportunities of the current UAS
in the introductory section. We then provide an overview of some of the key
deep learning and reinforcement learning techniques discussed throughout this
chapter. A key area of focus that will be essential to enable autonomy to UAS
is computer vision. Accordingly, we discuss how deep learning approaches have
been used to accomplish some of the basic tasks that contribute to providing
UAS autonomy. Then we discuss how reinforcement learning is explored for using
this information to provide autonomous control and navigation for UAS. Next, we
provide the reader with directions to choose appropriate simulation suites and
hardware platforms that will help to rapidly prototype novel machine learning
based solutions for UAS. We additionally discuss the open problems and
challenges pertaining to each aspect of developing autonomous UAS solutions to
shine light on potential research areas.


  We propose a minimal gauged $U(1)_{B-L}$ extension of the minimal
supersymmetric Standard Model (MSSM) which resolves the cosmological moduli
problem via thermal inflation, and realizes late-time Affleck-Dine leptogensis
so as to generate the right amount of baryon asymmetry at the end of thermal
inflation. The present relic density of dark matter can be explained by
sneutrinos, MSSM neutralinos, axinos, or axions. Cosmic strings from
$U(1)_{B-L}$ breaking are very thick, and so the expected stochastic
gravitational wave background from cosmic string loops has a spectrum different
from the one in the conventional Abelian-Higgs model, as would be
distinguishable at least at LISA and DECIGO. The characteristic spectrum is due
to a flat potential, and may be regarded as a hint of supersymmetry. Combined
with the resolution of moduli problem, the expected signal of gravitational
waves constrains the $U(1)_{B-L}$ breaking scale to be
$\mathcal{O}(10^{12-13})\,{\rm GeV}$. Interestingly, our model provides a
natural possibility for explaining the observed ultra-high-energy cosmic rays
thanks to the fact that the core width of strings in our scenario is very
large, allowing a large enhancement of particle emissions from the cusps of
string loops. Condensation of $LH_u$ flat-direction inside of string cores
arises inevitably and can also be the main source of the ultra-high-energy
cosmic rays accompanied by ultra-high-energy lightest supersymmetric particles.


  Most state-of-the-art object detection systems follow an anchor-based
diagram. Anchor boxes are densely proposed over the images and the network is
trained to predict the boxes position offset as well as the classification
confidence. Existing systems pre-define anchor box shapes and sizes and ad-hoc
heuristic adjustments are used to define the anchor configurations. However,
this might be sub-optimal or even wrong when a new dataset or a new model is
adopted. In this paper, we study the problem of automatically optimizing anchor
boxes for object detection. We first demonstrate that the number of anchors,
anchor scales and ratios are crucial factors for a reliable object detection
system. By carefully analyzing the existing bounding box patterns on the
feature hierarchy, we design a flexible and tight hyper-parameter space for
anchor configurations. Then we propose a novel hyper-parameter optimization
method named AABO to determine more appropriate anchor boxes for a certain
dataset, in which Bayesian Optimization and subsampling method are combined to
achieve precise and efficient anchor configuration optimization. Experiments
demonstrate the effectiveness of our proposed method on different detectors and
datasets, e.g. achieving around 2.4% mAP improvement on COCO, 1.6% on ADE and
1.5% on VG, and the optimal anchors can bring 1.4% to 2.4% mAP improvement on
SOTA detectors by only optimizing anchor configurations, e.g. boosting Mask
RCNN from 40.3% to 42.3%, and HTC detector from 46.8% to 48.2%.


  We report the evolution of the spin resonance in CeCoIn$_{5}$ as a function
of magnetic field and lanthanum substitution. In both cases, the resonance peak
position shifts to lower energy and the lineshape broadens. For La doping, it
is found that the ratio $\Omega_{res}/k_{B}T_{c}$ is almost constant as a
function of $x$. Under magnetic field the decrease of the excitation energy is
similar for H// [1,$\bar{1}$,0] and [1,1,1] and faster than the decrease of
$T_{c}(H)$. The Zeeman effect found for the field applied along [1,$\bar{1}$,0]
corresponds to the ground state magnetic moment.


  An analysis of the photometric observations of the light curves of the five
large amplitude, irregularly pulsating stars R UMi, RS Cyg, V CVn, UX Dra and
SX Her is presented. First, multi-periodicity is eliminated for these
pulsations, i.e. they are not caused by the excitation of a small number of
pulsation modes with constant amplitudes. Next, on the basis of energetics we
also eliminate stochasticity as a cause, leaving low dimensional chaos as the
only alternative. We then use a global flow reconstruction technique in an
attempt to extract quantitative information from the light curves, and to
uncover common physical features in this class of irregular variable stars that
straddle the RV Tau to the Mira variables. Evidence is presented that the
pulsational behavior of R UMi, RS Cyg, V CVn and UX Dra takes place in a
4-dimensional dynamical phase space, suggesting that two vibrational modes are
involved in the pulsation. A linear stability analysis of the fixed points of
the maps further indicates the existence of a two-mode resonance, similar to
the one we had uncovered earlier in R Sct: The irregular pulsations are the
result of a continual energy exchange between two strongly nonadiabatic modes,
a lower frequency pulsation mode and an overtone that are in a close 2:1
resonance. The evidence is particularly convincing for R UMi, RS Cyg and V CVn,
but much weaker for UX Dra. In contrast, the pulsations of SX Her appear to be
more complex and may require a 6D space.


  High-resolution aerial imagery allows fine details in the segmentation of
farmlands. However, small objects and features introduce distortions to the
delineation of object boundaries, and larger contextual views are needed to
mitigate class confusion. In this work, we present an end-to-end trainable
network for segmenting farmlands with contour levees from high-resolution
aerial imagery. A fusion block is devised that includes multiple voting blocks
to achieve image segmentation and classification. We integrate the fusion block
with a backbone and produce both semantic predictions and segmentation slices.
The segmentation slices are used to perform majority voting on the predictions.
The network is trained to assign the most likely class label of a segment to
its pixels, learning the concept of farmlands rather than analyzing
constitutive pixels separately. We evaluate our method using images from the
National Agriculture Imagery Program. Our method achieved an average accuracy
of 94.34\%. Compared to the state-of-the-art methods, the proposed method
obtains an improvement of 6.96% and 2.63% in the F1 score on average.


  This paper proposes new methods for set-based state estimation and active
fault diagnosis (AFD) of linear descriptor systems. In contrast to simple set
representations, such as intervals, ellipsoids, and zonotopes, linear static
constraints on the state variables, typical of descriptor systems, can be
directly incorporated in the mathematical description of constrained zonotopes.
Thanks to this feature, set-based methods using constrained zonotopes, as
proposed in previous works, could provide less conservative enclosures.
However, an enclosure on the states was assumed to be known for all $k \geq 0$.
Such assumption is violated in the case of unstable descriptor systems. In this
context, this paper proposes a new representation for unbounded sets, which
allows to develop methods for state estimation and tube-based AFD of stable and
unstable linear descriptor systems. The new set representation inherits most of
the properties of constrained zonotopes, including efficient complexity
reduction methods, while allowing to describe different classes of sets, such
as strips, hyperplanes, and the entire $n$-dimensional Euclidean space. The
advantages of the proposed approaches with respect to constrained zonotope
methods are highlighted in numerical examples.


  We prove necessary and sufficient conditions for the asymptotic normality of
multiple integrals with respect to a Poisson measure on a general measure
space, expressed both in terms of norms of contraction kernels and of variances
of carr\'e-du-champ operators. Our results substantially complete the fourth
moment theorems recently obtained by D\"obler and Peccati (2018) and D\"obler,
Vidotto and Zheng (2018). An important tool for achieving our goals is a novel
product formula for multiple integrals under minimal conditions.


  We construct the relative log de Rham-Witt complex. This is a generalization
of the relative de Rham-Witt complex of Langer-Zink to log schemes. We prove
the comparison theorem between the hypercohomology of the log de Rham-Witt
complex and the relative log crystalline cohomology in certain cases. We
construct the $p$-adic weight spectral sequence for relative proper strict
semistable log schemes. When the base log scheme is a log point, We show it
degenerates at $E_2$ after tensoring with the fraction field of the Witt ring.
We also extend the definition of the overconvergent de Rham-Witt complex of
Davis-Langer-Zink to log schemes $(X,D)$ associated with smooth schemes with
simple normal crossing divisor over a perfect field. Finally, we compare its
hypercohomology with the rigid cohomology of $X \setminus D$.


  Positive and negative features of the Copenhagen interpretation are
discussed. As positive features can be mentioned its pragmatism and its
awareness of the crucial role of measurement. However, the main part of the
contribution is devoted to the negative features, to wit, its pragmatism (once
again), its confounding of preparation and measurement, its classical account
of measurement, its completeness claims, the ambiguity of its notion of
correspondence, its confused notion of complementarity. It is demonstrated how
confusions and paradoxes stemming from the negative features of the Copenhagen
interpretation can be dealt with in an amended interpretation, to be referred
to as `neo-Copenhagen interpretation', in which the role of the measuring
instrument is taken seriously by recognizing the quantum mechanical character
of its interaction with the microscopic object. The ensuing necessity of
extending the notion of a quantum mechanical observable from the Hermitian
operator of the standard formalism to the positive operator-valued measure of a
generalized formalism is demonstrated to yield a sound mathematical basis for a
transition from the Copenhagen contextualistic-realist interpretation to the
neo-Copenhagen empiricist one. Applications to the uncertainty relations and to
the Bell inequalities are briefly discussed.


  The growing complexity of the power grid, driven by increasing share of
distributed energy resources and by massive deployment of intelligent
internet-connected devices, requires new modelling tools for planning and
operation. Physics-based state estimation models currently used for data
filtering, prediction and anomaly detection are hard to maintain and adapt to
the ever-changing complex dynamics of the power system. A data-driven approach
based on probabilistic graphs is proposed, where custom non-linear, localised
models of the joint density of subset of system variables can be combined to
model arbitrarily large and complex systems. The graphical model allows to
naturally embed domain knowledge in the form of variables dependency structure
or local quantitative relationships. A specific instance where neural-network
models are used to represent the local joint densities is proposed, although
the methodology generalises to other model classes. Accuracy and scalability
are evaluated on a large-scale data set representative of the European
transmission grid.


  A simple closed-form analytic expression for the probability of two-flavour
neutrino oscillations in a matter with an arbitrary density profile is derived.
Our formula is based on a perturbative expansion and allows an easy calculation
of higher order corrections. The expansion parameter is small when the density
changes relatively slowly along the neutrino path and/or neutrino energy is not
very close to the Mikheyev-Smirnov-Wolfenstein (MSW) resonance energy. Our
approximation is not equivalent to the adiabatic approximation and actually
goes beyond it. We demonstrate the validity of our results using a few model
density profiles, including the PREM density profile of the Earth. It is shown
that by combining the results obtained from the expansions valid below and
above the MSW resonance one can obtain a very good description of neutrino
oscillations in matter in the entire energy range, including the resonance
region.


  Semiconductor quantum dot arrays defined electrostatically in a 2D electron
gas provide a scalable platform for quantum information processing and quantum
simulations. For the operation of quantum dot arrays, appropriate voltages need
to be applied to the gate electrodes that define the quantum dot potential
landscape. Tuning the gate voltages has proven to be a time-consuming task,
because of initial electrostatic disorder and capacitive cross-talk effects.
Here, we report on the automated tuning of the inter-dot tunnel coupling in a
linear array of gate-defined semiconductor quantum dots. The automation of the
tuning of the inter-dot tunnel coupling is the next step forward in scalable
and efficient control of larger quantum dot arrays. This work greatly reduces
the effort of tuning semiconductor quantum dots for quantum information
processing and quantum simulation.


  Solutions to the differential equations of linear elasticity in the continuum
limit in arbitrary crystal symmetry are known only for steady-state
dislocations of arbitrary character, i.e. line defects moving at constant
velocity. Troubled by singularities at certain `critical' velocities (typically
close to certain sound speeds), these dislocation fields are thought to be too
idealized, and divergences are usually attributed to neglecting the finite size
of the core and to the restriction to constant velocity. In the isotropic
limit, accelerating pure screw and edge dislocations were studied some time
ago. A generalization to anisotropic crystals has been attempted for pure screw
and edge dislocations only for some special cases. This work aims to fill the
gap of deriving a general anisotropic solution for pure screw dislocations
applicable to slip systems featuring a reflection symmetry, a prerequisite to
studying pure screw dislocations without mixing with edge dislocations. Further
generalizations to arbitrary mixed dislocations as well as regularizations of
the dislocation core are beyond the scope of this paper and are left for future
work.


  The results of measurements of XPS spectra and magnetic properties of
graphene/Co composites prepared by adding of CoCl$_2$x6H$_2$O diluted in ethyl
alcohol to highly-splitted graphite are presented. XPS Co 2p measurements show
two sets of 2p$_{3/2,1/2}$-lines belonging to oxidized and metallic Co-atoms.
This means that metal in composite is partly oxidized. This conclusion is
confirmed by magnetic measurements which show the presence of the main (from
the metal) and shifted (from the oxide) hysteresis loops. The presence of oxide
layer on the metal surface prevents the metal from the full oxidation and (as
shown by magnetic measurements) provides the preservation of ferromagnetic
properties after long exposure in ambient air which enables the use of
graphene/metal composites in spintronics devices.


  The traveling-wave tube is a critical subsystem for satellite data
transmission. Its role in the history of wireless communications and in the
space conquest is significant, but largely ignored, even though the device
remains widely used nowadays. This paper present, albeit non-exhaustively,
circumstances and contexts that led to its invention, and its part in the
worldwide (in particular in Europe) expansion of TV broadcasting via microwave
radio-relays and satellites. We also discuss its actual contribution to space
applications and its conception. The originality of this paper comes from the
wide period covered (from first slow-wave structures in 1889 to present space
projects) and from connection points made between this device and commercial
exploitations. The appendix deals with an intuitive pedagogical description of
the wave-particle interaction.


  Grand unified theories often predict unification of Yukawa couplings (e.g.,
$h_{b} = h_{\tau}$), and thus certain relations among fermion masses. The
latter can distinguish these from models that predict only coupling constant
unification. The implications of Yukawa couplings of the heavy-family in the
supersymmetric extension of the standard model (when embedded in a GUT) are
discussed. In particular, uncertainties associated with $m_{t}$ and $m_{b}$,
threshold corrections at the low-scale, and threshold and
nonrenormalizable-operator corrections associated with a grand-unified sector
at the high-scale are parametrized and estimated. The implication of these and
of the correlation between $m_{t}$ and the prediction for $\alpha_{s}$ are
discussed. Constraints on the $\tan\beta$ range in such models and an upper
bound on the $t$-quark pole mass are given and are shown to be affected by the
$\alpha_{s}-m_{t}$ correlation. Constraints on the low-scale thresholds are
found to be weakened by uncertainties associated with the high-scale.


  In this paper we establish inhomogeneous coorbit spaces related to the
continuous shearlet transform and the weighted Lebesgue spaces $L_{p,v}, p\geq
1,$ for certain weights $v$. We present an inhomogeneous shearlet frame for
$L_2(\mathbb{R}^d)$ which gives rise to a reproducing kernel $R_\mathfrak{F}$
that is not contained in the space $\mathcal{A}_{1,m_v}$. To show that the
inhomogeneous shearlet coorbit spaces are Banach spaces we introduce a
generalization of the approach of Fornasier, Rauhut and Ullrich.


  Occluded person re-identification (ReID) is a person retrieval task which
aims at matching occluded person images with holistic ones. For addressing
occluded ReID, part-based methods have been shown beneficial as they offer
fine-grained information and are well suited to represent partially visible
human bodies. However, training a part-based model is a challenging task for
two reasons. Firstly, individual body part appearance is not as discriminative
as global appearance (two distinct IDs might have the same local appearance),
this means standard ReID training objectives using identity labels are not
adapted to local feature learning. Secondly, ReID datasets are not provided
with human topographical annotations. In this work, we propose BPBreID, a body
part-based ReID model for solving the above issues. We first design two modules
for predicting body part attention maps and producing body part-based features
of the ReID target. We then propose GiLt, a novel training scheme for learning
part-based representations that is robust to occlusions and non-discriminative
local appearance. Extensive experiments on popular holistic and occluded
datasets show the effectiveness of our proposed method, which outperforms
state-of-the-art methods by 0.7% mAP and 5.6% rank-1 accuracy on the
challenging Occluded-Duke dataset. Our code is available at
https://github.com/VlSomers/bpbreid.


  A spline wavelets construction of class C^n(R) supported by sequences of
aperiodic discretizations of R is presented. The construction is based on
multiresolution analysis recently elaborated by G. Bernuau. At a given scale,
we consider discretizations that are sets of left-hand ends of tiles in a
self-similar tiling of the real line with finite local complexity.
Corresponding tilings are determined by two-letter Sturmian substitution
sequences. We illustrate the construction with examples having quadratic
Pisot-Vijayaraghavan units (like tau = (1 + sqrt{5})/2 or tau^2 = (3 +
sqrt{5})/2) as scaling factor. In particular, we present a comprehensive
analysis of the Fibonacci chain and give the analytic form of related scaling
functions and wavelets as splines of second order. We also give some hints for
the construction of multidimensional spline wavelets based on stone-inflation
tilings in arbitrary dimension.


  Polymerization dynamics of single actin filaments is investigated
theoretically using a stochastic model that takes into account the hydrolysis
of ATP-actin subunits, the geometry of actin filament tips, the lateral
interactions between the monomers as well as the processes at both ends of the
polymer. Exact analytical expressions are obtained for a mean growth velocity
and for dispersion in length fluctuations. It is found that the ATP hydrolysis
has a strong effect on dynamic properties of single actin filaments. At high
concentrations of free actin monomers the mean size of unhydrolyzed ATP-cap is
very large, and the dynamics is governed by association/dissociation of
ATP-actin subunits. However, at low concentrations the size of the cap becomes
finite, and the dissociation of ADP-actin subunits makes a significant
contribution to overall dynamics. Actin filament length fluctuations reach the
maximum at the boundary between two dynamic regimes, and this boundary is
always larger than the critical concentration. Random and vectorial mechanisms
of hydrolysis are compared, and it is found that they predict qualitatively
similar dynamic properties. The possibility of attachment and detachment of
oligomers is also discussed. Our theoretical approach is successfully applied
to analyze the latest experiments on the growth and length fluctuations of
individual actin filaments.


  There is growing evidence that the properties of the molecular gas in the
nuclei of starburst galaxies and in AGN may be very different from those seen
in Galactic star forming regions and that a high kinetic temperature in the
molecular gas may lead to a non-standard initial mass function in the next
generation of stars. Unfortunately, among the fundamental parameters derived
from molecular line observations, the kinetic temperature of the molecular gas
in external galaxies is often not well determined due to a lack of suitable
tracer molecules. We discuss the diagnostic power of selected transition lines
of formaldehyde (H_2CO), which can be used as a molecular thermometer as well
as an excellent tracer of the molecular gas density. As a proof of concept, we
present the results of our multi-transition line study of the H_2CO emission
from the prototypical starburst galaxy M82. Using our large velocity gradient
model, we tightly constrain the physical properties of the dense gas in the
prominent molecular lobes, completely independent of the standard "cloud
thermometer" ammonia (NH_3) or other molecular tracers. Our results agree well
with the properties of the high-excitation molecular gas component found in the
most comprehensive CO studies. Our observations also indicate that there may be
an asymmetry between the two molecular lobes.


  Learning embeddings from large-scale networks is an open challenge. Despite
the overwhelming number of existing methods, is is unclear how to exploit
network structure in a way that generalizes easily to unseen nodes, edges or
graphs. In this work, we look at the problem of finding inductive network
embeddings in large networks without domain-dependent node/edge attributes. We
propose to use a set of basic predefined local encodings as the basis of a
learning algorithm. In particular, we consider the degree frequencies at
different distances from a node, which can be computed efficiently for
relatively short distances and a large number of nodes. Interestingly, the
resulting embeddings generalize well across unseen or distant regions in the
network, both in unsupervised settings, when combined with language model
learning, as well as in supervised tasks, when used as additional features in a
neural network. Despite its simplicity, this method achieves state-of-the-art
performance in tasks such as role detection, link prediction and node
classification, and represents an inductive network embedding method directly
applicable to large unattributed networks.


  Large Language Models (LLMs) have spurred progress in text-to-SQL, the task
of generating SQL queries from natural language questions based on a given
database schema. Despite the declarative nature of SQL, it continues to be a
complex programming language. In this paper, we investigate the potential of an
alternative query language with simpler syntax and modular specification of
complex queries. The purpose is to create a query language that can be learned
more easily by modern neural semantic parsing architectures while also enabling
non-programmers to better assess the validity of the query plans produced by an
interactive query plan assistant.
  The proposed alternative query language is called Query Plan Language (QPL).
It is designed to be modular and can be translated into a restricted form of
SQL Common Table Expressions (CTEs). The aim of QPL is to make complex data
retrieval accessible to non-programmers by allowing users to express their
questions in natural language while also providing an easier-to-verify target
language. The paper demonstrates how neural LLMs can benefit from QPL's
modularity to generate complex query plans in a compositional manner. This
involves a question decomposition strategy and a planning stage.
  We conduct experiments on a version of the Spider text-to-SQL dataset that
has been converted to QPL. The hierarchical structure of QPL programs enables
us to measure query complexity naturally. Based on this assessment, we identify
the low accuracy of existing text-to-SQL systems on complex compositional
queries. We present ways to address the challenge of complex queries in an
iterative, user-controlled manner, using fine-tuned LLMs and a variety of
prompting strategies in a compositional manner.


  A Large Ion Collider Experiment (ALICE) is one of the four large experiments
at the Large Hadron Collider (LHC), and it is dedicated to the study of
ultra-relativistic heavy-ion collisions, with the goal of investigating the
properties of the high-density state of QCD matter produced in these
collisions.
  The study of D meson production azimuthal anisotropy and the measurement of
their elliptic flow (v2) can provide insight on the degree of thermalisation of
charm quarks in the medium and on the charm hadronization mechanism.
  We present the measurement of the D+ and D0 meson v2 in Pb-Pb collisions at
sqrt(sNN)=2.76 TeV at the LHC with ALICE. We discuss the details of the
analysis and we show the results obtained from data samples collected in 2011.


  The aim of this report is to describe a field trial conducted in Italy during
the academic year 2009-10, with primary and secondary school teachers (grades
K-8), in order to test prototypes of "ready to use" kits to be used to
implement PBL laboratory sessions in the classroom. This work is meant to
provide a sort of snapshot of the classroom implementation of the teaching
recommendations (so that any readers can conduct their own analysis). The kits
were designed by matematita (Interuniversity Research Center for the
Communication and Informal Learning of Mathematics, http://www.matematita.it).
I wish to thank the "Ufficio Scolastico Regionale della Lombardia" for
sponsoring the trial.


  The problem of bound states in a double delta potential is revisited by means
of Fourier sine and cosine transforms


  In this work we investigate the magnetic field dependence of Ag octahedra
rotation (tilt) and B2g symmetric stretching modes frequency at different
temperatures. Our field-dependent Raman investigation at 10K is interpreted by
an ionic displacive nature of the magnetically induced ferroelectric phase
transition. The frequency change of the Ag tilt is in agreement with the
stabilization of the Mn-Gd spin arrangement, yielding the necessary conditions
for the onset of ferroelectricity on the basis of the inverse
Dzyaloshinskii-Moriya interaction. The role of the Jahn-Teller cooperative
interaction is also evidenced by the change of the B2g mode frequency at the
ferroelectric phase transition. This frequency change allows estimating the
shift of the oxygen position at the ferroelectric phase transition and the
corresponding spontaneous polarization of 480 {\mu}C/m2, which agrees with
earlier reported values in single crystals. Our study also confirms the
existence of a large magnetic hysteresis at the lowest temperatures, which is a
manifestation of magnetrostiction.


  A primary computational problem in kernel regression is solution of a dense
linear system with the $N\times N$ kernel matrix. Because a direct solution has
an O($N^3$) cost, iterative Krylov methods are often used with fast
matrix-vector products. For poorly conditioned problems, convergence of the
iteration is slow and preconditioning becomes necessary. We investigate
preconditioning from the viewpoint of scalability and efficiency. The problems
that conventional preconditioners face when applied to kernel methods are
demonstrated. A \emph{novel flexible preconditioner }that not only improves
convergence but also allows utilization of fast kernel matrix-vector products
is introduced. The performance of this preconditioner is first illustrated on
synthetic data, and subsequently on a suite of test problems in kernel
regression and geostatistical kriging.


  Some typical kinetic energy integrals which arise in the application of
extended Hylleraas-configuration interaction (E-Hy-CI) function in the
framework of Rayleigh-Ritz method of variation, have been evaluated
analytically for two-electron atomic systems. Closed-form expressions for the
corresponding integrals which occur in the application of Hylleraas-CI
functions, have also been derived as special cases.


  Sloan Digital Sky Survey (SDSS) DR5 photometric data with $120^{\circ} <
\alpha < 270^{\circ}$, $25^{\circ} < \delta < 70^{\circ}$ are searched for new
Milky Way companions or substructures in the Galactic halo. Five candidates are
identified as overdensities of faint stellar sources that have color-magnitude
diagrams similar to those of known globular clusters or dwarf spheroidal
galaxies. The distance to each candidate is estimated by fitting suitable
stellar isochrones to the color-magnitude diagrams. Geometric properties and
absolute magnitudes are roughly measured and used to determine whether the
candidates are likely dwarf spheroidal galaxies, stellar clusters or tidal
debris. SDSSJ1000+5730 and SDSSJ1329+2841 are likely faint dwarf galaxy
candidates while SDSSJ0814+5105, SDSSJ0821+5608 and SDSSJ1058+2843 are likely
extremely faint globular clusters. Follow-up study is needed to confirm these
candidates.


  Two-spin correlations generated by interactions which decay with distance r
as r^{-1-sigma} with -1 <sigma <0 are calculated for periodic Ising chains of
length L. Mean-field theory indicates that the correlations, C(r,L), diminish
in the thermodynamic limit L -> \infty, but they contain a singular structure
for r/L -> 0 which can be observed by introducing magnified correlations,
LC(r,L)-\sum_r C(r,L). The magnified correlations are shown to have a scaling
form F(r/L) and the singular structure of F(x) for x->0 is found to be the same
at all temperatures including the critical point. These conclusions are
supported by the results of Monte Carlo simulations for systems with sigma
=-0.50 and -0.25 both at the critical temperature T=Tc and at T=2Tc.


  Automating device pairing and credential exchange in consumer devices reduce
the time users spend with mundane tasks and improve the user experience.
Acoustic communication is gaining traction as a practical alternative to
Bluetooth or Wi-Fi because it can enable quick and localized information
transfer between consumer devices with built-in hardware. However, achieving
high data rates (>1 kbps) in such systems has been a challenge because the
systems and methods chosen for communication were not tailored to the
application. In this work, a high data rate, near-ultrasonic communication
(NUSC) system is proposed to transfer personal identification numbers (PINs) to
establish a connection between consumer laptops using built-in microphones and
speakers. The similarities between indoor near-ultrasonic and underwater
acoustic communication (UWAC) channels are identified, and appropriate UWAC
techniques are tailored to the NUSC system. The proposed system uses the
near-ultrasonic band at 18-20 kHz, and employs coherent modulation and
phase-coherent adaptive equalization. The capability of the proposed system is
explored in simulated and field experiments that span different device
orientations and distances. The experiments demonstrate data rates of 4 kbps
over distances of up to 5 meters, which is an order of magnitude higher than
the data rates reported with similar systems in the literature.